Structured Review

Illumina Inc 3 end adapter
Detailed comparison of the eCLIP and meCLIP protocols. Presentation of the different steps involved in eCLIP and meCLIP procedures. Following UV crosslinking, RNase treatment, and RBP purification, an RNA adaptor (green) is ligated at the 3′ end. For meCLIP, a biotinylated RNA linker (blue) is incorporated at the 5′ end. RNAs are fractionated by electrophoresis and eluted from gels. For meCLIP, biotinylated RNAs are purified on Streptavidin beads using stringent conditions. Reverse transcription (RT) is then performed, which leads to two distinct cDNA populations. One of them bears the 5′ linker if the reverse transcriptase reads through the crosslinked peptide (read-through cDNAs). The other one lacks the 5′ linker due to a stop of RT at the crosslinked peptide. A second adaptor (purple) is ligated at the <t>3′</t> end of the cDNAs which are next amplified by PCR and submitted to high-throughput sequencing. For meCLIP, two populations of reads are easily sorted out based on the presence or absence of the biotinylated linker sequence.
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1) Product Images from "Monitored eCLIP: high accuracy mapping of RNA-protein interactions"

Article Title: Monitored eCLIP: high accuracy mapping of RNA-protein interactions

Journal: Nucleic Acids Research

doi: 10.1093/nar/gky858

Detailed comparison of the eCLIP and meCLIP protocols. Presentation of the different steps involved in eCLIP and meCLIP procedures. Following UV crosslinking, RNase treatment, and RBP purification, an RNA adaptor (green) is ligated at the 3′ end. For meCLIP, a biotinylated RNA linker (blue) is incorporated at the 5′ end. RNAs are fractionated by electrophoresis and eluted from gels. For meCLIP, biotinylated RNAs are purified on Streptavidin beads using stringent conditions. Reverse transcription (RT) is then performed, which leads to two distinct cDNA populations. One of them bears the 5′ linker if the reverse transcriptase reads through the crosslinked peptide (read-through cDNAs). The other one lacks the 5′ linker due to a stop of RT at the crosslinked peptide. A second adaptor (purple) is ligated at the 3′ end of the cDNAs which are next amplified by PCR and submitted to high-throughput sequencing. For meCLIP, two populations of reads are easily sorted out based on the presence or absence of the biotinylated linker sequence.
Figure Legend Snippet: Detailed comparison of the eCLIP and meCLIP protocols. Presentation of the different steps involved in eCLIP and meCLIP procedures. Following UV crosslinking, RNase treatment, and RBP purification, an RNA adaptor (green) is ligated at the 3′ end. For meCLIP, a biotinylated RNA linker (blue) is incorporated at the 5′ end. RNAs are fractionated by electrophoresis and eluted from gels. For meCLIP, biotinylated RNAs are purified on Streptavidin beads using stringent conditions. Reverse transcription (RT) is then performed, which leads to two distinct cDNA populations. One of them bears the 5′ linker if the reverse transcriptase reads through the crosslinked peptide (read-through cDNAs). The other one lacks the 5′ linker due to a stop of RT at the crosslinked peptide. A second adaptor (purple) is ligated at the 3′ end of the cDNAs which are next amplified by PCR and submitted to high-throughput sequencing. For meCLIP, two populations of reads are easily sorted out based on the presence or absence of the biotinylated linker sequence.

Techniques Used: Purification, Electrophoresis, Amplification, Polymerase Chain Reaction, Next-Generation Sequencing, Sequencing

2) Product Images from "Co-Evolution of Transcriptional Silencing Proteins and the DNA Elements Specifying Their Assembly"

Article Title: Co-Evolution of Transcriptional Silencing Proteins and the DNA Elements Specifying Their Assembly

Journal: PLoS Biology

doi: 10.1371/journal.pbio.1000550

Partial reconstitution of Sb-HMR silencing in S. cerevisiae by transfer of S. bayanus Sir4 and Kos3 proteins. (A) Top panel: Silencing of the Sc::(Sb-HMR::URA3) replacement allele in S. cerevisiae MAT α haploids bearing either the endogenous Sc-SIR4 gene or an integrated Sb-SIR4 gene (top panel). Bottom panel: Silencing of the Sc::(Sb-HMR::URA3) replacement allele in the absence of Sc-SIR1 . (B) S. cerevisiae strains bearing the Sc::(Sb-HMR::URA3) replacement allele, and either the endogenous Sc-SIR4 gene or an integrated Sb-SIR4 gene, were transformed with plasmids encoding individual S. bayanus Sir1 paralogs and assayed for silencing function (FOA/-His, CSM/-His-Ura, or CSM/-His indicate silencing reporter media also selective for maintenance of plasmids bearing the HIS3 marker). Quantification of relative silencing function, based on growth on FOA/-His, is indicated at right. Fold-change comparisons were made relative to the Sc::(Sb-HMR::URA3) Sc-SIR4 strain bearing an empty vector (row 1). We note that the CEN/ARS plasmid itself appeared to enhance Sb-HMR silencing relative to the untransformed strains (compare Figure 8B , “empty vector” rows, to Figure 8A , rows 1 and 2). However, relative comparisons among transformed strains were still possible.
Figure Legend Snippet: Partial reconstitution of Sb-HMR silencing in S. cerevisiae by transfer of S. bayanus Sir4 and Kos3 proteins. (A) Top panel: Silencing of the Sc::(Sb-HMR::URA3) replacement allele in S. cerevisiae MAT α haploids bearing either the endogenous Sc-SIR4 gene or an integrated Sb-SIR4 gene (top panel). Bottom panel: Silencing of the Sc::(Sb-HMR::URA3) replacement allele in the absence of Sc-SIR1 . (B) S. cerevisiae strains bearing the Sc::(Sb-HMR::URA3) replacement allele, and either the endogenous Sc-SIR4 gene or an integrated Sb-SIR4 gene, were transformed with plasmids encoding individual S. bayanus Sir1 paralogs and assayed for silencing function (FOA/-His, CSM/-His-Ura, or CSM/-His indicate silencing reporter media also selective for maintenance of plasmids bearing the HIS3 marker). Quantification of relative silencing function, based on growth on FOA/-His, is indicated at right. Fold-change comparisons were made relative to the Sc::(Sb-HMR::URA3) Sc-SIR4 strain bearing an empty vector (row 1). We note that the CEN/ARS plasmid itself appeared to enhance Sb-HMR silencing relative to the untransformed strains (compare Figure 8B , “empty vector” rows, to Figure 8A , rows 1 and 2). However, relative comparisons among transformed strains were still possible.

Techniques Used: Transformation Assay, Marker, Plasmid Preparation

Evolutionary analyses of SIR4 in the sensu stricto clade. (A) Ratios of nonsynonymous to synonymous divergence (dN/dS, or ω) computed in 102 bp windows every 3 bp along alignments of the SIR4 gene from five sensu stricto species ( S. cerevisiae , S. paradoxus , S. mikatae , S. kudriavzevii , and S. bayanus ). Horizontal lines show the value of ω for the median SIR4 window (red solid line), the median window of all genes (blue solid line), and the limits within which 95% of all ∼1,500 windows, sampled from across coding regions of the genome, fall (dashed lines). Diamonds indicate codons having a posterior probability of (ω > 1)≥0.75 (corresponding to positions given in panel C). Each of these 11 rapidly evolving codons is labeled with the inferred ancestral amino acid at that position, the amino acid number, and the amino acid present in S. cerevisiae Sir4. Labeled boxes at top indicate the locations of functional domains. (B) Table summarizing statistics of PAML's M7 versus M8 evolutionary models for SIR2 , SIR3 , and SIR4 . For each gene, the starting nucleotide alignments were generated using sequences from the five sensu stricto species used in panel A (see Methods for further description of PAML analysis). NS, not significant. (C) Table summarizing a subset of the Bayes Empirical Bayes (BEB) analysis for model M8 of PAML. The identities of the 11 sites with posterior probability of (ω > 1)≥0.75 are shown. Nucleotide (nt) and amino acid (a.a.) positions from S. cerevisiae SIR4 are given.
Figure Legend Snippet: Evolutionary analyses of SIR4 in the sensu stricto clade. (A) Ratios of nonsynonymous to synonymous divergence (dN/dS, or ω) computed in 102 bp windows every 3 bp along alignments of the SIR4 gene from five sensu stricto species ( S. cerevisiae , S. paradoxus , S. mikatae , S. kudriavzevii , and S. bayanus ). Horizontal lines show the value of ω for the median SIR4 window (red solid line), the median window of all genes (blue solid line), and the limits within which 95% of all ∼1,500 windows, sampled from across coding regions of the genome, fall (dashed lines). Diamonds indicate codons having a posterior probability of (ω > 1)≥0.75 (corresponding to positions given in panel C). Each of these 11 rapidly evolving codons is labeled with the inferred ancestral amino acid at that position, the amino acid number, and the amino acid present in S. cerevisiae Sir4. Labeled boxes at top indicate the locations of functional domains. (B) Table summarizing statistics of PAML's M7 versus M8 evolutionary models for SIR2 , SIR3 , and SIR4 . For each gene, the starting nucleotide alignments were generated using sequences from the five sensu stricto species used in panel A (see Methods for further description of PAML analysis). NS, not significant. (C) Table summarizing a subset of the Bayes Empirical Bayes (BEB) analysis for model M8 of PAML. The identities of the 11 sites with posterior probability of (ω > 1)≥0.75 are shown. Nucleotide (nt) and amino acid (a.a.) positions from S. cerevisiae SIR4 are given.

Techniques Used: Labeling, Functional Assay, Generated

Transfer of Sb-HMR into S. cerevisiae , identifying cis -component of cross-species silencing incompatibility. (A) Schematic diagram depicts replacement of Sc-HMR by Sb-HMR::URA3 in S. cerevisiae , creating the Sc::(Sb-HMR::URA3) allele. Diagonal lines depict cross-overs for the HMR allele swap, with other genetic features of the two HMR loci as in Figure 2 . A hygromycin-resistance marker (Hyg R ) was inserted 3 kb to the right of Sb-HMR to allow targeted recombination. Shown above is percent identity (BLASTN) between S. cerevisiae and S. bayanus for the two silencers, the two cassette homology regions (light blue boxes), and the HMR a 1 gene (promoter plus ORF). Note that the silencer sequences show no significant alignment by BLAST. (B) Silencing of the Sc::(Sb-HMR::URA3) reporter in SIR4/sir4Δ S. cerevisiae diploids (first row), in Sc-sir4Δ/Sb-SIR4 S. cerevisiae/S. bayanus hybrids (second row), and in Sc-sir4Δ::Sb-SIR4/Sb-SIR4 S. cerevisiae/S. bayanus hybrids (third row). Note that the change in silencing between the first and second rows could be seen only on FOA, with similar growth on CSM/-Ura. This likely reflects Sb-SIR4 dosage sensitivity, as seen in the original hybrid diploids ( Figure 2A ). (C) Control strains showing expected silencing functions of Sc::(Sb-HMR::URA3) and Sc-sir4Δ::Sb-SIR4 replacement alleles in interspecies hybrids. Silencing of the Sb-HMR::URA3 reporter gene, located in its native S. bayanus chromosomal context, in Sc-sir4Δ/Sb-SIR4 hybrids (top row), and in Sc-sir4Δ::Sb-SIR4/Sb-sir4Δ hybrids (bottom row). Note that silencing of Sb-HMR::URA3 in these hybrids was equivalent to Sc::(Sb-HMR::URA3) silencing in (B), indicating that the functions of Sb-HMR and Sb-SIR4 were largely unaffected by S. cerevisiae chromosomal context.
Figure Legend Snippet: Transfer of Sb-HMR into S. cerevisiae , identifying cis -component of cross-species silencing incompatibility. (A) Schematic diagram depicts replacement of Sc-HMR by Sb-HMR::URA3 in S. cerevisiae , creating the Sc::(Sb-HMR::URA3) allele. Diagonal lines depict cross-overs for the HMR allele swap, with other genetic features of the two HMR loci as in Figure 2 . A hygromycin-resistance marker (Hyg R ) was inserted 3 kb to the right of Sb-HMR to allow targeted recombination. Shown above is percent identity (BLASTN) between S. cerevisiae and S. bayanus for the two silencers, the two cassette homology regions (light blue boxes), and the HMR a 1 gene (promoter plus ORF). Note that the silencer sequences show no significant alignment by BLAST. (B) Silencing of the Sc::(Sb-HMR::URA3) reporter in SIR4/sir4Δ S. cerevisiae diploids (first row), in Sc-sir4Δ/Sb-SIR4 S. cerevisiae/S. bayanus hybrids (second row), and in Sc-sir4Δ::Sb-SIR4/Sb-SIR4 S. cerevisiae/S. bayanus hybrids (third row). Note that the change in silencing between the first and second rows could be seen only on FOA, with similar growth on CSM/-Ura. This likely reflects Sb-SIR4 dosage sensitivity, as seen in the original hybrid diploids ( Figure 2A ). (C) Control strains showing expected silencing functions of Sc::(Sb-HMR::URA3) and Sc-sir4Δ::Sb-SIR4 replacement alleles in interspecies hybrids. Silencing of the Sb-HMR::URA3 reporter gene, located in its native S. bayanus chromosomal context, in Sc-sir4Δ/Sb-SIR4 hybrids (top row), and in Sc-sir4Δ::Sb-SIR4/Sb-sir4Δ hybrids (bottom row). Note that silencing of Sb-HMR::URA3 in these hybrids was equivalent to Sc::(Sb-HMR::URA3) silencing in (B), indicating that the functions of Sb-HMR and Sb-SIR4 were largely unaffected by S. cerevisiae chromosomal context.

Techniques Used: Marker

Further characterization of the silencing incompatibility. (A) Sc-SIR4 was unable to silence Sb-HMR in S. bayanus . Top row: Silencing of Sb-HMR::URA3 in an S. bayanus haploid strain bearing Sc-SIR4 integrated in place of Sb-SIR4 . Bottom row: Control showing that the Sb-sir4Δ::Sc-SIR4 replacement allele could supply silencing function to Sc-HMR in an S. cerevisiae/S. bayanus hybrid. (B) RNA analysis of HMR::URA3 reporters in S. cerevisiae/S. bayanus hybrids and S. bayanus diploids. URA3 amplification values were normalized to those of actin ( ACT1 ) for each strain. Error bars show standard deviations ( n = 3).
Figure Legend Snippet: Further characterization of the silencing incompatibility. (A) Sc-SIR4 was unable to silence Sb-HMR in S. bayanus . Top row: Silencing of Sb-HMR::URA3 in an S. bayanus haploid strain bearing Sc-SIR4 integrated in place of Sb-SIR4 . Bottom row: Control showing that the Sb-sir4Δ::Sc-SIR4 replacement allele could supply silencing function to Sc-HMR in an S. cerevisiae/S. bayanus hybrid. (B) RNA analysis of HMR::URA3 reporters in S. cerevisiae/S. bayanus hybrids and S. bayanus diploids. URA3 amplification values were normalized to those of actin ( ACT1 ) for each strain. Error bars show standard deviations ( n = 3).

Techniques Used: Amplification

Incompatibility between S. cerevisiae SIR4 and S. bayanus HMR in S. cerevisiae/S. bayanus interspecies hybrids. (A) Silencing of the Sb-HMR::URA3 reporter gene (top panel) or the Sc-HMR::URA3 reporter gene (bottom panel) in S. cerevisiae/S. bayanus hybrids was assayed by growth on selective media. For each strain, a 10-fold dilution series of yeast cells was spotted onto medium counter-selective for URA3 expression (FOA), selective for URA3 expression (CSM/-Ura), or rich medium (YPD). Schematics at left show the configurations of the salient features of two species' HMR loci in each hybrid strain: silencers (ovals), mating-type cassette homology regions (blue boxes), HMR a 1 ORF (red arrow), and URA3 ORF (green arrow). Gray oval indicates the presumed location of the Sb-HMR-I silencer. Presence or absence ( Δ ) of the S. cerevisiae ( Sc ) and S. bayanus ( Sb ) SIR4 alleles are indicated to the right of schematics. See Table S1 for complete strain genotypes. (B) Silencing of the Sb-HMR::URA3 reporter gene in wild-type, SIR4/sir4Δ , or sir4Δ/sir4Δ S. bayanus diploids.
Figure Legend Snippet: Incompatibility between S. cerevisiae SIR4 and S. bayanus HMR in S. cerevisiae/S. bayanus interspecies hybrids. (A) Silencing of the Sb-HMR::URA3 reporter gene (top panel) or the Sc-HMR::URA3 reporter gene (bottom panel) in S. cerevisiae/S. bayanus hybrids was assayed by growth on selective media. For each strain, a 10-fold dilution series of yeast cells was spotted onto medium counter-selective for URA3 expression (FOA), selective for URA3 expression (CSM/-Ura), or rich medium (YPD). Schematics at left show the configurations of the salient features of two species' HMR loci in each hybrid strain: silencers (ovals), mating-type cassette homology regions (blue boxes), HMR a 1 ORF (red arrow), and URA3 ORF (green arrow). Gray oval indicates the presumed location of the Sb-HMR-I silencer. Presence or absence ( Δ ) of the S. cerevisiae ( Sc ) and S. bayanus ( Sb ) SIR4 alleles are indicated to the right of schematics. See Table S1 for complete strain genotypes. (B) Silencing of the Sb-HMR::URA3 reporter gene in wild-type, SIR4/sir4Δ , or sir4Δ/sir4Δ S. bayanus diploids.

Techniques Used: Expressing

Additional comparative Sir4 ChIP and expression analyses. (A) ChIP-qPCR analysis of Sc-Sir4 versus Sb-Sir4. For each primer set, the IP/Input ratios for Sc-Sir4 (JRY9062), Sb-Sir4 (JRY9063), and the “No-tag” control (JRY9054) are shown. Error bars show standard deviations ( n = 3). (B) ChIP-Seq analysis of Sc-Sir4 versus Sb-Sir4 association on an S. bayanus contig containing subtelomeric sequence (GenBank accession number AACG02000166). Hybrid strains used in this analysis were identical to those used in Figures 4B and 5A: Sc-Sir4, JRY9062; Sb-Sir4, JRY9063; No tag, JRY9054. Per-base IP/Input ratios, determined as in Figure 4B , are plotted versus contig position. We note that the terminal TG 1–3 repeats are not present in the current S. bayanus genome assembly [77] . (C) RNA expression analysis of putative S. bayanus subtelomeric genes. Quantitative RT-PCR was performed on RNA isolated from S. bayanus wild-type ( Sb-SIR4 ), Sb-sir4Δ::Sb-SIR4 ( Sc-SIR4 ), or sir4Δ strains. The actin gene ( ACT1 ) served as a euchromatic control gene. Error bars show standard deviations ( n = 3).
Figure Legend Snippet: Additional comparative Sir4 ChIP and expression analyses. (A) ChIP-qPCR analysis of Sc-Sir4 versus Sb-Sir4. For each primer set, the IP/Input ratios for Sc-Sir4 (JRY9062), Sb-Sir4 (JRY9063), and the “No-tag” control (JRY9054) are shown. Error bars show standard deviations ( n = 3). (B) ChIP-Seq analysis of Sc-Sir4 versus Sb-Sir4 association on an S. bayanus contig containing subtelomeric sequence (GenBank accession number AACG02000166). Hybrid strains used in this analysis were identical to those used in Figures 4B and 5A: Sc-Sir4, JRY9062; Sb-Sir4, JRY9063; No tag, JRY9054. Per-base IP/Input ratios, determined as in Figure 4B , are plotted versus contig position. We note that the terminal TG 1–3 repeats are not present in the current S. bayanus genome assembly [77] . (C) RNA expression analysis of putative S. bayanus subtelomeric genes. Quantitative RT-PCR was performed on RNA isolated from S. bayanus wild-type ( Sb-SIR4 ), Sb-sir4Δ::Sb-SIR4 ( Sc-SIR4 ), or sir4Δ strains. The actin gene ( ACT1 ) served as a euchromatic control gene. Error bars show standard deviations ( n = 3).

Techniques Used: Chromatin Immunoprecipitation, Expressing, Real-time Polymerase Chain Reaction, Sequencing, RNA Expression, Quantitative RT-PCR, Isolation

Sc-Sir4 versus Sb-Sir4 ChIP-Seq analysis in S. cerevisiae/S. bayanus hybrids. (A) Left: Sir4 IP/Input ratios, normalized to control regions within each experiment, for the Sc-HMR-E silencer. Center: Normalized IP/Input ratios for the Sb-HMR-E silencer. Right: Normalized IP/Input ratios for the Sb-HMR::URA3 ORF. “Sc-Sir4” or “Sb-Sir4” labels indicate which species' Sir4 protein was examined by ChIP. Species' identities of both SIR4 alleles in each strain are given in parentheses, with the allele bearing the 13x-Myc tag indicated in red: ( Sc/Sc ), JRY9062; ( Sb/Sb ), JRY9063; ( Sc/Sb ), JRY9064 (see Table S1 for complete strain genotypes). Dashed lines indicated IP/Input ratio of non-silenced control regions. Error bars indicate the standard error of the mean of all 100 bp windows covering a region. See Table 1 for non-normalized IP/Input ratios and Methods for a description of data processing. (B) ChIP-Seq profiles of Sc-Sir4 (JRY9062), Sb-Sir4 (JRY9063), and the “No tag” control (JRY9054) at two S. cerevisiae telomere regions. The ratio of IP/Input read counts for each base of a telomeric region is plotted. Diagrams indicate salient genetic features of two telomeres (see key at left) with X elements (yellow boxes), Y′ elements, and terminal repeats (TR) containing Rap1 binding sites, labeled above. TELXV-L (left panel) has an X-element-only end, whereas TELVIII-R (right panel) has an X-Y′ end. The TELVIII-R Y′ element spans nucleotide positions 556986–562456, with two helicase-encoding ORFs located between positions 558014 and 562047 ( www.yeastgenome.org ). For the ORFs within this Y′ element, Sc-Sir4 had a mean IP/Input ratio of 1.2, and the “No tag” control had a mean IP/Input ratio of 0.9 (the mean IP/Input ratio for all non-silenced regions, genome wide, was approximately 0.7 for both Sc-Sir4 and Sb-Sir4 ChIPs).
Figure Legend Snippet: Sc-Sir4 versus Sb-Sir4 ChIP-Seq analysis in S. cerevisiae/S. bayanus hybrids. (A) Left: Sir4 IP/Input ratios, normalized to control regions within each experiment, for the Sc-HMR-E silencer. Center: Normalized IP/Input ratios for the Sb-HMR-E silencer. Right: Normalized IP/Input ratios for the Sb-HMR::URA3 ORF. “Sc-Sir4” or “Sb-Sir4” labels indicate which species' Sir4 protein was examined by ChIP. Species' identities of both SIR4 alleles in each strain are given in parentheses, with the allele bearing the 13x-Myc tag indicated in red: ( Sc/Sc ), JRY9062; ( Sb/Sb ), JRY9063; ( Sc/Sb ), JRY9064 (see Table S1 for complete strain genotypes). Dashed lines indicated IP/Input ratio of non-silenced control regions. Error bars indicate the standard error of the mean of all 100 bp windows covering a region. See Table 1 for non-normalized IP/Input ratios and Methods for a description of data processing. (B) ChIP-Seq profiles of Sc-Sir4 (JRY9062), Sb-Sir4 (JRY9063), and the “No tag” control (JRY9054) at two S. cerevisiae telomere regions. The ratio of IP/Input read counts for each base of a telomeric region is plotted. Diagrams indicate salient genetic features of two telomeres (see key at left) with X elements (yellow boxes), Y′ elements, and terminal repeats (TR) containing Rap1 binding sites, labeled above. TELXV-L (left panel) has an X-element-only end, whereas TELVIII-R (right panel) has an X-Y′ end. The TELVIII-R Y′ element spans nucleotide positions 556986–562456, with two helicase-encoding ORFs located between positions 558014 and 562047 ( www.yeastgenome.org ). For the ORFs within this Y′ element, Sc-Sir4 had a mean IP/Input ratio of 1.2, and the “No tag” control had a mean IP/Input ratio of 0.9 (the mean IP/Input ratio for all non-silenced regions, genome wide, was approximately 0.7 for both Sc-Sir4 and Sb-Sir4 ChIPs).

Techniques Used: Chromatin Immunoprecipitation, Binding Assay, Labeling, Genome Wide

Comparative analysis of Sir proteins in S. cerevisiae and S. bayanus . (A) Comparison of the Sir protein complements of S. cerevisiae and S. bayanus . Percent identity (ID) and similarity (sim) for each orthologous pair of proteins, as determined by BLASTP alignments, is indicated above each S. bayanus ortholog. Protein lengths in numbers of amino acids (a.a.) are given to the right of each schematic. Black boxes indicate known domains within each protein (to approximate scale), with domain names indicated below the S. cerevisiae orthologs. OIR, ORC-Interacting Region; BAH, Bromo-Adjacent Homology domain; PAD, Partitioning and Anchoring Domain; CC, Coiled-Coil. (B) Percent identities of orthologous S. cerevisiae and S. bayanus proteins as reported by BLASTP. Histogram shows percent identities of orthologous S. cerevisiae and S. bayanus proteins based on BLASTP alignments. The distribution of percent identity of orthologous protein pairs, in bins of 5 percent increments, is plotted versus the number of orthologous pairs in each bin. The bin containing Sir4 (45% identity) is indicated with an arrow.
Figure Legend Snippet: Comparative analysis of Sir proteins in S. cerevisiae and S. bayanus . (A) Comparison of the Sir protein complements of S. cerevisiae and S. bayanus . Percent identity (ID) and similarity (sim) for each orthologous pair of proteins, as determined by BLASTP alignments, is indicated above each S. bayanus ortholog. Protein lengths in numbers of amino acids (a.a.) are given to the right of each schematic. Black boxes indicate known domains within each protein (to approximate scale), with domain names indicated below the S. cerevisiae orthologs. OIR, ORC-Interacting Region; BAH, Bromo-Adjacent Homology domain; PAD, Partitioning and Anchoring Domain; CC, Coiled-Coil. (B) Percent identities of orthologous S. cerevisiae and S. bayanus proteins as reported by BLASTP. Histogram shows percent identities of orthologous S. cerevisiae and S. bayanus proteins based on BLASTP alignments. The distribution of percent identity of orthologous protein pairs, in bins of 5 percent increments, is plotted versus the number of orthologous pairs in each bin. The bin containing Sir4 (45% identity) is indicated with an arrow.

Techniques Used:

A new twist on co-evolution of transcriptional regulatory proteins and DNA target sites. Although the site-specific DNA binding proteins, ORC, Rap1, and Abf1 were largely interchangeable between S. cerevisiae and S. bayanus , the Sc-Sir4 protein showed a striking inability to function on S. bayanus silencers. Cis -regulatory information in the S. bayanus silencer was specifically tuned to the Sb-Sir4 and Sb-Kos3 silencing proteins, as shown by reconstitution experiments in S. cerevisiae ( Figure 8 ). Loss of Kos3 and changes in Sir4 in the S. cerevisiae lineage were compensated by changes in the silencers, thereby maintaining robust silencing.
Figure Legend Snippet: A new twist on co-evolution of transcriptional regulatory proteins and DNA target sites. Although the site-specific DNA binding proteins, ORC, Rap1, and Abf1 were largely interchangeable between S. cerevisiae and S. bayanus , the Sc-Sir4 protein showed a striking inability to function on S. bayanus silencers. Cis -regulatory information in the S. bayanus silencer was specifically tuned to the Sb-Sir4 and Sb-Kos3 silencing proteins, as shown by reconstitution experiments in S. cerevisiae ( Figure 8 ). Loss of Kos3 and changes in Sir4 in the S. cerevisiae lineage were compensated by changes in the silencers, thereby maintaining robust silencing.

Techniques Used: DNA Binding Assay

3) Product Images from "Dependence of Intracellular and Exosomal microRNAs on Viral E6/E7 Oncogene Expression in HPV-positive Tumor Cells"

Article Title: Dependence of Intracellular and Exosomal microRNAs on Viral E6/E7 Oncogene Expression in HPV-positive Tumor Cells

Journal: PLoS Pathogens

doi: 10.1371/journal.ppat.1004712

Silencing of HPV18 E6/E7 expression by RNA interference. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of HeLa cells with si18E6/E7, control siRNA siContr-1, or upon mock treatment. mRNA levels were normalized to ACTB and calculated relative to the mock control. Data represent mean ± SEM (n = 4). Asterisks above columns indicate statistically significant differences from siContr-1-treated cells (p ≤ 0.05 (*), p ≤ 0.001 (***)). (B) Immunoblot analysis of HPV18 E6, p53, and p21 protein levels, 72 h after transfection of HeLa cells with si18E6/E7 or siContr-1. α-Tubulin: loading control. (C) Immunoblot analysis of HPV18 E7, total pRb (pRb), phosphorylated pRb (pRb-P), and Cyclin A1 protein levels, 72 h after transfection of HeLa cells with si18E6/E7 or siContr-1. α-Tubulin: loading control.
Figure Legend Snippet: Silencing of HPV18 E6/E7 expression by RNA interference. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of HeLa cells with si18E6/E7, control siRNA siContr-1, or upon mock treatment. mRNA levels were normalized to ACTB and calculated relative to the mock control. Data represent mean ± SEM (n = 4). Asterisks above columns indicate statistically significant differences from siContr-1-treated cells (p ≤ 0.05 (*), p ≤ 0.001 (***)). (B) Immunoblot analysis of HPV18 E6, p53, and p21 protein levels, 72 h after transfection of HeLa cells with si18E6/E7 or siContr-1. α-Tubulin: loading control. (C) Immunoblot analysis of HPV18 E7, total pRb (pRb), phosphorylated pRb (pRb-P), and Cyclin A1 protein levels, 72 h after transfection of HeLa cells with si18E6/E7 or siContr-1. α-Tubulin: loading control.

Techniques Used: Expressing, Quantitative RT-PCR, Transfection

Inhibition of endogenous HPV18 E6/E7 expression: Effects on the intracellular miRNA composition of cervical cancer cells. Small RNA deep sequencing (A—D) and qRT-PCR analyses (E) of cellular miRNAs, 72 h after transfection of HeLa cells with si18E6/E7 or control siRNA siContr-1. (A) Mean read count distribution of mature miRNA sequences in si18E6/E7- and siContr-1-transfected cells (n = 2). Only miRNAs with a mean read count > 1 were considered. (B) The 15 most frequently sequenced cellular miRNAs. Selection based on siContr-1 samples, respective values for the si18E6/E7-treatment are indicated. Data represent mean ± SEM (n = 2). Interrupted x-Axis. (C) Overview on differentially affected ( > 1.5-fold) cellular miRNAs, determined by small RNA deep sequencing. RPM values of si18E6/E7-treated samples were calculated relative to the control treatment (siContr-1). Only miRNAs with > 1,000 RPM in each sample were considered (n = 2). (D) Relative quantification of miRNAs in si18E6/E7- versus siContr-1-treated cells as assessed by small RNA deep sequencing (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Only miRNAs with > 1,000 RPM in each sample were considered. Data represent mean ± SEM (n = 2). (E) qRT-PCR analyses of E6/E7 -dependent cellular miRNAs identified by small RNA deep sequencing. Cellular miRNA levels were normalized to snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). The column color shows regulation in the same (dark grey) or opposite (light grey) direction compared to the small RNA deep sequencing data of the individual miRNAs. Data represent mean ± SEM (n = 2 or 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).
Figure Legend Snippet: Inhibition of endogenous HPV18 E6/E7 expression: Effects on the intracellular miRNA composition of cervical cancer cells. Small RNA deep sequencing (A—D) and qRT-PCR analyses (E) of cellular miRNAs, 72 h after transfection of HeLa cells with si18E6/E7 or control siRNA siContr-1. (A) Mean read count distribution of mature miRNA sequences in si18E6/E7- and siContr-1-transfected cells (n = 2). Only miRNAs with a mean read count > 1 were considered. (B) The 15 most frequently sequenced cellular miRNAs. Selection based on siContr-1 samples, respective values for the si18E6/E7-treatment are indicated. Data represent mean ± SEM (n = 2). Interrupted x-Axis. (C) Overview on differentially affected ( > 1.5-fold) cellular miRNAs, determined by small RNA deep sequencing. RPM values of si18E6/E7-treated samples were calculated relative to the control treatment (siContr-1). Only miRNAs with > 1,000 RPM in each sample were considered (n = 2). (D) Relative quantification of miRNAs in si18E6/E7- versus siContr-1-treated cells as assessed by small RNA deep sequencing (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Only miRNAs with > 1,000 RPM in each sample were considered. Data represent mean ± SEM (n = 2). (E) qRT-PCR analyses of E6/E7 -dependent cellular miRNAs identified by small RNA deep sequencing. Cellular miRNA levels were normalized to snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). The column color shows regulation in the same (dark grey) or opposite (light grey) direction compared to the small RNA deep sequencing data of the individual miRNAs. Data represent mean ± SEM (n = 2 or 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).

Techniques Used: Inhibition, Expressing, Sequencing, Quantitative RT-PCR, Transfection, Selection

Influence of combined silencing of p21 and HPV18 E6/E7 expression on the senescent phenotype of HPV-positive cancer cells. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of HeLa cells with the indicated siRNAs or in mock-treated cells. mRNA levels were normalized to ACTB and calculated relative to the mock control. Data represent mean ± SEM (n = 2 or 3). Asterisks above columns indicate statistically significant differences between the indicated treatments (p ≤ 0.05 (*), p ≤ 0.01 (**)). (B) Immunoblot analysis of HPV18 E7, p53, and p21 protein levels, 72 h after transfection of HeLa cells with the indicated siRNAs or upon mock-treatment. α-Tubulin: loading control. (C + D) Cell cycle distribution analyzed by FACS, 72 h after transfection of HeLa cells with the indicated siRNAs or upon mock treatment. Percentage of cells in the G 1 , S and G 2 cell cycle phases are indicated. Representative samples of one experiment are shown as well as a summary of multiple biological replicates. Data represent mean ± SEM (n = 3). (E) HeLa cells were stained for expression of the senescence marker SA-β-Gal, 168 h after transfection with the indicated siRNAs. Visualization by bright field microscopy.
Figure Legend Snippet: Influence of combined silencing of p21 and HPV18 E6/E7 expression on the senescent phenotype of HPV-positive cancer cells. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of HeLa cells with the indicated siRNAs or in mock-treated cells. mRNA levels were normalized to ACTB and calculated relative to the mock control. Data represent mean ± SEM (n = 2 or 3). Asterisks above columns indicate statistically significant differences between the indicated treatments (p ≤ 0.05 (*), p ≤ 0.01 (**)). (B) Immunoblot analysis of HPV18 E7, p53, and p21 protein levels, 72 h after transfection of HeLa cells with the indicated siRNAs or upon mock-treatment. α-Tubulin: loading control. (C + D) Cell cycle distribution analyzed by FACS, 72 h after transfection of HeLa cells with the indicated siRNAs or upon mock treatment. Percentage of cells in the G 1 , S and G 2 cell cycle phases are indicated. Representative samples of one experiment are shown as well as a summary of multiple biological replicates. Data represent mean ± SEM (n = 3). (E) HeLa cells were stained for expression of the senescence marker SA-β-Gal, 168 h after transfection with the indicated siRNAs. Visualization by bright field microscopy.

Techniques Used: Expressing, Quantitative RT-PCR, Transfection, FACS, Staining, Marker, Microscopy

Inhibition of endogenous HPV18 E6/E7 expression: Effects on the miRNA composition of exosomes secreted by cervical cancer cells. Small RNA deep sequencing (A—D) and qRT-PCR analyses (E) of exosomal miRNAs, 72 h after transfection of HeLa cells with si18E6/E7 or control siRNA (siContr-1), and subsequent exosome purification from the cell culture supernatant. (A) Mean read count distribution of mature miRNA sequences in exosomes released from si18E6/E7- and siContr-1-treated HeLa cells (n = 3). Only miRNAs with a mean read count > 1 were considered. (B) The 15 most frequently sequenced exosomal miRNAs. Selection based on siContr-1 samples, respective values for si18E6/E7-treatment are indicated. Data represent mean ± SEM (n = 3). Interrupted x-Axis. (C) Overview on differentially deregulated ( > 1.5-fold) exosomal miRNAs determined by small RNA deep sequencing. RPM values of si18E6/E7-treated samples were calculated relative to the control treatment (siContr-1). Only miRNAs with > 1,000 RPM in each sample were considered (n = 2). (D) Relative quantification of miRNAs in exosomes released from si18E6/E7- versus siContr-1-treated cells, as assessed by small RNA deep sequencing (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Only miRNAs with > 1,000 RPM in each sample were considered. Data represent mean ± SEM (n = 3). (E) qRT-PCR analysis of E6/E7 -dependent exosomal miRNAs identified by small RNA deep sequencing. Exosomal miRNA levels were normalized to miR-452–5p and miR-183–5p and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). The column color shows regulation in the same (dark grey) or opposite (light grey) direction compared to the small RNA deep sequencing data of the individual miRNAs. Ct-values > 35 were considered as not detected (n.d.). Data represent mean ± SEM (n = 2 or 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**)).
Figure Legend Snippet: Inhibition of endogenous HPV18 E6/E7 expression: Effects on the miRNA composition of exosomes secreted by cervical cancer cells. Small RNA deep sequencing (A—D) and qRT-PCR analyses (E) of exosomal miRNAs, 72 h after transfection of HeLa cells with si18E6/E7 or control siRNA (siContr-1), and subsequent exosome purification from the cell culture supernatant. (A) Mean read count distribution of mature miRNA sequences in exosomes released from si18E6/E7- and siContr-1-treated HeLa cells (n = 3). Only miRNAs with a mean read count > 1 were considered. (B) The 15 most frequently sequenced exosomal miRNAs. Selection based on siContr-1 samples, respective values for si18E6/E7-treatment are indicated. Data represent mean ± SEM (n = 3). Interrupted x-Axis. (C) Overview on differentially deregulated ( > 1.5-fold) exosomal miRNAs determined by small RNA deep sequencing. RPM values of si18E6/E7-treated samples were calculated relative to the control treatment (siContr-1). Only miRNAs with > 1,000 RPM in each sample were considered (n = 2). (D) Relative quantification of miRNAs in exosomes released from si18E6/E7- versus siContr-1-treated cells, as assessed by small RNA deep sequencing (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Only miRNAs with > 1,000 RPM in each sample were considered. Data represent mean ± SEM (n = 3). (E) qRT-PCR analysis of E6/E7 -dependent exosomal miRNAs identified by small RNA deep sequencing. Exosomal miRNA levels were normalized to miR-452–5p and miR-183–5p and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). The column color shows regulation in the same (dark grey) or opposite (light grey) direction compared to the small RNA deep sequencing data of the individual miRNAs. Ct-values > 35 were considered as not detected (n.d.). Data represent mean ± SEM (n = 2 or 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**)).

Techniques Used: Inhibition, Expressing, Sequencing, Quantitative RT-PCR, Transfection, Purification, Cell Culture, Selection

Effects of the p53 status on the E6/E7 -dependent modulation of intracellular miRNAs. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7, control siRNA (siContr-1), or upon mock treatment. mRNA levels were normalized to ACTB and calculated relative to the mock control (mock). Data represent mean ± SEM (n = 3). Asterisks above columns indicate statistically significant differences from siContr-1-treated cells (p ≤ 0.05 (*), p ≤ 0.001 (***)). (B) Immunoblot analysis of HPV18 E6, p53 and p21 protein levels, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7 or siContr-1, or upon mock treatment. α-Tubulin: loading control. (C) qRT-PCR analyses of selected cellular miRNAs, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7 or siContr-1. miR-34a-3p, positive control miRNA (p53-inducible). Cellular miRNA levels were normalized to snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).
Figure Legend Snippet: Effects of the p53 status on the E6/E7 -dependent modulation of intracellular miRNAs. (A) qRT-PCR analysis of HPV18 E6/E7 (left panel) and p21 (right panel) mRNA expression, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7, control siRNA (siContr-1), or upon mock treatment. mRNA levels were normalized to ACTB and calculated relative to the mock control (mock). Data represent mean ± SEM (n = 3). Asterisks above columns indicate statistically significant differences from siContr-1-treated cells (p ≤ 0.05 (*), p ≤ 0.001 (***)). (B) Immunoblot analysis of HPV18 E6, p53 and p21 protein levels, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7 or siContr-1, or upon mock treatment. α-Tubulin: loading control. (C) qRT-PCR analyses of selected cellular miRNAs, 72 h after transfection of parental or “p53-null” HeLa cells with si18E6/E7 or siContr-1. miR-34a-3p, positive control miRNA (p53-inducible). Cellular miRNA levels were normalized to snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).

Techniques Used: Quantitative RT-PCR, Expressing, Transfection, Positive Control

HPV oncogenes control p21 expression at multiple levels. E6 can repress p21 transcription at the promoter level by inducing the degradation of the p21 transcriptional activator p53; sustained E6/E7 expression maintains the concentration of miR-17 family members in HPV-positive cancer cells which repress p21 expression by targeting the p21 mRNA; the E7 protein can directly bind to the p21 protein and inhibit its function.
Figure Legend Snippet: HPV oncogenes control p21 expression at multiple levels. E6 can repress p21 transcription at the promoter level by inducing the degradation of the p21 transcriptional activator p53; sustained E6/E7 expression maintains the concentration of miR-17 family members in HPV-positive cancer cells which repress p21 expression by targeting the p21 mRNA; the E7 protein can directly bind to the p21 protein and inhibit its function.

Techniques Used: Expressing, Concentration Assay

Inhibition of endogenous HPV16 E6/E7 expression: Effects on selected exosomal miRNAs. qRT-PCR analysis of selected exosomal miRNAs, 72 h after transfection of SiHa cells with si16E6/E7 or control siRNA (siContr-1), and subsequent exosome purification from the cell culture supernatant. Exosomal miRNA levels were normalized to miR-452–5p and miR-183–5p and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).
Figure Legend Snippet: Inhibition of endogenous HPV16 E6/E7 expression: Effects on selected exosomal miRNAs. qRT-PCR analysis of selected exosomal miRNAs, 72 h after transfection of SiHa cells with si16E6/E7 or control siRNA (siContr-1), and subsequent exosome purification from the cell culture supernatant. Exosomal miRNA levels were normalized to miR-452–5p and miR-183–5p and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*), p ≤ 0.01 (**) and p ≤ 0.001 (***)).

Techniques Used: Inhibition, Expressing, Quantitative RT-PCR, Transfection, Purification, Cell Culture

Inhibition of endogenous HPV16 E6/E7 expression: Effects on selected intracellular miRNAs. (A) Immunoblot analysis of HPV16 E7, HPV16 E6, p53 and p21 protein levels, 72 h after transfection of SiHa cells with si16E6/E7 or control siRNA (siContr-1), or upon mock treatment. α-Tubulin: loading control. (B) qRT-PCR analyses of ten selected cellular miRNAs, 72 h after transfection of SiHa cells with si16E6/E7 or siContr-1. Cellular miRNA levels were normalized to the snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*) and p ≤ 0.01 (**)).
Figure Legend Snippet: Inhibition of endogenous HPV16 E6/E7 expression: Effects on selected intracellular miRNAs. (A) Immunoblot analysis of HPV16 E7, HPV16 E6, p53 and p21 protein levels, 72 h after transfection of SiHa cells with si16E6/E7 or control siRNA (siContr-1), or upon mock treatment. α-Tubulin: loading control. (B) qRT-PCR analyses of ten selected cellular miRNAs, 72 h after transfection of SiHa cells with si16E6/E7 or siContr-1. Cellular miRNA levels were normalized to the snRNA RNU6–2 and calculated relative to siContr-1 (log 2 display). Dashed lines: 1.5-fold up- or downregulation (log 2 (1.5) = 0.585). Data represent mean ± SEM (n = 3). Asterisks indicate statistically significant differences (p ≤ 0.05 (*) and p ≤ 0.01 (**)).

Techniques Used: Inhibition, Expressing, Transfection, Quantitative RT-PCR

4) Product Images from "A cost-effective method for Illumina small RNA-Seq library preparation using T4 RNA ligase 1 adenylated adapters"

Article Title: A cost-effective method for Illumina small RNA-Seq library preparation using T4 RNA ligase 1 adenylated adapters

Journal: Plant Methods

doi: 10.1186/1746-4811-8-41

Adenylation of 3’ adapter using T4 RNA ligase 1. ( A ) Effect of PEG8000 concentration on adenylation efficiency. A synthetic oligo BL1 mimicking the first small RNA cloning linker reported by Lau et al. (2001) was adenylated overnight with 1 U/μL T4 RNA ligase at various PEG concentration. Non-adenylated oligo as the negative control (NC) is loaded on the left lane. ( B ) Effect of temperature and 5’ nucleotide composition on adenylation efficiency. Oligos were adenylated overnight in the presence of 20% PEG8000 at various temperatures. ( C ) Impact of oligo concentration on adenylation efficiency. Substrates with different concentrations were adenylated overnight with 20% PEG8000 at room temperature. All adenylation products were analyzed on the 20% denatured PAGE, stained with SYBR-Gold and photograph under UV.
Figure Legend Snippet: Adenylation of 3’ adapter using T4 RNA ligase 1. ( A ) Effect of PEG8000 concentration on adenylation efficiency. A synthetic oligo BL1 mimicking the first small RNA cloning linker reported by Lau et al. (2001) was adenylated overnight with 1 U/μL T4 RNA ligase at various PEG concentration. Non-adenylated oligo as the negative control (NC) is loaded on the left lane. ( B ) Effect of temperature and 5’ nucleotide composition on adenylation efficiency. Oligos were adenylated overnight in the presence of 20% PEG8000 at various temperatures. ( C ) Impact of oligo concentration on adenylation efficiency. Substrates with different concentrations were adenylated overnight with 20% PEG8000 at room temperature. All adenylation products were analyzed on the 20% denatured PAGE, stained with SYBR-Gold and photograph under UV.

Techniques Used: Concentration Assay, Clone Assay, Negative Control, Polyacrylamide Gel Electrophoresis, Staining

5) Product Images from "A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations"

Article Title: A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations

Journal: TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik

doi: 10.1007/s00122-016-2736-9

Workflow of modified RAD-seq library construction. a shearing the cellular DNA into fragments, b ligating the adapters to fragment ends, c pooling of samples and fragment size selection, d second round of digestion to remove the DNA fragments from rRNA genes and chloroplast sequence, e PCR amplification, f second round of fragment size selection
Figure Legend Snippet: Workflow of modified RAD-seq library construction. a shearing the cellular DNA into fragments, b ligating the adapters to fragment ends, c pooling of samples and fragment size selection, d second round of digestion to remove the DNA fragments from rRNA genes and chloroplast sequence, e PCR amplification, f second round of fragment size selection

Techniques Used: Modification, Selection, Sequencing, Polymerase Chain Reaction, Amplification

6) Product Images from "A high throughput screen for active human transposable elements"

Article Title: A high throughput screen for active human transposable elements

Journal: BMC Genomics

doi: 10.1186/s12864-018-4485-4

TE-NGS sequencing workflow. Enrichment for genomic fragments spanning active TEs and their unique flanking sequence is achieved by several enzymatic steps as described in the main text. First, genomic DNA is sheared, and adapters for sequencing are ligated to the genomic fragments following standard library preparation protocols. Next, a small aliquot (10 ng) of library is used as template for targeted amplification with primers complementary to TE subfamily-specific sequences and to the Illumina Universal PCR (P5) primer. Remaining genomic background fragments and inverted TEs in head-to-head orientation are removed by ssDNA exonuclease digestion after linear PCR amplification with TE-target primers or Illumina Universal primer, respectively. Last, amplification with nested primers targeting TE diagnostic bases, and containing Illumina i7 index and P7 primer sequences generates full double-stranded dual-adapter libraries containing unique indices for each sample and each TE subfamily, allowing for downstream pooling and multiplexing of many samples simultaneously. High throughput sequencing followed by alignment to the reference genome demarcates the TE insertion site by its 3′ end (read 2) and unique flanking sequence (read 1). TE insertions present in the reference genome can be identified by clustering of read pairs, whereas read 2 generated from polymorphic or novel TE insertions absent from the reference will map with lower quality and/or not at all; these TE can be identified by clusters of read 1 alone (see Methods; Supplemental Material for detailed procedures)
Figure Legend Snippet: TE-NGS sequencing workflow. Enrichment for genomic fragments spanning active TEs and their unique flanking sequence is achieved by several enzymatic steps as described in the main text. First, genomic DNA is sheared, and adapters for sequencing are ligated to the genomic fragments following standard library preparation protocols. Next, a small aliquot (10 ng) of library is used as template for targeted amplification with primers complementary to TE subfamily-specific sequences and to the Illumina Universal PCR (P5) primer. Remaining genomic background fragments and inverted TEs in head-to-head orientation are removed by ssDNA exonuclease digestion after linear PCR amplification with TE-target primers or Illumina Universal primer, respectively. Last, amplification with nested primers targeting TE diagnostic bases, and containing Illumina i7 index and P7 primer sequences generates full double-stranded dual-adapter libraries containing unique indices for each sample and each TE subfamily, allowing for downstream pooling and multiplexing of many samples simultaneously. High throughput sequencing followed by alignment to the reference genome demarcates the TE insertion site by its 3′ end (read 2) and unique flanking sequence (read 1). TE insertions present in the reference genome can be identified by clustering of read pairs, whereas read 2 generated from polymorphic or novel TE insertions absent from the reference will map with lower quality and/or not at all; these TE can be identified by clusters of read 1 alone (see Methods; Supplemental Material for detailed procedures)

Techniques Used: Next-Generation Sequencing, Sequencing, Amplification, Polymerase Chain Reaction, Diagnostic Assay, Multiplexing, Generated

7) Product Images from "Reference genome-independent assessment of mutation density using restriction enzyme-phased sequencing"

Article Title: Reference genome-independent assessment of mutation density using restriction enzyme-phased sequencing

Journal: BMC Genomics

doi: 10.1186/1471-2164-13-72

Confirmation of SNP detected by the RESCAN type I approach . A. RESCAN type I SNP can be identified in sites that are found for the target restriction site in the query (in this case IR64) but are absent in the reference. In most cases, examination of the reference sequence reveals the presence of a proto sequence, i.e. a sequence that diverges by one base from the expected sequence TTAA: VTAA, TVAA, TTBA, TTAB, where V and B are, respectively, not T and not A. For a proto such as GTAA, a T > G SNP is inferred. A SNP cannot be inferred for a proto site such as TTTAG since either T3 > A or G5 > A could have produced the MseI site. B. We chose 20 type I sites that allowed inference and were detected through 1 or 2 RESCAN reads. The products amplified using flanking PCR primers from Nipponbare and IR64 are shown. C. The amplified products were subjected to digestion with MseI and analyzed by agarose gel electrophoresis. The presence of an extra restriction site in the amplified IR64 DNA and not in the control Nipponbare is evident in 17 of the 19 amplified products, confirming the presence of a SNP producing a restriction site in IR64.
Figure Legend Snippet: Confirmation of SNP detected by the RESCAN type I approach . A. RESCAN type I SNP can be identified in sites that are found for the target restriction site in the query (in this case IR64) but are absent in the reference. In most cases, examination of the reference sequence reveals the presence of a proto sequence, i.e. a sequence that diverges by one base from the expected sequence TTAA: VTAA, TVAA, TTBA, TTAB, where V and B are, respectively, not T and not A. For a proto such as GTAA, a T > G SNP is inferred. A SNP cannot be inferred for a proto site such as TTTAG since either T3 > A or G5 > A could have produced the MseI site. B. We chose 20 type I sites that allowed inference and were detected through 1 or 2 RESCAN reads. The products amplified using flanking PCR primers from Nipponbare and IR64 are shown. C. The amplified products were subjected to digestion with MseI and analyzed by agarose gel electrophoresis. The presence of an extra restriction site in the amplified IR64 DNA and not in the control Nipponbare is evident in 17 of the 19 amplified products, confirming the presence of a SNP producing a restriction site in IR64.

Techniques Used: Sequencing, Produced, Amplification, Polymerase Chain Reaction, Agarose Gel Electrophoresis

8) Product Images from "YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs"

Article Title: YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkx005

Adapter-tRNA ligation efficiencies with a conventional method and YAMAT-seq. ( A ) Schematic representation of the adapter ligation reactions used in the conventional and YAMAT-seq methods. In the conventional method, tRNA was subjected to 3΄-adapter (3΄-AD) and 5΄-adapter (5΄-AD) ligations catalyzed by truncated Rnl2 and Rnl1, respectively, using the Illumina TruSeq Small RNA Sample Preparation Kit. In contrast, in the YAMAT-seq method, a Y-shaped adapter (Y-AD) is ligated to a tRNA by Rnl2. ( B ) Ligation products of synthetic human cyto tRNA AspGUC and 5΄-AD or 3΄-AD were quantified by real-time qRT-PCR. The amounts of ligation products were determined based on standard curves, and ligation efficiencies were calculated as percentages of ligated tRNA versus input tRNA (set as 100%). Each data set represents the average of three independent experiments with bars showing the SD. ( C ) Ligation products of the indicated native cyto tRNAs in BT-474 total RNA and 5΄-AD or 3΄-AD were quantified by real-time qRT-PCR. Each data set represents the average Ct values of three independent experiments with bars showing the SD. ( D ) Image of 8% native polyacrylamide gel electrophoresis (PAGE) of amplified cDNAs resulting from BT-474 total RNA sequencing by conventional and YAMAT-seq procedures. The total adapter lengths of the conventional and YAMAT-seq procedures are 118 and 140 bp, respectively. The YAMAT-seq-derived cDNAs in the designated Bands 1–3 regions were gel-purified and subjected to cloning; the identified sequences are shown in Supplementary Table S1 . The cDNAs in regions designated with gray lines are expected to contain tRNA fraction.
Figure Legend Snippet: Adapter-tRNA ligation efficiencies with a conventional method and YAMAT-seq. ( A ) Schematic representation of the adapter ligation reactions used in the conventional and YAMAT-seq methods. In the conventional method, tRNA was subjected to 3΄-adapter (3΄-AD) and 5΄-adapter (5΄-AD) ligations catalyzed by truncated Rnl2 and Rnl1, respectively, using the Illumina TruSeq Small RNA Sample Preparation Kit. In contrast, in the YAMAT-seq method, a Y-shaped adapter (Y-AD) is ligated to a tRNA by Rnl2. ( B ) Ligation products of synthetic human cyto tRNA AspGUC and 5΄-AD or 3΄-AD were quantified by real-time qRT-PCR. The amounts of ligation products were determined based on standard curves, and ligation efficiencies were calculated as percentages of ligated tRNA versus input tRNA (set as 100%). Each data set represents the average of three independent experiments with bars showing the SD. ( C ) Ligation products of the indicated native cyto tRNAs in BT-474 total RNA and 5΄-AD or 3΄-AD were quantified by real-time qRT-PCR. Each data set represents the average Ct values of three independent experiments with bars showing the SD. ( D ) Image of 8% native polyacrylamide gel electrophoresis (PAGE) of amplified cDNAs resulting from BT-474 total RNA sequencing by conventional and YAMAT-seq procedures. The total adapter lengths of the conventional and YAMAT-seq procedures are 118 and 140 bp, respectively. The YAMAT-seq-derived cDNAs in the designated Bands 1–3 regions were gel-purified and subjected to cloning; the identified sequences are shown in Supplementary Table S1 . The cDNAs in regions designated with gray lines are expected to contain tRNA fraction.

Techniques Used: Ligation, Sample Prep, Quantitative RT-PCR, Polyacrylamide Gel Electrophoresis, Amplification, RNA Sequencing Assay, Derivative Assay, Purification, Clone Assay

Schematic representation of mature tRNA sequencing by YAMAT-seq. Initially, amino acids at the 3΄-ends of mature aminoacylated tRNAs are removed by deacylation treatment. A DNA/RNA hybrid Y-shaped adapter is then specifically hybridized to these deacylated mature tRNAs. The bold line regions of the adapter contain identical sequences to those used for Illumina sequencing. Following hybridization, Rnl2 ligates nicks between the adapter and mature tRNA, and the resultant ligation product is amplified, gel-purified and subjected to Illumina sequencing.
Figure Legend Snippet: Schematic representation of mature tRNA sequencing by YAMAT-seq. Initially, amino acids at the 3΄-ends of mature aminoacylated tRNAs are removed by deacylation treatment. A DNA/RNA hybrid Y-shaped adapter is then specifically hybridized to these deacylated mature tRNAs. The bold line regions of the adapter contain identical sequences to those used for Illumina sequencing. Following hybridization, Rnl2 ligates nicks between the adapter and mature tRNA, and the resultant ligation product is amplified, gel-purified and subjected to Illumina sequencing.

Techniques Used: Sequencing, Hybridization, Ligation, Amplification, Purification

9) Product Images from "NGS-based biodiversity and community structure analysis of meiofaunal eukaryotes in shell sand from Hållö island, Smögen, and soft mud from Gullmarn Fjord, Sweden"

Article Title: NGS-based biodiversity and community structure analysis of meiofaunal eukaryotes in shell sand from Hållö island, Smögen, and soft mud from Gullmarn Fjord, Sweden

Journal: Biodiversity Data Journal

doi: 10.3897/BDJ.5.e12731

Beta diversity PCoA plots for COI and 18S datasets including unassigned OTUs. According to extraction method for COI (A) 18S (B) HI flotation in red, HI MgCl2 in blue, GF flotation in yellow and GF siphoning in green. According to primer for COI (C) COI Leray primer in red, COI Lobo primer in blue
Figure Legend Snippet: Beta diversity PCoA plots for COI and 18S datasets including unassigned OTUs. According to extraction method for COI (A) 18S (B) HI flotation in red, HI MgCl2 in blue, GF flotation in yellow and GF siphoning in green. According to primer for COI (C) COI Leray primer in red, COI Lobo primer in blue

Techniques Used:

Alpha diversity rarefaction plots for COI and 18S datasets including unassigned OTUs. According to location for COI (A) 18S (B). Hållö Island (HI) in red, Gullmarn Fjord (GF) in blue. According to extraction method for COI (C) 18S (D). HI flotation in red, HI MgCl2 in blue, GF flotation in yellow, GF siphoning in green. According to primer pair for COI (E). CO1 Leray primer in red, COI Lobo primer in blue.
Figure Legend Snippet: Alpha diversity rarefaction plots for COI and 18S datasets including unassigned OTUs. According to location for COI (A) 18S (B). Hållö Island (HI) in red, Gullmarn Fjord (GF) in blue. According to extraction method for COI (C) 18S (D). HI flotation in red, HI MgCl2 in blue, GF flotation in yellow, GF siphoning in green. According to primer pair for COI (E). CO1 Leray primer in red, COI Lobo primer in blue.

Techniques Used:

10) Product Images from "NGS-based biodiversity and community structure analysis of meiofaunal eukaryotes in shell sand from Hållö island, Smögen, and soft mud from Gullmarn Fjord, Sweden"

Article Title: NGS-based biodiversity and community structure analysis of meiofaunal eukaryotes in shell sand from Hållö island, Smögen, and soft mud from Gullmarn Fjord, Sweden

Journal: Biodiversity Data Journal

doi: 10.3897/BDJ.5.e12731

Beta diversity PCoA plots for COI and 18S datasets including unassigned OTUs. According to extraction method for COI (A) 18S (B) HI flotation in red, HI MgCl2 in blue, GF flotation in yellow and GF siphoning in green. According to primer for COI (C) COI Leray primer in red, COI Lobo primer in blue
Figure Legend Snippet: Beta diversity PCoA plots for COI and 18S datasets including unassigned OTUs. According to extraction method for COI (A) 18S (B) HI flotation in red, HI MgCl2 in blue, GF flotation in yellow and GF siphoning in green. According to primer for COI (C) COI Leray primer in red, COI Lobo primer in blue

Techniques Used:

Alpha diversity rarefaction plots for COI and 18S datasets including unassigned OTUs. According to location for COI (A) 18S (B). Hållö Island (HI) in red, Gullmarn Fjord (GF) in blue. According to extraction method for COI (C) 18S (D). HI flotation in red, HI MgCl2 in blue, GF flotation in yellow, GF siphoning in green. According to primer pair for COI (E). CO1 Leray primer in red, COI Lobo primer in blue.
Figure Legend Snippet: Alpha diversity rarefaction plots for COI and 18S datasets including unassigned OTUs. According to location for COI (A) 18S (B). Hållö Island (HI) in red, Gullmarn Fjord (GF) in blue. According to extraction method for COI (C) 18S (D). HI flotation in red, HI MgCl2 in blue, GF flotation in yellow, GF siphoning in green. According to primer pair for COI (E). CO1 Leray primer in red, COI Lobo primer in blue.

Techniques Used:

11) Product Images from "Structure-seq2: sensitive and accurate genome-wide profiling of RNA structure in vivo"

Article Title: Structure-seq2: sensitive and accurate genome-wide profiling of RNA structure in vivo

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkx533

Structure-seq2 leads to a lower ligation bias. ( A ) After RT (Figure 1 , step 1A/1B), excess of the 27 nt primer (blue, top, right) is still present in the solution. During ligation (Figure 1 , step 3A/3B), this primer can also ligate to the 40 nt hairpin adaptor (pink) to form an unwanted 67 nt by-product which has no insert and so results in sequencing reads with no utility. ( B ) The complement of the first nucleotide after the adaptor sequence read during sequencing is the nucleotide that ligated to the adaptor. Our new T4 DNA ligase-based method (green, –DMS and pink, +DMS) substantially decreases ligation bias as compared to the previous Circligase-based method (blue). Percentages equaling the transcriptomic distribution of the four nucleotides (black) are ideal.
Figure Legend Snippet: Structure-seq2 leads to a lower ligation bias. ( A ) After RT (Figure 1 , step 1A/1B), excess of the 27 nt primer (blue, top, right) is still present in the solution. During ligation (Figure 1 , step 3A/3B), this primer can also ligate to the 40 nt hairpin adaptor (pink) to form an unwanted 67 nt by-product which has no insert and so results in sequencing reads with no utility. ( B ) The complement of the first nucleotide after the adaptor sequence read during sequencing is the nucleotide that ligated to the adaptor. Our new T4 DNA ligase-based method (green, –DMS and pink, +DMS) substantially decreases ligation bias as compared to the previous Circligase-based method (blue). Percentages equaling the transcriptomic distribution of the four nucleotides (black) are ideal.

Techniques Used: Ligation, Sequencing

Two versions of Structure-seq2 produce high quality data. In Structure-seq2, RNA (kelly green) is first modified by DMS or another chemical that can be read-out through reverse transcription. The RNA is then prepared for Illumina NGS sequencing by conversion to cDNA (Step 1A/1B, blue), ligating an adaptor (Step 3A/3B), and amplifying the products while incorporating TruSeq primer sequences (Step 5A/5B). In order to increase library quality, numerous improvements were made to the original Structure-seq protocol (boxed). These include performing the ligation with a hairpin adaptor and T4 DNA ligase (Step 3A/3B; pink) ( 10 ), and adding various purification steps to remove a deleterious by-product (Figure 2A ). We present two options for purification: PAGE purification ( A ) or a biotin–streptavidin pull down ( B ). In the PAGE purification method, an additional PAGE purification step is added after reverse transcription (Step 2A). In the biotin–streptavidin pull down method, biotinylated dNTPs (cyan) are incorporated into the extended product during reverse transcription (Step 1B) and are purified via a magnetic streptavidin pull down after reverse transcription (Step 2B) and after ligation (Step 4B). There is also a common, final PAGE purification step following amplification (Step 5A/5B). Finally, a custom sequencing primer (light green) is used during sequencing (Step 7A/7B) to further provide high quality data. Supplementary Figure S1 is a version of this figure with all the nucleotides shown explicitly.
Figure Legend Snippet: Two versions of Structure-seq2 produce high quality data. In Structure-seq2, RNA (kelly green) is first modified by DMS or another chemical that can be read-out through reverse transcription. The RNA is then prepared for Illumina NGS sequencing by conversion to cDNA (Step 1A/1B, blue), ligating an adaptor (Step 3A/3B), and amplifying the products while incorporating TruSeq primer sequences (Step 5A/5B). In order to increase library quality, numerous improvements were made to the original Structure-seq protocol (boxed). These include performing the ligation with a hairpin adaptor and T4 DNA ligase (Step 3A/3B; pink) ( 10 ), and adding various purification steps to remove a deleterious by-product (Figure 2A ). We present two options for purification: PAGE purification ( A ) or a biotin–streptavidin pull down ( B ). In the PAGE purification method, an additional PAGE purification step is added after reverse transcription (Step 2A). In the biotin–streptavidin pull down method, biotinylated dNTPs (cyan) are incorporated into the extended product during reverse transcription (Step 1B) and are purified via a magnetic streptavidin pull down after reverse transcription (Step 2B) and after ligation (Step 4B). There is also a common, final PAGE purification step following amplification (Step 5A/5B). Finally, a custom sequencing primer (light green) is used during sequencing (Step 7A/7B) to further provide high quality data. Supplementary Figure S1 is a version of this figure with all the nucleotides shown explicitly.

Techniques Used: Modification, Next-Generation Sequencing, Sequencing, Ligation, Purification, Polyacrylamide Gel Electrophoresis, Amplification

Structure-seq2 identifies a previously unreported m 1 A in 25S rRNA. ( A ) Using the original Structure-seq method for RT denaturation (65°C with no monovalent salt), there are regions that receive no reads (denoted with arrows). ( B ) Increasing the denaturation conditions (90°C with monovalent salt) allows these regions to be read (denoted with color-matched arrows) and narrows regions of low read depth. Total number of reads is similar in panels a and b. Location of the large drop in reads downstream of the single region in 25S that remains absent of reads (red arrow) corresponds to a site known to contain a m 1 A in yeast, human, and H. marismortui ( C , Supplementary Figure S13 ) ( 16 , 18 ). Reads continue to decrease until they go to zero at nucleotide 539. The region between nucleotides 432 and 644 is 79% GC-rich with a read depth
Figure Legend Snippet: Structure-seq2 identifies a previously unreported m 1 A in 25S rRNA. ( A ) Using the original Structure-seq method for RT denaturation (65°C with no monovalent salt), there are regions that receive no reads (denoted with arrows). ( B ) Increasing the denaturation conditions (90°C with monovalent salt) allows these regions to be read (denoted with color-matched arrows) and narrows regions of low read depth. Total number of reads is similar in panels a and b. Location of the large drop in reads downstream of the single region in 25S that remains absent of reads (red arrow) corresponds to a site known to contain a m 1 A in yeast, human, and H. marismortui ( C , Supplementary Figure S13 ) ( 16 , 18 ). Reads continue to decrease until they go to zero at nucleotide 539. The region between nucleotides 432 and 644 is 79% GC-rich with a read depth

Techniques Used:

Structure-seq2 demonstrates the presence of two hidden breaks in chloroplast rRNA. At the two locations known to harbor hidden breaks in chloroplast rRNA, the –DMS RT stop count data spike. The spike at the first hidden break ( A ) differs by one nucleotide from the published break site in spinach and Arabidopsis ( 21 , 28 ), which could be due to the slight sequence variation between species (Arabidopsis: 5′-GGGAGUGAAA*UAGAACA-3′, Rice: 5′-GGGUAGUGAAAU*AGAACG-3′, where * indicates the proposed break site). The spike at the second hidden break ( B ) occurs precisely at the published cleavage site for spinach and Arabidopsis ( 21 , 28 ).
Figure Legend Snippet: Structure-seq2 demonstrates the presence of two hidden breaks in chloroplast rRNA. At the two locations known to harbor hidden breaks in chloroplast rRNA, the –DMS RT stop count data spike. The spike at the first hidden break ( A ) differs by one nucleotide from the published break site in spinach and Arabidopsis ( 21 , 28 ), which could be due to the slight sequence variation between species (Arabidopsis: 5′-GGGAGUGAAA*UAGAACA-3′, Rice: 5′-GGGUAGUGAAAU*AGAACG-3′, where * indicates the proposed break site). The spike at the second hidden break ( B ) occurs precisely at the published cleavage site for spinach and Arabidopsis ( 21 , 28 ).

Techniques Used: Sequencing

12) Product Images from "Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA"

Article Title: Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA

Journal: Epigenetics & Chromatin

doi: 10.1186/s13072-017-0123-7

hMeDIP-seq hydroxymethylation profiling in cell line DNA. a Scatter plot showing the correlation between hMeDIP-seq replicates in LNCaP cells. For each genomic tile from one replicate the average enrichment score for the second replicate was calculated. Each dot represents one genomic tile. b Scatter plot showing the correlation between hMeDIP-seq in LNCaP cells and public hMeDIP-seq in MCF7 cells. c Scatter plot showing the correlation between hMeDIP-seq in LNCaP cells and brain hMeDIP-seq. d Genomic region showing the correspondence of hMeDIP-seq replicates in LNCaP cells as well as MCF7 cells. e Density plot showing the distribution of p Bis − p OxBis values in the Brain versus LNCaP WG Bis/OxBis data. f The percentages of significantly hydroxymethylated CpGs of all CpGs with at least 10× coverage on the WG Bis/OxBis in the Brain versus LNCaP. g Density plot showing the distribution of p Bis − p OxBis values in the Brain versus LNCaP HM450K Bis/OxBis data. h The percentages of significantly hydroxymethylated CpGs of all CpGs with at least 10× coverage on the HM450K Bis/OxBis in the Brain versus LNCaP
Figure Legend Snippet: hMeDIP-seq hydroxymethylation profiling in cell line DNA. a Scatter plot showing the correlation between hMeDIP-seq replicates in LNCaP cells. For each genomic tile from one replicate the average enrichment score for the second replicate was calculated. Each dot represents one genomic tile. b Scatter plot showing the correlation between hMeDIP-seq in LNCaP cells and public hMeDIP-seq in MCF7 cells. c Scatter plot showing the correlation between hMeDIP-seq in LNCaP cells and brain hMeDIP-seq. d Genomic region showing the correspondence of hMeDIP-seq replicates in LNCaP cells as well as MCF7 cells. e Density plot showing the distribution of p Bis − p OxBis values in the Brain versus LNCaP WG Bis/OxBis data. f The percentages of significantly hydroxymethylated CpGs of all CpGs with at least 10× coverage on the WG Bis/OxBis in the Brain versus LNCaP. g Density plot showing the distribution of p Bis − p OxBis values in the Brain versus LNCaP HM450K Bis/OxBis data. h The percentages of significantly hydroxymethylated CpGs of all CpGs with at least 10× coverage on the HM450K Bis/OxBis in the Brain versus LNCaP

Techniques Used:

The workflow of conventional bisulphite (Bis), oxidative bisulphite (OxBis) and TET-assisted bisulphite (TAB) approaches for the detection of 5mC and 5hmC. Bisulphite treatment alone results in the conversion of unmethylated cytosine into uracil that will be read as thymine after PCR amplification, with both 5mC and 5hmC being read as cytosine. The readout of Bis is denoted as 5modC (5mC + 5hmC). The addition of an oxidation step prior to bisulphite treatment results in the conversion of 5hmC to 5fC that will be converted to uracil together with an unmethylated cytosine. Thus, the readout of OxBis is 5mC. In TAB, the first step involves β-glucosyltransferase-mediated protection of 5hmC with a glucose moiety, followed by TET-mediated oxidation of 5mC to 5caC, which will be converted to uracil. Thus, the readout of TAB is 5hmC
Figure Legend Snippet: The workflow of conventional bisulphite (Bis), oxidative bisulphite (OxBis) and TET-assisted bisulphite (TAB) approaches for the detection of 5mC and 5hmC. Bisulphite treatment alone results in the conversion of unmethylated cytosine into uracil that will be read as thymine after PCR amplification, with both 5mC and 5hmC being read as cytosine. The readout of Bis is denoted as 5modC (5mC + 5hmC). The addition of an oxidation step prior to bisulphite treatment results in the conversion of 5hmC to 5fC that will be converted to uracil together with an unmethylated cytosine. Thus, the readout of OxBis is 5mC. In TAB, the first step involves β-glucosyltransferase-mediated protection of 5hmC with a glucose moiety, followed by TET-mediated oxidation of 5mC to 5caC, which will be converted to uracil. Thus, the readout of TAB is 5hmC

Techniques Used: Polymerase Chain Reaction, Amplification

DNA methylation and hydroxymethylation profiling by whole-genome Bis-seq/OxBis-seq. a Methylation density plot showing the distribution of 5hmC and 5modC levels. Both 5modC and 5hmC density plots include CpG sites showing significant hydroxymethylation. b The relationship between the hydroxymethylated fraction and total methylation levels at each CpG site. CpG sites were binned into groups based on the total methylation levels, and the distribution of hydroxymethylation levels was calculated for each of these groups. c Bar plot showing observed over expected by chance enrichment of CpGs with different 5hmC levels at multiple genomic locations. Genomic regions comprise of Brain Frontal Lobe ChromHMM features as well as CpG islands and CpG island shores. d The percentage of genomic regions harbouring no hydroxymethylated CpG sites ( grey ) and those harbouring at least one hydroxymethylated CpG site ( blue ). e The proportion of hydroxymethylated CpGs of the total number of CpGs per genomic region. For each region, the total number of CpGs and number of hydroxymethylated CpGs were calculated (Additional file 2 : Figure S1D). From that, for each region, the percentage of hydroxymethylated CpGs of all CpGs was calculated and distribution of those percentages was plotted. f The distribution of the total number of CpG sites and the number of hydroxymethylated CpG sites per genomic region. g The relationship between average total methylation (5modC) ( x -axis) and average hydroxymethylation (5hmC) ( y -axis) at different genomic regions. Each dot represents a single region. Hydroxymethylation levels of CpG sites that did not pass the statistical significance criteria were assigned to zero. h The hydroxymethylation contribution to the average total methylation at different genomic regions. For each genomic region, the percentage of hydroxymethylation contribution to the total methylation was calculated; the numbers of regions with the corresponding 5hmC contribution were plotted
Figure Legend Snippet: DNA methylation and hydroxymethylation profiling by whole-genome Bis-seq/OxBis-seq. a Methylation density plot showing the distribution of 5hmC and 5modC levels. Both 5modC and 5hmC density plots include CpG sites showing significant hydroxymethylation. b The relationship between the hydroxymethylated fraction and total methylation levels at each CpG site. CpG sites were binned into groups based on the total methylation levels, and the distribution of hydroxymethylation levels was calculated for each of these groups. c Bar plot showing observed over expected by chance enrichment of CpGs with different 5hmC levels at multiple genomic locations. Genomic regions comprise of Brain Frontal Lobe ChromHMM features as well as CpG islands and CpG island shores. d The percentage of genomic regions harbouring no hydroxymethylated CpG sites ( grey ) and those harbouring at least one hydroxymethylated CpG site ( blue ). e The proportion of hydroxymethylated CpGs of the total number of CpGs per genomic region. For each region, the total number of CpGs and number of hydroxymethylated CpGs were calculated (Additional file 2 : Figure S1D). From that, for each region, the percentage of hydroxymethylated CpGs of all CpGs was calculated and distribution of those percentages was plotted. f The distribution of the total number of CpG sites and the number of hydroxymethylated CpG sites per genomic region. g The relationship between average total methylation (5modC) ( x -axis) and average hydroxymethylation (5hmC) ( y -axis) at different genomic regions. Each dot represents a single region. Hydroxymethylation levels of CpG sites that did not pass the statistical significance criteria were assigned to zero. h The hydroxymethylation contribution to the average total methylation at different genomic regions. For each genomic region, the percentage of hydroxymethylation contribution to the total methylation was calculated; the numbers of regions with the corresponding 5hmC contribution were plotted

Techniques Used: DNA Methylation Assay, Methylation

Comparative evaluation of HM450K Bis/OxBis and whole-genome Bis-/OxBis-seq for 5hmC profiling. a Scatter plots showing the correlation of 5modC (Bis, left ), 5mC (OxBis, middle ) and 5hmC (Bis-OxBis, right ) between WG and HM450K Bis/OxBis across CpG sites ( n = 42,537) considered as significantly hydroxymethylated by both approaches. Spearman’s correlation is indicated on each scatter plot . b The agreement in 5modC, 5mC and 5hmC levels detected by WG and HM450K Bis/OxBis as a function of WG sequencing coverage. The difference in methylation calling is plotted along the y -axis for each bin with defined sequencing coverage indicated ( > 10×, > 20×, > 30×– > 60×). Green lines indicate ± 5% difference in methylation value detected between approaches (WG-HM450K). c Venn diagrams show the overlap of hydroxymethylated regions between WG and HM450K Bis/OxBis. Genomic regions with at least one CpG probe and at least 10× WG sequencing coverage were chosen for this analysis (11,625 of 25,235 total TssA; 14,945 of 27,078 total TssA_Flnk; 22,249 of 26,707 total Tx; 47,082 of 73,063 total Enh). Of those, the number of regions with at least one hydroxymethylated CpG according to HM450K only, WG only or both approaches was calculated and overlap was plotted. d The distribution of maximal hydroxymethylation values at the regions identified as hydroxymethylated according to the HM450K only ( yellow ) and according to the both WG and HM450K ( green ). For the active promoters (TssA), the median of the max(5hmC) distribution is 0.067 for the yellow group and 0.147 for the green group. For the regions flanking active promoters (TssA Flank), the median of the max(5hmC) distribution is 0.105 for the yellow group and 0.167 for the green group. The difference between the distributions of maximal 5hmC values between yellow and green groups of regions is statistically significant as determined by Kruskal–Wallis nonparametric test ( p
Figure Legend Snippet: Comparative evaluation of HM450K Bis/OxBis and whole-genome Bis-/OxBis-seq for 5hmC profiling. a Scatter plots showing the correlation of 5modC (Bis, left ), 5mC (OxBis, middle ) and 5hmC (Bis-OxBis, right ) between WG and HM450K Bis/OxBis across CpG sites ( n = 42,537) considered as significantly hydroxymethylated by both approaches. Spearman’s correlation is indicated on each scatter plot . b The agreement in 5modC, 5mC and 5hmC levels detected by WG and HM450K Bis/OxBis as a function of WG sequencing coverage. The difference in methylation calling is plotted along the y -axis for each bin with defined sequencing coverage indicated ( > 10×, > 20×, > 30×– > 60×). Green lines indicate ± 5% difference in methylation value detected between approaches (WG-HM450K). c Venn diagrams show the overlap of hydroxymethylated regions between WG and HM450K Bis/OxBis. Genomic regions with at least one CpG probe and at least 10× WG sequencing coverage were chosen for this analysis (11,625 of 25,235 total TssA; 14,945 of 27,078 total TssA_Flnk; 22,249 of 26,707 total Tx; 47,082 of 73,063 total Enh). Of those, the number of regions with at least one hydroxymethylated CpG according to HM450K only, WG only or both approaches was calculated and overlap was plotted. d The distribution of maximal hydroxymethylation values at the regions identified as hydroxymethylated according to the HM450K only ( yellow ) and according to the both WG and HM450K ( green ). For the active promoters (TssA), the median of the max(5hmC) distribution is 0.067 for the yellow group and 0.147 for the green group. For the regions flanking active promoters (TssA Flank), the median of the max(5hmC) distribution is 0.105 for the yellow group and 0.167 for the green group. The difference between the distributions of maximal 5hmC values between yellow and green groups of regions is statistically significant as determined by Kruskal–Wallis nonparametric test ( p

Techniques Used: Sequencing, Methylation

DNA methylation and hydroxymethylation profiling by HM450K Bis/OxBis. a Scatter plots showing the high correlation between HM450K Bis ( left ) and HM450K OxBis ( right ) replicates. Each dot (smoothed) reflects each probe 5modC ( left ) or 5mC ( right ) levels detected by two technical replicates ( x- and y -axes). Spearman’s correlation 0.987406 ( left ) and 0.985664 ( right ), respectively. b , c 5hmC and 5modC MiSeq amplicon validation of candidate loci using Bis- and TAB-Seq. b Scatter plots showing the correlation of 5modC ( left ) and 5hmC ( right ) levels between HM450K and amplicon Bis- and TAB-seq. Each dot represents single CpG site/probe. The pink and blue regression lines show the intercept and slope of the plots. c HM450K screen shots of candidate regions, showing 450K_5hmC, 450K_Bis, 450K_OxBis. Amplicon validation of these genomic regions shows agreement in total methylation (5modC) and hydroxymethylation levels detected by HM450K Bis/OxBis and loci-specific Bis/TAB-seq, respectively. Red dots depict 5modC ( top ) and 5hmC ( bottom ) levels of each CpG site detected by loci-specific Bis-/TAB-seq, respectively. Green dots depict 5modC ( top ) and 5hmC ( bottom ) levels of HM450K CpG probes on the array. d The relationship between hydroxymethylation and different levels of total methylation detected by HM450K. CpG probes were binned into groups based on the total methylation levels, and the distribution of hydroxymethylation levels was calculated for each of these groups. e Bar plot showing observed over expected by chance enrichment of CpGs with different 5hmC levels (0–10, 10–20, 20–30, > 30%) at multiple genomic locations; computationally derived chromatin segmentation (ChromHMM) of Brain Frontal Lobe genome, as well as CpG islands and CpG island shores. f Pie charts showing the proportion of genomic regions defined as hydroxymethylated by HM450K Bis/OxBis compared to the total number defined as hydroxymethylated according to the WG Bis/OxBis-seq. A region is considered hydroxymethylated if it contains > 1 significantly hydroxymethylated CpG site
Figure Legend Snippet: DNA methylation and hydroxymethylation profiling by HM450K Bis/OxBis. a Scatter plots showing the high correlation between HM450K Bis ( left ) and HM450K OxBis ( right ) replicates. Each dot (smoothed) reflects each probe 5modC ( left ) or 5mC ( right ) levels detected by two technical replicates ( x- and y -axes). Spearman’s correlation 0.987406 ( left ) and 0.985664 ( right ), respectively. b , c 5hmC and 5modC MiSeq amplicon validation of candidate loci using Bis- and TAB-Seq. b Scatter plots showing the correlation of 5modC ( left ) and 5hmC ( right ) levels between HM450K and amplicon Bis- and TAB-seq. Each dot represents single CpG site/probe. The pink and blue regression lines show the intercept and slope of the plots. c HM450K screen shots of candidate regions, showing 450K_5hmC, 450K_Bis, 450K_OxBis. Amplicon validation of these genomic regions shows agreement in total methylation (5modC) and hydroxymethylation levels detected by HM450K Bis/OxBis and loci-specific Bis/TAB-seq, respectively. Red dots depict 5modC ( top ) and 5hmC ( bottom ) levels of each CpG site detected by loci-specific Bis-/TAB-seq, respectively. Green dots depict 5modC ( top ) and 5hmC ( bottom ) levels of HM450K CpG probes on the array. d The relationship between hydroxymethylation and different levels of total methylation detected by HM450K. CpG probes were binned into groups based on the total methylation levels, and the distribution of hydroxymethylation levels was calculated for each of these groups. e Bar plot showing observed over expected by chance enrichment of CpGs with different 5hmC levels (0–10, 10–20, 20–30, > 30%) at multiple genomic locations; computationally derived chromatin segmentation (ChromHMM) of Brain Frontal Lobe genome, as well as CpG islands and CpG island shores. f Pie charts showing the proportion of genomic regions defined as hydroxymethylated by HM450K Bis/OxBis compared to the total number defined as hydroxymethylated according to the WG Bis/OxBis-seq. A region is considered hydroxymethylated if it contains > 1 significantly hydroxymethylated CpG site

Techniques Used: DNA Methylation Assay, Amplification, Methylation, Derivative Assay

13) Product Images from "Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA"

Article Title: Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA

Journal: Epigenetics & Chromatin

doi: 10.1186/s13072-017-0123-7

The workflow of conventional bisulphite (Bis), oxidative bisulphite (OxBis) and TET-assisted bisulphite (TAB) approaches for the detection of 5mC and 5hmC. Bisulphite treatment alone results in the conversion of unmethylated cytosine into uracil that will be read as thymine after PCR amplification, with both 5mC and 5hmC being read as cytosine. The readout of Bis is denoted as 5modC (5mC + 5hmC). The addition of an oxidation step prior to bisulphite treatment results in the conversion of 5hmC to 5fC that will be converted to uracil together with an unmethylated cytosine. Thus, the readout of OxBis is 5mC. In TAB, the first step involves β-glucosyltransferase-mediated protection of 5hmC with a glucose moiety, followed by TET-mediated oxidation of 5mC to 5caC, which will be converted to uracil. Thus, the readout of TAB is 5hmC
Figure Legend Snippet: The workflow of conventional bisulphite (Bis), oxidative bisulphite (OxBis) and TET-assisted bisulphite (TAB) approaches for the detection of 5mC and 5hmC. Bisulphite treatment alone results in the conversion of unmethylated cytosine into uracil that will be read as thymine after PCR amplification, with both 5mC and 5hmC being read as cytosine. The readout of Bis is denoted as 5modC (5mC + 5hmC). The addition of an oxidation step prior to bisulphite treatment results in the conversion of 5hmC to 5fC that will be converted to uracil together with an unmethylated cytosine. Thus, the readout of OxBis is 5mC. In TAB, the first step involves β-glucosyltransferase-mediated protection of 5hmC with a glucose moiety, followed by TET-mediated oxidation of 5mC to 5caC, which will be converted to uracil. Thus, the readout of TAB is 5hmC

Techniques Used: Polymerase Chain Reaction, Amplification

14) Product Images from "Template-switching mechanism of a group II intron-encoded reverse transcriptase and its implications for biological function and RNA-Seq"

Article Title: Template-switching mechanism of a group II intron-encoded reverse transcriptase and its implications for biological function and RNA-Seq

Journal: The Journal of Biological Chemistry

doi: 10.1074/jbc.RA119.011337

Models of template switching and non-templated nucleotide addition reactions. A , template switching to an acceptor RNA from an RNA template/DNA primer heteroduplex with a 1-nt 3′ overhang added by NTA after completion of cDNA synthesis or as an artificial starter duplex. B , NTA to a blunt-end RNA/DNA heteroduplex in the absence of an acceptor nucleic acid. C , template-switching to an acceptor RNA from a blunt-end RNA/DNA heteroduplex without NTA. See under “Discussion” for details.
Figure Legend Snippet: Models of template switching and non-templated nucleotide addition reactions. A , template switching to an acceptor RNA from an RNA template/DNA primer heteroduplex with a 1-nt 3′ overhang added by NTA after completion of cDNA synthesis or as an artificial starter duplex. B , NTA to a blunt-end RNA/DNA heteroduplex in the absence of an acceptor nucleic acid. C , template-switching to an acceptor RNA from a blunt-end RNA/DNA heteroduplex without NTA. See under “Discussion” for details.

Techniques Used:

15) Product Images from "Cost-effective, high-throughput, single-haplotype iterative mapping and sequencing for complex genomic structures"

Article Title: Cost-effective, high-throughput, single-haplotype iterative mapping and sequencing for complex genomic structures

Journal: Nature protocols

doi: 10.1038/nprot.2018.019

Overview of SHIMS 2.0 protocol. A timeline of a single iteration of the SHIMS 2.0 protocol, showing the major protocol steps, with key quality controls on the right. During a single week-long iteration, 192 clones are processed in parallel, and the resulting draft clone sequences are used to identify sequence family variants (SFVs) that distinguish paralogous ampliconic sequences. A single technician can proceed from a list of clones to completed Illumina libraries in 5 days. After a 2-day long MiSeq run, a bioinformatics specialist assembles demultiplexed fastq sequences into draft clone assemblies and identifies SFVs to select clones for the next iteration.
Figure Legend Snippet: Overview of SHIMS 2.0 protocol. A timeline of a single iteration of the SHIMS 2.0 protocol, showing the major protocol steps, with key quality controls on the right. During a single week-long iteration, 192 clones are processed in parallel, and the resulting draft clone sequences are used to identify sequence family variants (SFVs) that distinguish paralogous ampliconic sequences. A single technician can proceed from a list of clones to completed Illumina libraries in 5 days. After a 2-day long MiSeq run, a bioinformatics specialist assembles demultiplexed fastq sequences into draft clone assemblies and identifies SFVs to select clones for the next iteration.

Techniques Used: Clone Assay, Sequencing

16) Product Images from "Establishment of Bacterial Herbicide Degraders in a Rapid Sand Filter for Bioremediation of Phenoxypropionate-Polluted Groundwater"

Article Title: Establishment of Bacterial Herbicide Degraders in a Rapid Sand Filter for Bioremediation of Phenoxypropionate-Polluted Groundwater

Journal: Applied and Environmental Microbiology

doi: 10.1128/AEM.02600-15

Development of the total number of bacteria (A), number of sdpA gene copies (B), and number of rdpA gene copies (C) in the top (black bars) and depth (hatched bars) of the sand filter. The numbers were determined by qPCR of the 16S rRNA, sdpA , and rdpA
Figure Legend Snippet: Development of the total number of bacteria (A), number of sdpA gene copies (B), and number of rdpA gene copies (C) in the top (black bars) and depth (hatched bars) of the sand filter. The numbers were determined by qPCR of the 16S rRNA, sdpA , and rdpA

Techniques Used: Real-time Polymerase Chain Reaction

Composition of bacterial 16S rRNA genes in MPN samples (replicates A, B, and C) prepared from the top and depth of the sand filter at day 14. The key shows the identities of OTUs based on 16S rRNA genes that had an accumulated relative abundance of > 1%
Figure Legend Snippet: Composition of bacterial 16S rRNA genes in MPN samples (replicates A, B, and C) prepared from the top and depth of the sand filter at day 14. The key shows the identities of OTUs based on 16S rRNA genes that had an accumulated relative abundance of > 1%

Techniques Used:

Composition of bacterial 16S rRNA genes in duplicate samples (samples A and B) from the sand filter collected at days 14, 57, and 85. The key shows the identities of the 16S rRNA genes that had an accumulated relative abundance of > 1% across all
Figure Legend Snippet: Composition of bacterial 16S rRNA genes in duplicate samples (samples A and B) from the sand filter collected at days 14, 57, and 85. The key shows the identities of the 16S rRNA genes that had an accumulated relative abundance of > 1% across all

Techniques Used:

17) Product Images from "Hybrid Capture and Next-Generation Sequencing Identify Viral Integration Sites from Formalin-Fixed, Paraffin-Embedded Tissue"

Article Title: Hybrid Capture and Next-Generation Sequencing Identify Viral Integration Sites from Formalin-Fixed, Paraffin-Embedded Tissue

Journal: The Journal of Molecular Diagnostics : JMD

doi: 10.1016/j.jmoldx.2011.01.006

Pictorial representation of Washington University Capture. Washington University Capture (WUCap) enables solution-phase hybridization between double-stranded DNA PCR “bait” and whole-genome shotgun libraries. The solution-phase method we have developed for hybrid capture is robust and involves only a few basic steps. The bait used for targeting is dictated by primer-specific amplification of genomic targets generated during the PCR. Subsequently, the amplicons are used as a template in a second PCR incorporating biotin-14-dCTP. Genomic DNA is prepared from each of the samples to be sequenced, sheared to an average fragment size of 300 bp, enzymatically repaired to blunt the ends, and ligated to Illumina adapter sequences (at both ends). Five hundred nanograms of genomic DNA library is denatured, combined with 100 ng of the biotinylated “bait,” and hybridized for 48 hours. Mixing this hybridization reaction with streptavidin-coated superparamagnetic beads allows binding of biotinylated bait–target hybrids and selective removal from solution by applying a magnet field. The remaining supernatant is removed, and the beads are washed, removing nonspecific DNA. The enriched target sequences are released from the bead-bound bait sequences by denaturation (0.125 N NaOH), neutralized, amplified in the PCR to generate double-stranded Illumina libraries, and then sequenced.
Figure Legend Snippet: Pictorial representation of Washington University Capture. Washington University Capture (WUCap) enables solution-phase hybridization between double-stranded DNA PCR “bait” and whole-genome shotgun libraries. The solution-phase method we have developed for hybrid capture is robust and involves only a few basic steps. The bait used for targeting is dictated by primer-specific amplification of genomic targets generated during the PCR. Subsequently, the amplicons are used as a template in a second PCR incorporating biotin-14-dCTP. Genomic DNA is prepared from each of the samples to be sequenced, sheared to an average fragment size of 300 bp, enzymatically repaired to blunt the ends, and ligated to Illumina adapter sequences (at both ends). Five hundred nanograms of genomic DNA library is denatured, combined with 100 ng of the biotinylated “bait,” and hybridized for 48 hours. Mixing this hybridization reaction with streptavidin-coated superparamagnetic beads allows binding of biotinylated bait–target hybrids and selective removal from solution by applying a magnet field. The remaining supernatant is removed, and the beads are washed, removing nonspecific DNA. The enriched target sequences are released from the bead-bound bait sequences by denaturation (0.125 N NaOH), neutralized, amplified in the PCR to generate double-stranded Illumina libraries, and then sequenced.

Techniques Used: Hybridization, Polymerase Chain Reaction, Amplification, Generated, Binding Assay

18) Product Images from "Facile single-stranded DNA sequencing of human plasma DNA via thermostable group II intron reverse transcriptase template switching"

Article Title: Facile single-stranded DNA sequencing of human plasma DNA via thermostable group II intron reverse transcriptase template switching

Journal: Scientific Reports

doi: 10.1038/s41598-017-09064-w

TGIRT ssDNA-seq workflow. The target DNA (2–50 ng in this work) is treated with alkaline phosphatase to remove 3′ phosphates and heat denatured prior to DNA-seq library construction. The resulting ssDNAs with 3′ OH termini are then used for TGIRT template-switching DNA synthesis coupled to Illumina read 2 reverse (R2R) DNA-seq adapter addition. In this novel reaction, the TGIRT-III enzyme (InGex) binds first to a synthetic 34-bp R2 RNA/R2R DNA heteroduplex in which the R2R DNA primer has a single nucleotide 3′ overhang that can direct TGIRT template switching by base pairing to the 3′ nucleotide of a target DNA strand. For minimally biased library preparation, the 3′-overhang nucleotide is an equimolar mixture of A, C, G, and T (denoted N). A 3′-blocking group (C3 spacer; 3′SpC3) is attached to the end of the R2 RNA oligonucleotide to prevent template-switching to that RNA. After the TGIRT enzyme extends the DNA primer to produce a DNA copy of the target DNA strand with an R2R adapter seamlessly linked to its 5′ end, a 5′ adenylated (App) Illumina read 1 reverse (R1R) adapter is added to its 3′ end by single-stranded DNA ligation using a Thermostable 5′ AppDNA/RNA ligase (New England Biolabs). In the workflow shown, an unique molecular identifier (UMI) is positioned at the 5′ end of the R1R DNA oligonucleotide. A final PCR step adds flow cell capture sites and barcodes for Illumina sequencing and sample multiplexing.
Figure Legend Snippet: TGIRT ssDNA-seq workflow. The target DNA (2–50 ng in this work) is treated with alkaline phosphatase to remove 3′ phosphates and heat denatured prior to DNA-seq library construction. The resulting ssDNAs with 3′ OH termini are then used for TGIRT template-switching DNA synthesis coupled to Illumina read 2 reverse (R2R) DNA-seq adapter addition. In this novel reaction, the TGIRT-III enzyme (InGex) binds first to a synthetic 34-bp R2 RNA/R2R DNA heteroduplex in which the R2R DNA primer has a single nucleotide 3′ overhang that can direct TGIRT template switching by base pairing to the 3′ nucleotide of a target DNA strand. For minimally biased library preparation, the 3′-overhang nucleotide is an equimolar mixture of A, C, G, and T (denoted N). A 3′-blocking group (C3 spacer; 3′SpC3) is attached to the end of the R2 RNA oligonucleotide to prevent template-switching to that RNA. After the TGIRT enzyme extends the DNA primer to produce a DNA copy of the target DNA strand with an R2R adapter seamlessly linked to its 5′ end, a 5′ adenylated (App) Illumina read 1 reverse (R1R) adapter is added to its 3′ end by single-stranded DNA ligation using a Thermostable 5′ AppDNA/RNA ligase (New England Biolabs). In the workflow shown, an unique molecular identifier (UMI) is positioned at the 5′ end of the R1R DNA oligonucleotide. A final PCR step adds flow cell capture sites and barcodes for Illumina sequencing and sample multiplexing.

Techniques Used: DNA Sequencing, DNA Synthesis, Blocking Assay, DNA Ligation, Polymerase Chain Reaction, Flow Cytometry, Sequencing, Multiplexing

TGIRT DNA-seq metrics. E. coli K12 strain MG1655 genomic DNA was sequenced by TGIRT-seq (3 replicates with R1R-UMI), and the resulting datasets (EG1–3; Supplementary Table S2 ) were compared to datasets obtained previously for this DNA by Nextera-XT (3 replicates; Illumina Basespace Project 21071065; datasets NX10, 50, 60). ( a ) Histogram of base coverage across the E. coli genome in 10 randomly subsampled datasets of ~16X coverage from each TGIRT-seq (black) and Nextera-XT (pink) replicate. The TGIRT-seq and Nextera-XT subsampled datasets show similar agreement to expected Poisson distributions (dashed black and pink lines; R 2 = 0.90 ± 0.01 and 0.91 ± 0.01, respectively). ( b ) Normalized coverage as a function of GC content over a 100-nt sliding window across the E. coli genome for TGIRT-seq (black lines; 3 replicates) and Nextera-XT (pink lines; 3 replicates) compared to theoretical uniform coverage (dashed line). The green histogram shows the percentage of windows of each GC content in the E. coli genome. TGIRT-seq gives better coverage of regions having low GC content, but over-represents regions of GC content > 60%. (c) Lorenz curves showing the cumulative distribution of normalized coverage in a 100-nt sliding window across the E. coli genome for TGIRT-seq and Nextera-XT (3 replicates each). The curves show that TGIRT-seq and Nextera-XT give cumulatively similar uniform coverage over the range of GC contents in the E. coli genome (Gini coefficients: 0.26 ± 0.02 and 0.28 ± 0.01, respectively). Dashed line denotes no bias. (d) Base substitution and indel rates for TGIRT-seq with or without UMI correction (black and green dots, respectively) compared to Nextera-XT (pink dots) for 10 subsampled datasets at 16X coverage from each TGIRT-seq and Nextera-XT replicate. The left panels show error rates for the whole genome (WGS), and the right panels show the error rates excluding mononucleotide runs ≥4. (e) Plot of indel frequency versus mononucleotide run length for 10 subsampled libraries at 16X coverage from each of 3 error-corrected TGIRT-seq (black) and 3 Nextera-XT (pink) datasets. TGIRT shows an increase in indel frequency at mononucleotide runs ≥ 4 (see also Supplementary Fig. S7 ).
Figure Legend Snippet: TGIRT DNA-seq metrics. E. coli K12 strain MG1655 genomic DNA was sequenced by TGIRT-seq (3 replicates with R1R-UMI), and the resulting datasets (EG1–3; Supplementary Table S2 ) were compared to datasets obtained previously for this DNA by Nextera-XT (3 replicates; Illumina Basespace Project 21071065; datasets NX10, 50, 60). ( a ) Histogram of base coverage across the E. coli genome in 10 randomly subsampled datasets of ~16X coverage from each TGIRT-seq (black) and Nextera-XT (pink) replicate. The TGIRT-seq and Nextera-XT subsampled datasets show similar agreement to expected Poisson distributions (dashed black and pink lines; R 2 = 0.90 ± 0.01 and 0.91 ± 0.01, respectively). ( b ) Normalized coverage as a function of GC content over a 100-nt sliding window across the E. coli genome for TGIRT-seq (black lines; 3 replicates) and Nextera-XT (pink lines; 3 replicates) compared to theoretical uniform coverage (dashed line). The green histogram shows the percentage of windows of each GC content in the E. coli genome. TGIRT-seq gives better coverage of regions having low GC content, but over-represents regions of GC content > 60%. (c) Lorenz curves showing the cumulative distribution of normalized coverage in a 100-nt sliding window across the E. coli genome for TGIRT-seq and Nextera-XT (3 replicates each). The curves show that TGIRT-seq and Nextera-XT give cumulatively similar uniform coverage over the range of GC contents in the E. coli genome (Gini coefficients: 0.26 ± 0.02 and 0.28 ± 0.01, respectively). Dashed line denotes no bias. (d) Base substitution and indel rates for TGIRT-seq with or without UMI correction (black and green dots, respectively) compared to Nextera-XT (pink dots) for 10 subsampled datasets at 16X coverage from each TGIRT-seq and Nextera-XT replicate. The left panels show error rates for the whole genome (WGS), and the right panels show the error rates excluding mononucleotide runs ≥4. (e) Plot of indel frequency versus mononucleotide run length for 10 subsampled libraries at 16X coverage from each of 3 error-corrected TGIRT-seq (black) and 3 Nextera-XT (pink) datasets. TGIRT shows an increase in indel frequency at mononucleotide runs ≥ 4 (see also Supplementary Fig. S7 ).

Techniques Used: DNA Sequencing

19) Product Images from "Genome-wide interrogation of extracellular vesicle biology using barcoded miRNAs"

Article Title: Genome-wide interrogation of extracellular vesicle biology using barcoded miRNAs

Journal: eLife

doi: 10.7554/eLife.41460

Genome-wide CRISPR/Cas9 screen using bEXOmiRs enables systematic interrogation of EV biology. ( A ). ( B ), Initial pilot screen using a 25,000 bEXOmiR-sgRNA library targeting membrane trafficking, mitochondrial and motility (MMM) genes. Colored insets display zoomed activator (red nodes in red inset) and suppressor (blue nodes in blue inset) hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 1.5. ( C ), genome-wide (minus MMM sublibrary) screen. Colored insets display zoomed activator and suppressor hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 2.5. Green labels in ( B ) and ( C ) indicate previously known EV regulators; yellow labels represent genes that regulate miRNA trafficking or processing.
Figure Legend Snippet: Genome-wide CRISPR/Cas9 screen using bEXOmiRs enables systematic interrogation of EV biology. ( A ). ( B ), Initial pilot screen using a 25,000 bEXOmiR-sgRNA library targeting membrane trafficking, mitochondrial and motility (MMM) genes. Colored insets display zoomed activator (red nodes in red inset) and suppressor (blue nodes in blue inset) hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 1.5. ( C ), genome-wide (minus MMM sublibrary) screen. Colored insets display zoomed activator and suppressor hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 2.5. Green labels in ( B ) and ( C ) indicate previously known EV regulators; yellow labels represent genes that regulate miRNA trafficking or processing.

Techniques Used: Genome Wide, CRISPR

20) Product Images from "Whole genome bisulfite sequencing of cell-free DNA and its cellular contributors uncovers placenta hypomethylated domains"

Article Title: Whole genome bisulfite sequencing of cell-free DNA and its cellular contributors uncovers placenta hypomethylated domains

Journal: Genome Biology

doi: 10.1186/s13059-015-0645-x

Methylome of ccf DNA isolated from pregnant plasma. (a) Cytosine methylation in non-pregnant and pregnant ccf DNA for CpG, CHG, and CHH contexts are shown. P values were calculated using a Wilcox rank sum test. (b) Methylation of all cytosines located within the DMRs hypermethylated in placenta tissue relative to non-pregnant ccf DNA. The y-axis (density) is the defined as the proportion of CpG sites at a given methylation level. (c) Methylation of all cytosines located within the DMRs hypermethylated in non-pregnant ccf DNA relative to placenta tissue. The y-axis (density) is the defined as the proportion of CpG sites at a given methylation level.
Figure Legend Snippet: Methylome of ccf DNA isolated from pregnant plasma. (a) Cytosine methylation in non-pregnant and pregnant ccf DNA for CpG, CHG, and CHH contexts are shown. P values were calculated using a Wilcox rank sum test. (b) Methylation of all cytosines located within the DMRs hypermethylated in placenta tissue relative to non-pregnant ccf DNA. The y-axis (density) is the defined as the proportion of CpG sites at a given methylation level. (c) Methylation of all cytosines located within the DMRs hypermethylated in non-pregnant ccf DNA relative to placenta tissue. The y-axis (density) is the defined as the proportion of CpG sites at a given methylation level.

Techniques Used: Isolation, Methylation

Linkage between fragment size and local DNA methylation in non-pregnant ccf DNA. (a) Fragment size of ccf DNA as measured by WGBS. Each line represents an individual ccf sample. Loss of representation at approximately 92 to 98 bp is an artifact of adapter trimming prior to alignment. (b) Ratio of methylated CpG, CHG, and CHH cytosines within large fragments ( > 200 bp) relative to methylated cytosines in small fragments (
Figure Legend Snippet: Linkage between fragment size and local DNA methylation in non-pregnant ccf DNA. (a) Fragment size of ccf DNA as measured by WGBS. Each line represents an individual ccf sample. Loss of representation at approximately 92 to 98 bp is an artifact of adapter trimming prior to alignment. (b) Ratio of methylated CpG, CHG, and CHH cytosines within large fragments ( > 200 bp) relative to methylated cytosines in small fragments (

Techniques Used: DNA Methylation Assay, Methylation

Methylation patterns in buffy coat, placenta, and non-pregnant ccf DNA. (a) The distribution of mean CpG methylation for each sample type (non-pregnant ccf DNA, maternal buffy coat, and placenta). The y-axis represents the relative proportion of all evaluated CpG dinucleotides exhibiting a particular level of CpG methylation. The histogram bins each have a width of 1%. (b) CpG methylation of non-pregnant ccf DNA samples was assessed in ENCODE-defined enriched regions for H3K4me1, H3K4me3, H3K9me3, and H3K27me3. Unenriched data were generated by a random sampling of the same number of CpG sites as used for enrichment, but located elsewhere in the genome. The width of each violin plot is representative of data density at a given CpG methylation level. (c) The number of DMRs more methylated in placenta (red) and non-pregnant (NP) ccf DNA (blue).
Figure Legend Snippet: Methylation patterns in buffy coat, placenta, and non-pregnant ccf DNA. (a) The distribution of mean CpG methylation for each sample type (non-pregnant ccf DNA, maternal buffy coat, and placenta). The y-axis represents the relative proportion of all evaluated CpG dinucleotides exhibiting a particular level of CpG methylation. The histogram bins each have a width of 1%. (b) CpG methylation of non-pregnant ccf DNA samples was assessed in ENCODE-defined enriched regions for H3K4me1, H3K4me3, H3K9me3, and H3K27me3. Unenriched data were generated by a random sampling of the same number of CpG sites as used for enrichment, but located elsewhere in the genome. The width of each violin plot is representative of data density at a given CpG methylation level. (c) The number of DMRs more methylated in placenta (red) and non-pregnant (NP) ccf DNA (blue).

Techniques Used: Methylation, CpG Methylation Assay, Generated, Sampling

Identification of placenta hypomethylated domains (PHDs). (a) Mean methylation per 50 kbp genomic bin on chromosome 16 with non-pregnant ccf DNA (NP ccf DNA) and placenta shown. CpG sites (blue) and genes (orange) were summed per 50kbp genomic bin. (b) Genomic methylation level by CpG density at 50 kbp bin level. Values on the x-axis represent the number of CpG sites per 50 kbp bin. Numbers along the top indicate the number of genomic bins analyzed. (c) Differential methylation between placenta and non-pregnant plasma as a function of CpG density at 50 kbp bin level. A negative value on the y-axis is indicative of placenta hypomethylation. The red line corresponds to a loess smoothed fit.
Figure Legend Snippet: Identification of placenta hypomethylated domains (PHDs). (a) Mean methylation per 50 kbp genomic bin on chromosome 16 with non-pregnant ccf DNA (NP ccf DNA) and placenta shown. CpG sites (blue) and genes (orange) were summed per 50kbp genomic bin. (b) Genomic methylation level by CpG density at 50 kbp bin level. Values on the x-axis represent the number of CpG sites per 50 kbp bin. Numbers along the top indicate the number of genomic bins analyzed. (c) Differential methylation between placenta and non-pregnant plasma as a function of CpG density at 50 kbp bin level. A negative value on the y-axis is indicative of placenta hypomethylation. The red line corresponds to a loess smoothed fit.

Techniques Used: Methylation

21) Product Images from "Near full-length 16S rRNA gene next-generation sequencing revealed Asaia as a common midgut bacterium of wild and domesticated Queensland fruit fly larvae"

Article Title: Near full-length 16S rRNA gene next-generation sequencing revealed Asaia as a common midgut bacterium of wild and domesticated Queensland fruit fly larvae

Journal: Microbiome

doi: 10.1186/s40168-018-0463-y

Relative abundance of bacterial taxa in Bactrocera tryoni larval midguts. Near full-length sequences were clustered at 99% similarity. Sequences belonging to OTUs from the same genus or family (when genus could not be determined due to the representative OTU sequence matching to 16S rRNA gene sequences from various genera with similar identity) were pooled. The group “Other” includes OTUs with five or less sequences and does not belong to the other families listed. The prefixes Bux, Tum, FFPF, GPII, and MQ refer to the source of samples, and P and Col indicate whether the larva was from a peach or a domesticated colony, respectively. Larvae from the same peach have the same letter before the larval number. For example, Bux.P.A1, Bux.P.A2, and Bux.P.A3 were different larvae from the same whole peach. The number of near full-length sequences included in the OTU clustering for each sample is listed above the respective column
Figure Legend Snippet: Relative abundance of bacterial taxa in Bactrocera tryoni larval midguts. Near full-length sequences were clustered at 99% similarity. Sequences belonging to OTUs from the same genus or family (when genus could not be determined due to the representative OTU sequence matching to 16S rRNA gene sequences from various genera with similar identity) were pooled. The group “Other” includes OTUs with five or less sequences and does not belong to the other families listed. The prefixes Bux, Tum, FFPF, GPII, and MQ refer to the source of samples, and P and Col indicate whether the larva was from a peach or a domesticated colony, respectively. Larvae from the same peach have the same letter before the larval number. For example, Bux.P.A1, Bux.P.A2, and Bux.P.A3 were different larvae from the same whole peach. The number of near full-length sequences included in the OTU clustering for each sample is listed above the respective column

Techniques Used: Sequencing

22) Product Images from "A high throughput screen for active human transposable elements"

Article Title: A high throughput screen for active human transposable elements

Journal: BMC Genomics

doi: 10.1186/s12864-018-4485-4

TE-NGS sequencing workflow. Enrichment for genomic fragments spanning active TEs and their unique flanking sequence is achieved by several enzymatic steps as described in the main text. First, genomic DNA is sheared, and adapters for sequencing are ligated to the genomic fragments following standard library preparation protocols. Next, a small aliquot (10 ng) of library is used as template for targeted amplification with primers complementary to TE subfamily-specific sequences and to the Illumina Universal PCR (P5) primer. Remaining genomic background fragments and inverted TEs in head-to-head orientation are removed by ssDNA exonuclease digestion after linear PCR amplification with TE-target primers or Illumina Universal primer, respectively. Last, amplification with nested primers targeting TE diagnostic bases, and containing Illumina i7 index and P7 primer sequences generates full double-stranded dual-adapter libraries containing unique indices for each sample and each TE subfamily, allowing for downstream pooling and multiplexing of many samples simultaneously. High throughput sequencing followed by alignment to the reference genome demarcates the TE insertion site by its 3′ end (read 2) and unique flanking sequence (read 1). TE insertions present in the reference genome can be identified by clustering of read pairs, whereas read 2 generated from polymorphic or novel TE insertions absent from the reference will map with lower quality and/or not at all; these TE can be identified by clusters of read 1 alone (see Methods; Supplemental Material for detailed procedures)
Figure Legend Snippet: TE-NGS sequencing workflow. Enrichment for genomic fragments spanning active TEs and their unique flanking sequence is achieved by several enzymatic steps as described in the main text. First, genomic DNA is sheared, and adapters for sequencing are ligated to the genomic fragments following standard library preparation protocols. Next, a small aliquot (10 ng) of library is used as template for targeted amplification with primers complementary to TE subfamily-specific sequences and to the Illumina Universal PCR (P5) primer. Remaining genomic background fragments and inverted TEs in head-to-head orientation are removed by ssDNA exonuclease digestion after linear PCR amplification with TE-target primers or Illumina Universal primer, respectively. Last, amplification with nested primers targeting TE diagnostic bases, and containing Illumina i7 index and P7 primer sequences generates full double-stranded dual-adapter libraries containing unique indices for each sample and each TE subfamily, allowing for downstream pooling and multiplexing of many samples simultaneously. High throughput sequencing followed by alignment to the reference genome demarcates the TE insertion site by its 3′ end (read 2) and unique flanking sequence (read 1). TE insertions present in the reference genome can be identified by clustering of read pairs, whereas read 2 generated from polymorphic or novel TE insertions absent from the reference will map with lower quality and/or not at all; these TE can be identified by clusters of read 1 alone (see Methods; Supplemental Material for detailed procedures)

Techniques Used: Next-Generation Sequencing, Sequencing, Amplification, Polymerase Chain Reaction, Diagnostic Assay, Multiplexing, Generated

23) Product Images from "Shifts on Gut Microbiota Associated to Mediterranean Diet Adherence and Specific Dietary Intakes on General Adult Population"

Article Title: Shifts on Gut Microbiota Associated to Mediterranean Diet Adherence and Specific Dietary Intakes on General Adult Population

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2018.00890

Microbiota composition by 16S rDNA sequencing. Microbial Relative abundances (%) at phylum ( A : General profile, B : according to BMI, and C : according to MD adherence) and family level ( D : General profile, E : according to BMI, and F : according to MD adherence) found in the gut microbiome of volunteers.
Figure Legend Snippet: Microbiota composition by 16S rDNA sequencing. Microbial Relative abundances (%) at phylum ( A : General profile, B : according to BMI, and C : according to MD adherence) and family level ( D : General profile, E : according to BMI, and F : according to MD adherence) found in the gut microbiome of volunteers.

Techniques Used: Sequencing

24) Product Images from "Genome-wide interrogation of extracellular vesicle biology using barcoded miRNAs"

Article Title: Genome-wide interrogation of extracellular vesicle biology using barcoded miRNAs

Journal: eLife

doi: 10.7554/eLife.41460

Batch retest mini screen using different sgRNA-bEXOmiR associations. Top 100 hits from initial MMM screen ( Figure 2B ) were targeted with the same, previously-used sgRNAs but paired with different bEXOmiRs, as shown in ( A ). ( B ), Volcano plot showing results of the top 100 MMM hit-focused screen (two replicates). Selected activators and suppressors are labeled in red and blue, respectively.
Figure Legend Snippet: Batch retest mini screen using different sgRNA-bEXOmiR associations. Top 100 hits from initial MMM screen ( Figure 2B ) were targeted with the same, previously-used sgRNAs but paired with different bEXOmiRs, as shown in ( A ). ( B ), Volcano plot showing results of the top 100 MMM hit-focused screen (two replicates). Selected activators and suppressors are labeled in red and blue, respectively.

Techniques Used: Labeling

Genome-wide CRISPR/Cas9 screen using bEXOmiRs enables systematic interrogation of EV biology. ( A ) Diagram depicting key steps of the screen performed in this study. Oligonucleotides encoding sgRNA-bEXOmiR pairs were designed computationally and then synthesized using solid-phase technology. Next, oligonucleotides were pool-cloned (1) into a Lentivirus vector that drives expression of both sgRNA and bEXOmiR under U6 and EF1α promoters, respectively. WT and Cas9-positive K562 cells were then infected at low MOI (2), such that after infection and selection, each cell expresses only a single sgRNA-bEXOmiR pair (3). This approach enables identification and quantification of both EVs and their respective cell of origin via unique molecular identifiers: barcodes and sgRNAs respectively. sgRNA-bEXOmiR-expressing cells were then grown for 48 hr before collection of culture supernatants from which EVs were purified (4). Finally, barcode abundance was measured, comparing WT and Cas9-expressing cells, by deep sequencing from EV-extracted RNA ( Villarroya-Beltri et al., 2013 ). ( B ), Initial pilot screen using a 25,000 bEXOmiR-sgRNA library targeting membrane trafficking, mitochondrial and motility (MMM) genes. Colored insets display zoomed activator (red nodes in red inset) and suppressor (blue nodes in blue inset) hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 1.5. ( C ), genome-wide (minus MMM sublibrary) screen. Colored insets display zoomed activator and suppressor hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 2.5. Green labels in ( B ) and ( C ) indicate previously known EV regulators; yellow labels represent genes that regulate miRNA trafficking or processing.
Figure Legend Snippet: Genome-wide CRISPR/Cas9 screen using bEXOmiRs enables systematic interrogation of EV biology. ( A ) Diagram depicting key steps of the screen performed in this study. Oligonucleotides encoding sgRNA-bEXOmiR pairs were designed computationally and then synthesized using solid-phase technology. Next, oligonucleotides were pool-cloned (1) into a Lentivirus vector that drives expression of both sgRNA and bEXOmiR under U6 and EF1α promoters, respectively. WT and Cas9-positive K562 cells were then infected at low MOI (2), such that after infection and selection, each cell expresses only a single sgRNA-bEXOmiR pair (3). This approach enables identification and quantification of both EVs and their respective cell of origin via unique molecular identifiers: barcodes and sgRNAs respectively. sgRNA-bEXOmiR-expressing cells were then grown for 48 hr before collection of culture supernatants from which EVs were purified (4). Finally, barcode abundance was measured, comparing WT and Cas9-expressing cells, by deep sequencing from EV-extracted RNA ( Villarroya-Beltri et al., 2013 ). ( B ), Initial pilot screen using a 25,000 bEXOmiR-sgRNA library targeting membrane trafficking, mitochondrial and motility (MMM) genes. Colored insets display zoomed activator (red nodes in red inset) and suppressor (blue nodes in blue inset) hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 1.5. ( C ), genome-wide (minus MMM sublibrary) screen. Colored insets display zoomed activator and suppressor hits that passed effect size cutoffs (≤ −2 or ≥+2) and had a -Log p-value > 2.5. Green labels in ( B ) and ( C ) indicate previously known EV regulators; yellow labels represent genes that regulate miRNA trafficking or processing.

Techniques Used: Genome Wide, CRISPR, Synthesized, Plasmid Preparation, Expressing, Infection, Selection, Purification, Sequencing

Characterization of bEXOmiRs in EVs. ( A ) Detailed design of bEXOmiR reporters. The double stranded stem-region contains a 15 nt-random sequence (barcode; highlighted in blue) with perfect base complementarity. Three examples of barcode sequences, A, B and C are shown at right. The barcode sequence is then followed by a constant 7nt exosome-targeting motif (EXO motif, green) that contains two asymmetric bulges (one in each strand; a, bottom). The EXO motif is then followed by a loop sequence (orange); both were derived from endogenous hsa-miR-601. Finally, mini-miR-30 context sequences ( Chang et al., 2013 ) were placed at the base of the stem region (red). N indicates any ribonucleotide base. ( B ) Left, two protocols (P1 and P2) for EV isolation used in this study. Biochemical characterization of whole cell lysate (Cells) and EV fractions derived from P1 and P2 is shown in immunoblot panels at right using antibodies for LAMP1, CD81, Calnexin, Golgin 97, α-Tubulin and GDI-β. Molecular mass marker mobility is shown at left in kilodaltons. ( C ), Schematic for Stem-loop RT-PCR protocol used to detect bEXOmiRs in extracted RNA samples. Panel at right, lane 1 (EVs) shows expression of bEXOmiR-C (panel A ) detected by RT-PCR using RNA extracted from EVs released during 48 hr from HEK293T cells transfected with a bEXOmiR-expression vector. Reactions lacking either Stem-Loop primer (ΔFS-primer control, Lane 2) or reverse transcriptase (RT (-), Lane 3) are shown. Molecular marker mobility is shown at left in base pairs. ( D ) bEXOmiR-expressing HEK293T cells were grown for 48 hr prior to EV isolation and flotation using a discontinuous sucrose gradient; the presence of the bEXOmiR reporter was determined by RT-PCR at the indicated gradient interface (dotted red arrow), as shown in lane 1 (floated EVs) of the agarose gel at right. No bEXOmiR signal was observed in reactions lacking Stem-loop primer (lane 2). ( E ) RNase protection assay. Isolated EVs from bEXOmiR-expressing K562 cells were incubated with PBS (gray bar), PBS + RNase (black bar) or PBS + TX100 + RNase (red bar). t test: *p
Figure Legend Snippet: Characterization of bEXOmiRs in EVs. ( A ) Detailed design of bEXOmiR reporters. The double stranded stem-region contains a 15 nt-random sequence (barcode; highlighted in blue) with perfect base complementarity. Three examples of barcode sequences, A, B and C are shown at right. The barcode sequence is then followed by a constant 7nt exosome-targeting motif (EXO motif, green) that contains two asymmetric bulges (one in each strand; a, bottom). The EXO motif is then followed by a loop sequence (orange); both were derived from endogenous hsa-miR-601. Finally, mini-miR-30 context sequences ( Chang et al., 2013 ) were placed at the base of the stem region (red). N indicates any ribonucleotide base. ( B ) Left, two protocols (P1 and P2) for EV isolation used in this study. Biochemical characterization of whole cell lysate (Cells) and EV fractions derived from P1 and P2 is shown in immunoblot panels at right using antibodies for LAMP1, CD81, Calnexin, Golgin 97, α-Tubulin and GDI-β. Molecular mass marker mobility is shown at left in kilodaltons. ( C ), Schematic for Stem-loop RT-PCR protocol used to detect bEXOmiRs in extracted RNA samples. Panel at right, lane 1 (EVs) shows expression of bEXOmiR-C (panel A ) detected by RT-PCR using RNA extracted from EVs released during 48 hr from HEK293T cells transfected with a bEXOmiR-expression vector. Reactions lacking either Stem-Loop primer (ΔFS-primer control, Lane 2) or reverse transcriptase (RT (-), Lane 3) are shown. Molecular marker mobility is shown at left in base pairs. ( D ) bEXOmiR-expressing HEK293T cells were grown for 48 hr prior to EV isolation and flotation using a discontinuous sucrose gradient; the presence of the bEXOmiR reporter was determined by RT-PCR at the indicated gradient interface (dotted red arrow), as shown in lane 1 (floated EVs) of the agarose gel at right. No bEXOmiR signal was observed in reactions lacking Stem-loop primer (lane 2). ( E ) RNase protection assay. Isolated EVs from bEXOmiR-expressing K562 cells were incubated with PBS (gray bar), PBS + RNase (black bar) or PBS + TX100 + RNase (red bar). t test: *p

Techniques Used: Sequencing, Derivative Assay, Isolation, Marker, Reverse Transcription Polymerase Chain Reaction, Expressing, Transfection, Plasmid Preparation, Agarose Gel Electrophoresis, Rnase Protection Assay, Incubation

Analysis of bEXOmiR EV-targeting. Reproducibility of ~32,000 bEXOmiR abundances measured in EVs isolated from replicated WT- ( A ) or Cas9-positive ( B ) cell cultures (REP#1 and #2). ( C ) Correlation of ~32,000 bEXOmiR abundances in EVs versus intact cells (Cells) from the same WT replicated cultures (left, REP#1; right, REP#2) shown in ( A ). ( D ) Correlation of growth versus EV phenotypes observed in the genome-wide screen. ( E ) Correlation of growth versus EV phenotypic scores calculated using the casTLE algorithm (see Materials and methods) in the genome-wide analysis. Red and blue dots represent identified activator or suppressor hits from the EV generation screen, respectively.
Figure Legend Snippet: Analysis of bEXOmiR EV-targeting. Reproducibility of ~32,000 bEXOmiR abundances measured in EVs isolated from replicated WT- ( A ) or Cas9-positive ( B ) cell cultures (REP#1 and #2). ( C ) Correlation of ~32,000 bEXOmiR abundances in EVs versus intact cells (Cells) from the same WT replicated cultures (left, REP#1; right, REP#2) shown in ( A ). ( D ) Correlation of growth versus EV phenotypes observed in the genome-wide screen. ( E ) Correlation of growth versus EV phenotypic scores calculated using the casTLE algorithm (see Materials and methods) in the genome-wide analysis. Red and blue dots represent identified activator or suppressor hits from the EV generation screen, respectively.

Techniques Used: Isolation, Genome Wide

Characterization of CD63-positive structures in cells with or without bEXOmiR expression. Top, K562 cells visualized after centrifugation onto coverslips, immunostained for CD63; bottom, quantitation of total CD63-vesicle area. Each dot represents a single, CD63-positive structure in 18 or 20 parental or bEXOmiR expressing cells, respectively (n ~ 600 structures counted for each condition; mean ~32 structures per cell for the parental and ~34 for the bEXOmiR expressing cells. Red line indicates the median area for each population.
Figure Legend Snippet: Characterization of CD63-positive structures in cells with or without bEXOmiR expression. Top, K562 cells visualized after centrifugation onto coverslips, immunostained for CD63; bottom, quantitation of total CD63-vesicle area. Each dot represents a single, CD63-positive structure in 18 or 20 parental or bEXOmiR expressing cells, respectively (n ~ 600 structures counted for each condition; mean ~32 structures per cell for the parental and ~34 for the bEXOmiR expressing cells. Red line indicates the median area for each population.

Techniques Used: Expressing, Centrifugation, Quantitation Assay

25) Product Images from "Transcriptomic and GC-MS Metabolomic Analyses Reveal the Sink Strength Changes during Petunia Anther Development"

Article Title: Transcriptomic and GC-MS Metabolomic Analyses Reveal the Sink Strength Changes during Petunia Anther Development

Journal: International Journal of Molecular Sciences

doi: 10.3390/ijms19040955

The qRT-PCR validation of DEGs. The relative expression levels of 18 transcription factors ( A ), 14 starch and sucrose metabolism pathways ( B ) and 6 photosynthesis related genes ( C ). The left Y axis represents the relative transcript amount obtained by qRT-PCR. The right Y axis represents the fragments per kb per million fragments (FPKM) value of each gene using RNA-Seq analysis. Error bars indicate the standard errors. ( D ) Correlation analysis of the gene expression ratios between qRT-PCR and RNA-seq.
Figure Legend Snippet: The qRT-PCR validation of DEGs. The relative expression levels of 18 transcription factors ( A ), 14 starch and sucrose metabolism pathways ( B ) and 6 photosynthesis related genes ( C ). The left Y axis represents the relative transcript amount obtained by qRT-PCR. The right Y axis represents the fragments per kb per million fragments (FPKM) value of each gene using RNA-Seq analysis. Error bars indicate the standard errors. ( D ) Correlation analysis of the gene expression ratios between qRT-PCR and RNA-seq.

Techniques Used: Quantitative RT-PCR, Expressing, RNA Sequencing Assay

26) Product Images from "High-throughput ChIPmentation: freely scalable, single day ChIPseq data generation from very low cell-numbers"

Article Title: High-throughput ChIPmentation: freely scalable, single day ChIPseq data generation from very low cell-numbers

Journal: BMC Genomics

doi: 10.1186/s12864-018-5299-0

High-throughput ChIPmentation (HT-CM) through direct amplification of tagmented chromatin, allows for rapid and technically simple analysis of histone modifications and transcription factor binding in low numbers of FACS sorted cells. a Schematic overview of the HT-CM workflow (for a direct comparison between the HT-CM and original ChIPmentation (CM) methods, see Additional file 1 : Figure S1). In brief, FACS sorted cells are sonicated, subjected to ChIP and tagmented. Library amplification is subsequently done without prior DNA purification. Input controls are prepared through direct tagmentation of sonicated chromatin. b Genome-browser profiles from CM, HT-CM and input control samples generated using indicated cell-numbers and antibodies. c Correlation between H3K27Ac signals (in a merged catalog containing all peaks identified in displayed samples) generated using indicated methods and cell numbers. d Overlap (%) between top peaks (peaks with the 50% highest peak quality scores) identified in high cell-number (150 and 50 k) H3K27Ac HT-CM and CM samples. e RPKM of 1 kb bins covering the whole genome in input control samples generated using indicated method and cell-equivalents of chromatin. f Percentage of unique reads in H3K27Ac HT-CM and CM samples generated in parallel. g Correlation between H3K27Ac/CTCF signals in samples generated using indicated methods and cell-numbers. h Overlap (%) between top peaks identified in H3K27Ac and CTCF HT-CM samples generated using indicated cell-numbers. ND, not done. i Time required to perform ChIP, library preparation and sequencing for the CM, HT-CM and 1-day HT-CM workflows. Hours (h) needed to perform each step are indicated
Figure Legend Snippet: High-throughput ChIPmentation (HT-CM) through direct amplification of tagmented chromatin, allows for rapid and technically simple analysis of histone modifications and transcription factor binding in low numbers of FACS sorted cells. a Schematic overview of the HT-CM workflow (for a direct comparison between the HT-CM and original ChIPmentation (CM) methods, see Additional file 1 : Figure S1). In brief, FACS sorted cells are sonicated, subjected to ChIP and tagmented. Library amplification is subsequently done without prior DNA purification. Input controls are prepared through direct tagmentation of sonicated chromatin. b Genome-browser profiles from CM, HT-CM and input control samples generated using indicated cell-numbers and antibodies. c Correlation between H3K27Ac signals (in a merged catalog containing all peaks identified in displayed samples) generated using indicated methods and cell numbers. d Overlap (%) between top peaks (peaks with the 50% highest peak quality scores) identified in high cell-number (150 and 50 k) H3K27Ac HT-CM and CM samples. e RPKM of 1 kb bins covering the whole genome in input control samples generated using indicated method and cell-equivalents of chromatin. f Percentage of unique reads in H3K27Ac HT-CM and CM samples generated in parallel. g Correlation between H3K27Ac/CTCF signals in samples generated using indicated methods and cell-numbers. h Overlap (%) between top peaks identified in H3K27Ac and CTCF HT-CM samples generated using indicated cell-numbers. ND, not done. i Time required to perform ChIP, library preparation and sequencing for the CM, HT-CM and 1-day HT-CM workflows. Hours (h) needed to perform each step are indicated

Techniques Used: High Throughput Screening Assay, Amplification, Binding Assay, FACS, Sonication, Chromatin Immunoprecipitation, DNA Purification, Generated, Sequencing

27) Product Images from "Virological and immunological outcome of treatment interruption in HIV-1-infected subjects vaccinated with MVA-B"

Article Title: Virological and immunological outcome of treatment interruption in HIV-1-infected subjects vaccinated with MVA-B

Journal: PLoS ONE

doi: 10.1371/journal.pone.0184929

HIV-1 DNA copy numbers in CD4 cells before vaccination predicts extent of viral reservoir replenishment and plasma viral loads after structured treatment interruption (STI). (A) HIV DNA copy numbers in PBMC-derived, purified CD4+ T cells at start of STI (STI-w0), and 2 (STI-w2) or 12 (STI-w12) weeks after start of STI in placebo (white) and vaccinated individuals (grey). Median copy number (with interquartile range) is shown in all conditions (p-values Wilcoxon paired test). (B) Correlation between HIV DNA copy number in purified CD4+ T cells before any vaccination and after 12 weeks into STI (n = 16). Spearman correlation coefficient and p-value are shown. Linear regression line with 95% confidence intervals is represented. (C) Correlation between HIV DNA copy numbers per 10 6 CD4 T cells at 12 weeks into STI and plasma viral loads (log 10 copies/mL) 4 or 8 weeks after start of STI. Viral load at 4 weeks into STI (n = 16) is shown in white triangles and at 8 weeks (n = 12) in black triangles (r and p-value are shown for Spearman correlation). (D) Correlation between peak of viral load (log 10 copies/mL) uring STI and HIV DNA copies detected before vaccination. Spearman correlation coefficient and p-value are shown. Linear regression line with 95% confidence intervals is represented.
Figure Legend Snippet: HIV-1 DNA copy numbers in CD4 cells before vaccination predicts extent of viral reservoir replenishment and plasma viral loads after structured treatment interruption (STI). (A) HIV DNA copy numbers in PBMC-derived, purified CD4+ T cells at start of STI (STI-w0), and 2 (STI-w2) or 12 (STI-w12) weeks after start of STI in placebo (white) and vaccinated individuals (grey). Median copy number (with interquartile range) is shown in all conditions (p-values Wilcoxon paired test). (B) Correlation between HIV DNA copy number in purified CD4+ T cells before any vaccination and after 12 weeks into STI (n = 16). Spearman correlation coefficient and p-value are shown. Linear regression line with 95% confidence intervals is represented. (C) Correlation between HIV DNA copy numbers per 10 6 CD4 T cells at 12 weeks into STI and plasma viral loads (log 10 copies/mL) 4 or 8 weeks after start of STI. Viral load at 4 weeks into STI (n = 16) is shown in white triangles and at 8 weeks (n = 12) in black triangles (r and p-value are shown for Spearman correlation). (D) Correlation between peak of viral load (log 10 copies/mL) uring STI and HIV DNA copies detected before vaccination. Spearman correlation coefficient and p-value are shown. Linear regression line with 95% confidence intervals is represented.

Techniques Used: Derivative Assay, Purification

Structured treatment interruption (STI) increases levels of Env specific antibodies. Mean flourescence intensity (MFI) of stained MOLT cells expressing trimeric Env (from isolates HIV-1 NL4.3 and HIV-1 BaL ) or lacking Env expression (uninfected) is show for plasma samples obtained at the start (STI-w0) or after 12 weeks (STI-w12) into STI in the placebo (white, n = 10) or the vaccinated (grey, n = 15) group. P-values for Wilcoxon paired test comparing w0-STI values to w12-STI are shown on top of the figure.
Figure Legend Snippet: Structured treatment interruption (STI) increases levels of Env specific antibodies. Mean flourescence intensity (MFI) of stained MOLT cells expressing trimeric Env (from isolates HIV-1 NL4.3 and HIV-1 BaL ) or lacking Env expression (uninfected) is show for plasma samples obtained at the start (STI-w0) or after 12 weeks (STI-w12) into STI in the placebo (white, n = 10) or the vaccinated (grey, n = 15) group. P-values for Wilcoxon paired test comparing w0-STI values to w12-STI are shown on top of the figure.

Techniques Used: Staining, Expressing

Increased cellular immune responses to HIV after treatment interruption. Magnitude (A) and breadth (B) of T cell responses to the entire HIV-1 proteome at start (STI-w0) and after w12 (STI-w12) of structured treatment in interruption (STI) is shown for placebo recipients (white) and the vaccinated group (grey). Median and interquartile range and p-values (Wilcoxon paired test) are shown. In (C), responses are divided into responses to regions of HIV that are covered (IN) or are not covered (OUT) by the MVA-B vaccine immunogen sequence.
Figure Legend Snippet: Increased cellular immune responses to HIV after treatment interruption. Magnitude (A) and breadth (B) of T cell responses to the entire HIV-1 proteome at start (STI-w0) and after w12 (STI-w12) of structured treatment in interruption (STI) is shown for placebo recipients (white) and the vaccinated group (grey). Median and interquartile range and p-values (Wilcoxon paired test) are shown. In (C), responses are divided into responses to regions of HIV that are covered (IN) or are not covered (OUT) by the MVA-B vaccine immunogen sequence.

Techniques Used: Sequencing

28) Product Images from "Genome-wide RNA pol II initiation and pausing in neural progenitors of the rat"

Article Title: Genome-wide RNA pol II initiation and pausing in neural progenitors of the rat

Journal: BMC Genomics

doi: 10.1186/s12864-019-5829-4

Validation of TSS-RNA sequencing in rat neural precursors. a . A scheme of an updated protocol for the preparation of Start-seq libraries for Illumina sequencing. b . UCSC browser shot of highly expressed Actb gene showing tracks from this study including 5′-tracks for TSS-RNA for each strand (red and blue) and mRNA-sequencing (black), alongside Pol II ChIP-seq (using an antibody against the Pol II N-terminus) track from mature rat neurons [ 10 ] representing a rat Pol II dataset that is most closely related to the current cell type. c . A zoomed-in view of Actb promoter-proximal region showing 5′- (red) and 3′-end (gold) of TSS-RNAs on this gene. The annotated Actb TSS is shown in blue bar and is located 2 bp downstream of the 5′ TSS-RNA peak. d . Correlation plot for promoter-proximal counts between two independent biological Start-Seq replicates. TSS-RNAs on the gene (sense) strand were counted in a +/− 500 bp interval from each RefSeq-annotated TSS
Figure Legend Snippet: Validation of TSS-RNA sequencing in rat neural precursors. a . A scheme of an updated protocol for the preparation of Start-seq libraries for Illumina sequencing. b . UCSC browser shot of highly expressed Actb gene showing tracks from this study including 5′-tracks for TSS-RNA for each strand (red and blue) and mRNA-sequencing (black), alongside Pol II ChIP-seq (using an antibody against the Pol II N-terminus) track from mature rat neurons [ 10 ] representing a rat Pol II dataset that is most closely related to the current cell type. c . A zoomed-in view of Actb promoter-proximal region showing 5′- (red) and 3′-end (gold) of TSS-RNAs on this gene. The annotated Actb TSS is shown in blue bar and is located 2 bp downstream of the 5′ TSS-RNA peak. d . Correlation plot for promoter-proximal counts between two independent biological Start-Seq replicates. TSS-RNAs on the gene (sense) strand were counted in a +/− 500 bp interval from each RefSeq-annotated TSS

Techniques Used: RNA Sequencing Assay, Sequencing, Chromatin Immunoprecipitation

29) Product Images from "Small RNA Sequencing in Cells and Exosomes Identifies eQTLs and 14q32 as a Region of Active Export"

Article Title: Small RNA Sequencing in Cells and Exosomes Identifies eQTLs and 14q32 as a Region of Active Export

Journal: G3: Genes|Genomes|Genetics

doi: 10.1534/g3.116.036137

A large miRNA cluster on chromosome 14q32 is exported in exosomes. (A) Diagram of the 14q32 locus, which contains two miRNA clusters denoted as cluster A and cluster B that comprise 15 and 74 mature miRNAs, respectively. These miRNA clusters are flanked by lincRNAs and separated by a lincRNA and an snoRNA cluster. (B) MA plot of our miRNA differential expression results ( n = 34) with miRNAs from the larger miRNA cluster on 14q32 circled in dark blue. DESeq2 uses independent filtering to reduce the number of explicit differential expression tests it runs ( Love et al. 2014 ). miRNAs that were not differentially expressed are depicted in light gray if they were removed by independent filtering and in dark gray otherwise. Significantly differentially expressed miRNAs (FDR = 1%) are colored in red. (C and D) Replication of the overrepresentation in exosomes of miRNAs from the large cluster on 14q32 using HeLa cell data ( n = 5) from Honegger et al. (2015) (C) and B cell line data ( n = 6) from Koppers-Lalic et al. (2014) (D). Note that the Koppers-Lalic et al. data were tested for differential expression using EdgeR, so the x -axis is in counts per million (instead of in DESeq2 normalized counts). Since only miRNAs that were explicitly tested for differential expression were reported, no light gray points appear in D.
Figure Legend Snippet: A large miRNA cluster on chromosome 14q32 is exported in exosomes. (A) Diagram of the 14q32 locus, which contains two miRNA clusters denoted as cluster A and cluster B that comprise 15 and 74 mature miRNAs, respectively. These miRNA clusters are flanked by lincRNAs and separated by a lincRNA and an snoRNA cluster. (B) MA plot of our miRNA differential expression results ( n = 34) with miRNAs from the larger miRNA cluster on 14q32 circled in dark blue. DESeq2 uses independent filtering to reduce the number of explicit differential expression tests it runs ( Love et al. 2014 ). miRNAs that were not differentially expressed are depicted in light gray if they were removed by independent filtering and in dark gray otherwise. Significantly differentially expressed miRNAs (FDR = 1%) are colored in red. (C and D) Replication of the overrepresentation in exosomes of miRNAs from the large cluster on 14q32 using HeLa cell data ( n = 5) from Honegger et al. (2015) (C) and B cell line data ( n = 6) from Koppers-Lalic et al. (2014) (D). Note that the Koppers-Lalic et al. data were tested for differential expression using EdgeR, so the x -axis is in counts per million (instead of in DESeq2 normalized counts). Since only miRNAs that were explicitly tested for differential expression were reported, no light gray points appear in D.

Techniques Used: Expressing

Cells and exosomes cluster by their miRNA and piRNA expression profiles. Hierarchical clustering of samples by the Spearman correlation coefficients of (A) miRNA and (B) piRNA expression. Samples cluster by compartment, confirming that cells and exosomes have distinct expression profiles. On average, the correlations between cell samples are higher than between exosome samples for both miRNA (0.83 vs. 0.80) and piRNA (0.72 vs. 0.61) (two-sided Wilcoxon rank sum test, p
Figure Legend Snippet: Cells and exosomes cluster by their miRNA and piRNA expression profiles. Hierarchical clustering of samples by the Spearman correlation coefficients of (A) miRNA and (B) piRNA expression. Samples cluster by compartment, confirming that cells and exosomes have distinct expression profiles. On average, the correlations between cell samples are higher than between exosome samples for both miRNA (0.83 vs. 0.80) and piRNA (0.72 vs. 0.61) (two-sided Wilcoxon rank sum test, p

Techniques Used: Expressing

Shared miRNA eQTL between cells and exosomes. (A) Table of all miRNAs with an eQTL at FDR ≤ 20% in either cells or exosomes. The four miRNAs that pass the FDR threshold in both cells and exosomes are marked with a dagger and depicted in (B and C). (B and C) Putative shared miRNA eQTLs. The normalized expression levels of the 11 children are shown in cells and exosomes for both products of hsa-miR-151a (B) and hsa-miR-335 (C). The expression values are segregated by their inherited paternal haplotype, denoted as 0 or 1. The maternal haplotypes are not depicted because they did not show a strong association with expression.
Figure Legend Snippet: Shared miRNA eQTL between cells and exosomes. (A) Table of all miRNAs with an eQTL at FDR ≤ 20% in either cells or exosomes. The four miRNAs that pass the FDR threshold in both cells and exosomes are marked with a dagger and depicted in (B and C). (B and C) Putative shared miRNA eQTLs. The normalized expression levels of the 11 children are shown in cells and exosomes for both products of hsa-miR-151a (B) and hsa-miR-335 (C). The expression values are segregated by their inherited paternal haplotype, denoted as 0 or 1. The maternal haplotypes are not depicted because they did not show a strong association with expression.

Techniques Used: Expressing

LCL exosome isolation procedure yields vesicles characteristic of exosomes. (A) Flow diagram of the exosome isolation procedure. All centrifugations were performed at 4°. (B) Transmission electron microscopy of isolated LCL exosomes. Four arrowheads denote isolated examples. Bar, 100 nm. (C) Example NanoSight tracing of LCL exosomes from a representative sample. For that sample, the maximal concentration of exosomes was at 107 nm diameter, as indicated by the dashed line. (D) Western blots of 50 µg total protein lysates from LCLs or their isolated exosomes hybridized with HSP70-specific (left) or calnexin-specific (right) antibodies. Arrowheads indicate expected bands at 70 and 90 kDa, respectively.
Figure Legend Snippet: LCL exosome isolation procedure yields vesicles characteristic of exosomes. (A) Flow diagram of the exosome isolation procedure. All centrifugations were performed at 4°. (B) Transmission electron microscopy of isolated LCL exosomes. Four arrowheads denote isolated examples. Bar, 100 nm. (C) Example NanoSight tracing of LCL exosomes from a representative sample. For that sample, the maximal concentration of exosomes was at 107 nm diameter, as indicated by the dashed line. (D) Western blots of 50 µg total protein lysates from LCLs or their isolated exosomes hybridized with HSP70-specific (left) or calnexin-specific (right) antibodies. Arrowheads indicate expected bands at 70 and 90 kDa, respectively.

Techniques Used: Isolation, Flow Cytometry, Transmission Assay, Electron Microscopy, Concentration Assay, Western Blot

Cells and exosomes differ in their small RNA profiles. (A) Small RNA composition of cells and exosomes averaged over the 17 individuals. Error bars show the SD. Paired two-sided t -tests were used to compare the cell and exosome proportions for each miRNA type and the p -values for the six tests were corrected by the Bonferroni method. Asterisks denote the significance of the corrected p -values: *** p
Figure Legend Snippet: Cells and exosomes differ in their small RNA profiles. (A) Small RNA composition of cells and exosomes averaged over the 17 individuals. Error bars show the SD. Paired two-sided t -tests were used to compare the cell and exosome proportions for each miRNA type and the p -values for the six tests were corrected by the Bonferroni method. Asterisks denote the significance of the corrected p -values: *** p

Techniques Used:

30) Product Images from "DADA2: High resolution sample inference from Illumina amplicon data"

Article Title: DADA2: High resolution sample inference from Illumina amplicon data

Journal: Nature methods

doi: 10.1038/nmeth.3869

Lactobacillus crispatus sequence variants in the human vaginal community during pregnancy DADA2 identified six Lactobacillus crispatus 16S rRNA sequence variants present in multiple samples and a significant fraction of all reads (L1: 19.7%, L2: 11.1%, L3: 6.5%, L4: 3.1%, L5: 1.3%, L6: 0.4%). (a) The frequency of L1–L6 in each sample. Black bars at the bottom link samples from the same subject. The frequency of (b) L1 vs. L2, and (c) L1 vs. L3, by sample. The dashed line indicates a total frequency of 1.
Figure Legend Snippet: Lactobacillus crispatus sequence variants in the human vaginal community during pregnancy DADA2 identified six Lactobacillus crispatus 16S rRNA sequence variants present in multiple samples and a significant fraction of all reads (L1: 19.7%, L2: 11.1%, L3: 6.5%, L4: 3.1%, L5: 1.3%, L6: 0.4%). (a) The frequency of L1–L6 in each sample. Black bars at the bottom link samples from the same subject. The frequency of (b) L1 vs. L2, and (c) L1 vs. L3, by sample. The dashed line indicates a total frequency of 1.

Techniques Used: Sequencing

31) Product Images from "High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptases"

Article Title: High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptases

Journal: RNA

doi: 10.1261/rna.054809.115

Other classes of small noncoding RNAs identified as full-length mature transcripts in human plasma by TGIRT-seq. ( A ) IGV screen shots showing coverage plots (CP; above ) and alignments ( below ) of reads mapping to small ncRNAs loci in RNA-seq data sets
Figure Legend Snippet: Other classes of small noncoding RNAs identified as full-length mature transcripts in human plasma by TGIRT-seq. ( A ) IGV screen shots showing coverage plots (CP; above ) and alignments ( below ) of reads mapping to small ncRNAs loci in RNA-seq data sets

Techniques Used: RNA Sequencing Assay

Percentage of TGIRT-seq reads from total plasma RNA data sets mapping to different categories of genomic features. RNA-seq data sets were constructed by using TeI4c RT for total plasma RNA prepared by the Direct-zol method and either not treated (NT;
Figure Legend Snippet: Percentage of TGIRT-seq reads from total plasma RNA data sets mapping to different categories of genomic features. RNA-seq data sets were constructed by using TeI4c RT for total plasma RNA prepared by the Direct-zol method and either not treated (NT;

Techniques Used: RNA Sequencing Assay, Construct

TGIRT-seq of plasma RNA samples
Figure Legend Snippet: TGIRT-seq of plasma RNA samples

Techniques Used:

Tissue expression profiles for mature miRNAs in plasma. The figure shows tissue expression profiles of the mature miRNAs identified by TGIRT-Seq in total plasma RNA prepared by the Direct-zol method with on-column DNase I treatment (OCD; combined DS7–10).
Figure Legend Snippet: Tissue expression profiles for mature miRNAs in plasma. The figure shows tissue expression profiles of the mature miRNAs identified by TGIRT-Seq in total plasma RNA prepared by the Direct-zol method with on-column DNase I treatment (OCD; combined DS7–10).

Techniques Used: Expressing

Human plasma RNA is enriched in intron and antisense sequences compared with whole-cell RNAs. Reads mapping to protein-coding genes were analyzed to assess coverage across different regions and both DNA strands in RNA-seq data sets constructed with TGIRT
Figure Legend Snippet: Human plasma RNA is enriched in intron and antisense sequences compared with whole-cell RNAs. Reads mapping to protein-coding genes were analyzed to assess coverage across different regions and both DNA strands in RNA-seq data sets constructed with TGIRT

Techniques Used: RNA Sequencing Assay, Construct

TGIRT-seq overview. ( A ) RNA-seq library construction via TGIRT template-switching. TGIRT template-switching reverse transcription reactions use an initial template–primer substrate comprised of an RNA oligonucleotide, which contains an Illumina
Figure Legend Snippet: TGIRT-seq overview. ( A ) RNA-seq library construction via TGIRT template-switching. TGIRT template-switching reverse transcription reactions use an initial template–primer substrate comprised of an RNA oligonucleotide, which contains an Illumina

Techniques Used: RNA Sequencing Assay

TGIRT-seq identifies full-length mature tRNAs and tRNA fragments in human plasma. ( A ) Relative abundance of tRNAs identified in RNA-seq data sets constructed with TeI4c RT for total plasma RNA prepared by the Direct-zol method without (NT; combined DS1–3)
Figure Legend Snippet: TGIRT-seq identifies full-length mature tRNAs and tRNA fragments in human plasma. ( A ) Relative abundance of tRNAs identified in RNA-seq data sets constructed with TeI4c RT for total plasma RNA prepared by the Direct-zol method without (NT; combined DS1–3)

Techniques Used: RNA Sequencing Assay, Construct

32) Product Images from "A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations"

Article Title: A highly robust and optimized sequence-based approach for genetic polymorphism discovery and genotyping in large plant populations

Journal: TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik

doi: 10.1007/s00122-016-2736-9

Workflow of modified RAD-seq library construction. a shearing the cellular DNA into fragments, b ligating the adapters to fragment ends, c pooling of samples and fragment size selection, d second round of digestion to remove the DNA fragments from rRNA genes and chloroplast sequence, e PCR amplification, f second round of fragment size selection
Figure Legend Snippet: Workflow of modified RAD-seq library construction. a shearing the cellular DNA into fragments, b ligating the adapters to fragment ends, c pooling of samples and fragment size selection, d second round of digestion to remove the DNA fragments from rRNA genes and chloroplast sequence, e PCR amplification, f second round of fragment size selection

Techniques Used: Modification, Selection, Sequencing, Polymerase Chain Reaction, Amplification

33) Product Images from "Genome-Wide Fitness and Genetic Interactions Determined by Tn-seq, a High-Throughput Massively Parallel Sequencing Method for Microorganisms"

Article Title: Genome-Wide Fitness and Genetic Interactions Determined by Tn-seq, a High-Throughput Massively Parallel Sequencing Method for Microorganisms

Journal: Current protocols in microbiology

doi: 10.1002/9780471729259.mc01e03s36

Detailed schema of how the magellan6 -specific primers and adapter combine to result in a 120-bp DNA fragment that can be sequenced on an Illumina Genome Analyzer II (GAII) platform. AP-B_bc-ACAC (AP-B) and AP-A_bc-ACAC (AP-A) are two oligos that make
Figure Legend Snippet: Detailed schema of how the magellan6 -specific primers and adapter combine to result in a 120-bp DNA fragment that can be sequenced on an Illumina Genome Analyzer II (GAII) platform. AP-B_bc-ACAC (AP-B) and AP-A_bc-ACAC (AP-A) are two oligos that make

Techniques Used:

34) Product Images from "Decreasing miRNA sequencing bias using a single adapter and circularization approach"

Article Title: Decreasing miRNA sequencing bias using a single adapter and circularization approach

Journal: Genome Biology

doi: 10.1186/s13059-018-1488-z

Bias in miRNA detection using various small-RNA library preparation kits. For each kit, sequencing libraries were prepared from the miRXplore™ pool and sequenced; the sequence data were then used to calculate fold-deviations from the equimolar input and plotted as log 2 values. Densities of miRNAs within a two-fold deviation from the expected values (between vertical lines ) are considered unbiased according to [ 8 ]. Under-represented, over-represented, and accurately quantified percentages of miRNAs are shown in red font . Results for two-adapter schemes are a TruSeq® Small RNA, b NEBNext®, and c QIAseq. d NEXTFlex™, a scheme using two adapters with randomized sequences. e SMARTer, which uses template switching. f RealSeq®-AC, which uses a single-adapter and circularization (* p value vs other kits
Figure Legend Snippet: Bias in miRNA detection using various small-RNA library preparation kits. For each kit, sequencing libraries were prepared from the miRXplore™ pool and sequenced; the sequence data were then used to calculate fold-deviations from the equimolar input and plotted as log 2 values. Densities of miRNAs within a two-fold deviation from the expected values (between vertical lines ) are considered unbiased according to [ 8 ]. Under-represented, over-represented, and accurately quantified percentages of miRNAs are shown in red font . Results for two-adapter schemes are a TruSeq® Small RNA, b NEBNext®, and c QIAseq. d NEXTFlex™, a scheme using two adapters with randomized sequences. e SMARTer, which uses template switching. f RealSeq®-AC, which uses a single-adapter and circularization (* p value vs other kits

Techniques Used: Sequencing

Differential quantification of brain samples between different small RNA library preparation kits. Data obtained with either a TruSeq®, b NEBNext®, c NEXTFlex™, d QIAseq, or e SMARTer kits were compared with data obtained with RealSeq®-AC to obtain differential quantification (log 2 ) values for 276 high-confidence miRNAs. These values were plotted against the accuracy of detection of that miRNA when profiling the equimolar pool of synthetic miRNAs (Fig. 2 a–c). f–j The reverse comparison, with the differential quantification of RealSeq®-AC versus each of the other kits plotted against the accuracy of RealSeq®-AC when quantifying the synthetic pool of miRNAs. FN false negative, FP false positive. See Methods for more details
Figure Legend Snippet: Differential quantification of brain samples between different small RNA library preparation kits. Data obtained with either a TruSeq®, b NEBNext®, c NEXTFlex™, d QIAseq, or e SMARTer kits were compared with data obtained with RealSeq®-AC to obtain differential quantification (log 2 ) values for 276 high-confidence miRNAs. These values were plotted against the accuracy of detection of that miRNA when profiling the equimolar pool of synthetic miRNAs (Fig. 2 a–c). f–j The reverse comparison, with the differential quantification of RealSeq®-AC versus each of the other kits plotted against the accuracy of RealSeq®-AC when quantifying the synthetic pool of miRNAs. FN false negative, FP false positive. See Methods for more details

Techniques Used:

35) Product Images from "A Modified RNA-Seq Approach for Whole Genome Sequencing of RNA Viruses from Faecal and Blood Samples"

Article Title: A Modified RNA-Seq Approach for Whole Genome Sequencing of RNA Viruses from Faecal and Blood Samples

Journal: PLoS ONE

doi: 10.1371/journal.pone.0066129

Schematic representation of different strategies for viral genome resequencing. A) Total RNA library: all the RNA species present in the sample are sequenced, no assumption on which genome is present, B) Hybridisation capture of a mRNA library: a good reference genome is needed to design the probes for capture, C) PCR enrichment: the desired genome is amplified from cDNA, a reference genome is needed to design specific oligos. Red lines, genomes of interest; Blue segments, Illumina adapters; Black lines, other RNA species.
Figure Legend Snippet: Schematic representation of different strategies for viral genome resequencing. A) Total RNA library: all the RNA species present in the sample are sequenced, no assumption on which genome is present, B) Hybridisation capture of a mRNA library: a good reference genome is needed to design the probes for capture, C) PCR enrichment: the desired genome is amplified from cDNA, a reference genome is needed to design specific oligos. Red lines, genomes of interest; Blue segments, Illumina adapters; Black lines, other RNA species.

Techniques Used: Hybridization, Capture-C, Polymerase Chain Reaction, Amplification

36) Product Images from "Temporal dynamics and developmental memory of 3D chromatin architecture at Hox gene loci"

Article Title: Temporal dynamics and developmental memory of 3D chromatin architecture at Hox gene loci

Journal: eLife

doi: 10.7554/eLife.02557

Temporal colinearity occurs without dynamic long-range interactions. ( A ) Distribution of long-range contacts in the centromeric and telomeric gene deserts surrounding the HoxD cluster. Smoothed 4C-seq signals (11 fragment window size) for the indicated HoxD viewpoints either in ES (orange), E8.5 pre-somitic mesoderm (cyan), E9.5 tail bud (brown) or E10.5 tail bud (purple) cells over the same genomic interval as analyzed in Woltering et al. (2014) . Genomic location of the HoxD cluster and surrounding genes is indicated below. TADs observed in ES cells (from Dixon et al. 2012 ) are indicated on the top. The positions of both the HoxD cluster and the centromeric and telomeric gene deserts are indicated by arrows. The dashed lines demarcate the domain of high signals over the HoxD cluster, which is excluded from the analysis. ( B ) Hierarchical clustering of global patterns of long-range interactions in the surrounding gene deserts, for Hoxd viewpoints in ES cells and at different stages of sequential Hox gene activation. The Hoxd4 , Hoxd11 and Hoxd13 viewpoints are consistently clustered together, with the Hoxd13 behaving as an outlier. The correlations between samples (indicated by heatmaps) were calculated using Spearman's ranking of smoothed 4C-seq signals (11 fragment window size) over the combined genomic intervals as used in Woltering et al. (2014) , with the HoxD cluster itself excluded. The samples were subsequently clustered (top) according to standard hierarchical clustering. ( C ) Hierarchical clustering of global patterns of long-range interactions in the surrounding gene deserts for Hoxd viewpoints in autopod (digits) and zeugopod (limbs) cells. Data are from Woltering et al. (2014) . DOI: http://dx.doi.org/10.7554/eLife.02557.018
Figure Legend Snippet: Temporal colinearity occurs without dynamic long-range interactions. ( A ) Distribution of long-range contacts in the centromeric and telomeric gene deserts surrounding the HoxD cluster. Smoothed 4C-seq signals (11 fragment window size) for the indicated HoxD viewpoints either in ES (orange), E8.5 pre-somitic mesoderm (cyan), E9.5 tail bud (brown) or E10.5 tail bud (purple) cells over the same genomic interval as analyzed in Woltering et al. (2014) . Genomic location of the HoxD cluster and surrounding genes is indicated below. TADs observed in ES cells (from Dixon et al. 2012 ) are indicated on the top. The positions of both the HoxD cluster and the centromeric and telomeric gene deserts are indicated by arrows. The dashed lines demarcate the domain of high signals over the HoxD cluster, which is excluded from the analysis. ( B ) Hierarchical clustering of global patterns of long-range interactions in the surrounding gene deserts, for Hoxd viewpoints in ES cells and at different stages of sequential Hox gene activation. The Hoxd4 , Hoxd11 and Hoxd13 viewpoints are consistently clustered together, with the Hoxd13 behaving as an outlier. The correlations between samples (indicated by heatmaps) were calculated using Spearman's ranking of smoothed 4C-seq signals (11 fragment window size) over the combined genomic intervals as used in Woltering et al. (2014) , with the HoxD cluster itself excluded. The samples were subsequently clustered (top) according to standard hierarchical clustering. ( C ) Hierarchical clustering of global patterns of long-range interactions in the surrounding gene deserts for Hoxd viewpoints in autopod (digits) and zeugopod (limbs) cells. Data are from Woltering et al. (2014) . DOI: http://dx.doi.org/10.7554/eLife.02557.018

Techniques Used: Activation Assay

Activated Hoxd genes switch compartments. Quantitative local 4C-seq signals for the Hoxd13 , Hoxd11 Hoxd9 and Hoxd4 viewpoints in either E8.5 pre-somitic mesoderm (cyan), E9.5 tail bud (brown) or E10.5 tail bud (purple) cells. The colinear expression status of Hoxd genes is schematized below each profile and, on the left, below each cartoon. Ratios between 4C-seq signals in different samples are indicated between the corresponding profiles. The boundaries between active and inactive Hox gene compartments are indicated by dashed lines and regions displaying important changes in interactions, as discussed in the text, are highlighted. Black arrows point towards opposing interacting behaviors due to the heterogeneous activity state of the viewpoint in the sample. The locations of Hoxd genes (red) and other transcripts (black) are shown below. DOI: http://dx.doi.org/10.7554/eLife.02557.015
Figure Legend Snippet: Activated Hoxd genes switch compartments. Quantitative local 4C-seq signals for the Hoxd13 , Hoxd11 Hoxd9 and Hoxd4 viewpoints in either E8.5 pre-somitic mesoderm (cyan), E9.5 tail bud (brown) or E10.5 tail bud (purple) cells. The colinear expression status of Hoxd genes is schematized below each profile and, on the left, below each cartoon. Ratios between 4C-seq signals in different samples are indicated between the corresponding profiles. The boundaries between active and inactive Hox gene compartments are indicated by dashed lines and regions displaying important changes in interactions, as discussed in the text, are highlighted. Black arrows point towards opposing interacting behaviors due to the heterogeneous activity state of the viewpoint in the sample. The locations of Hoxd genes (red) and other transcripts (black) are shown below. DOI: http://dx.doi.org/10.7554/eLife.02557.015

Techniques Used: Expressing, Activity Assay

37) Product Images from "RNA degradation by the plant RNA exosome involves both phosphorolytic and hydrolytic activities"

Article Title: RNA degradation by the plant RNA exosome involves both phosphorolytic and hydrolytic activities

Journal: Nature Communications

doi: 10.1038/s41467-017-02066-2

Exo9 activity is involved in processing or degradation of 5.8S rRNA precursors. a High density mapping of 5.8S rRNA precursors by 3′RACE-seq. Density profiles of 5.8S rRNA precursors degradation intermediates are shown for positions +4 to +28, +1 corresponding to the first nucleotide after the mature 5.8S rRNA (see Supplementary Fig. 5 ). Two replicates are shown in black and orange. The presence of the endogenous RRP41 or the complementation of the rrp41 mutations by RRP41 WT or RRP41 Pi-Cat- , respectively, is indicated at the top of the panels. The Col-0, rrp6L2 , RRP44KD rrp6L2 , or mtr4 genetic background is indicated on the left. Numbering of each panel refers to the lane numbers of the northern blot shown in c . b Diagram of the 5.8S rRNA processing intermediates. Numbers refer to the transcription start site. Vertical arrows above the diagram indicate endonucleolytic processing sites. Key steps leading to the maturation of the 5.8S rRNA are sketched below. The location of the hybridization oligonucleotides O5 and O6 is shown by a magenta arrow. The location of the oligonucleotides used for 3´RACE-seq is shown by blue arrows. O2 was used to map mature 5.8S rRNA mature ends (Supplementary Fig. 5 ), O3 to map 3′ ends of 5.8S rRNA precursors in a . c Northern blot analysis of the accumulation of 5.8S rRNA precursors and mature 5.8S rRNA upon inactivation of Exo9’s activity. A portion of the ethidium bromide (Etbr)-stained gel is used as loading control. Lane numbers refer to the panels in a
Figure Legend Snippet: Exo9 activity is involved in processing or degradation of 5.8S rRNA precursors. a High density mapping of 5.8S rRNA precursors by 3′RACE-seq. Density profiles of 5.8S rRNA precursors degradation intermediates are shown for positions +4 to +28, +1 corresponding to the first nucleotide after the mature 5.8S rRNA (see Supplementary Fig. 5 ). Two replicates are shown in black and orange. The presence of the endogenous RRP41 or the complementation of the rrp41 mutations by RRP41 WT or RRP41 Pi-Cat- , respectively, is indicated at the top of the panels. The Col-0, rrp6L2 , RRP44KD rrp6L2 , or mtr4 genetic background is indicated on the left. Numbering of each panel refers to the lane numbers of the northern blot shown in c . b Diagram of the 5.8S rRNA processing intermediates. Numbers refer to the transcription start site. Vertical arrows above the diagram indicate endonucleolytic processing sites. Key steps leading to the maturation of the 5.8S rRNA are sketched below. The location of the hybridization oligonucleotides O5 and O6 is shown by a magenta arrow. The location of the oligonucleotides used for 3´RACE-seq is shown by blue arrows. O2 was used to map mature 5.8S rRNA mature ends (Supplementary Fig. 5 ), O3 to map 3′ ends of 5.8S rRNA precursors in a . c Northern blot analysis of the accumulation of 5.8S rRNA precursors and mature 5.8S rRNA upon inactivation of Exo9’s activity. A portion of the ethidium bromide (Etbr)-stained gel is used as loading control. Lane numbers refer to the panels in a

Techniques Used: Activity Assay, Northern Blot, Hybridization, Staining

Exo9 activity participates in the elimination of rRNA maturation by-products. a Diagram of the 5′ ETS and its degradation intermediates. A portion of the 35S rRNA precursor comprising the 5′ ETS is drawn at the top. Numbers refer to the transcription start site. Vertical arrows above the diagram indicate processing sites. Key steps leading to the elimination of the 5′ ETS are sketched below. The location of the hybridization oligonucleotide O4 used for Northern analysis is shown by a magenta arrow. The location of the oligonucleotide O1 used for 3’RACE-seq is shown by a blue arrow. b Northern blot analysis of Exo9’s specific in vivo substrates during the elimination of the 5′ ETS. The main 5′ ETS degradation intermediates are noted as P-P’ and P-P1 on the right. Two exposures of the lower part of the blot are shown. A portion of the Ethidium bromide (Etbr)-stained gel is used as control for loading. Lane numbers at the bottom refer to the panels shown in c – f . c – f High density mapping of 3′ extremities of P-P1 degradation intermediates by 3´RACE-Seq. Density profiles are shown for positions +140 to +200, +1 corresponding to the first nucleotide of the P-P’ fragment. Two biological replicates are shown in black and orange, respectively. The presence of endogenous RRP41 or the complementation of the rrp41 mutations by RRP41 WT or RRP41 Pi-Cat- , respectively, is indicated at the top of the panels. The Col-0, rrp6L2 , RRP44KD rrp6L2 or mtr4 genetic backgrounds are indicated on the left in c , d , e , and f , respectively. Numbering of each panel refers to the lane numbers of the northern blot shown in b
Figure Legend Snippet: Exo9 activity participates in the elimination of rRNA maturation by-products. a Diagram of the 5′ ETS and its degradation intermediates. A portion of the 35S rRNA precursor comprising the 5′ ETS is drawn at the top. Numbers refer to the transcription start site. Vertical arrows above the diagram indicate processing sites. Key steps leading to the elimination of the 5′ ETS are sketched below. The location of the hybridization oligonucleotide O4 used for Northern analysis is shown by a magenta arrow. The location of the oligonucleotide O1 used for 3’RACE-seq is shown by a blue arrow. b Northern blot analysis of Exo9’s specific in vivo substrates during the elimination of the 5′ ETS. The main 5′ ETS degradation intermediates are noted as P-P’ and P-P1 on the right. Two exposures of the lower part of the blot are shown. A portion of the Ethidium bromide (Etbr)-stained gel is used as control for loading. Lane numbers at the bottom refer to the panels shown in c – f . c – f High density mapping of 3′ extremities of P-P1 degradation intermediates by 3´RACE-Seq. Density profiles are shown for positions +140 to +200, +1 corresponding to the first nucleotide of the P-P’ fragment. Two biological replicates are shown in black and orange, respectively. The presence of endogenous RRP41 or the complementation of the rrp41 mutations by RRP41 WT or RRP41 Pi-Cat- , respectively, is indicated at the top of the panels. The Col-0, rrp6L2 , RRP44KD rrp6L2 or mtr4 genetic backgrounds are indicated on the left in c , d , e , and f , respectively. Numbering of each panel refers to the lane numbers of the northern blot shown in b

Techniques Used: Activity Assay, Hybridization, Northern Blot, In Vivo, Staining

38) Product Images from "Systematic comparison of small RNA library preparation protocols for next-generation sequencing"

Article Title: Systematic comparison of small RNA library preparation protocols for next-generation sequencing

Journal: BMC Genomics

doi: 10.1186/s12864-018-4491-6

a Predicted secondary structures of the synthetic sRNAs 1–6 used in this study ( Methods ). The free energies at 28 °C are indicated for each sRNA without or with 2’ OMe. Nucleotide substitutions introduced to distinguish between the unmodified RNAs (RNA1–6) and the 2’OMe variants (RNA-OMe1–6) are indicated in red. These nucleotide substitutions did not alter the predicted secondary structures. The absence or presence of 2’ OMe modification is indicated by “-”or “+” signs, respectively. b Predicted secondary structures of RNAs1–6 ligated with the Illumina 3′ adapter. The ligation junctions are indicated by green arrows. c Predicted secondary structures of RNAs1–6 ligated with both the Illumina 3′ and 5′ adapter. The 3′ ligation junctions are indicated by green arrows, the 5′ ligation junctions are indicated by red arrows. Note that for 3′ adapter ligation the structures in ( b ) should be considered and for subsequent 5′ adapter ligation the structures in ( c )
Figure Legend Snippet: a Predicted secondary structures of the synthetic sRNAs 1–6 used in this study ( Methods ). The free energies at 28 °C are indicated for each sRNA without or with 2’ OMe. Nucleotide substitutions introduced to distinguish between the unmodified RNAs (RNA1–6) and the 2’OMe variants (RNA-OMe1–6) are indicated in red. These nucleotide substitutions did not alter the predicted secondary structures. The absence or presence of 2’ OMe modification is indicated by “-”or “+” signs, respectively. b Predicted secondary structures of RNAs1–6 ligated with the Illumina 3′ adapter. The ligation junctions are indicated by green arrows. c Predicted secondary structures of RNAs1–6 ligated with both the Illumina 3′ and 5′ adapter. The 3′ ligation junctions are indicated by green arrows, the 5′ ligation junctions are indicated by red arrows. Note that for 3′ adapter ligation the structures in ( b ) should be considered and for subsequent 5′ adapter ligation the structures in ( c )

Techniques Used: Modification, Ligation

39) Product Images from "Efficient yeast ChIP-Seq using multiplex short-read DNA sequencing"

Article Title: Efficient yeast ChIP-Seq using multiplex short-read DNA sequencing

Journal: BMC Genomics

doi: 10.1186/1471-2164-10-37

PolII signal profiles recapitulate findings from Steinmetz et al . PolII ChIP-Seq signal profiles resemble very closely to those published in Figure 3 of Steinmetz et al [ 54 ]. We obtained consistent binding at the Bap2-Tat1 loci (a) and at the Sed1-Shu2 loci (b). As expected, we did not observe binding at the Flo11 locus (c). For PolII ChIP-Seq experiments, two biological replicates were barcoded with ACGT (PolII_Rep1, dark blue; PolII_Rep2, orange), one was barcoded with TGCT (PolII_Rep3, red) and a fourth replicate had non-barcoded adapters (PolII_Rep4, green). Input DNA serves as a reference (light blue). Axis and scale normalizations are similar to Figure 2 . ORFs above the coordinates axis are on the Watson strand while ORFs below this axis are on the Crick strand.
Figure Legend Snippet: PolII signal profiles recapitulate findings from Steinmetz et al . PolII ChIP-Seq signal profiles resemble very closely to those published in Figure 3 of Steinmetz et al [ 54 ]. We obtained consistent binding at the Bap2-Tat1 loci (a) and at the Sed1-Shu2 loci (b). As expected, we did not observe binding at the Flo11 locus (c). For PolII ChIP-Seq experiments, two biological replicates were barcoded with ACGT (PolII_Rep1, dark blue; PolII_Rep2, orange), one was barcoded with TGCT (PolII_Rep3, red) and a fourth replicate had non-barcoded adapters (PolII_Rep4, green). Input DNA serves as a reference (light blue). Axis and scale normalizations are similar to Figure 2 . ORFs above the coordinates axis are on the Watson strand while ORFs below this axis are on the Crick strand.

Techniques Used: Chromatin Immunoprecipitation, Binding Assay

Comparison of input DNA signal tracks among all four barcoded adapters relative to standard Illumina adapters . An input sample was split in five aliquots. Four were barcoded differentially (top four lanes) and one had non-barcoded, Illumina adapters (fifth lane, labeled 'None'). Barcoded inputs were scored against non-barcoded input. IGB signal tracks of yeast chromosome 16 are shown for each sample, with ORF locations on the x-axis. ORFs are depicted in purple. On the y-axis, a normalized scale represents the number of read counts at a particular location. Each scale is normalized according to the number of mapped reads (Table 10 ). A box in the left panel depicts the enlarged section shown in the right panel for positions between 828,000 and 833,000 to demonstrate the overlap among all signal tracks.
Figure Legend Snippet: Comparison of input DNA signal tracks among all four barcoded adapters relative to standard Illumina adapters . An input sample was split in five aliquots. Four were barcoded differentially (top four lanes) and one had non-barcoded, Illumina adapters (fifth lane, labeled 'None'). Barcoded inputs were scored against non-barcoded input. IGB signal tracks of yeast chromosome 16 are shown for each sample, with ORF locations on the x-axis. ORFs are depicted in purple. On the y-axis, a normalized scale represents the number of read counts at a particular location. Each scale is normalized according to the number of mapped reads (Table 10 ). A box in the left panel depicts the enlarged section shown in the right panel for positions between 828,000 and 833,000 to demonstrate the overlap among all signal tracks.

Techniques Used: Labeling

Barcoded adapters perform similarly to standard Illumina adapters and do not crossover to other samples in the same lane . (a) RNA PolII binding profiles from different biological replicates with the same barcode (PolII_Rep1, dark blue; PolII_Rep3, red), with different barcodes (PolII_Rep2, orange) or without barcode (PolII_Rep4, green) strongly overlap. See also Table 3 . Input DNA serves as a reference (light blue). IGB signal tracks of chromosome 5 between 130,000 and 320,000 are shown for each library. A box in the left panel depicts the enlarged section shown in the right panel between positions 298,000 and 309,000 to illustrate the overlap among all PolII signal tracks. (b) Binding profiles from four different libraries pooled and sequenced in the same flowcell lane show very little resemblance. Shown here are the binding profiles for Cse4_Rep2 (dark blue), Ste12_Rep2 (red), PolII_Rep2 (green) and Input_ACGT (light blue). IGB signal tracks of chromosome 12 between 80,000 and 210,000 are shown for each sample. For (a) and (b), axis and scale normalizations are similar to Figure 2 . (c) Left: Rank-rank comparison of target lists between all pairwise barcoded replicates for Cse4, PolII and Ste12. The horizontal axis shows the fraction of the two lists being compared and the vertical axis shows the fraction of those targets that agree between a given pair of target lists. All comparisons show strong agreement, although the rank lists for Cse4 differ more than PolII or Ste12 for the second half of their length. Right: Rank-rank comparison between barcoded replicates from the same factors (averaged over all pairwise comparisons) compared to rank-rank comparisons for barcoded replicates between different factors: PolII_Rep1 (ACGT) vs. Ste12_Rep1 (TGCT) and Cse4_Rep2 (CATT) vs. Ste12_Rep2 (GTAT).
Figure Legend Snippet: Barcoded adapters perform similarly to standard Illumina adapters and do not crossover to other samples in the same lane . (a) RNA PolII binding profiles from different biological replicates with the same barcode (PolII_Rep1, dark blue; PolII_Rep3, red), with different barcodes (PolII_Rep2, orange) or without barcode (PolII_Rep4, green) strongly overlap. See also Table 3 . Input DNA serves as a reference (light blue). IGB signal tracks of chromosome 5 between 130,000 and 320,000 are shown for each library. A box in the left panel depicts the enlarged section shown in the right panel between positions 298,000 and 309,000 to illustrate the overlap among all PolII signal tracks. (b) Binding profiles from four different libraries pooled and sequenced in the same flowcell lane show very little resemblance. Shown here are the binding profiles for Cse4_Rep2 (dark blue), Ste12_Rep2 (red), PolII_Rep2 (green) and Input_ACGT (light blue). IGB signal tracks of chromosome 12 between 80,000 and 210,000 are shown for each sample. For (a) and (b), axis and scale normalizations are similar to Figure 2 . (c) Left: Rank-rank comparison of target lists between all pairwise barcoded replicates for Cse4, PolII and Ste12. The horizontal axis shows the fraction of the two lists being compared and the vertical axis shows the fraction of those targets that agree between a given pair of target lists. All comparisons show strong agreement, although the rank lists for Cse4 differ more than PolII or Ste12 for the second half of their length. Right: Rank-rank comparison between barcoded replicates from the same factors (averaged over all pairwise comparisons) compared to rank-rank comparisons for barcoded replicates between different factors: PolII_Rep1 (ACGT) vs. Ste12_Rep1 (TGCT) and Cse4_Rep2 (CATT) vs. Ste12_Rep2 (GTAT).

Techniques Used: Binding Assay

Ste12 distribution during pseudohyphal growth is similar across three different biological replicates . Two barcoded replicates (Ste12_Rep2, dark blue; Ste12_Rep1, red) and a non-barcoded replicate (Ste12_Rep3, green) were compared to input DNA (light blue). Ste12 ChIP samples were scored against a pool of input DNA. IGB signal tracks of chromosome 2 between 340,000 and 410,000 are shown for each sample. Axis and scale normalizations are similar to Figure 2 . A box in the left panel containing the TEC1 gene and its surrounding intergenic region was enlarged in panel B and rescaled to emphasize the strong signal at the TEC1 promoter. The same normalization as in Figure 2 was applied. Ste12p and Tec1p act as a dimer during pseudohyphal growth [ 31 ].
Figure Legend Snippet: Ste12 distribution during pseudohyphal growth is similar across three different biological replicates . Two barcoded replicates (Ste12_Rep2, dark blue; Ste12_Rep1, red) and a non-barcoded replicate (Ste12_Rep3, green) were compared to input DNA (light blue). Ste12 ChIP samples were scored against a pool of input DNA. IGB signal tracks of chromosome 2 between 340,000 and 410,000 are shown for each sample. Axis and scale normalizations are similar to Figure 2 . A box in the left panel containing the TEC1 gene and its surrounding intergenic region was enlarged in panel B and rescaled to emphasize the strong signal at the TEC1 promoter. The same normalization as in Figure 2 was applied. Ste12p and Tec1p act as a dimer during pseudohyphal growth [ 31 ].

Techniques Used: Chromatin Immunoprecipitation, Activated Clotting Time Assay

Cse4p is found robustly at centromeres . All biological replicates were strongly and tightly bound to centromeres, as it is depicted here in the case of CEN11 . Two barcoded replicates (Cse4_Rep2, dark blue; Cse4_Rep1, red) and a non-barcoded replicate (Cse4_Rep3, green) were compared to input DNA (light blue). Cse4 ChIP samples were scored against a pool of input DNA. IGB signal tracks of the CEN11 on chromosome 11 are shown for each sample. CEN11 is highlighted in a yellow box. Axis and scale normalizations are similar to Figure 2 .
Figure Legend Snippet: Cse4p is found robustly at centromeres . All biological replicates were strongly and tightly bound to centromeres, as it is depicted here in the case of CEN11 . Two barcoded replicates (Cse4_Rep2, dark blue; Cse4_Rep1, red) and a non-barcoded replicate (Cse4_Rep3, green) were compared to input DNA (light blue). Cse4 ChIP samples were scored against a pool of input DNA. IGB signal tracks of the CEN11 on chromosome 11 are shown for each sample. CEN11 is highlighted in a yellow box. Axis and scale normalizations are similar to Figure 2 .

Techniques Used: Chromatin Immunoprecipitation

Scheme for yeast barcoded ChIP-Seq . (a) Barcoded ChIP-Seq workflow. Ovals depict yeast cells and squares depict proteins. An aliquot of sheared cell lysate is not immunoprecipitated but is otherwise processed normally (green). This DNA, termed input DNA, is a reference sample for ChIP-Seq. Illumina DNA libraries are generated from both ChIP and input DNA samples. In multiplex ChIP-Seq, a barcoded adapter is ligated to an individual DNA sample. The barcode has 3 unique bases followed by a 'T' to anneal with the end-repaired DNA. Four libraries are then pooled together and applied to a single flowcell lane. After sequencing on the Genome Analyzer, reads are separated according to the first four bases and aligned to the yeast genome. Reads are stacked to generate a signal profile and scored against a pool of input DNA to determine significant transcription factor binding sites. (b) The barcode (orange) is located between Illumina adapter sequences (purple) and ChIP or input DNA inserts (black). The sequencing primer (pink) anneals to the adapter sequences and short reads start with the four bases of the barcode (orange) followed by DNA inserts (black). For the sequencing primer and Illumina adapter, oligonucleotide sequences were given by the manufacturer © 2006 Illumina, Inc. All rights reserved.
Figure Legend Snippet: Scheme for yeast barcoded ChIP-Seq . (a) Barcoded ChIP-Seq workflow. Ovals depict yeast cells and squares depict proteins. An aliquot of sheared cell lysate is not immunoprecipitated but is otherwise processed normally (green). This DNA, termed input DNA, is a reference sample for ChIP-Seq. Illumina DNA libraries are generated from both ChIP and input DNA samples. In multiplex ChIP-Seq, a barcoded adapter is ligated to an individual DNA sample. The barcode has 3 unique bases followed by a 'T' to anneal with the end-repaired DNA. Four libraries are then pooled together and applied to a single flowcell lane. After sequencing on the Genome Analyzer, reads are separated according to the first four bases and aligned to the yeast genome. Reads are stacked to generate a signal profile and scored against a pool of input DNA to determine significant transcription factor binding sites. (b) The barcode (orange) is located between Illumina adapter sequences (purple) and ChIP or input DNA inserts (black). The sequencing primer (pink) anneals to the adapter sequences and short reads start with the four bases of the barcode (orange) followed by DNA inserts (black). For the sequencing primer and Illumina adapter, oligonucleotide sequences were given by the manufacturer © 2006 Illumina, Inc. All rights reserved.

Techniques Used: Chromatin Immunoprecipitation, Immunoprecipitation, Generated, Multiplex Assay, Sequencing, Binding Assay

40) Product Images from "Small Non-coding RNA Expression and Vertebrate Anoxia Tolerance"

Article Title: Small Non-coding RNA Expression and Vertebrate Anoxia Tolerance

Journal: Frontiers in Genetics

doi: 10.3389/fgene.2018.00230

Annotation of abundant (top 100) small ncRNA sequences in normoxia, anoxia, and in other species of interest. Most small ncRNAs annotate to known stress-responsive miRNAs in the (A) epaulette shark, leopard frog, crucian carp, and painted turtle during normoxia and anoxia, (B) highly anoxia-tolerant annual killifish embryos, and (C) brain tissue of highly anoxia-sensitive species. Data for whole annual killifish embryos from Riggs and Podrabsky (2017) . Data from Riggs and Podrabsky reanalyzed to present identical RNA subclass categories in this figure. Percentages for human and rhesus macaques based on top 40 miRNAs in brain ( Shao et al., 2010 ).
Figure Legend Snippet: Annotation of abundant (top 100) small ncRNA sequences in normoxia, anoxia, and in other species of interest. Most small ncRNAs annotate to known stress-responsive miRNAs in the (A) epaulette shark, leopard frog, crucian carp, and painted turtle during normoxia and anoxia, (B) highly anoxia-tolerant annual killifish embryos, and (C) brain tissue of highly anoxia-sensitive species. Data for whole annual killifish embryos from Riggs and Podrabsky (2017) . Data from Riggs and Podrabsky reanalyzed to present identical RNA subclass categories in this figure. Percentages for human and rhesus macaques based on top 40 miRNAs in brain ( Shao et al., 2010 ).

Techniques Used:

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RNA Sequencing Assay:

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Isolation:

Article Title: The lupus susceptibility locus Sgp3 encodes the suppressor of endogenous retrovirus expression SNERV
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Next-Generation Sequencing:

Article Title: A comparative analysis of library prep approaches for sequencing low input translatome samples
Article Snippet: .. We compared 5 methods of library preparation for Illumina Next Generation sequencing: NuGEN Ovation RNA-Seq system V2 Kit, TaKaRa SMARTer Stranded Total RNA-Seq Kit, TaKaRa SMART-Seq v4 Ultra Low Input RNA Kit, Illumina TruSeq RNA Library Prep Kit v2 and NEBNext® Ultra™ Directional RNA Library Prep Kit using slightly modified protocols each with 4 ng of total RNA. ..

Sequencing:

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Generated:

Article Title: A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples
Article Snippet: .. Sequencing libraries Poly-A enriched strand-specific libraries were generated with the TruSeq mRNA V2 sample preparation kit (#RS-122-2001, Illumina), ribosomal RNA depleted strand-specific RNA libraries with the TruSeq Stranded Total RNA LT sample preparation kit with Ribo-Zero Gold (#RS-122-2301and (#RS-122-2302, Illumina), and transcriptome capture based libraries with the TruSeq RNA Access Library Prep Kit (#RS-301-2001, Illumina). ..

Modification:

Article Title: A comparative analysis of library prep approaches for sequencing low input translatome samples
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Sample Prep:

Article Title: A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples
Article Snippet: .. Sequencing libraries Poly-A enriched strand-specific libraries were generated with the TruSeq mRNA V2 sample preparation kit (#RS-122-2001, Illumina), ribosomal RNA depleted strand-specific RNA libraries with the TruSeq Stranded Total RNA LT sample preparation kit with Ribo-Zero Gold (#RS-122-2301and (#RS-122-2302, Illumina), and transcriptome capture based libraries with the TruSeq RNA Access Library Prep Kit (#RS-301-2001, Illumina). ..

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