Structured Review

Illumina Inc barcodes
Flowchart for generating MinION <t>barcodes</t> from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.
Barcodes, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 88/100, based on 40 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/barcodes/product/Illumina Inc
Average 88 stars, based on 40 article reviews
Price from $9.99 to $1999.99
barcodes - by Bioz Stars, 2022-10
88/100 stars

Images

1) Product Images from "Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing"

Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

Journal: bioRxiv

doi: 10.1101/622365

Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.
Figure Legend Snippet: Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.

Techniques Used:

Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.
Figure Legend Snippet: Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.

Techniques Used:

Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage
Figure Legend Snippet: Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

Techniques Used:

2) Product Images from "Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria"

Article Title: Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

Journal: mSystems

doi: 10.1128/mSystems.00143-17

Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.
Figure Legend Snippet: Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.

Techniques Used: Mutagenesis

Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.
Figure Legend Snippet: Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.

Techniques Used: Plasmid Preparation, Clone Assay, Sequencing, DNA Sequencing, Mutagenesis, Construct

3) Product Images from "Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories"

Article Title: Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories

Journal: eLife

doi: 10.7554/eLife.70564

Overview of experiment and results. ( A ) Isolates transformed with the MoBY 2.0 overexpression library were grown competitively and changes in plasmid abundance were quantified, see Materials and methods for details. ( B ) Heat map of hierarchically clustered log 2 (relative fitness scores) for 4064 genes (rows) measured in 15 strains in biological triplicate (columns) after 10 generations of growth. Strain labels are colored according to lineage. Blue and yellow colors represent plasmids that become enriched or depleted in frequency to indicate fitness defects or benefits, respectively, according to the key. Some barcodes with missing values after growth were inferred (see Materials and methods); those that are significant are indicated as an orange box in the heat map. A source data file is included (see Figure 1—source data 1 : Hierarchical clustered fitness scores). Hierarchical clustered fitness scores.
Figure Legend Snippet: Overview of experiment and results. ( A ) Isolates transformed with the MoBY 2.0 overexpression library were grown competitively and changes in plasmid abundance were quantified, see Materials and methods for details. ( B ) Heat map of hierarchically clustered log 2 (relative fitness scores) for 4064 genes (rows) measured in 15 strains in biological triplicate (columns) after 10 generations of growth. Strain labels are colored according to lineage. Blue and yellow colors represent plasmids that become enriched or depleted in frequency to indicate fitness defects or benefits, respectively, according to the key. Some barcodes with missing values after growth were inferred (see Materials and methods); those that are significant are indicated as an orange box in the heat map. A source data file is included (see Figure 1—source data 1 : Hierarchical clustered fitness scores). Hierarchical clustered fitness scores.

Techniques Used: Transformation Assay, Over Expression, Plasmid Preparation

4) Product Images from "Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing"

Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

Journal: BMC Biology

doi: 10.1186/s12915-019-0706-9

Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green, and the scripts available in miniBarcoder for analyses are further indicated
Figure Legend Snippet: Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green, and the scripts available in miniBarcoder for analyses are further indicated

Techniques Used:

Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage
Figure Legend Snippet: Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

Techniques Used:

Ambiguities in MAFFT+AA (purple), RACON+AA (yellow), and consolidated barcodes (green) with varying namino parameters (1, 2, and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining
Figure Legend Snippet: Ambiguities in MAFFT+AA (purple), RACON+AA (yellow), and consolidated barcodes (green) with varying namino parameters (1, 2, and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining

Techniques Used:

5) Product Images from "DNMT3A knockouts in human iPSCs prevent de novo DNA methylation and reveal growth advantage during hematopoietic differentiation"

Article Title: DNMT3A knockouts in human iPSCs prevent de novo DNA methylation and reveal growth advantage during hematopoietic differentiation

Journal: bioRxiv

doi: 10.1101/2021.12.15.472782

Competitive growth advantage of exon 23 -/- cells during hematopoietic differentiation. a) Syngeneic wildtype, exon 19 -/- and exon 23 -/- iPSCs were transduced with a lentiviral barcoding system and the fluorophores Venus, Cerulean, and mCherry, respectively. The schematic representation depicts competitive growth in co-culture during embryoid body (EB) formation, hematopoietic differentiation, and additional long-term culture (n = 3, all donor 1). b) Representative phase contrast and fluorescence microscopic images of EBs with mixed populations at day -4 (day 3 of EB growth). c) Flow cytometry analysis of iHPCs after 15 days of hematopoietic differentiation (only cells with a clear fluorescent signal were considered). n = 3 (mean ± SD). d) Alternatively, we analyzed the fluorophore-specific genetic barcodes by amplicon sequencing after mixing of the iPSCs (d-7), in EBs (d0), in iHPCs (d15), and after additional long-term expansion (d43). e) Area plots show clonal growth during differentiation and expansion of the three replicates. The graded colors depict corresponding unique molecular identifiers of the lentiviral barcoding. All statistics were performed with 1-way ANOVA and Tukey’s PostHoc test. * P
Figure Legend Snippet: Competitive growth advantage of exon 23 -/- cells during hematopoietic differentiation. a) Syngeneic wildtype, exon 19 -/- and exon 23 -/- iPSCs were transduced with a lentiviral barcoding system and the fluorophores Venus, Cerulean, and mCherry, respectively. The schematic representation depicts competitive growth in co-culture during embryoid body (EB) formation, hematopoietic differentiation, and additional long-term culture (n = 3, all donor 1). b) Representative phase contrast and fluorescence microscopic images of EBs with mixed populations at day -4 (day 3 of EB growth). c) Flow cytometry analysis of iHPCs after 15 days of hematopoietic differentiation (only cells with a clear fluorescent signal were considered). n = 3 (mean ± SD). d) Alternatively, we analyzed the fluorophore-specific genetic barcodes by amplicon sequencing after mixing of the iPSCs (d-7), in EBs (d0), in iHPCs (d15), and after additional long-term expansion (d43). e) Area plots show clonal growth during differentiation and expansion of the three replicates. The graded colors depict corresponding unique molecular identifiers of the lentiviral barcoding. All statistics were performed with 1-way ANOVA and Tukey’s PostHoc test. * P

Techniques Used: Transduction, Co-Culture Assay, Fluorescence, Flow Cytometry, Amplification, Sequencing

6) Product Images from "Impact of next-generation sequencing error on analysis of barcoded plasmid libraries of known complexity and sequence"

Article Title: Impact of next-generation sequencing error on analysis of barcoded plasmid libraries of known complexity and sequence

Journal: Nucleic Acids Research

doi: 10.1093/nar/gku607

Distribution of the relative abundance of the 500 most abundant barcode sequences detected following analysis of the defined barcode libraries using different sequencing platforms. Libraries containing ( A ) 1, ( B ) 10 and ( C ) 100 defined Illumina-compatible barcode(s) sequenced using the first sequencing run. For the 100-barcode library, the first 89 most abundant barcodes matched expected sequences, and a point of inflection in the distribution of the relative frequencies of barcodes occurred at the 82nd-most abundant barcode. Six putatively false barcodes that were not in the 100-barcode library were detected within the top 100. ( D ) Library containing the same 100 defined Illumina-compatible barcodes sequenced using the second sequencing run after an independent amplification. Seven putatively false barcodes were detected within the top 100. A point of inflection occurred at the 79th-most abundant barcode and again, the first 89 most abundant barcodes matched expected sequences. ( E ) Library containing 100 defined SOLiD-compatible barcodes. The first 82 most abundant barcodes matched expected sequences; however, 13 putatively false barcodes were detected in the top 100. ( F ) Mean and range of relative abundances of expected and false barcodes, for each sample.
Figure Legend Snippet: Distribution of the relative abundance of the 500 most abundant barcode sequences detected following analysis of the defined barcode libraries using different sequencing platforms. Libraries containing ( A ) 1, ( B ) 10 and ( C ) 100 defined Illumina-compatible barcode(s) sequenced using the first sequencing run. For the 100-barcode library, the first 89 most abundant barcodes matched expected sequences, and a point of inflection in the distribution of the relative frequencies of barcodes occurred at the 82nd-most abundant barcode. Six putatively false barcodes that were not in the 100-barcode library were detected within the top 100. ( D ) Library containing the same 100 defined Illumina-compatible barcodes sequenced using the second sequencing run after an independent amplification. Seven putatively false barcodes were detected within the top 100. A point of inflection occurred at the 79th-most abundant barcode and again, the first 89 most abundant barcodes matched expected sequences. ( E ) Library containing 100 defined SOLiD-compatible barcodes. The first 82 most abundant barcodes matched expected sequences; however, 13 putatively false barcodes were detected in the top 100. ( F ) Mean and range of relative abundances of expected and false barcodes, for each sample.

Techniques Used: Sequencing, Amplification

7) Product Images from "Transcript-indexed ATAC-seq for precision immune profiling"

Article Title: Transcript-indexed ATAC-seq for precision immune profiling

Journal: Nature medicine

doi: 10.1038/s41591-018-0008-8

T-ATAC-seq generates open chromatin and TCR profiles in single T cells (a) Outline of the T-ATAC-seq protocol. Squares indicate individual microfluidic chambers in the IFC. T cells are individually captured and sequentially subjected to ATAC-seq (chambers 1–3), reverse transcription of TCRα and TCRβ chain transcripts, and amplification of ATAC-seq and TCR-seq amplicons, in nanoliter-scale reaction volumes. Single-cell libraries are then amplified with cell-identifying barcodes and analyzed by high-throughput sequencing. (b) Pie chart indicating overlap of TCR-seq and ATAC-seq data from single Jurkat cells (231 single cells from 3 independent experiments) that passed quality control filters. Shown are the proportion of cells generating ATAC-seq profiles in which TCRα or TCRβ sequence was also obtained. The gray bar indicates the portion of cells in which ATAC-seq data was obtained, but TCRα or TCRβ data was not (2.6%). (c) T-ATAC-seq data quality control filters. Shown are the number of unique ATAC-seq nuclear fragments in each single Jurkat cell compared to the percentage of fragments in ATAC-seq peaks derived from ensemble Jurkat ATAC-seq profiles. (d) Aggregate (top) and single-cell (bottom) T-ATAC-seq profile characteristics. Shown are enrichments of ATAC-seq Tn5 insertions around transcription start sites (TSS) and the nucleosomal periodicity of ATAC-seq fragment lengths. Aggregate profiles obtained from all T-ATAC-seq single cells, T-ATAC-seq single cells passing quality control filters (QC), and scATAC-seq cells are shown. Fragment length indicates the genomic distance between two Tn5 insertion sites, as determined by paired-end sequencing of ATAC fragments. Density indicates the fraction of fragments with the indicated length. The cell # indicates the position of each individual cell in the IFC, and the associated fragment number indicates the number of unique nuclear fragments obtained in that cell. Count indicates the number of fragments for each fragment length. (e) Quality control filters for TCRα (left) and TCRβ (right) sequences. Shown are TCRα or TCRβ paired-end sequencing read counts for each single cell compared to TCR dominance of the top clone for each cell. TCR dominance is quantified as the fraction of reads that support the most prevalent TCR clone by sequence identity 6 . Dashed lines represent quality control filters of 100 reads and 70% dominance for Jurkat cells. (f) Heat maps showing TCRα or TCRβ rearrangements identified in Jurkat cells. Each axis represents all possible genes within the indicated TCR locus. The labeled genes indicate the sequences identified using T-ATAC-seq. (g) Mouse/human T cell mixing experiment. Shown are visualized cells in the IFC (left), unique nuclear ATAC-seq fragments aligning to the mouse or human genome, and TCR-seq clones identified when compared to mouse or human references (right). In the IFC, human T cells are labeled in green and mouse T cells are labeled in red.
Figure Legend Snippet: T-ATAC-seq generates open chromatin and TCR profiles in single T cells (a) Outline of the T-ATAC-seq protocol. Squares indicate individual microfluidic chambers in the IFC. T cells are individually captured and sequentially subjected to ATAC-seq (chambers 1–3), reverse transcription of TCRα and TCRβ chain transcripts, and amplification of ATAC-seq and TCR-seq amplicons, in nanoliter-scale reaction volumes. Single-cell libraries are then amplified with cell-identifying barcodes and analyzed by high-throughput sequencing. (b) Pie chart indicating overlap of TCR-seq and ATAC-seq data from single Jurkat cells (231 single cells from 3 independent experiments) that passed quality control filters. Shown are the proportion of cells generating ATAC-seq profiles in which TCRα or TCRβ sequence was also obtained. The gray bar indicates the portion of cells in which ATAC-seq data was obtained, but TCRα or TCRβ data was not (2.6%). (c) T-ATAC-seq data quality control filters. Shown are the number of unique ATAC-seq nuclear fragments in each single Jurkat cell compared to the percentage of fragments in ATAC-seq peaks derived from ensemble Jurkat ATAC-seq profiles. (d) Aggregate (top) and single-cell (bottom) T-ATAC-seq profile characteristics. Shown are enrichments of ATAC-seq Tn5 insertions around transcription start sites (TSS) and the nucleosomal periodicity of ATAC-seq fragment lengths. Aggregate profiles obtained from all T-ATAC-seq single cells, T-ATAC-seq single cells passing quality control filters (QC), and scATAC-seq cells are shown. Fragment length indicates the genomic distance between two Tn5 insertion sites, as determined by paired-end sequencing of ATAC fragments. Density indicates the fraction of fragments with the indicated length. The cell # indicates the position of each individual cell in the IFC, and the associated fragment number indicates the number of unique nuclear fragments obtained in that cell. Count indicates the number of fragments for each fragment length. (e) Quality control filters for TCRα (left) and TCRβ (right) sequences. Shown are TCRα or TCRβ paired-end sequencing read counts for each single cell compared to TCR dominance of the top clone for each cell. TCR dominance is quantified as the fraction of reads that support the most prevalent TCR clone by sequence identity 6 . Dashed lines represent quality control filters of 100 reads and 70% dominance for Jurkat cells. (f) Heat maps showing TCRα or TCRβ rearrangements identified in Jurkat cells. Each axis represents all possible genes within the indicated TCR locus. The labeled genes indicate the sequences identified using T-ATAC-seq. (g) Mouse/human T cell mixing experiment. Shown are visualized cells in the IFC (left), unique nuclear ATAC-seq fragments aligning to the mouse or human genome, and TCR-seq clones identified when compared to mouse or human references (right). In the IFC, human T cells are labeled in green and mouse T cells are labeled in red.

Techniques Used: Amplification, Next-Generation Sequencing, Sequencing, Derivative Assay, Cell Counting, Labeling, Clone Assay

8) Product Images from "Complete mapping of mutations to the SARS-CoV-2 spike receptor-binding domain that escape antibody recognition"

Article Title: Complete mapping of mutations to the SARS-CoV-2 spike receptor-binding domain that escape antibody recognition

Journal: bioRxiv

doi: 10.1101/2020.09.10.292078

FACS gating. (A) Representative hierarchical gates drawn to isolate RBD+ single cells as the parent population for FACS gates in (B, C). First, hierarchical gates were drawn to select single-cell events: forward scatter (FSC) versus side scatter (SSC, top left), SSC width versus height (bottom left), and FSC width versus height (top right). Next, FITC+ labeling of a C-terminal epitope tag on the RBD was used to identify RBD+ cells (purple, bottom right). Selection gates for ACE2+ and antibody-negative sorts (B, C) are nested within this RBD+ population. (B) RBD mutant libraries were first sorted for variants that could bind ACE2 with at least 0.01x the affinity of unmutated SARS-CoV-2 RBD. Top three plots show unmutated SARS-CoV-2 labeled at 0 M, 1e-10 M, and 1e-8 M ACE2. A selection gate was drawn to capture unmutated cells labeled at 1e-10 M ACE2. The bottom two plots show the application of this selection gate to the duplicate RBD mutant libraries labeled at 1e-8 M ACE2. Percentages of RBD+ cells (yellow) in each control and library sample that fall into the ACE2+ sort bin are shown in the upper-right of each FACS plot. These ACE2+ sorted libraries were grown overnight and used for subsequent antibody-escape selections. (C) Selection gates for the antibody-escape sorts. Unmutated SARS-CoV-2 RBD was labeled at 400 ng/mL (1x) and 4 ng/mL (0.01x) with each antibody. Antibody-escape selection gates were drawn to capture 0.2% or less of the 1x and up to 95% of the 0.01x antibody-labeled unmutated RBD control cells. Each mutant RBD library was labeled with 400 ng/mL (1x) antibody, and cells that were captured in the “antibody-escape bin” were sorted and their barcodes were sequenced. Percentages of RBD+ cells in each control and library sample that fall into the antibody-escape bin are shown in the bottom-right of each FACS plot.
Figure Legend Snippet: FACS gating. (A) Representative hierarchical gates drawn to isolate RBD+ single cells as the parent population for FACS gates in (B, C). First, hierarchical gates were drawn to select single-cell events: forward scatter (FSC) versus side scatter (SSC, top left), SSC width versus height (bottom left), and FSC width versus height (top right). Next, FITC+ labeling of a C-terminal epitope tag on the RBD was used to identify RBD+ cells (purple, bottom right). Selection gates for ACE2+ and antibody-negative sorts (B, C) are nested within this RBD+ population. (B) RBD mutant libraries were first sorted for variants that could bind ACE2 with at least 0.01x the affinity of unmutated SARS-CoV-2 RBD. Top three plots show unmutated SARS-CoV-2 labeled at 0 M, 1e-10 M, and 1e-8 M ACE2. A selection gate was drawn to capture unmutated cells labeled at 1e-10 M ACE2. The bottom two plots show the application of this selection gate to the duplicate RBD mutant libraries labeled at 1e-8 M ACE2. Percentages of RBD+ cells (yellow) in each control and library sample that fall into the ACE2+ sort bin are shown in the upper-right of each FACS plot. These ACE2+ sorted libraries were grown overnight and used for subsequent antibody-escape selections. (C) Selection gates for the antibody-escape sorts. Unmutated SARS-CoV-2 RBD was labeled at 400 ng/mL (1x) and 4 ng/mL (0.01x) with each antibody. Antibody-escape selection gates were drawn to capture 0.2% or less of the 1x and up to 95% of the 0.01x antibody-labeled unmutated RBD control cells. Each mutant RBD library was labeled with 400 ng/mL (1x) antibody, and cells that were captured in the “antibody-escape bin” were sorted and their barcodes were sequenced. Percentages of RBD+ cells in each control and library sample that fall into the antibody-escape bin are shown in the bottom-right of each FACS plot.

Techniques Used: FACS, Labeling, Selection, Mutagenesis

9) Product Images from "COV-ID: A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva"

Article Title: COV-ID: A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva

Journal: medRxiv

doi: 10.1101/2021.04.23.21255523

Optimization of COV-ID in human saliva (A) Saliva COV-ID sequence validation. Single saliva COV-ID reaction using N2 primers was sequenced by the Sanger method. (B) Validation of control human amplicons for RT-LAMP on saliva. RT-LAMP of TCEP/EDTA inactivated saliva was performed with conventional RT-LAMP primer sets for ACTB and STATH in the presence or absence of RNase A. (C) Characterization of COV-ID sequencing libraries. Breakdown of reads for sequence data presented in Fig. 2D . Samples without added template consist of predominantly adapter dimers. (D) Validation of COV-ID LAMP barcodes. 32 potential barcodes were tested for LAMP primer sets indicated, incompatible barcodes are marked in red. (E) Validation of pooled PCR. COV-ID was performed on saliva samples using unique LAMP barcodes. The RT-LAMP reactions were then amplified either by individual PCR or by first pooling and then performing a single PCR on the pool.
Figure Legend Snippet: Optimization of COV-ID in human saliva (A) Saliva COV-ID sequence validation. Single saliva COV-ID reaction using N2 primers was sequenced by the Sanger method. (B) Validation of control human amplicons for RT-LAMP on saliva. RT-LAMP of TCEP/EDTA inactivated saliva was performed with conventional RT-LAMP primer sets for ACTB and STATH in the presence or absence of RNase A. (C) Characterization of COV-ID sequencing libraries. Breakdown of reads for sequence data presented in Fig. 2D . Samples without added template consist of predominantly adapter dimers. (D) Validation of COV-ID LAMP barcodes. 32 potential barcodes were tested for LAMP primer sets indicated, incompatible barcodes are marked in red. (E) Validation of pooled PCR. COV-ID was performed on saliva samples using unique LAMP barcodes. The RT-LAMP reactions were then amplified either by individual PCR or by first pooling and then performing a single PCR on the pool.

Techniques Used: Sequencing, Polymerase Chain Reaction, Amplification

10) Product Images from "Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics"

Article Title: Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics

Journal: bioRxiv

doi: 10.1101/2022.07.31.502046

The ExBarSeq image processing pipeline integrates data across fields of view and sequencing rounds to identify distinct cellular barcodes. (A) Each sequencing round is stitched in 3D before being downsampled and registered with a sample-wide affine transform: Sequencing rounds 1, 2, 3 and 6 are shown in different colors and overlaid: white indicates overlapping signal of well-registered parts of the sample. Virtual fields of view (vFOV) are then created from the full, roughly aligned original data and then each vFOV is registered again at full resolution, from which the cellular barcodes can be automatically extracted from the cell bodies. Two sample extracted cells are shown. Pre-expansion confocal image of the injection site (left) and the post expansion 3D image of the volume that was in situ sequenced (right) (C) Representative data across six in situ imaging rounds - for clarity, only the two sequencing channels (red and green) are shown. (D) Conceptual diagram of the NMF-based barcode extraction method to create the dictionary of barcodes present in the data (E) Results of the NMF based barcode discovery and alignment across the cubic millimeter dataset. White arrow denotes the position of the cells shown at higher resolution in (B), the four circled cells in A are visible as three yellow cells and a light blue cell in the pseudocolored barcode image. Scale bars are 250 µ m in (B), 20 µ m post expansion in (C) and 100 µ m post expansion in (E).
Figure Legend Snippet: The ExBarSeq image processing pipeline integrates data across fields of view and sequencing rounds to identify distinct cellular barcodes. (A) Each sequencing round is stitched in 3D before being downsampled and registered with a sample-wide affine transform: Sequencing rounds 1, 2, 3 and 6 are shown in different colors and overlaid: white indicates overlapping signal of well-registered parts of the sample. Virtual fields of view (vFOV) are then created from the full, roughly aligned original data and then each vFOV is registered again at full resolution, from which the cellular barcodes can be automatically extracted from the cell bodies. Two sample extracted cells are shown. Pre-expansion confocal image of the injection site (left) and the post expansion 3D image of the volume that was in situ sequenced (right) (C) Representative data across six in situ imaging rounds - for clarity, only the two sequencing channels (red and green) are shown. (D) Conceptual diagram of the NMF-based barcode extraction method to create the dictionary of barcodes present in the data (E) Results of the NMF based barcode discovery and alignment across the cubic millimeter dataset. White arrow denotes the position of the cells shown at higher resolution in (B), the four circled cells in A are visible as three yellow cells and a light blue cell in the pseudocolored barcode image. Scale bars are 250 µ m in (B), 20 µ m post expansion in (C) and 100 µ m post expansion in (E).

Techniques Used: Sequencing, Injection, In Situ, Imaging

Automatically identified barcodes can be studied in situ for distal trafficking into neuropil. (A) GFP expression in the cortical sample illustrates the location of studied barcode trafficking locations. (B) Extracted barcodes from the neurons in the neuropil-rich Layer 2/3 indicate high barcode expression in cell bodies but lower barcode presence in the neuronal processes. Each dot is a barcode amplicon colored by barcode identity (C) Visualizing just one barcode’s spatial pattern indicates potential distal trafficking and, by lack of a GFP signal, illustrates the the barcode’s sub-cellular anti-correlation with GFP. (D) An RNA barcode signature indicates a clear spatial pattern indicating the presence of a neuron. One neuronal barcode, shown in green with its soma at the bottom of the image, demonstrates the expected apical projection in the cortex and can be visualized concurrently with all other aligned barcodes shown in red. The orange dotted “FOV boundary” denotes the point at which two adjacent FOVs were stitched successfully. (E) The statistical patterns of apical and lateral spatial distribution of RNA barcodes relative to the centroid of the Soma matches expected spatial distribution of predominantly apical projections. Scale of 100 µ m in (A) and 25 µ m in (B,C,D).
Figure Legend Snippet: Automatically identified barcodes can be studied in situ for distal trafficking into neuropil. (A) GFP expression in the cortical sample illustrates the location of studied barcode trafficking locations. (B) Extracted barcodes from the neurons in the neuropil-rich Layer 2/3 indicate high barcode expression in cell bodies but lower barcode presence in the neuronal processes. Each dot is a barcode amplicon colored by barcode identity (C) Visualizing just one barcode’s spatial pattern indicates potential distal trafficking and, by lack of a GFP signal, illustrates the the barcode’s sub-cellular anti-correlation with GFP. (D) An RNA barcode signature indicates a clear spatial pattern indicating the presence of a neuron. One neuronal barcode, shown in green with its soma at the bottom of the image, demonstrates the expected apical projection in the cortex and can be visualized concurrently with all other aligned barcodes shown in red. The orange dotted “FOV boundary” denotes the point at which two adjacent FOVs were stitched successfully. (E) The statistical patterns of apical and lateral spatial distribution of RNA barcodes relative to the centroid of the Soma matches expected spatial distribution of predominantly apical projections. Scale of 100 µ m in (A) and 25 µ m in (B,C,D).

Techniques Used: In Situ, Expressing, Amplification

ExBarSeq visualizes barcodes colocalized with antibody stains to endogenous synaptic markers. (A) Examples of clearly distinct synapses as detected in 3.3x expanded ExSeq gel with a library preparation of RNA barcodes (amplicons in red) co-stained with homer (magenta), bassoon (blue) and GFP (green) and imaged on a 40x laser-scanning confocal. The barcode amplicon (arrowhead) in the dendrites is in close proximity to a synapse. (B) Images of a barcode amplicon at an axon terminal. Separate images of only-synapse and only-barcodes included with morphology annotation for clarity. Scale Bars: 20 µ m, 5 µ m post-expansion (zoom in). Red arrows show the location of RNA barcodes and blue/magenta arrows show the directionality of the synapses Time and data estimates for optical imaging of an intact mouse brain with a 40x objective across multiple expansion factors. Arrow indicates the expansion factor used in this study, which corresponds to 7.2 petabytes and 2.65 years of continuous imaging per round of molecular multiplexing. While other expansion factors have been demonstrated, 3.3x presents a balance of clearly distinctive synapses while being conceivably practical with sufficient microscopes.
Figure Legend Snippet: ExBarSeq visualizes barcodes colocalized with antibody stains to endogenous synaptic markers. (A) Examples of clearly distinct synapses as detected in 3.3x expanded ExSeq gel with a library preparation of RNA barcodes (amplicons in red) co-stained with homer (magenta), bassoon (blue) and GFP (green) and imaged on a 40x laser-scanning confocal. The barcode amplicon (arrowhead) in the dendrites is in close proximity to a synapse. (B) Images of a barcode amplicon at an axon terminal. Separate images of only-synapse and only-barcodes included with morphology annotation for clarity. Scale Bars: 20 µ m, 5 µ m post-expansion (zoom in). Red arrows show the location of RNA barcodes and blue/magenta arrows show the directionality of the synapses Time and data estimates for optical imaging of an intact mouse brain with a 40x objective across multiple expansion factors. Arrow indicates the expansion factor used in this study, which corresponds to 7.2 petabytes and 2.65 years of continuous imaging per round of molecular multiplexing. While other expansion factors have been demonstrated, 3.3x presents a balance of clearly distinctive synapses while being conceivably practical with sufficient microscopes.

Techniques Used: Staining, Amplification, Optical Imaging, Imaging, Multiplexing

Experimental pipeline of ExBarSeq. (A) Sindbis vector libraries are injected into an adult mouse brain where each vector expresses many copies of one distinct RNA barcode per neuron (B) The ExBarSeq library preparation protocol involved converting RNA barcodes into cDNA which, along with antibody stains, get anchored into an expandable hydrogel. Amplification of cDNA using rolling circle amplification creates amplicons that can be subjected to in situ sequencing. (C) In situ sequencing processes base-by-base in 3D, for 6 rounds. The image on the right shows representative data for an individual sequencing round. Scale bar is 50 µ m post-expansion.
Figure Legend Snippet: Experimental pipeline of ExBarSeq. (A) Sindbis vector libraries are injected into an adult mouse brain where each vector expresses many copies of one distinct RNA barcode per neuron (B) The ExBarSeq library preparation protocol involved converting RNA barcodes into cDNA which, along with antibody stains, get anchored into an expandable hydrogel. Amplification of cDNA using rolling circle amplification creates amplicons that can be subjected to in situ sequencing. (C) In situ sequencing processes base-by-base in 3D, for 6 rounds. The image on the right shows representative data for an individual sequencing round. Scale bar is 50 µ m post-expansion.

Techniques Used: Plasmid Preparation, Injection, Amplification, In Situ, Sequencing

ExBarSeq resolves RNA barcodes inside dendritic spines. (A) Representative image of a round of sequencing within the injection bolus throughout multiple layers of mouse cortex, dense labeling is observed in the cell bodies. (B) Widefield image of Sindbis library injection site in the mouse cortex. GFP fluorescence is overlaid with a brightfield image. (C) Viewing a single barcoded neuron for one round of in situ sequencing with a 40x objective demonstrates clear morphology of dendritic spines as well as rolony barcode amplicons (Rol) located adjacent to synapses (i, arrowheads). Distal dendritic spines did not have observable barcode amplicons (ii). (D) Visualizing the same neuron as in (C) across six rounds of in situ sequencing in both the dendritic section (Ci) and the cell body. Yellow circles around dendritic spines correspond to the same locations as arrowheads in (Ci). Note these images were not registered, so imaging Round 1 is offset by about 50 µ m. Scale bars are 20 µ m (A), 250 µ m in (B), and 20 µ m for the cell body image in (C) and (D), then 2 µ m for the dendrite view in (Ci, Cii and first two rows of D), post-expansion except for (B) which was not expanded.
Figure Legend Snippet: ExBarSeq resolves RNA barcodes inside dendritic spines. (A) Representative image of a round of sequencing within the injection bolus throughout multiple layers of mouse cortex, dense labeling is observed in the cell bodies. (B) Widefield image of Sindbis library injection site in the mouse cortex. GFP fluorescence is overlaid with a brightfield image. (C) Viewing a single barcoded neuron for one round of in situ sequencing with a 40x objective demonstrates clear morphology of dendritic spines as well as rolony barcode amplicons (Rol) located adjacent to synapses (i, arrowheads). Distal dendritic spines did not have observable barcode amplicons (ii). (D) Visualizing the same neuron as in (C) across six rounds of in situ sequencing in both the dendritic section (Ci) and the cell body. Yellow circles around dendritic spines correspond to the same locations as arrowheads in (Ci). Note these images were not registered, so imaging Round 1 is offset by about 50 µ m. Scale bars are 20 µ m (A), 250 µ m in (B), and 20 µ m for the cell body image in (C) and (D), then 2 µ m for the dendrite view in (Ci, Cii and first two rows of D), post-expansion except for (B) which was not expanded.

Techniques Used: Sequencing, Injection, Labeling, Fluorescence, In Situ, Imaging

11) Product Images from "Breast Tumors Maintain a Reservoir of Subclonal Diversity During Expansion"

Article Title: Breast Tumors Maintain a Reservoir of Subclonal Diversity During Expansion

Journal: Nature

doi: 10.1038/s41586-021-03357-x

ACT Method and Technical Performance (a) Experimental steps to perform Acoustic Cell Tagmentation involve the dissociation of nuclei from tissues, isolation of single nuclei into high density 384-well plates by FACS, acoustic liquid transfer of tagmentation reagents, PCR addition of dual barcodes and pooling of single cell libraries for multiplexed sequencing. (b) Breadth of coverage for sparse scDNA-seq data from four different methods, including ACT, DLP, 10X Genomics CNV and DOP-PCR using N = 100 sampled cells. (c) Overdispersion of bin counts in sparse scDNA-seq data from ACT, DLP, 10X Genomics CNV and DOP-PCR using N=100 sampled cells. (d) Copy number ratio and integer segmentation plots for a single cell from TN1.
Figure Legend Snippet: ACT Method and Technical Performance (a) Experimental steps to perform Acoustic Cell Tagmentation involve the dissociation of nuclei from tissues, isolation of single nuclei into high density 384-well plates by FACS, acoustic liquid transfer of tagmentation reagents, PCR addition of dual barcodes and pooling of single cell libraries for multiplexed sequencing. (b) Breadth of coverage for sparse scDNA-seq data from four different methods, including ACT, DLP, 10X Genomics CNV and DOP-PCR using N = 100 sampled cells. (c) Overdispersion of bin counts in sparse scDNA-seq data from ACT, DLP, 10X Genomics CNV and DOP-PCR using N=100 sampled cells. (d) Copy number ratio and integer segmentation plots for a single cell from TN1.

Techniques Used: Isolation, FACS, Polymerase Chain Reaction, Sequencing, Degenerate Oligonucleotide–primed Polymerase Chain Reaction

12) Product Images from "TagGD: Fast and Accurate Software for DNA Tag Generation and Demultiplexing"

Article Title: TagGD: Fast and Accurate Software for DNA Tag Generation and Demultiplexing

Journal: PLoS ONE

doi: 10.1371/journal.pone.0057521

The generation of barcodes along with all the filtering steps are performed concurrently with the execution of the main application. Each barcode that passes filtering is added to a pool and generation of more barcodes continues. This pool is in time drained by the main application where the insertion into the solution set takes place.
Figure Legend Snippet: The generation of barcodes along with all the filtering steps are performed concurrently with the execution of the main application. Each barcode that passes filtering is added to a pool and generation of more barcodes continues. This pool is in time drained by the main application where the insertion into the solution set takes place.

Techniques Used:

Let barcode 1 and 2 are the barcodes within the designed unique barcode set and another barcode containing errors introduced during the experiment, and the edges of the triangles represent the Levenshtein edit distance between them. A) Barcode 1 can be converted to Barcode 3 with three operations. However two errors introduced either in barcode 1 or 2 can result in a new sequence, which requires same number of operations to transform to either barcode 1 or 2. Therefore, it cannot be classified. B) Barcode 1 is incorrectly synthesised or sequenced in such a way that it now has a smaller edit distance to barcode 2, which leads to its misclassification.
Figure Legend Snippet: Let barcode 1 and 2 are the barcodes within the designed unique barcode set and another barcode containing errors introduced during the experiment, and the edges of the triangles represent the Levenshtein edit distance between them. A) Barcode 1 can be converted to Barcode 3 with three operations. However two errors introduced either in barcode 1 or 2 can result in a new sequence, which requires same number of operations to transform to either barcode 1 or 2. Therefore, it cannot be classified. B) Barcode 1 is incorrectly synthesised or sequenced in such a way that it now has a smaller edit distance to barcode 2, which leads to its misclassification.

Techniques Used: Sequencing

13) Product Images from "Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity"

Article Title: Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity

Journal: Nature Communications

doi: 10.1038/s41467-017-01519-y

Multiplexed, quantitative analysis of Kras mutant oncogenicity using AAV/Cas9-mediated somatic HDR and high-throughput sequencing of barcoded lung tumors. a Pipeline to quantitatively determine the number, size, and genotype of individual tumors directly from bulk lung samples by high-throughput sequencing of tumor barcodes. b – e Number of lung tumors harboring each mutant Kras allele normalized to its initial representation (mutant representation in the AAV plasmid library divided by WT representation in the AAV plasmid library) and relative to WT (mutant tumor # divided by WT tumor #). Variants present in significantly more tumors than WT (two-sided Fisher’s exact test; p
Figure Legend Snippet: Multiplexed, quantitative analysis of Kras mutant oncogenicity using AAV/Cas9-mediated somatic HDR and high-throughput sequencing of barcoded lung tumors. a Pipeline to quantitatively determine the number, size, and genotype of individual tumors directly from bulk lung samples by high-throughput sequencing of tumor barcodes. b – e Number of lung tumors harboring each mutant Kras allele normalized to its initial representation (mutant representation in the AAV plasmid library divided by WT representation in the AAV plasmid library) and relative to WT (mutant tumor # divided by WT tumor #). Variants present in significantly more tumors than WT (two-sided Fisher’s exact test; p

Techniques Used: Mutagenesis, Next-Generation Sequencing, Plasmid Preparation

14) Product Images from "Protocol: A Multiplexed Reporter Assay to Study Effects of Chromatin Context on DNA Double-Strand Break Repair"

Article Title: Protocol: A Multiplexed Reporter Assay to Study Effects of Chromatin Context on DNA Double-Strand Break Repair

Journal: Frontiers in Genetics

doi: 10.3389/fgene.2021.785947

Scheme of DSB-TRIP. (A) Scheme of the barcoded DSB reporter. In grey the PiggyBac inverted terminal repeats, in light green the LBR endogenous sequence with the 20 bp gRNA sequence in dark green. Primers F and R are used to sequence the indels and the barcode. (B) Representation of the barcoded library and an illustration of the TRIP cell pools and clones with the different barcodes represented by different colours. Adapted from ( Schep et al., 2021 ).
Figure Legend Snippet: Scheme of DSB-TRIP. (A) Scheme of the barcoded DSB reporter. In grey the PiggyBac inverted terminal repeats, in light green the LBR endogenous sequence with the 20 bp gRNA sequence in dark green. Primers F and R are used to sequence the indels and the barcode. (B) Representation of the barcoded library and an illustration of the TRIP cell pools and clones with the different barcodes represented by different colours. Adapted from ( Schep et al., 2021 ).

Techniques Used: Sequencing, Clone Assay

IPR expansion and drift over time. Stacked barplot of the percentage of reads each barcode represents over time (days). Each color represents a different barcode (IPR) that are linked between the plots N = 1. Over the time course of the experiment samples were taken from a TRIP cell pool and processed as for scoring indels. The barcodes were retrieved from the indelPCR data, counted and their proportion was plotted per day.
Figure Legend Snippet: IPR expansion and drift over time. Stacked barplot of the percentage of reads each barcode represents over time (days). Each color represents a different barcode (IPR) that are linked between the plots N = 1. Over the time course of the experiment samples were taken from a TRIP cell pool and processed as for scoring indels. The barcodes were retrieved from the indelPCR data, counted and their proportion was plotted per day.

Techniques Used:

15) Product Images from "A genome‐scale yeast library with inducible expression of individual genes"

Article Title: A genome‐scale yeast library with inducible expression of individual genes

Journal: Molecular Systems Biology

doi: 10.15252/msb.202110207

The Z 3 EV system Outline of the β‐estradiol‐inducible gene expression system. Z 3 EV is composed of a 3‐zinc finger DNA‐binding domain (Zif268), human estrogen receptor domain (hER), and transcription activation domain (VP16). β‐estradiol displaces Hsp90 from the estrogen receptor, allowing Z 3 EV to translocate to the nucleus and induce gene expression. Zif268 binds preferentially to a sequence that is present in six copies in Z 3 pr. In the strain collection, gene‐specific DNA barcodes are flanked by universal primer sequences: 5’‐GCACCAGGAACCATATA‐3’ and 5’‐GATCCGCTCGCACCG‐3’. GFP intensity as a function of β‐estradiol concentration. Strains with an integrated Z 3 pr driving GFP (Y15292; blue) and a control strain (Y15483; gray) were incubated with a concentration series of β‐estradiol in YNB for 6 h, and then cells were fixed. GFP intensity was measured by flow cytometry. Error bars represent standard deviation for three replicates. Y15292 (blue) and Y15477 (gray) cultures were induced with 10 nM β‐estradiol for 6 h. Cells were washed, and β‐estradiol was removed from the medium at time = 0 h on the figure. Error bars represent ± 1 standard deviation for three biological replicates.
Figure Legend Snippet: The Z 3 EV system Outline of the β‐estradiol‐inducible gene expression system. Z 3 EV is composed of a 3‐zinc finger DNA‐binding domain (Zif268), human estrogen receptor domain (hER), and transcription activation domain (VP16). β‐estradiol displaces Hsp90 from the estrogen receptor, allowing Z 3 EV to translocate to the nucleus and induce gene expression. Zif268 binds preferentially to a sequence that is present in six copies in Z 3 pr. In the strain collection, gene‐specific DNA barcodes are flanked by universal primer sequences: 5’‐GCACCAGGAACCATATA‐3’ and 5’‐GATCCGCTCGCACCG‐3’. GFP intensity as a function of β‐estradiol concentration. Strains with an integrated Z 3 pr driving GFP (Y15292; blue) and a control strain (Y15483; gray) were incubated with a concentration series of β‐estradiol in YNB for 6 h, and then cells were fixed. GFP intensity was measured by flow cytometry. Error bars represent standard deviation for three replicates. Y15292 (blue) and Y15477 (gray) cultures were induced with 10 nM β‐estradiol for 6 h. Cells were washed, and β‐estradiol was removed from the medium at time = 0 h on the figure. Error bars represent ± 1 standard deviation for three biological replicates.

Techniques Used: Expressing, Binding Assay, Activation Assay, Sequencing, Concentration Assay, Incubation, Flow Cytometry, Standard Deviation

16) Product Images from "Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing"

Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

Journal: BMC Biology

doi: 10.1186/s12915-019-0706-9

Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green, and the scripts available in miniBarcoder for analyses are further indicated
Figure Legend Snippet: Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green, and the scripts available in miniBarcoder for analyses are further indicated

Techniques Used:

Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage
Figure Legend Snippet: Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

Techniques Used:

Ambiguities in MAFFT+AA (purple), RACON+AA (yellow), and consolidated barcodes (green) with varying namino parameters (1, 2, and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining
Figure Legend Snippet: Ambiguities in MAFFT+AA (purple), RACON+AA (yellow), and consolidated barcodes (green) with varying namino parameters (1, 2, and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining

Techniques Used:

17) Product Images from "A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva"

Article Title: A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva

Journal: eLife

doi: 10.7554/eLife.69949

Clinical validation of COV-ID on RNA from nasopharyngeal (NP) swabs. ( A ) COV-ID on RNA from 120 patient-derived NP swabs. COV-ID for SARS-CoV-2 and ACTB was performed using 10 unique LAMP barcodes. Pools of 10 reactions were PCR amplified and sequenced to a minimum depth of 1,000 reads. Scatterplot shows SARS/(SCS +1) ratio against mean N1/N2 Ct value from RT-qPCR assays. Red circles represent samples with Ct
Figure Legend Snippet: Clinical validation of COV-ID on RNA from nasopharyngeal (NP) swabs. ( A ) COV-ID on RNA from 120 patient-derived NP swabs. COV-ID for SARS-CoV-2 and ACTB was performed using 10 unique LAMP barcodes. Pools of 10 reactions were PCR amplified and sequenced to a minimum depth of 1,000 reads. Scatterplot shows SARS/(SCS +1) ratio against mean N1/N2 Ct value from RT-qPCR assays. Red circles represent samples with Ct

Techniques Used: Derivative Assay, Polymerase Chain Reaction, Amplification, Quantitative RT-PCR

Optimization of COV-ID in human saliva. ( A ) Saliva COV-ID sequence validation. Single saliva COV-ID reaction using N2 primers was sequenced by the Sanger method. ( B ) Validation of control human amplicons for reverse transcription loop-mediated isothermal amplification (RT-LAMP) on saliva. RT-LAMP of TCEP/EDTAinactivated saliva was performed with conventional RT-LAMP primer sets for ACTB and STATH in the presence or absence of RNase A. Bars show the mean. Individual biological replicates are shown by circles. ( C ) Characterization of COV-ID sequencing libraries. Breakdown of reads for sequence data presented in Figure 2D . Samples without added template consist of predominantly adapter dimers. ( D ) Validation of COV-ID LAMP barcodes. 32 potential barcodes were tested for LAMP primer sets indicated, incompatible barcodes are marked in red. ( E ) Validation of pooled PCR. COV-ID was performed on saliva samples using unique LAMP barcodes. The RT-LAMP reactions were then amplified either by individual PCR or by first pooling and then performing a single PCR on the pool. Individual biological replicates are shown by circles. Lines indicate the median and interquartile range.
Figure Legend Snippet: Optimization of COV-ID in human saliva. ( A ) Saliva COV-ID sequence validation. Single saliva COV-ID reaction using N2 primers was sequenced by the Sanger method. ( B ) Validation of control human amplicons for reverse transcription loop-mediated isothermal amplification (RT-LAMP) on saliva. RT-LAMP of TCEP/EDTAinactivated saliva was performed with conventional RT-LAMP primer sets for ACTB and STATH in the presence or absence of RNase A. Bars show the mean. Individual biological replicates are shown by circles. ( C ) Characterization of COV-ID sequencing libraries. Breakdown of reads for sequence data presented in Figure 2D . Samples without added template consist of predominantly adapter dimers. ( D ) Validation of COV-ID LAMP barcodes. 32 potential barcodes were tested for LAMP primer sets indicated, incompatible barcodes are marked in red. ( E ) Validation of pooled PCR. COV-ID was performed on saliva samples using unique LAMP barcodes. The RT-LAMP reactions were then amplified either by individual PCR or by first pooling and then performing a single PCR on the pool. Individual biological replicates are shown by circles. Lines indicate the median and interquartile range.

Techniques Used: Sequencing, Amplification, Polymerase Chain Reaction

18) Product Images from "Fast and accurate matching of cellular barcodes across short-reads and long-reads of single-cell RNA-seq experiments"

Article Title: Fast and accurate matching of cellular barcodes across short-reads and long-reads of single-cell RNA-seq experiments

Journal: iScience

doi: 10.1016/j.isci.2022.104530

Cumulative SR coverage with batches of 1,000 barcodes for the real datasets
Figure Legend Snippet: Cumulative SR coverage with batches of 1,000 barcodes for the real datasets

Techniques Used:

Library prepration and sequencing templates for short- and long- reads (A) Overview of the library preparation: Microfluidic chips are used to generate 10x Chromium GEMs, which tag the RNA transcripts with cellular barcodes. After the transcripts are tagged, the GEMs are burst, and the tagged RNA material is split into two pools of sequencing, one for SRs and one for LRs. (B) The SR template. Inside the GEMs, RNA transcripts are tagged with an Illumina adapter that is a fixed sequence, followed by a 16bp cellular barcode (CB), followed by a random 10bp sequence for the unique molecular identifier (UMI). (C) The LR template. Note that the LR template is essentially the same as the SR template with the LR sequencing adapter added. Depending on the specifics of the library preparation, LRs may sequence the forward or the reverse strand of the RNA molecule. In either case, we expect the cellular barcode to be adjacent to the SR adapter sequence.
Figure Legend Snippet: Library prepration and sequencing templates for short- and long- reads (A) Overview of the library preparation: Microfluidic chips are used to generate 10x Chromium GEMs, which tag the RNA transcripts with cellular barcodes. After the transcripts are tagged, the GEMs are burst, and the tagged RNA material is split into two pools of sequencing, one for SRs and one for LRs. (B) The SR template. Inside the GEMs, RNA transcripts are tagged with an Illumina adapter that is a fixed sequence, followed by a 16bp cellular barcode (CB), followed by a random 10bp sequence for the unique molecular identifier (UMI). (C) The LR template. Note that the LR template is essentially the same as the SR template with the LR sequencing adapter added. Depending on the specifics of the library preparation, LRs may sequence the forward or the reverse strand of the RNA molecule. In either case, we expect the cellular barcode to be adjacent to the SR adapter sequence.

Techniques Used: Sequencing

19) Product Images from "YAP/TAZ and ATF4 drive resistance to Sorafenib in hepatocellular carcinoma by preventing ferroptosis"

Article Title: YAP/TAZ and ATF4 drive resistance to Sorafenib in hepatocellular carcinoma by preventing ferroptosis

Journal: EMBO Molecular Medicine

doi: 10.15252/emmm.202114351

YAP/TAZ are key drivers of Sorafenib resistance by inhibiting ferroptosis Scheme of the shRNA‐mediated synthetic lethal screen. Huh7‐IR and CR cells were infected with lentiviral vectors (MOI = 0.5) expressing the shRNA library (human genome‐wide pooled lentiviral shRNA library module 1, vector: pRSI16cb, Cellecta) and cultured with 2 μg/ml puromycin for the selection of shRNA‐expressing cells plus 7 μM Sorafenib (Srf). After 4 weeks of culture, genomic DNA was extracted, and shRNA barcodes were amplified for next‐generation sequencing to uncover the critical genes for Sorafenib resistance. Combinatorial analysis of genes differentially expressed between Sorafenib‐sensitive and resistant cells and genes with depleted barcodes in the synthetic lethal screen in Huh7‐IR and CR cells. Thirty‐eight common genes were identified, among which was WWTR1 coding for TAZ. Huh7‐parental, IR and CR, and Hep3B‐parental, and IR and CR cells were treated with different concentrations of Sorafenib (0, 3, 6, 9 μM) for Huh7‐P/IR/CR and Sorafenib (0, 2, 4, 6 μM) for Hep3B‐P/IR/CR for 18 h before harvest. Protein levels of YAP and TAZ were determined by immunoblotting illustrating higher protein levels of YAP/TAZ in Sorafenib‐resistant cells. GAPDH served as loading control. Results represent three independent experiments. Colony formation assay showing that shRNA‐mediated depletion of YAP/TAZ leads to cell numbers in response to Sorafenib treatment. Huh7 IR and CR cells either expressing a control shRNA (shLuc, non‐targeting shRNA) or shRNA against both YAP and TAZ (shY/T) were treated with different concentrations of Sorafenib (0, 4, 8 μM) for 2 weeks and colonies were visualized by crystal violet staining. Results represent three independent experiments. Gene Set Enrichment Analysis (GSEA) of the genes differentially expressed between YAP/TAZ‐deficient (siY/T) and control siRNA (siCtrl) transfected HLE cells showed an enrichment for genes involved in the regulation of lipid peroxidation. Basal reactive oxygen (ROS) levels increased upon loss of YAP/TAZ. HLE‐shLuc and HLE‐shY/T cell lines were stained with CellROX™ Green Flow Cytometry Assay Kit, and ROS levels were measured by flow cytometry using a 488 nm laser. Results represent three independent experiments. Basal lipid peroxidation levels increased with the loss of function of YAP/TAZ. HLE‐shLuc and HLE‐shY/T cells were stained with C11‐BODIPY 581/591. Reduced‐Bodipy was measured by flow cytometry using a 488 nm laser, and oxidized‐Bodipy was measured with a 561 nm laser. A significant shift of oxidized‐Bodipy occurred upon depletion of YAP/TAZ. Results represent three independent experiments. Colony formation assay demonstrating that the ferroptosis inhibitor Ferrostatin‐1 (Fer) reversed Sorafenib‐induced cell death in YAP/TAZ‐deficient HCC cells. HLE‐shLuc and shY/T cells were treated with different concentrations of Sorafenib (0, 2, 4 μM) and either DMSO or Ferrostatin‐1 (Fer; 5 μM) for 2 weeks. Results represent three independent experiments. Source data are available online for this figure.
Figure Legend Snippet: YAP/TAZ are key drivers of Sorafenib resistance by inhibiting ferroptosis Scheme of the shRNA‐mediated synthetic lethal screen. Huh7‐IR and CR cells were infected with lentiviral vectors (MOI = 0.5) expressing the shRNA library (human genome‐wide pooled lentiviral shRNA library module 1, vector: pRSI16cb, Cellecta) and cultured with 2 μg/ml puromycin for the selection of shRNA‐expressing cells plus 7 μM Sorafenib (Srf). After 4 weeks of culture, genomic DNA was extracted, and shRNA barcodes were amplified for next‐generation sequencing to uncover the critical genes for Sorafenib resistance. Combinatorial analysis of genes differentially expressed between Sorafenib‐sensitive and resistant cells and genes with depleted barcodes in the synthetic lethal screen in Huh7‐IR and CR cells. Thirty‐eight common genes were identified, among which was WWTR1 coding for TAZ. Huh7‐parental, IR and CR, and Hep3B‐parental, and IR and CR cells were treated with different concentrations of Sorafenib (0, 3, 6, 9 μM) for Huh7‐P/IR/CR and Sorafenib (0, 2, 4, 6 μM) for Hep3B‐P/IR/CR for 18 h before harvest. Protein levels of YAP and TAZ were determined by immunoblotting illustrating higher protein levels of YAP/TAZ in Sorafenib‐resistant cells. GAPDH served as loading control. Results represent three independent experiments. Colony formation assay showing that shRNA‐mediated depletion of YAP/TAZ leads to cell numbers in response to Sorafenib treatment. Huh7 IR and CR cells either expressing a control shRNA (shLuc, non‐targeting shRNA) or shRNA against both YAP and TAZ (shY/T) were treated with different concentrations of Sorafenib (0, 4, 8 μM) for 2 weeks and colonies were visualized by crystal violet staining. Results represent three independent experiments. Gene Set Enrichment Analysis (GSEA) of the genes differentially expressed between YAP/TAZ‐deficient (siY/T) and control siRNA (siCtrl) transfected HLE cells showed an enrichment for genes involved in the regulation of lipid peroxidation. Basal reactive oxygen (ROS) levels increased upon loss of YAP/TAZ. HLE‐shLuc and HLE‐shY/T cell lines were stained with CellROX™ Green Flow Cytometry Assay Kit, and ROS levels were measured by flow cytometry using a 488 nm laser. Results represent three independent experiments. Basal lipid peroxidation levels increased with the loss of function of YAP/TAZ. HLE‐shLuc and HLE‐shY/T cells were stained with C11‐BODIPY 581/591. Reduced‐Bodipy was measured by flow cytometry using a 488 nm laser, and oxidized‐Bodipy was measured with a 561 nm laser. A significant shift of oxidized‐Bodipy occurred upon depletion of YAP/TAZ. Results represent three independent experiments. Colony formation assay demonstrating that the ferroptosis inhibitor Ferrostatin‐1 (Fer) reversed Sorafenib‐induced cell death in YAP/TAZ‐deficient HCC cells. HLE‐shLuc and shY/T cells were treated with different concentrations of Sorafenib (0, 2, 4 μM) and either DMSO or Ferrostatin‐1 (Fer; 5 μM) for 2 weeks. Results represent three independent experiments. Source data are available online for this figure.

Techniques Used: shRNA, Infection, Expressing, Genome Wide, Plasmid Preparation, Cell Culture, Selection, Amplification, Next-Generation Sequencing, Colony Assay, Staining, Transfection, Flow Cytometry

20) Product Images from "Geographic clonal tracking in macaques provides insights into HSPC migration and differentiation"

Article Title: Geographic clonal tracking in macaques provides insights into HSPC migration and differentiation

Journal: The Journal of Experimental Medicine

doi: 10.1084/jem.20171341

Geographic HSPC clonal segregation 3.5–7 mo after CD34 + HSPC transplantation. (A) Top: Scatter plots of barcode sequencing read fractions in left and right BM CD34 + HSPCs for the earliest time point posttransplantation sampled in each animal (3.5–7 mo). Each dot represents a single clone (barcode). Bottom: Bias histograms generated by calculating the ratio of read fractions for each clone between left and right BM CD34 + HSPCs. The x axis consists of bins for bias ratios, with the middle bin consisting of clones with less than twofold bias toward left or right BM, and the far left and far right bins containing clones with at 10-fold or greater bias toward the left or right BM sample, respectively. The stacked bars represent cumulative contributions from clones in that bin to total barcoded hematopoiesis, with each horizontal line in the stack delineating contributions from individual clones. (B) Pearson correlation coefficients comparing pairwise fractional contributions between CD34 + and granulocyte (Gr) samples from left (L) and right (R) BM samples and Gr from concurrent PB at the initial sampling time point for each animal. The color scale for r values is shown on the right. (C) Heat maps representing the log fractional contributions of the top 10 most abundant clones in CD34 + and Gr samples from left (L) and right (R) BM and PB, mapped over all samples for that animal at the designated time point. Each row maps contributions from an individual clone, and each column is a sample. Each * designates that the barcode is one of the top 10 contributing clones in that sample. The top 10 clones in each sample are plotted across all samples, so each row in the heat map has at least one *, and each column has exactly ten *. The barcodes are ordered by unsupervised hierarchical clustering using Euclidean distances to group clones together that manifest patterns of contribution similar to the samples shown. The color scale on the right depicts the log fractional clonal contribution size. m, months.
Figure Legend Snippet: Geographic HSPC clonal segregation 3.5–7 mo after CD34 + HSPC transplantation. (A) Top: Scatter plots of barcode sequencing read fractions in left and right BM CD34 + HSPCs for the earliest time point posttransplantation sampled in each animal (3.5–7 mo). Each dot represents a single clone (barcode). Bottom: Bias histograms generated by calculating the ratio of read fractions for each clone between left and right BM CD34 + HSPCs. The x axis consists of bins for bias ratios, with the middle bin consisting of clones with less than twofold bias toward left or right BM, and the far left and far right bins containing clones with at 10-fold or greater bias toward the left or right BM sample, respectively. The stacked bars represent cumulative contributions from clones in that bin to total barcoded hematopoiesis, with each horizontal line in the stack delineating contributions from individual clones. (B) Pearson correlation coefficients comparing pairwise fractional contributions between CD34 + and granulocyte (Gr) samples from left (L) and right (R) BM samples and Gr from concurrent PB at the initial sampling time point for each animal. The color scale for r values is shown on the right. (C) Heat maps representing the log fractional contributions of the top 10 most abundant clones in CD34 + and Gr samples from left (L) and right (R) BM and PB, mapped over all samples for that animal at the designated time point. Each row maps contributions from an individual clone, and each column is a sample. Each * designates that the barcode is one of the top 10 contributing clones in that sample. The top 10 clones in each sample are plotted across all samples, so each row in the heat map has at least one *, and each column has exactly ten *. The barcodes are ordered by unsupervised hierarchical clustering using Euclidean distances to group clones together that manifest patterns of contribution similar to the samples shown. The color scale on the right depicts the log fractional clonal contribution size. m, months.

Techniques Used: Transplantation Assay, Sequencing, Generated, Clone Assay, Sampling

Intravascular versus tissue-resident delineation of cells. (A) CD45-Alexa Fluor 647 positivity (delineating cells that have been within the vasculature during the 4 h after antibody infusion; CD45-Alexa Fluor 647 + is defined as IVas + ) in PB, left BM (left), and right BM (right) for CD16 + and CD56 + NK cells. (B) CD45-Alexa Fluor 647 positivity in PB, left, and right BM for CD3 + T cells, and GFP expression in CD45-BV510 + CD3 + IVas − cells (red line) and CD45-BV510 + CD3 + IVas + (blue line) T cells. (C) Further phenotyping of CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + cells in BM and PB, including CD4, CD8, CD16, CD56, and CCR5 coexpression. (D) TCR-αβ, TCR-γδ, and TCR-Vα24 expression on CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + cells in the BM. The percentages of the gated cells are displayed on the plots for A–D. (E) Top 10 clone heat map of barcodes retrieved from BM CD34 + HSPCs and sorted CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + T cell subsets in the left BM and PB.
Figure Legend Snippet: Intravascular versus tissue-resident delineation of cells. (A) CD45-Alexa Fluor 647 positivity (delineating cells that have been within the vasculature during the 4 h after antibody infusion; CD45-Alexa Fluor 647 + is defined as IVas + ) in PB, left BM (left), and right BM (right) for CD16 + and CD56 + NK cells. (B) CD45-Alexa Fluor 647 positivity in PB, left, and right BM for CD3 + T cells, and GFP expression in CD45-BV510 + CD3 + IVas − cells (red line) and CD45-BV510 + CD3 + IVas + (blue line) T cells. (C) Further phenotyping of CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + cells in BM and PB, including CD4, CD8, CD16, CD56, and CCR5 coexpression. (D) TCR-αβ, TCR-γδ, and TCR-Vα24 expression on CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + cells in the BM. The percentages of the gated cells are displayed on the plots for A–D. (E) Top 10 clone heat map of barcodes retrieved from BM CD34 + HSPCs and sorted CD45-BV510 + CD3 + IVas − or CD45-BV510 + CD3 + IVas + T cell subsets in the left BM and PB.

Techniques Used: Expressing

Clonal contributions to T, B, Mono, Gr, and NK lineages in BM and PB. (A) Heat map representing the log fractional contribution to hematopoiesis of the top 10 most abundant clones in purified CD34 + and Gr, Mono, T, B, and NK subsets (CD56 + : CD56 + CD16 − CD3 − CD20 − CD14 − NK, and CD16 + : CD56 − CD16 + CD3 − CD20 − CD14 − NK) from left and right BM and PB obtained from ZJ31 3.5 mo posttransplantation. The barcodes are ordered by unsupervised hierarchical clustering of Pearson correlations between barcodes. The heat map clusters distinct sets of locally produced clones in the left and right BM (red and blue bars on the right side of the heat map) contributing to Gr, Mono, B, and T cells (black boxed clusters), sharing barcodes with local CD34 + HSPCs. The purple bar indicates clusters of T cell clones present as high contributors both in PB and in both sides of BM. The PB and BM CD16 + NK dominant clones (green bar) are found in all sites and do not overlap with local BM CD34 + HSPC clones or with other lineages in the BM or PB, including CD56 + NK. The cluster delineated with the black bar shows multipotent clones present in all lineages except CD16 + NK, and in all locations. (B) The cumulative fractional contribution of the left BM (top) and right BM (bottom) 10× biased CD34 + clones (defined as 10-fold higher fractional contribution to one side of BM CD34 + than to the other side of BM CD34 + ) in all lineages all locations in ZJ31 at 3.5 mo. (C) Top 10 clone heat map for ZH19 at 6 mo posttransplantation, with delineation of clusters as detailed in A. (D) Cumulative fractional contribution of the left BM (top) and right BM (bottom) 10× biased CD34 + clones in all lineages in all locations in ZH19 at 6 mo. m, months.
Figure Legend Snippet: Clonal contributions to T, B, Mono, Gr, and NK lineages in BM and PB. (A) Heat map representing the log fractional contribution to hematopoiesis of the top 10 most abundant clones in purified CD34 + and Gr, Mono, T, B, and NK subsets (CD56 + : CD56 + CD16 − CD3 − CD20 − CD14 − NK, and CD16 + : CD56 − CD16 + CD3 − CD20 − CD14 − NK) from left and right BM and PB obtained from ZJ31 3.5 mo posttransplantation. The barcodes are ordered by unsupervised hierarchical clustering of Pearson correlations between barcodes. The heat map clusters distinct sets of locally produced clones in the left and right BM (red and blue bars on the right side of the heat map) contributing to Gr, Mono, B, and T cells (black boxed clusters), sharing barcodes with local CD34 + HSPCs. The purple bar indicates clusters of T cell clones present as high contributors both in PB and in both sides of BM. The PB and BM CD16 + NK dominant clones (green bar) are found in all sites and do not overlap with local BM CD34 + HSPC clones or with other lineages in the BM or PB, including CD56 + NK. The cluster delineated with the black bar shows multipotent clones present in all lineages except CD16 + NK, and in all locations. (B) The cumulative fractional contribution of the left BM (top) and right BM (bottom) 10× biased CD34 + clones (defined as 10-fold higher fractional contribution to one side of BM CD34 + than to the other side of BM CD34 + ) in all lineages all locations in ZJ31 at 3.5 mo. (C) Top 10 clone heat map for ZH19 at 6 mo posttransplantation, with delineation of clusters as detailed in A. (D) Cumulative fractional contribution of the left BM (top) and right BM (bottom) 10× biased CD34 + clones in all lineages in all locations in ZH19 at 6 mo. m, months.

Techniques Used: Clone Assay, Purification, Produced

21) Product Images from "Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria"

Article Title: Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

Journal: mSystems

doi: 10.1128/mSystems.00143-17

Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.
Figure Legend Snippet: Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.

Techniques Used: Mutagenesis

Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.
Figure Legend Snippet: Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.

Techniques Used: Plasmid Preparation, Clone Assay, Sequencing, DNA Sequencing, Mutagenesis, Construct

22) Product Images from "Annual periodicity in planktonic bacterial and archaeal community composition of eutrophic Lake Taihu"

Article Title: Annual periodicity in planktonic bacterial and archaeal community composition of eutrophic Lake Taihu

Journal: Scientific Reports

doi: 10.1038/srep15488

Difference of the bacterial community structure and β-diversity between samples with different PCR barcodes and sequencing platforms. ( A ) Genus-level taxonomy profile of samples using different PCR barcodes. Sample IDs are composed of sampling month, site and barcode index. Legends of the bar colors are omitted in this figure as the purpose is to check the consistence between samples using different barcodes. Details of genera are listed in supplementary Table S6 . ( B ) PCoA results of 56 samples sequenced by the GAIIx platform and the Hiseq2000 platform based on relative abundance of OTUs using unweighted Unifrac metric.
Figure Legend Snippet: Difference of the bacterial community structure and β-diversity between samples with different PCR barcodes and sequencing platforms. ( A ) Genus-level taxonomy profile of samples using different PCR barcodes. Sample IDs are composed of sampling month, site and barcode index. Legends of the bar colors are omitted in this figure as the purpose is to check the consistence between samples using different barcodes. Details of genera are listed in supplementary Table S6 . ( B ) PCoA results of 56 samples sequenced by the GAIIx platform and the Hiseq2000 platform based on relative abundance of OTUs using unweighted Unifrac metric.

Techniques Used: Polymerase Chain Reaction, Sequencing, Sampling

23) Product Images from "Genomic environments scale the activities of diverse core promoters"

Article Title: Genomic environments scale the activities of diverse core promoters

Journal: bioRxiv

doi: 10.1101/2021.03.08.434469

patchMPRA measurements are reproducible. (A) Number of promoter barcodes recovered from each location per biological replicate. (B) Number of promoters recovered from each location per biological replicate. (C) Reproducibility of core promoter measurements from independent patchMPRA transfections.
Figure Legend Snippet: patchMPRA measurements are reproducible. (A) Number of promoter barcodes recovered from each location per biological replicate. (B) Number of promoters recovered from each location per biological replicate. (C) Reproducibility of core promoter measurements from independent patchMPRA transfections.

Techniques Used: Transfection

24) Product Images from "Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing"

Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

Journal: bioRxiv

doi: 10.1101/622365

Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.
Figure Legend Snippet: Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.

Techniques Used:

Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.
Figure Legend Snippet: Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.

Techniques Used:

Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage
Figure Legend Snippet: Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

Techniques Used:

25) Product Images from "Optical pooled screens in human cells"

Article Title: Optical pooled screens in human cells

Journal: Cell

doi: 10.1016/j.cell.2019.09.016

Optical pooled genetic screens (A) In pooled screens, a library of genetic perturbations is introduced, typically at a single copy per target cell. In existing approaches, cellular phenotypes are evaluated by bulk NGS of enriched cell populations or single-cell molecular profiling (e.g. single-cell RNA-seq). In optical pooled screens, high-content imaging assays are used to extract rich spatiotemporal information from the sample prior to enzymatic amplification and in situ detection of RNA barcodes, enabling linkage between the phenotype and perturbation genotype of each cell. (B) Targeted in situ sequencing is used to read out RNA barcodes expressed from a single genomic integration. Barcode transcripts are fixed in place, reverse transcribed, and hybridized with single-stranded DNA padlock probes, which bind to common sequences flanking the barcode. The 3’ arm of the padlock is extended and ligated, copying the barcode into a circularized ssDNA molecule, which then undergoes rolling circle amplification. The barcode sequence is then read out by multiple rounds of in situ .
Figure Legend Snippet: Optical pooled genetic screens (A) In pooled screens, a library of genetic perturbations is introduced, typically at a single copy per target cell. In existing approaches, cellular phenotypes are evaluated by bulk NGS of enriched cell populations or single-cell molecular profiling (e.g. single-cell RNA-seq). In optical pooled screens, high-content imaging assays are used to extract rich spatiotemporal information from the sample prior to enzymatic amplification and in situ detection of RNA barcodes, enabling linkage between the phenotype and perturbation genotype of each cell. (B) Targeted in situ sequencing is used to read out RNA barcodes expressed from a single genomic integration. Barcode transcripts are fixed in place, reverse transcribed, and hybridized with single-stranded DNA padlock probes, which bind to common sequences flanking the barcode. The 3’ arm of the padlock is extended and ligated, copying the barcode into a circularized ssDNA molecule, which then undergoes rolling circle amplification. The barcode sequence is then read out by multiple rounds of in situ .

Techniques Used: Next-Generation Sequencing, RNA Sequencing Assay, Imaging, Amplification, In Situ, Sequencing

Accuracy of phenotype-to-genotype mapping assessed with a fluorescent reporter (A) Workflow for CRISPR-Cas9 knockout-based screening of a genetically-encoded frameshift reporter. A library of targeting and non-targeting guides was cloned into either LentiGuide-BC or the CROP-seq vector and transduced into cells at low MOI. Cas9 expression generates indels at the frameshift reporter target locus in cells with a targeting guide and leads to expression of a nuclear-localized HA epitope. HA expression was assayed by immunofluorescence and correlated with sgRNAs detected by in situ sequencing. Frameshift reporter accuracy was estimated using the relative abundances of HA + cells mapped to targeting and non-targeting guides (X and Y, respectively). Scale bar is 30 μm. (B) Targeting and control barcodes expressed from LentiGuide-BC in HeLa-TetR-Cas9 cells were well separated by fraction of HA + cells. (C) The same cell library was screened by flow sorting cells into HA + and HA - . (D) The experiment was repeated across a panel of cell lines using the CROP-seq library and an optimized padlock detection protocol, yielding a similar distribution of mapped reads (top) and frameshift reporter accuracies (bottom). Error bars indicate the range between two replicate sequencing experiments. Cell types are indicated by the same colors in both plots.
Figure Legend Snippet: Accuracy of phenotype-to-genotype mapping assessed with a fluorescent reporter (A) Workflow for CRISPR-Cas9 knockout-based screening of a genetically-encoded frameshift reporter. A library of targeting and non-targeting guides was cloned into either LentiGuide-BC or the CROP-seq vector and transduced into cells at low MOI. Cas9 expression generates indels at the frameshift reporter target locus in cells with a targeting guide and leads to expression of a nuclear-localized HA epitope. HA expression was assayed by immunofluorescence and correlated with sgRNAs detected by in situ sequencing. Frameshift reporter accuracy was estimated using the relative abundances of HA + cells mapped to targeting and non-targeting guides (X and Y, respectively). Scale bar is 30 μm. (B) Targeting and control barcodes expressed from LentiGuide-BC in HeLa-TetR-Cas9 cells were well separated by fraction of HA + cells. (C) The same cell library was screened by flow sorting cells into HA + and HA - . (D) The experiment was repeated across a panel of cell lines using the CROP-seq library and an optimized padlock detection protocol, yielding a similar distribution of mapped reads (top) and frameshift reporter accuracies (bottom). Error bars indicate the range between two replicate sequencing experiments. Cell types are indicated by the same colors in both plots.

Techniques Used: CRISPR, Knock-Out, Clone Assay, Plasmid Preparation, Expressing, Immunofluorescence, In Situ, Sequencing

Identification of perturbation barcodes by in situ sequencing (A) Schematic of perturbation detection by in situ sequencing. Barcodes representing perturbations are expressed on a Pol II transcript and enzymatically converted into cDNA and amplified by RCA. RCA products serve as templates for sequencing-by-synthesis, in which barcodes are read out by multiple cycles of fluorescent nucleotide incorporation, imaging and dye cleavage. . . (D) Most cells contain multiple barcode reads that map to the designed library. (E) Cellular read distribution further categorized by read identity for 77% of cells containing at least one read. (F) The number of possible barcodes scales geometrically with barcode length. Sufficient 12-nt barcodes can be designed to cover a genome-scale perturbation library while maintaining the ability to detect and reject single or double sequencing errors (minimum pairwise Levenshtein distance d = 2 or 3, respectively).
Figure Legend Snippet: Identification of perturbation barcodes by in situ sequencing (A) Schematic of perturbation detection by in situ sequencing. Barcodes representing perturbations are expressed on a Pol II transcript and enzymatically converted into cDNA and amplified by RCA. RCA products serve as templates for sequencing-by-synthesis, in which barcodes are read out by multiple cycles of fluorescent nucleotide incorporation, imaging and dye cleavage. . . (D) Most cells contain multiple barcode reads that map to the designed library. (E) Cellular read distribution further categorized by read identity for 77% of cells containing at least one read. (F) The number of possible barcodes scales geometrically with barcode length. Sufficient 12-nt barcodes can be designed to cover a genome-scale perturbation library while maintaining the ability to detect and reject single or double sequencing errors (minimum pairwise Levenshtein distance d = 2 or 3, respectively).

Techniques Used: In Situ, Sequencing, Amplification, Imaging

26) Product Images from "Impact of next-generation sequencing error on analysis of barcoded plasmid libraries of known complexity and sequence"

Article Title: Impact of next-generation sequencing error on analysis of barcoded plasmid libraries of known complexity and sequence

Journal: Nucleic Acids Research

doi: 10.1093/nar/gku607

Distribution of the relative abundance of the 500 most abundant barcode sequences detected following analysis of the defined barcode libraries using different sequencing platforms. Libraries containing ( A ) 1, ( B ) 10 and ( C ) 100 defined Illumina-compatible barcode(s) sequenced using the first sequencing run. For the 100-barcode library, the first 89 most abundant barcodes matched expected sequences, and a point of inflection in the distribution of the relative frequencies of barcodes occurred at the 82nd-most abundant barcode. Six putatively false barcodes that were not in the 100-barcode library were detected within the top 100. ( D ) Library containing the same 100 defined Illumina-compatible barcodes sequenced using the second sequencing run after an independent amplification. Seven putatively false barcodes were detected within the top 100. A point of inflection occurred at the 79th-most abundant barcode and again, the first 89 most abundant barcodes matched expected sequences. ( E ) Library containing 100 defined SOLiD-compatible barcodes. The first 82 most abundant barcodes matched expected sequences; however, 13 putatively false barcodes were detected in the top 100. ( F ) Mean and range of relative abundances of expected and false barcodes, for each sample.
Figure Legend Snippet: Distribution of the relative abundance of the 500 most abundant barcode sequences detected following analysis of the defined barcode libraries using different sequencing platforms. Libraries containing ( A ) 1, ( B ) 10 and ( C ) 100 defined Illumina-compatible barcode(s) sequenced using the first sequencing run. For the 100-barcode library, the first 89 most abundant barcodes matched expected sequences, and a point of inflection in the distribution of the relative frequencies of barcodes occurred at the 82nd-most abundant barcode. Six putatively false barcodes that were not in the 100-barcode library were detected within the top 100. ( D ) Library containing the same 100 defined Illumina-compatible barcodes sequenced using the second sequencing run after an independent amplification. Seven putatively false barcodes were detected within the top 100. A point of inflection occurred at the 79th-most abundant barcode and again, the first 89 most abundant barcodes matched expected sequences. ( E ) Library containing 100 defined SOLiD-compatible barcodes. The first 82 most abundant barcodes matched expected sequences; however, 13 putatively false barcodes were detected in the top 100. ( F ) Mean and range of relative abundances of expected and false barcodes, for each sample.

Techniques Used: Sequencing, Amplification

27) Product Images from "Genomic environments scale the activities of diverse core promoters"

Article Title: Genomic environments scale the activities of diverse core promoters

Journal: bioRxiv

doi: 10.1101/2021.03.08.434469

patchMPRA measurements are reproducible. (A) Number of promoter barcodes recovered from each location per biological replicate. (B) Number of promoters recovered from each location per biological replicate. (C) Reproducibility of core promoter measurements from independent patchMPRA transfections.
Figure Legend Snippet: patchMPRA measurements are reproducible. (A) Number of promoter barcodes recovered from each location per biological replicate. (B) Number of promoters recovered from each location per biological replicate. (C) Reproducibility of core promoter measurements from independent patchMPRA transfections.

Techniques Used: Transfection

28) Product Images from "MinION barcodes: biodiversity discovery and identification by everyone, for everyone"

Article Title: MinION barcodes: biodiversity discovery and identification by everyone, for everyone

Journal: bioRxiv

doi: 10.1101/2021.03.09.434692

Relationship between barcoding success and number of raw reads for six amplicon pools (191-9932 specimens; barcoding success rates 84-97%). Percentage of barcodes recovered is relative to the final estimate based on all data.
Figure Legend Snippet: Relationship between barcoding success and number of raw reads for six amplicon pools (191-9932 specimens; barcoding success rates 84-97%). Percentage of barcodes recovered is relative to the final estimate based on all data.

Techniques Used: Amplification

Rapid recovery of accurate MinION barcodes over time (in hours, x-axis) (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red). The solid black line represents the number of barcodes available for comparison. White dotted line represents the amount of raw reads collected over time, blue represents number of demultiplexed reads over time (plotted against Z-axis)
Figure Legend Snippet: Rapid recovery of accurate MinION barcodes over time (in hours, x-axis) (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red). The solid black line represents the number of barcodes available for comparison. White dotted line represents the amount of raw reads collected over time, blue represents number of demultiplexed reads over time (plotted against Z-axis)

Techniques Used:

Relationship between barcode quality and coverage. Subsetting the data to 5-200X coverage shows that there are very minor gains to barcode quality after 25-50X coverage. (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red).
Figure Legend Snippet: Relationship between barcode quality and coverage. Subsetting the data to 5-200X coverage shows that there are very minor gains to barcode quality after 25-50X coverage. (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red).

Techniques Used:

29) Product Images from "MinION barcodes: biodiversity discovery and identification by everyone, for everyone"

Article Title: MinION barcodes: biodiversity discovery and identification by everyone, for everyone

Journal: bioRxiv

doi: 10.1101/2021.03.09.434692

Relationship between barcoding success and number of raw reads for six amplicon pools (191-9932 specimens; barcoding success rates 84-97%). Percentage of barcodes recovered is relative to the final estimate based on all data.
Figure Legend Snippet: Relationship between barcoding success and number of raw reads for six amplicon pools (191-9932 specimens; barcoding success rates 84-97%). Percentage of barcodes recovered is relative to the final estimate based on all data.

Techniques Used: Amplification

Rapid recovery of accurate MinION barcodes over time (in hours, x-axis) (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red). The solid black line represents the number of barcodes available for comparison. White dotted line represents the amount of raw reads collected over time, blue represents number of demultiplexed reads over time (plotted against Z-axis)
Figure Legend Snippet: Rapid recovery of accurate MinION barcodes over time (in hours, x-axis) (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red). The solid black line represents the number of barcodes available for comparison. White dotted line represents the amount of raw reads collected over time, blue represents number of demultiplexed reads over time (plotted against Z-axis)

Techniques Used:

Relationship between barcode quality and coverage. Subsetting the data to 5-200X coverage shows that there are very minor gains to barcode quality after 25-50X coverage. (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red).
Figure Legend Snippet: Relationship between barcode quality and coverage. Subsetting the data to 5-200X coverage shows that there are very minor gains to barcode quality after 25-50X coverage. (filtered barcodes: dark green = barcodes passing all 4 QC criteria, light green = one ambiguous base; lighter green = more than 1N, no barcode = white with pattern, 1 mismatch = orange, > 1 mismatch = red).

Techniques Used:

30) Product Images from "Unbiased genome-scale identification of cis-regulatory modules in the human genome by GRAMc"

Article Title: Unbiased genome-scale identification of cis-regulatory modules in the human genome by GRAMc

Journal: bioRxiv

doi: 10.1101/468405

GRAMc library building. ( a ) Controlling genomic coverage of the library. Size-selected and end-repaired random genomic DNA fragments are circularized by ligation with a fused adapter. Linear DNAs are removed by exonuclease treatment followed by RNaseHII digestion to linearize ligation product and dice adapter-concatemers. The purple box indicates two ribonucleotides for RNaseHII cut. Adapter-ligated products are then serially diluted to determine the genomic coverage of each dilution by QPCR. A dilution of intended coverage is Gibson assembled with a SCP-GFP cassette and the vector backbone to form barcode-less, linear constructs. ( b ) Controlling barcode numbers of the library. Random 25bp (N25) barcodes and a core-poly adenylation signal are added to the library of linear constructs by PCR. Barcoded constructs are self-ligated and linear DNAs are removed by exonucleases I/III. A small fraction of ligates is transformed to determine the scale of transformation. To avoid inflation of colony counts due to cell division, transformants for counting colonies should be immediately plated without rescuing. A desired amount of ligates are transformed to produce a GRAMc library with the intended number of barcodes. Plasmids extracted from liquid media are used for library characterization and reporter assay. Inserts and associated barcodes are identified by Illumina paired-end sequencing. ( c ) Size distribution of inserts in the human GRAMc library. ( d ) Cumulative distribution of barcode numbers per insert in the human GRAMc library.
Figure Legend Snippet: GRAMc library building. ( a ) Controlling genomic coverage of the library. Size-selected and end-repaired random genomic DNA fragments are circularized by ligation with a fused adapter. Linear DNAs are removed by exonuclease treatment followed by RNaseHII digestion to linearize ligation product and dice adapter-concatemers. The purple box indicates two ribonucleotides for RNaseHII cut. Adapter-ligated products are then serially diluted to determine the genomic coverage of each dilution by QPCR. A dilution of intended coverage is Gibson assembled with a SCP-GFP cassette and the vector backbone to form barcode-less, linear constructs. ( b ) Controlling barcode numbers of the library. Random 25bp (N25) barcodes and a core-poly adenylation signal are added to the library of linear constructs by PCR. Barcoded constructs are self-ligated and linear DNAs are removed by exonucleases I/III. A small fraction of ligates is transformed to determine the scale of transformation. To avoid inflation of colony counts due to cell division, transformants for counting colonies should be immediately plated without rescuing. A desired amount of ligates are transformed to produce a GRAMc library with the intended number of barcodes. Plasmids extracted from liquid media are used for library characterization and reporter assay. Inserts and associated barcodes are identified by Illumina paired-end sequencing. ( c ) Size distribution of inserts in the human GRAMc library. ( d ) Cumulative distribution of barcode numbers per insert in the human GRAMc library.

Techniques Used: Ligation, Real-time Polymerase Chain Reaction, Plasmid Preparation, Construct, Polymerase Chain Reaction, Transformation Assay, Reporter Assay, Sequencing

31) Product Images from "Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria"

Article Title: Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

Journal: mSystems

doi: 10.1128/mSystems.00143-17

Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.
Figure Legend Snippet: Preference for part variants in the Erm magic pools. (A) As determined by DNA barcodes identified by TnSeq, the fraction of each of eight part2 variants in the combined mariner and Tn 5 preliminary mutant libraries for Echinicola vietnamensis (Cola), Pontibacter actiniarum (Ponti), and Pedobacter sp. GW460-11-11-14-LB5 (Pedo557). (B) The fraction of each of the four part3 variants in the combined mariner and Tn 5 preliminary mutant libraries for each bacterium. (C) The fraction of each of the 24 mariner part5 variants in Cola, Ponti, and Pedo557. (D) The fraction of each of the 25 Tn 5 part5 variants in Cola and Ponti.

Techniques Used: Mutagenesis

Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.
Figure Legend Snippet: Overview of the magic pool strategy. (A) Basic structure of a typical transposon delivery vector (not drawn to scale). The inverted repeat (IR) for the specific transposase is indicated. We dissected the transposon delivery vector into five different parts compatible with Golden Gate assembly, and the different parts are indicated by different colors. (B) General workflow of construction and application of magic pools. In step 1, variants of the five different parts are designed, cloned into a part-holding vector, confirmed by sequencing, and archived. In step 2, the part vectors are mixed and assembled using Golden Gate assembly to produce the magic pools of transposon delivery vectors. In step 3, the magic pool vectors are characterized by DNA sequencing whereby each unique DNA barcode (random 20-nucleotide DNA barcode [N20]) is linked to a specific combination of parts. In step 4, preliminary mutant libraries of approximately 5,000 CFU are made using the magic pool, and TnSeq is performed to link the DNA barcode to the insertion site, thereby simultaneously assessing the efficacy of the vectors in the magic pool. ID, identification. In step 5, an effective vector is reassembled using the archived parts, fully barcoded with millions of random DNA barcodes, and a full RB-TnSeq transposon mutant library is constructed. oriT is the origin of transfer. AmpR is the beta-lactam resistance cassette. R6K is the conditional replication origin.

Techniques Used: Plasmid Preparation, Clone Assay, Sequencing, DNA Sequencing, Mutagenesis, Construct

32) Product Images from "Takeaways from Mobile DNA Barcoding with BentoLab and MinION"

Article Title: Takeaways from Mobile DNA Barcoding with BentoLab and MinION

Journal: Genes

doi: 10.3390/genes11101121

Percentage of ambiguous bases (%) for the three types of error-corrected MinION barcodes: ( A ) MAFFT + AA, ( B ) RACON + AA, and ( C ) consolidated. Colors represent the type of flow cell used (R9.4.1 or R10.3), along with the basecalling model applied (Fast or HAC). For the R10.3 datasets, we generated a subset for the same sequencing time (ST) as R9.4.1, and another dataset for the same number of reads (SR) as R9.4.1. Note that the y-axis was scaled using pseudo-log2 transformation for better representation.
Figure Legend Snippet: Percentage of ambiguous bases (%) for the three types of error-corrected MinION barcodes: ( A ) MAFFT + AA, ( B ) RACON + AA, and ( C ) consolidated. Colors represent the type of flow cell used (R9.4.1 or R10.3), along with the basecalling model applied (Fast or HAC). For the R10.3 datasets, we generated a subset for the same sequencing time (ST) as R9.4.1, and another dataset for the same number of reads (SR) as R9.4.1. Note that the y-axis was scaled using pseudo-log2 transformation for better representation.

Techniques Used: HAC Assay, Generated, Sequencing, Transformation Assay

33) Product Images from "The adaptive potential of the middle domain of yeast Hsp90"

Article Title: The adaptive potential of the middle domain of yeast Hsp90

Journal: bioRxiv

doi: 10.1101/832022

Average number of barcodes per mutant for each 9 amino acid window shows an average of 10 barcodes associated with each variant.
Figure Legend Snippet: Average number of barcodes per mutant for each 9 amino acid window shows an average of 10 barcodes associated with each variant.

Techniques Used: Mutagenesis, Variant Assay

Barcoding mutant library strategy. (A) Schematic of how to incorporate barcodes into plasmid libraries using restriction digests and ligation. (B) Sanger sequence TRACE result of barcoded region of the library at positions 475-493. (C) Schematic of how to map barcodes to ORF mutants.
Figure Legend Snippet: Barcoding mutant library strategy. (A) Schematic of how to incorporate barcodes into plasmid libraries using restriction digests and ligation. (B) Sanger sequence TRACE result of barcoded region of the library at positions 475-493. (C) Schematic of how to map barcodes to ORF mutants.

Techniques Used: Mutagenesis, Plasmid Preparation, Ligation, Sequencing

34) Product Images from "uPIC–M: efficient and scalable preparation of clonal single mutant libraries for high-throughput protein biochemistry"

Article Title: uPIC–M: efficient and scalable preparation of clonal single mutant libraries for high-throughput protein biochemistry

Journal: bioRxiv

doi: 10.1101/2021.08.04.455146

Schematic of uPIC–M sequencing library preparation. Preparation of sequencing libraries takes place in multi-well plate format (96 or 384) via the following steps: ( i ) ORF regions of target plasmids are amplified from each clone using universal primers to obtain enriched amplicon DNA; ( iia ) For amplicons ≤ 600 bp, universal Illumina adapters may be ligated directed to amplicons or added by amplification in a second PCR step; ( iib ) For amplicons > 600 bp, DNA is fragmented and tagged using adapter-loaded Tn5 transposase, i.e. tagmented ; ( iii ) amplicons or fragments are further amplified with Nextera primers that incorporate dual-unique i7 and i5 index barcodes; ( iv - vi ) amplified and barcoded clonal libraries are pooled for NGS, sequenced, and barcodes are used to report the plate-well location and genotype of each variant. ( C ) Mutant amplicons generated at ( i ) can be used directly for high-throughput biochemistry applications (shown here: cell-free expression and fluorogenic assay of an enzyme library using a microfluidic platform to obtain kinetic parameters).
Figure Legend Snippet: Schematic of uPIC–M sequencing library preparation. Preparation of sequencing libraries takes place in multi-well plate format (96 or 384) via the following steps: ( i ) ORF regions of target plasmids are amplified from each clone using universal primers to obtain enriched amplicon DNA; ( iia ) For amplicons ≤ 600 bp, universal Illumina adapters may be ligated directed to amplicons or added by amplification in a second PCR step; ( iib ) For amplicons > 600 bp, DNA is fragmented and tagged using adapter-loaded Tn5 transposase, i.e. tagmented ; ( iii ) amplicons or fragments are further amplified with Nextera primers that incorporate dual-unique i7 and i5 index barcodes; ( iv - vi ) amplified and barcoded clonal libraries are pooled for NGS, sequenced, and barcodes are used to report the plate-well location and genotype of each variant. ( C ) Mutant amplicons generated at ( i ) can be used directly for high-throughput biochemistry applications (shown here: cell-free expression and fluorogenic assay of an enzyme library using a microfluidic platform to obtain kinetic parameters).

Techniques Used: Sequencing, Amplification, Polymerase Chain Reaction, Next-Generation Sequencing, Variant Assay, Mutagenesis, Generated, High Throughput Screening Assay, Expressing

NGS data processing and read mapping pipeline and results for the SpAP scanning library. ( A ) Data processing steps and observed statistics. Raw FASTQ files (demultiplexed and unpaired) are filtered for barcodes containing 1 or more reads followed by adapter sequence trimming and pairing with read mates (if both reads are present and meet length/quality thresholds). Sequence-redundant readthrough read pairs are flagged at this stage and redundant read mates are discarded. ( B ) Trimmed and paired reads are mapped to the SpAP-eGFP amplicon, E. coli , and full plasmid genomes. ( C ) Histogram of total reads per barcode across all sublibraries following read trimming and pairing (n = 4645). ( D ) Barcode counts for each sublibrary plate at several read depth thresholds for the SpAP-eGFP ORF ( > 0 represents barcodes containing any mapped reads and remaining thresholds represent the minimum number of mapped reads at all positions; only barcodes containing at least one mapped read are included). The horizontal dashed line at 384 barcodes represents the maximum possible number of barcodes.
Figure Legend Snippet: NGS data processing and read mapping pipeline and results for the SpAP scanning library. ( A ) Data processing steps and observed statistics. Raw FASTQ files (demultiplexed and unpaired) are filtered for barcodes containing 1 or more reads followed by adapter sequence trimming and pairing with read mates (if both reads are present and meet length/quality thresholds). Sequence-redundant readthrough read pairs are flagged at this stage and redundant read mates are discarded. ( B ) Trimmed and paired reads are mapped to the SpAP-eGFP amplicon, E. coli , and full plasmid genomes. ( C ) Histogram of total reads per barcode across all sublibraries following read trimming and pairing (n = 4645). ( D ) Barcode counts for each sublibrary plate at several read depth thresholds for the SpAP-eGFP ORF ( > 0 represents barcodes containing any mapped reads and remaining thresholds represent the minimum number of mapped reads at all positions; only barcodes containing at least one mapped read are included). The horizontal dashed line at 384 barcodes represents the maximum possible number of barcodes.

Techniques Used: Next-Generation Sequencing, Sequencing, Amplification, Plasmid Preparation

35) Product Images from "scTagger: Fast and accurate matching of cellular barcodes across short- and long-reads of single-cell RNA-seq experiments"

Article Title: scTagger: Fast and accurate matching of cellular barcodes across short- and long-reads of single-cell RNA-seq experiments

Journal: bioRxiv

doi: 10.1101/2022.04.21.489097

A) Overview of the library preparation: Microfluidic chips are used to generate 10x Chromium GEMs which tag the RNA transcripts with cellular barcodes. After the transcripts are tagged, the GEMs are burst, and the tagged RNA material is split into two pools of sequencing, one for SRs and one for LRs. B) The SR template. Inside the GEMs, RNA transcripts are tagged with an Illumina adapter that is a fixed sequence, followed by a 16bp cellular barcode (CB), followed by a random 10bp sequence for the unique molecular identifier (UMI). C) The LR template. Note that the LR template is essentially the same as the SR template with the LR sequencing adapter added. Depending on the specifics of the library preparation, LRs may sequence the forward or the reverse strand of the RNA molecule. In either case, we expect the cellular barcode to be adjacent to the SR adapter sequence.
Figure Legend Snippet: A) Overview of the library preparation: Microfluidic chips are used to generate 10x Chromium GEMs which tag the RNA transcripts with cellular barcodes. After the transcripts are tagged, the GEMs are burst, and the tagged RNA material is split into two pools of sequencing, one for SRs and one for LRs. B) The SR template. Inside the GEMs, RNA transcripts are tagged with an Illumina adapter that is a fixed sequence, followed by a 16bp cellular barcode (CB), followed by a random 10bp sequence for the unique molecular identifier (UMI). C) The LR template. Note that the LR template is essentially the same as the SR template with the LR sequencing adapter added. Depending on the specifics of the library preparation, LRs may sequence the forward or the reverse strand of the RNA molecule. In either case, we expect the cellular barcode to be adjacent to the SR adapter sequence.

Techniques Used: Sequencing

Cumulative SR coverage with batches of 1,000 barcodes for the real datasets.
Figure Legend Snippet: Cumulative SR coverage with batches of 1,000 barcodes for the real datasets.

Techniques Used:

36) Product Images from "Genome-wide screening reveals a novel class of carbonic anhydrase-like inorganic carbon pumps in chemoautotrophic bacteria"

Article Title: Genome-wide screening reveals a novel class of carbonic anhydrase-like inorganic carbon pumps in chemoautotrophic bacteria

Journal: bioRxiv

doi: 10.1101/476713

Transposon mutagenesis reveals the essential gene set of a chemoautotrophic organism. A. Schematic depicting the generation and screening of the RB-TnSeq library. Transposons were inserted into the Hnea genome by conjugation with an E. coli donor strain. The transposon contains a random 20 base pair barcode (yellow) and a kanamycin selection marker (green). Single colonies were selected for insertion in the presence of kanamycin at 5% CO 2 and insertions were mapped by Illumina sequencing as described in the Methods. Subsequent screens were carried out as bulk competition assays and quantified by Illumina sequencing. B. Insertions and essential genes are well-distributed throughout the Hnea genome. The outer track (blue) is a histogram of the number of barcodes that were mapped to a 1 kb window. The inner track annotates essential genes in purple. The pie chart shows the percentages of the genome called essential (purple), ambiguous (orange), and nonessential (green). C. Representative essential genes and nonessential genes in the Hnea genome. The blue track indicates the presence of an insertion. Genes in purple were called essential and genes in green are nonessential. Genes labeled “unk.” are hypothetical proteins. The top operon contains 5 genes involved in glycolysis or the CBB cycle. The second operon contains genes encoding 30S and 50S subunits of the ribosome, the secY secretory channel, and an RNA polymerase subunit. The third operon contains genes involved in DNA replication. Acronyms: exopolyphosphatase (PP-ase), fructose-bisphosphate aldolase class II (fba), pyruvate kinase (pyk), phosphoglycerate kinase (pgk), type I glyceraldehyde-3-phosphate dehydrogenase (gapdh), transketolase (tkt), 30S ribosomal protein (30S), 50S ribosomal protein (50S), preprotein translocase subunit SecY (SecY), DNA-directed RNA polymerase subunit alpha (RNAPɑ), hypothetical protein (unk.), excinuclease ABC subunit UvrB (UvrB), chromosomal replication initiator protein dnaA (dnaA), DNA polymerase III subunit beta (DNAPIII□), DNA replication and repair protein recF (recF), DNA topoisomerase (ATP-hydrolyzing) subunit B (topoisomerase), lemA family protein (LemA).
Figure Legend Snippet: Transposon mutagenesis reveals the essential gene set of a chemoautotrophic organism. A. Schematic depicting the generation and screening of the RB-TnSeq library. Transposons were inserted into the Hnea genome by conjugation with an E. coli donor strain. The transposon contains a random 20 base pair barcode (yellow) and a kanamycin selection marker (green). Single colonies were selected for insertion in the presence of kanamycin at 5% CO 2 and insertions were mapped by Illumina sequencing as described in the Methods. Subsequent screens were carried out as bulk competition assays and quantified by Illumina sequencing. B. Insertions and essential genes are well-distributed throughout the Hnea genome. The outer track (blue) is a histogram of the number of barcodes that were mapped to a 1 kb window. The inner track annotates essential genes in purple. The pie chart shows the percentages of the genome called essential (purple), ambiguous (orange), and nonessential (green). C. Representative essential genes and nonessential genes in the Hnea genome. The blue track indicates the presence of an insertion. Genes in purple were called essential and genes in green are nonessential. Genes labeled “unk.” are hypothetical proteins. The top operon contains 5 genes involved in glycolysis or the CBB cycle. The second operon contains genes encoding 30S and 50S subunits of the ribosome, the secY secretory channel, and an RNA polymerase subunit. The third operon contains genes involved in DNA replication. Acronyms: exopolyphosphatase (PP-ase), fructose-bisphosphate aldolase class II (fba), pyruvate kinase (pyk), phosphoglycerate kinase (pgk), type I glyceraldehyde-3-phosphate dehydrogenase (gapdh), transketolase (tkt), 30S ribosomal protein (30S), 50S ribosomal protein (50S), preprotein translocase subunit SecY (SecY), DNA-directed RNA polymerase subunit alpha (RNAPɑ), hypothetical protein (unk.), excinuclease ABC subunit UvrB (UvrB), chromosomal replication initiator protein dnaA (dnaA), DNA polymerase III subunit beta (DNAPIII□), DNA replication and repair protein recF (recF), DNA topoisomerase (ATP-hydrolyzing) subunit B (topoisomerase), lemA family protein (LemA).

Techniques Used: Mutagenesis, Conjugation Assay, Selection, Marker, Sequencing, Labeling

37) Product Images from "Highly accurate barcode and UMI error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing"

Article Title: Highly accurate barcode and UMI error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

Journal: bioRxiv

doi: 10.1101/2021.01.18.427145

Developing a strategy to error correct barcode and UMI sequences from droplet-based sequencing. a Schematic bead and oligonucleotide structure using dimer blocks of nucleotides for BUC-seq. b Cell barcode assignment strategy. c UMI deduplication strategy. d Simulated data showing the number of barcodes recovered with increasing simulated sequencing error rates. e, f Simulated data showing the difference and coefficient of variation between the deduplicated UMIs and the ground truth. Deduplication was performed using a basic directional network-based approach and accounting for sequencing errors within paired nucleotides.
Figure Legend Snippet: Developing a strategy to error correct barcode and UMI sequences from droplet-based sequencing. a Schematic bead and oligonucleotide structure using dimer blocks of nucleotides for BUC-seq. b Cell barcode assignment strategy. c UMI deduplication strategy. d Simulated data showing the number of barcodes recovered with increasing simulated sequencing error rates. e, f Simulated data showing the difference and coefficient of variation between the deduplicated UMIs and the ground truth. Deduplication was performed using a basic directional network-based approach and accounting for sequencing errors within paired nucleotides.

Techniques Used: Sequencing

Error correction of both Illumina and Nanopore droplet based scRNA-seq data Human HEK293T and mouse 3T3 were mixed at a 1:1 ratio and approximately 500 cells were taken for encapsulation and cDNA synthesis. Barcodes and UMIs identified as having at least one sequencing error were processed a before and b after barcode error correction. The proportion of mouse and human UMIs are shown in the Barnyard plot. Insert bar plots show the number of cells identified for each species. c The length of the input cDNA Nanopore library, as measured using a tapestation. d The read length of the sequenced Nanopore library. e The percent of reads that have a polyA tail. The percent of polyA + reads that show perfect based on the nucleotide pairing complementarity and the percent of reads that ccan be recovered using an Levenshtein distance of 6. Boxes and error bars indicate the means and standard deviations for n=4 individual experiments. Barnyard plots showing the expression of mouse and human UMIs using a g Levenshtein distance (LD) of 6 and a h Levenshtein distance of 7. The insert bar plots show the number of cells recovered for each species. UMAP plots of the showing human, mouse or mixed human and mouse cells when barcodes are corrected using a i Levenshtein distance of 6 or a j Levenshtein distance of 7.
Figure Legend Snippet: Error correction of both Illumina and Nanopore droplet based scRNA-seq data Human HEK293T and mouse 3T3 were mixed at a 1:1 ratio and approximately 500 cells were taken for encapsulation and cDNA synthesis. Barcodes and UMIs identified as having at least one sequencing error were processed a before and b after barcode error correction. The proportion of mouse and human UMIs are shown in the Barnyard plot. Insert bar plots show the number of cells identified for each species. c The length of the input cDNA Nanopore library, as measured using a tapestation. d The read length of the sequenced Nanopore library. e The percent of reads that have a polyA tail. The percent of polyA + reads that show perfect based on the nucleotide pairing complementarity and the percent of reads that ccan be recovered using an Levenshtein distance of 6. Boxes and error bars indicate the means and standard deviations for n=4 individual experiments. Barnyard plots showing the expression of mouse and human UMIs using a g Levenshtein distance (LD) of 6 and a h Levenshtein distance of 7. The insert bar plots show the number of cells recovered for each species. UMAP plots of the showing human, mouse or mixed human and mouse cells when barcodes are corrected using a i Levenshtein distance of 6 or a j Levenshtein distance of 7.

Techniques Used: Sequencing, Expressing

38) Product Images from "Hackflex: low cost Illumina Nextera Flex sequencing library construction"

Article Title: Hackflex: low cost Illumina Nextera Flex sequencing library construction

Journal: bioRxiv

doi: 10.1101/779215

Barcode distribution and GC bias of Hackflex barcode v1 libraries. Unique barcode distribution across 96 Hackflex libraries constructed from barcodes v1(left) and their GC bias: the relation between barcode counts obtained for each entire barcode (i.e.: F5+i5+N5 or F7+i7+N7), and its GC content (i5 R =-0.17 p=0.1; i7 R =0.03 p=0.77) (right).
Figure Legend Snippet: Barcode distribution and GC bias of Hackflex barcode v1 libraries. Unique barcode distribution across 96 Hackflex libraries constructed from barcodes v1(left) and their GC bias: the relation between barcode counts obtained for each entire barcode (i.e.: F5+i5+N5 or F7+i7+N7), and its GC content (i5 R =-0.17 p=0.1; i7 R =0.03 p=0.77) (right).

Techniques Used: Construct

39) Product Images from "Bar-seq strategies for the LeishGEdit toolbox"

Article Title: Bar-seq strategies for the LeishGEdit toolbox

Journal: bioRxiv

doi: 10.1101/2020.03.19.998856

Overview of primer design and a bar-seq strategy for the LeishGEdit toolbox. (A) Overview of the previously designed strategy for bar-seq phenotyping [ 2 ]. (1) A cell line expressing Cas9 and T7 RNAP is subjected for a double allele deletion using two different drug selectable markers. A 17 nt barcode (yellow), surrounded by two constant regions (purple and red) is inserted into the target locus by using donor DNA with 30 nt HF (green and gray). (2) Barcoded mutants are pooled and (3) analyzed in an in vitro or in vivo screen. (4) Barcode abundance is read out by amplifying barcodes using their surrounding constant regions. (B and C) Figure adapted from Beneke and Gluenz [ 10 ]. Shown is the PCR strategy for donor DNA amplification from pT and pPLOT plasmids. (B) Overview of constant and variable sequences in the LeishGEdit primers: Forward and reverse primers for donor DNA amplification contain target-gene specific 30 nt homology flanks ([HFN30]) adjacent to pT and pPLOT plasmid primer binding sites (underlined in red). The upstream forward primer can be barcoded ([bar17]). An additional primer binding site is required for the read out by sequencing (underlined in purple). Primers for sgRNA template amplification contain the T7 promotor sequence (underlined in blue), the 20 nt target sequence ([sgN20]) and an overhang sequence to the sgRNA backbone sequence (underlined in green). (C) pT plasmids consist of a L. mexicana derived 5’ and 3’UTR and a drug resistance marker gene to allow gene replacement by drug selection. pPLOT plasmids contain drug resistance markers and Crithidia and T. brucei UTRs, as well as myc epitope tags in-frame with various protein tags. pPLOTs can be used for amplification of tagging cassettes, allowing generation of fusion proteins with epitope tags fused at the N- or C-terminus. (D) Criteria used by CCTop to identify suitable sgRNA target sites. sgRNA target sites may have up to 2 MM in the first 12 nt upstream of the PAM site or up to 4 MM in the entire sgRNA target sequence [ 22 ]. (E and F) Illumina sequencing strategy for reading out barcode abundances. (E) (1) Two long primers (p5 and p7 primers; specified in (F)) bind to constant regions adjacent to the 17 nt barcode (binding sites in red font). (2) Library size and expected sequencing read length of the amplicon is indicated. (F) Primer sequences of p5 and p7 primers used for Illumina sequences. Long p5 and p7 primers contain flow cell binding sites, additional indices for Illumina sequencing and an index/read Illumina sequencing binding site.
Figure Legend Snippet: Overview of primer design and a bar-seq strategy for the LeishGEdit toolbox. (A) Overview of the previously designed strategy for bar-seq phenotyping [ 2 ]. (1) A cell line expressing Cas9 and T7 RNAP is subjected for a double allele deletion using two different drug selectable markers. A 17 nt barcode (yellow), surrounded by two constant regions (purple and red) is inserted into the target locus by using donor DNA with 30 nt HF (green and gray). (2) Barcoded mutants are pooled and (3) analyzed in an in vitro or in vivo screen. (4) Barcode abundance is read out by amplifying barcodes using their surrounding constant regions. (B and C) Figure adapted from Beneke and Gluenz [ 10 ]. Shown is the PCR strategy for donor DNA amplification from pT and pPLOT plasmids. (B) Overview of constant and variable sequences in the LeishGEdit primers: Forward and reverse primers for donor DNA amplification contain target-gene specific 30 nt homology flanks ([HFN30]) adjacent to pT and pPLOT plasmid primer binding sites (underlined in red). The upstream forward primer can be barcoded ([bar17]). An additional primer binding site is required for the read out by sequencing (underlined in purple). Primers for sgRNA template amplification contain the T7 promotor sequence (underlined in blue), the 20 nt target sequence ([sgN20]) and an overhang sequence to the sgRNA backbone sequence (underlined in green). (C) pT plasmids consist of a L. mexicana derived 5’ and 3’UTR and a drug resistance marker gene to allow gene replacement by drug selection. pPLOT plasmids contain drug resistance markers and Crithidia and T. brucei UTRs, as well as myc epitope tags in-frame with various protein tags. pPLOTs can be used for amplification of tagging cassettes, allowing generation of fusion proteins with epitope tags fused at the N- or C-terminus. (D) Criteria used by CCTop to identify suitable sgRNA target sites. sgRNA target sites may have up to 2 MM in the first 12 nt upstream of the PAM site or up to 4 MM in the entire sgRNA target sequence [ 22 ]. (E and F) Illumina sequencing strategy for reading out barcode abundances. (E) (1) Two long primers (p5 and p7 primers; specified in (F)) bind to constant regions adjacent to the 17 nt barcode (binding sites in red font). (2) Library size and expected sequencing read length of the amplicon is indicated. (F) Primer sequences of p5 and p7 primers used for Illumina sequences. Long p5 and p7 primers contain flow cell binding sites, additional indices for Illumina sequencing and an index/read Illumina sequencing binding site.

Techniques Used: Expressing, In Vitro, In Vivo, Polymerase Chain Reaction, Amplification, Plasmid Preparation, Binding Assay, Sequencing, Derivative Assay, Marker, Selection

40) Product Images from "Promoter-Intrinsic and Local Chromatin Features Determine Gene Repression in LADs"

Article Title: Promoter-Intrinsic and Local Chromatin Features Determine Gene Repression in LADs

Journal: Cell

doi: 10.1016/j.cell.2019.03.009

Precise Measurement of Promoter Activities in Episomal Plasmid Context Each indicated promoter was cloned in the same promoter-less reporter plasmid with about 100 different random barcodes. A pool of the resulting ∼700 plasmids was transiently transfected into K562 cells. Barcodes were counted in cDNA and plasmid DNA isolated from these cells after 2 days. The plot shows the distribution of expression levels of all barcodes sorted by promoter; horizontal lines depict medians. Data are average of at least two independent experiments.
Figure Legend Snippet: Precise Measurement of Promoter Activities in Episomal Plasmid Context Each indicated promoter was cloned in the same promoter-less reporter plasmid with about 100 different random barcodes. A pool of the resulting ∼700 plasmids was transiently transfected into K562 cells. Barcodes were counted in cDNA and plasmid DNA isolated from these cells after 2 days. The plot shows the distribution of expression levels of all barcodes sorted by promoter; horizontal lines depict medians. Data are average of at least two independent experiments.

Techniques Used: Plasmid Preparation, Clone Assay, Transfection, Isolation, Expressing

Similar Products

  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 88
    Illumina Inc barcodes
    Flowchart for generating MinION <t>barcodes</t> from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.
    Barcodes, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 88/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/barcodes/product/Illumina Inc
    Average 88 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    barcodes - by Bioz Stars, 2022-10
    88/100 stars
      Buy from Supplier

    90
    Illumina Inc barcode
    Comparative schematic of small RNA barcoding methods. The three methods start with ligation of a 3' and 5' RNA adapter to generate a substrate for RT-PCR. In the pre-PCR barcoding method, the <t>barcode</t> is incorporated in the 5' adapter. In the TruSeq method, the barcode is incorporated in one of the RT-PCR primers. In the PALM barcoding method, the amplified RT-PCR product is A-tailed and ligated to a T-tailed barcoded adapter.
    Barcode, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/barcode/product/Illumina Inc
    Average 90 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    barcode - by Bioz Stars, 2022-10
    90/100 stars
      Buy from Supplier

    92
    illumina inc cell barcode assignment
    Sicelore and ScNapBar CPU time comparison. ( A ) ScNapBar CPU time depends on the number of whitelist barcodes (allowing an edit distance of > 2 and and offset of up to 4 bp between adapter and <t>barcode).</t> Gray area represents the standard deviation for 10 runs. ( B ) Comparison of ScNapBar and Sicelore CPU times. Benchmark was measured using one million barcode sequences and 2052 barcodes in the whitelist.
    Cell Barcode Assignment, supplied by illumina inc, used in various techniques. Bioz Stars score: 92/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cell barcode assignment/product/illumina inc
    Average 92 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    cell barcode assignment - by Bioz Stars, 2022-10
    92/100 stars
      Buy from Supplier

    90
    Illumina Inc potential barcode combinations
    Nanoparticles co-formulated with siRNA and a DNA <t>barcode</t> can be used to readout quantify how > 100 different LNPs functionally deliver RNA into the cytoplasm of target cells in a single mouse. (A) Unlike previous biodistribution screens, which cannot distinguish between bound particles, particles stuck in endosomes, and particles that delivered RNA into the cytoplasm, our method identifies LNPs that functionally deliver siRNA. We do so by isolating cells that are ICAM Low and sequencing barcodes in those cells. (B,C) ICAM-2 protein expression in lung endothelial cells after mice were treated with 7C1 carrying a barcode and either siLuc or siICAM-2. ICAM-2 protein expression decreased in a dose-dependent manner. (D) siRNA-mediated silencing also led to a dose-dependent increase in ICAM Low lung endothelial cells.
    Potential Barcode Combinations, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/potential barcode combinations/product/Illumina Inc
    Average 90 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    potential barcode combinations - by Bioz Stars, 2022-10
    90/100 stars
      Buy from Supplier

    Image Search Results


    Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.

    Journal: bioRxiv

    Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

    doi: 10.1101/622365

    Figure Lengend Snippet: Flowchart for generating MinION barcodes from experimental set-up to final barcodes. The novel steps introduced in this study are highlighted in green and the scripts available in miniBarcoder for analyses are further indicated.

    Article Snippet: Indeed, even the initial estimates of barcodes (“MAFFT” & “RACON”) have very high accuracy ( > 99.5%) when compared to Illumina data, while the accuracy of consolidated barcodes is even higher ( > 99.9%).

    Techniques:

    Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.

    Journal: bioRxiv

    Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

    doi: 10.1101/622365

    Figure Lengend Snippet: Ambiguities in MAFFT+AA (Purple), RACON+AA (Yellow) and Consolidated barcodes (Green) with varying namino parameters (1,2 and 3). One outlier value for Racon+3AA barcode was excluded from the plot. The plot shows that the consolidated barcodes have few ambiguities remaining.

    Article Snippet: Indeed, even the initial estimates of barcodes (“MAFFT” & “RACON”) have very high accuracy ( > 99.5%) when compared to Illumina data, while the accuracy of consolidated barcodes is even higher ( > 99.9%).

    Techniques:

    Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

    Journal: bioRxiv

    Article Title: Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

    doi: 10.1101/622365

    Figure Lengend Snippet: Effect of re-pooling on coverage of barcodes for both sets of specimens. Barcodes with coverage

    Article Snippet: Indeed, even the initial estimates of barcodes (“MAFFT” & “RACON”) have very high accuracy ( > 99.5%) when compared to Illumina data, while the accuracy of consolidated barcodes is even higher ( > 99.9%).

    Techniques:

    Comparative schematic of small RNA barcoding methods. The three methods start with ligation of a 3' and 5' RNA adapter to generate a substrate for RT-PCR. In the pre-PCR barcoding method, the barcode is incorporated in the 5' adapter. In the TruSeq method, the barcode is incorporated in one of the RT-PCR primers. In the PALM barcoding method, the amplified RT-PCR product is A-tailed and ligated to a T-tailed barcoded adapter.

    Journal: PLoS ONE

    Article Title: Quantitative Bias in Illumina TruSeq and a Novel Post Amplification Barcoding Strategy for Multiplexed DNA and Small RNA Deep Sequencing

    doi: 10.1371/journal.pone.0026969

    Figure Lengend Snippet: Comparative schematic of small RNA barcoding methods. The three methods start with ligation of a 3' and 5' RNA adapter to generate a substrate for RT-PCR. In the pre-PCR barcoding method, the barcode is incorporated in the 5' adapter. In the TruSeq method, the barcode is incorporated in one of the RT-PCR primers. In the PALM barcoding method, the amplified RT-PCR product is A-tailed and ligated to a T-tailed barcoded adapter.

    Article Snippet: The adapters used in the protocol were modified to include a barcode and to allow for Illumina index sequencing with the Illumina multiplexing index read sequencing primer.

    Techniques: Ligation, Reverse Transcription Polymerase Chain Reaction, Polymerase Chain Reaction, Amplification

    Sicelore and ScNapBar CPU time comparison. ( A ) ScNapBar CPU time depends on the number of whitelist barcodes (allowing an edit distance of > 2 and and offset of up to 4 bp between adapter and barcode). Gray area represents the standard deviation for 10 runs. ( B ) Comparison of ScNapBar and Sicelore CPU times. Benchmark was measured using one million barcode sequences and 2052 barcodes in the whitelist.

    Journal: RNA

    Article Title: Single-cell transcriptome sequencing on the Nanopore platform with ScNapBar

    doi: 10.1261/rna.078154.120

    Figure Lengend Snippet: Sicelore and ScNapBar CPU time comparison. ( A ) ScNapBar CPU time depends on the number of whitelist barcodes (allowing an edit distance of > 2 and and offset of up to 4 bp between adapter and barcode). Gray area represents the standard deviation for 10 runs. ( B ) Comparison of ScNapBar and Sicelore CPU times. Benchmark was measured using one million barcode sequences and 2052 barcodes in the whitelist.

    Article Snippet: We performed an in silico benchmark of cell barcode assignment when both, cell barcode and UMI, are found in the Nanopore read.

    Techniques: Standard Deviation

    Combined single-cell Illumina and Nanopore sequencing strategy. GFP+/− cells are pooled and sequenced on the Illumina and Nanopore platform. The Nanopore platform generates long cDNA sequencing reads that are used in barcode calling and estimating read error parameters. The Illumina data are used to estimate the total number of cells in sequencing and the represented cell barcodes. The simulated data are then used to parameterize a Bayesian model of barcode alignment features to discriminate correct versus false barcode assignments. This model is then used on the real data to assign cell barcodes to Nanopore reads. The GFP label and known NMD transcripts can be used to validate this assignment.

    Journal: RNA

    Article Title: Single-cell transcriptome sequencing on the Nanopore platform with ScNapBar

    doi: 10.1261/rna.078154.120

    Figure Lengend Snippet: Combined single-cell Illumina and Nanopore sequencing strategy. GFP+/− cells are pooled and sequenced on the Illumina and Nanopore platform. The Nanopore platform generates long cDNA sequencing reads that are used in barcode calling and estimating read error parameters. The Illumina data are used to estimate the total number of cells in sequencing and the represented cell barcodes. The simulated data are then used to parameterize a Bayesian model of barcode alignment features to discriminate correct versus false barcode assignments. This model is then used on the real data to assign cell barcodes to Nanopore reads. The GFP label and known NMD transcripts can be used to validate this assignment.

    Article Snippet: We performed an in silico benchmark of cell barcode assignment when both, cell barcode and UMI, are found in the Nanopore read.

    Techniques: Nanopore Sequencing, Sequencing

    Number of the Nanopore reads identified by ScNapBar and Sicelore at each processing step. We inspected each processing step on real data (low lllumina saturation of 11.3%). The first two steps are identical for both workflows. Total Reads: Number of input reads, aligned to genome: Number of reads aligned to genome. The next three steps are workflow-specific: Aligned to adapter: Number of reads with identified adapter sequence, aligned to barcode: Number of reads with aligned barcode sequence, Assigned to barcode: Number of predictions by each workflow. The last step is a validation of the previous assignment step after additional Illumina sequencing, which increases the Illumina saturation to 52%, and using UMI matches, see main text.

    Journal: RNA

    Article Title: Single-cell transcriptome sequencing on the Nanopore platform with ScNapBar

    doi: 10.1261/rna.078154.120

    Figure Lengend Snippet: Number of the Nanopore reads identified by ScNapBar and Sicelore at each processing step. We inspected each processing step on real data (low lllumina saturation of 11.3%). The first two steps are identical for both workflows. Total Reads: Number of input reads, aligned to genome: Number of reads aligned to genome. The next three steps are workflow-specific: Aligned to adapter: Number of reads with identified adapter sequence, aligned to barcode: Number of reads with aligned barcode sequence, Assigned to barcode: Number of predictions by each workflow. The last step is a validation of the previous assignment step after additional Illumina sequencing, which increases the Illumina saturation to 52%, and using UMI matches, see main text.

    Article Snippet: We performed an in silico benchmark of cell barcode assignment when both, cell barcode and UMI, are found in the Nanopore read.

    Techniques: Sequencing

    Sensitivity and specificity of ScNapBar and Sicelore on 100 Illumina libraries with different levels of saturation. ( A ) Barcode assignment with UMI matches. ( B ) Barcode assignment without UMI matches (ScNapBar score > 50). ( C ) Benchmark of the specificity and sensitivity of the Illumina library with 100% saturation. We compared the barcode assignments with ScNapBar score > 1–99, and the assignments from Sicelore with UMI support are roughly equivalent to the ScNapBar score > 90.

    Journal: RNA

    Article Title: Single-cell transcriptome sequencing on the Nanopore platform with ScNapBar

    doi: 10.1261/rna.078154.120

    Figure Lengend Snippet: Sensitivity and specificity of ScNapBar and Sicelore on 100 Illumina libraries with different levels of saturation. ( A ) Barcode assignment with UMI matches. ( B ) Barcode assignment without UMI matches (ScNapBar score > 50). ( C ) Benchmark of the specificity and sensitivity of the Illumina library with 100% saturation. We compared the barcode assignments with ScNapBar score > 1–99, and the assignments from Sicelore with UMI support are roughly equivalent to the ScNapBar score > 90.

    Article Snippet: We performed an in silico benchmark of cell barcode assignment when both, cell barcode and UMI, are found in the Nanopore read.

    Techniques:

    Nanoparticles co-formulated with siRNA and a DNA barcode can be used to readout quantify how > 100 different LNPs functionally deliver RNA into the cytoplasm of target cells in a single mouse. (A) Unlike previous biodistribution screens, which cannot distinguish between bound particles, particles stuck in endosomes, and particles that delivered RNA into the cytoplasm, our method identifies LNPs that functionally deliver siRNA. We do so by isolating cells that are ICAM Low and sequencing barcodes in those cells. (B,C) ICAM-2 protein expression in lung endothelial cells after mice were treated with 7C1 carrying a barcode and either siLuc or siICAM-2. ICAM-2 protein expression decreased in a dose-dependent manner. (D) siRNA-mediated silencing also led to a dose-dependent increase in ICAM Low lung endothelial cells.

    Journal: Journal of the American Chemical Society

    Article Title: Nanoparticles that deliver RNA to bone marrow identified by in vivo directed evolution

    doi: 10.1021/jacs.8b08976

    Figure Lengend Snippet: Nanoparticles co-formulated with siRNA and a DNA barcode can be used to readout quantify how > 100 different LNPs functionally deliver RNA into the cytoplasm of target cells in a single mouse. (A) Unlike previous biodistribution screens, which cannot distinguish between bound particles, particles stuck in endosomes, and particles that delivered RNA into the cytoplasm, our method identifies LNPs that functionally deliver siRNA. We do so by isolating cells that are ICAM Low and sequencing barcodes in those cells. (B,C) ICAM-2 protein expression in lung endothelial cells after mice were treated with 7C1 carrying a barcode and either siLuc or siICAM-2. ICAM-2 protein expression decreased in a dose-dependent manner. (D) siRNA-mediated silencing also led to a dose-dependent increase in ICAM Low lung endothelial cells.

    Article Snippet: Of the 65,536 (i.e., 48 ) potential barcode combinations, we selected 156 which would work together on Illumina sequencers.

    Techniques: Sequencing, Expressing, Mouse Assay