superscript double stranded cdna synthesis kit  (Thermo Fisher)


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    Structured Review

    Thermo Fisher superscript double stranded cdna synthesis kit
    Comparison of normalized signal intensity between direct <t>cDNA</t> sequencing and 3′-UTR sequencing for bacteria grown in <t>CDM</t> (Spearman coefficient, 0.686; P
    Superscript Double Stranded Cdna Synthesis Kit, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 216 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    superscript double stranded cdna synthesis kit - by Bioz Stars, 2020-01
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    1) Product Images from "Comparative Analysis of Lactobacillus plantarum WCFS1 Transcriptomes by Using DNA Microarray and Next-Generation Sequencing Technologies"

    Article Title: Comparative Analysis of Lactobacillus plantarum WCFS1 Transcriptomes by Using DNA Microarray and Next-Generation Sequencing Technologies

    Journal:

    doi: 10.1128/AEM.00470-12

    Comparison of normalized signal intensity between direct cDNA sequencing and 3′-UTR sequencing for bacteria grown in CDM (Spearman coefficient, 0.686; P
    Figure Legend Snippet: Comparison of normalized signal intensity between direct cDNA sequencing and 3′-UTR sequencing for bacteria grown in CDM (Spearman coefficient, 0.686; P

    Techniques Used: Sequencing

    Comparison of 152 transcript levels (40 downregulated in CDM and 112 upregulated in CDM) that were consistently classified among the DEG gene sets as determined by microarray transcriptomes or direct cDNA and 3′-UTR transcriptome sequencing. Data
    Figure Legend Snippet: Comparison of 152 transcript levels (40 downregulated in CDM and 112 upregulated in CDM) that were consistently classified among the DEG gene sets as determined by microarray transcriptomes or direct cDNA and 3′-UTR transcriptome sequencing. Data

    Techniques Used: Microarray, Sequencing

    Comparison between normalized signal intensity level of microarray and normalized read counts of direct cDNA sequencing (A and B) and 3′-UTR sequencing (C and D) in transcriptome data sets from bacteria grown in CDM and MRS.
    Figure Legend Snippet: Comparison between normalized signal intensity level of microarray and normalized read counts of direct cDNA sequencing (A and B) and 3′-UTR sequencing (C and D) in transcriptome data sets from bacteria grown in CDM and MRS.

    Techniques Used: Microarray, Sequencing

    2) Product Images from "In TCR-Stimulated T-cells, N-ras Regulates Specific Genes and Signal Transduction Pathways"

    Article Title: In TCR-Stimulated T-cells, N-ras Regulates Specific Genes and Signal Transduction Pathways

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0063193

    Four of the candidate genes from the second set of microarray experiments exhibited similar patterns of expression in the microarray, in the empty vector controls, and in the Ras isoform transduction validations. Graphical representation of the fold-changes for Dntt, Slc9a6 , Lars2 , and Chst1 in the microarray, in the empty vector control experiments and in the Ras isoform transduction validation experiments. For each candidate gene, the fold change in the [WT] vs. [KO] microarray comparison, in the [WT + MIGR1] vs. [KO + MIGR1] empty vector control experiment, and in the [KO + WT N-ras] vs. [KO + WT H-ras] and [KO + WT N-ras] vs. [KO + N-ras-Palm H ] Ras isoform transduction validation experiments are shown. The entire experiment, from RNA analysis through cDNA synthesis and microarray hybridization, was repeated three times, and for each repetition of the experiment, RNA was isolated from a different mouse. The relevant data were normalized to the [KO + MIGR1] condition.
    Figure Legend Snippet: Four of the candidate genes from the second set of microarray experiments exhibited similar patterns of expression in the microarray, in the empty vector controls, and in the Ras isoform transduction validations. Graphical representation of the fold-changes for Dntt, Slc9a6 , Lars2 , and Chst1 in the microarray, in the empty vector control experiments and in the Ras isoform transduction validation experiments. For each candidate gene, the fold change in the [WT] vs. [KO] microarray comparison, in the [WT + MIGR1] vs. [KO + MIGR1] empty vector control experiment, and in the [KO + WT N-ras] vs. [KO + WT H-ras] and [KO + WT N-ras] vs. [KO + N-ras-Palm H ] Ras isoform transduction validation experiments are shown. The entire experiment, from RNA analysis through cDNA synthesis and microarray hybridization, was repeated three times, and for each repetition of the experiment, RNA was isolated from a different mouse. The relevant data were normalized to the [KO + MIGR1] condition.

    Techniques Used: Microarray, Expressing, Plasmid Preparation, Transduction, Gene Knockout, Hybridization, Isolation

    3) Product Images from "Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms"

    Article Title: Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

    Journal: Nature biotechnology

    doi: 10.1038/nbt.1621

    Overview of Cufflinks. The algorithm takes as input cDNA fragment sequences that have been ( a ) aligned to the genome by software capable of producing spliced alignments, such as TopHat. With paired-end RNA-Seq, Cufflinks treats each pair of fragment reads as a single alignment. The algorithm assembles overlapping ‘bundles’ of fragment alignments ( b-c ) separately, which reduces running time and memory use because each bundle typically contains the fragments from no more than a few genes. Cufflinks then estimates the abundances of the assembled transcripts ( d-e ). ( b ) The first step in fragment assembly is to identify pairs of ‘incompatible’ fragments that must have originated from distinct spliced mRNA isoforms. Fragments are connected in an ‘overlap graph’ when they are compatible and their alignments overlap in the genome. Each fragment has one node in the graph, and an edge, directed from left to right along the genome, is placed between each pair of compatible fragments. In this example, the yellow, blue, and red fragments must have originated from separate isoforms, but any other fragment could have come from the same transcript as one of these three. ( c ) Assembling isoforms from the overlap graph. Paths through the graph correspond to sets of mutually compatible fragments that could be merged into complete isoforms. The overlap graph here can be minimally ‘covered’ by three paths, each representing a different isoform. Dilworth's Theorem states that the number of mutually incompatible reads is the same as the minimum number of transcripts needed to “explain” all the fragments. Cufflinks implements a proof of Dilworth's Theorem that produces a minimal set of paths that cover all the fragments in the overlap graph by finding the largest set of reads with the property that no two could have originated from the same isoform. ( d ) Estimating transcript abundance. Fragments are matched (denoted here using color) to the transcripts from which they could have originated. The violet fragment could have originated from the blue or red isoform. Gray fragments could have come from any of the three shown. Cufflinks estimates transcript abundances using a statistical model in which the probability of observing each fragment is a linear function of the abundances of the transcripts from which it could have originated. Because only the ends of each fragment are sequenced, the length of each may be unknown. Assigning a fragment to different isoforms often implies a different length for it. Cufflinks can incorporate the distribution of fragment lengths to help assign fragments to isoforms. For example, the violet fragment would be much longer, and very improbable according to Cufflinks' model, if it were to come from the red isoform instead of the blue isoform. ( e ) The program then numerically maximizes a function that assigns a likelihood to all possible sets of relative abundances of the yellow, red and blue isoforms (γ 1 ,γ 2 ,γ 3 ), producing the abundances that best explain the observed fragments, shown as a pie chart.
    Figure Legend Snippet: Overview of Cufflinks. The algorithm takes as input cDNA fragment sequences that have been ( a ) aligned to the genome by software capable of producing spliced alignments, such as TopHat. With paired-end RNA-Seq, Cufflinks treats each pair of fragment reads as a single alignment. The algorithm assembles overlapping ‘bundles’ of fragment alignments ( b-c ) separately, which reduces running time and memory use because each bundle typically contains the fragments from no more than a few genes. Cufflinks then estimates the abundances of the assembled transcripts ( d-e ). ( b ) The first step in fragment assembly is to identify pairs of ‘incompatible’ fragments that must have originated from distinct spliced mRNA isoforms. Fragments are connected in an ‘overlap graph’ when they are compatible and their alignments overlap in the genome. Each fragment has one node in the graph, and an edge, directed from left to right along the genome, is placed between each pair of compatible fragments. In this example, the yellow, blue, and red fragments must have originated from separate isoforms, but any other fragment could have come from the same transcript as one of these three. ( c ) Assembling isoforms from the overlap graph. Paths through the graph correspond to sets of mutually compatible fragments that could be merged into complete isoforms. The overlap graph here can be minimally ‘covered’ by three paths, each representing a different isoform. Dilworth's Theorem states that the number of mutually incompatible reads is the same as the minimum number of transcripts needed to “explain” all the fragments. Cufflinks implements a proof of Dilworth's Theorem that produces a minimal set of paths that cover all the fragments in the overlap graph by finding the largest set of reads with the property that no two could have originated from the same isoform. ( d ) Estimating transcript abundance. Fragments are matched (denoted here using color) to the transcripts from which they could have originated. The violet fragment could have originated from the blue or red isoform. Gray fragments could have come from any of the three shown. Cufflinks estimates transcript abundances using a statistical model in which the probability of observing each fragment is a linear function of the abundances of the transcripts from which it could have originated. Because only the ends of each fragment are sequenced, the length of each may be unknown. Assigning a fragment to different isoforms often implies a different length for it. Cufflinks can incorporate the distribution of fragment lengths to help assign fragments to isoforms. For example, the violet fragment would be much longer, and very improbable according to Cufflinks' model, if it were to come from the red isoform instead of the blue isoform. ( e ) The program then numerically maximizes a function that assigns a likelihood to all possible sets of relative abundances of the yellow, red and blue isoforms (γ 1 ,γ 2 ,γ 3 ), producing the abundances that best explain the observed fragments, shown as a pie chart.

    Techniques Used: Software, RNA Sequencing Assay

    4) Product Images from "Gene expression profiling by cDNA-AFLP reveals potential candidate genes for partial resistance of ‘Président Roulin’ against Venturia inaequalis"

    Article Title: Gene expression profiling by cDNA-AFLP reveals potential candidate genes for partial resistance of ‘Président Roulin’ against Venturia inaequalis

    Journal: BMC Genomics

    doi: 10.1186/1471-2164-15-1043

    Expression patterns of apple genes displayed by cDNA-AFLP fingerprints. The cDNA-AFLP compares transcriptional profiles from ‘Président Roulin’ (partially resistant) and ‘Gala’ (susceptible) mock-inoculated or challenged by V. inaequalis at 48 hpi. The 32 samples are arranged in 8 groups according to the different specific primers tested during the selective amplification step of the AFLP procedure. E and M refer to the Eco RI and Mse I primers, followed by the selective nucleotides used. Within each of the 8 groups samples are ordered as follows: ‘Président Roulin’ infected (Ri) and mock-inoculated (Rm), and ‘Gala’ infected (Si) and mock-inoculated (Sm). Differentially expressed TDFs were classified into 2 categories: genotype-specific TDFs (group I) and pathogen-responsive TDFs (group II), further divided into two sub-groups; pathogen-responsive TDFs expressed in common by both genotypes (sub-group IIa) and pathogen-responsive and genotype specific TDFs (sub-group IIb). Illustrations are given.
    Figure Legend Snippet: Expression patterns of apple genes displayed by cDNA-AFLP fingerprints. The cDNA-AFLP compares transcriptional profiles from ‘Président Roulin’ (partially resistant) and ‘Gala’ (susceptible) mock-inoculated or challenged by V. inaequalis at 48 hpi. The 32 samples are arranged in 8 groups according to the different specific primers tested during the selective amplification step of the AFLP procedure. E and M refer to the Eco RI and Mse I primers, followed by the selective nucleotides used. Within each of the 8 groups samples are ordered as follows: ‘Président Roulin’ infected (Ri) and mock-inoculated (Rm), and ‘Gala’ infected (Si) and mock-inoculated (Sm). Differentially expressed TDFs were classified into 2 categories: genotype-specific TDFs (group I) and pathogen-responsive TDFs (group II), further divided into two sub-groups; pathogen-responsive TDFs expressed in common by both genotypes (sub-group IIa) and pathogen-responsive and genotype specific TDFs (sub-group IIb). Illustrations are given.

    Techniques Used: Expressing, cDNA-AFLP Assay, Amplification, Infection

    Over-representation of GO categories in ‘Président Roulin’cDNA-AFLP library compared to Rvi6 ( HcrVf2 )-’Gala’ transformed library. The comparison has been made by gene enrichment analysis for the Biological Process GO category between our cDNA-AFLP library (scab-infected leaves of ‘Président Roulin’, partially resistant) compared with a cDNA library from completely resistant Rvi6 ( HcrVf2 )-transformed ‘Gala’ lines challenged with V. inaequalis [ 25 ]. Gene enrichment analysis was conducted with the software Blast2Go using Fisher’s Exact Test at a p-value
    Figure Legend Snippet: Over-representation of GO categories in ‘Président Roulin’cDNA-AFLP library compared to Rvi6 ( HcrVf2 )-’Gala’ transformed library. The comparison has been made by gene enrichment analysis for the Biological Process GO category between our cDNA-AFLP library (scab-infected leaves of ‘Président Roulin’, partially resistant) compared with a cDNA library from completely resistant Rvi6 ( HcrVf2 )-transformed ‘Gala’ lines challenged with V. inaequalis [ 25 ]. Gene enrichment analysis was conducted with the software Blast2Go using Fisher’s Exact Test at a p-value

    Techniques Used: cDNA-AFLP Assay, Transformation Assay, Infection, cDNA Library Assay, Software

    Over-representation of GO categories in ‘Président Roulin’ cDNA-AFLP library compared to non-infected EST apple libraries. The comparison has been made by gene enrichment analysis for Biological Process GO categories between our cDNA-AFLP library from scab-infected leaves of ‘Président Roulin’ (partially resistant) and two EST libraries from uninfected actively growing shoot of: (A) cultivar ‘Royal Gala’ in the library AELA [ 34 ] and (B) cultivar ‘Wijcik’ in the library Mdstw [ 35 ]. Gene enrichment analysis was conducted with the software Blast2Go using Fisher’s Exact Test at a p-value
    Figure Legend Snippet: Over-representation of GO categories in ‘Président Roulin’ cDNA-AFLP library compared to non-infected EST apple libraries. The comparison has been made by gene enrichment analysis for Biological Process GO categories between our cDNA-AFLP library from scab-infected leaves of ‘Président Roulin’ (partially resistant) and two EST libraries from uninfected actively growing shoot of: (A) cultivar ‘Royal Gala’ in the library AELA [ 34 ] and (B) cultivar ‘Wijcik’ in the library Mdstw [ 35 ]. Gene enrichment analysis was conducted with the software Blast2Go using Fisher’s Exact Test at a p-value

    Techniques Used: cDNA-AFLP Assay, Infection, Software

    5) Product Images from "Gene expression profiling of microglia infected by a highly neurovirulent murine leukemia virus: implications for neuropathogenesis"

    Article Title: Gene expression profiling of microglia infected by a highly neurovirulent murine leukemia virus: implications for neuropathogenesis

    Journal: Retrovirology

    doi: 10.1186/1742-4690-3-26

    Taqman real-time RT-PCR validation assessment of microglial genes identified in Fr57E versus FrCasE gene arrays . Panel A shows qRT-PCR analysis of RNA from two independent microglial culture experiments assaying three separate cultures in triplicate for SIGIRR, exosome component 4 (Exosc4), and Riken cDNA 1810008K03 gene (ChaC). These cultures were distinct from those used for microarray analysis. Panel B shows qRT-PCR analysis of SIGIRR RNA obtained from microglia isolated from the brains of virus-infected and uninfected mice. FrCasE- infected (black); F43- infected (gray); mock-infected (white)
    Figure Legend Snippet: Taqman real-time RT-PCR validation assessment of microglial genes identified in Fr57E versus FrCasE gene arrays . Panel A shows qRT-PCR analysis of RNA from two independent microglial culture experiments assaying three separate cultures in triplicate for SIGIRR, exosome component 4 (Exosc4), and Riken cDNA 1810008K03 gene (ChaC). These cultures were distinct from those used for microarray analysis. Panel B shows qRT-PCR analysis of SIGIRR RNA obtained from microglia isolated from the brains of virus-infected and uninfected mice. FrCasE- infected (black); F43- infected (gray); mock-infected (white)

    Techniques Used: Quantitative RT-PCR, Microarray, Isolation, Infection, Mouse Assay

    6) Product Images from "Archaeal Signal Transduction: Impact of Protein Phosphatase Deletions on Cell Size, Motility, and Energy Metabolism in Sulfolobus acidocaldariu"

    Article Title: Archaeal Signal Transduction: Impact of Protein Phosphatase Deletions on Cell Size, Motility, and Energy Metabolism in Sulfolobus acidocaldariu

    Journal: Molecular & Cellular Proteomics : MCP

    doi: 10.1074/mcp.M113.027375

    Differential expression levels of archaella operon genes and respiratory chain genes in Δ saci_pp2a and Δ saci_ptp . Total RNA isolated from S. acidocaldarius MW001, Δ saci_pp2a and Δ saci_ptp cultures were used for cDNAs synthesis. qRT-PCR analysis was performed using specific primers for each archaella component ( A ) and components of the terminal oxidase complexes ( B ). Relative transcript levels of each gene were normalized to an internal control gene secY . The values reflect the fold change compared with cDNA prepared from MW001. The means and standard deviations of three biological replicates are shown. Up-regulation of all archaella and the terminal oxidase genes in the saci_pp2a deletion strain reflect the RNA-seq results. * significant ( p value ≤ 0.05), ** highly significant ( p value ≤ 0.01).
    Figure Legend Snippet: Differential expression levels of archaella operon genes and respiratory chain genes in Δ saci_pp2a and Δ saci_ptp . Total RNA isolated from S. acidocaldarius MW001, Δ saci_pp2a and Δ saci_ptp cultures were used for cDNAs synthesis. qRT-PCR analysis was performed using specific primers for each archaella component ( A ) and components of the terminal oxidase complexes ( B ). Relative transcript levels of each gene were normalized to an internal control gene secY . The values reflect the fold change compared with cDNA prepared from MW001. The means and standard deviations of three biological replicates are shown. Up-regulation of all archaella and the terminal oxidase genes in the saci_pp2a deletion strain reflect the RNA-seq results. * significant ( p value ≤ 0.05), ** highly significant ( p value ≤ 0.01).

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

    7) Product Images from "mosR, a Novel Transcriptional Regulator of Hypoxia and Virulence in Mycobacterium tuberculosis "

    Article Title: mosR, a Novel Transcriptional Regulator of Hypoxia and Virulence in Mycobacterium tuberculosis

    Journal: Journal of Bacteriology

    doi: 10.1128/JB.00778-09

    Deletion, complementation and overexpression of Rv0348. (A) Organization of the Rv0348 operon and our strategy for gene disruption. See Materials and Methods for details. (B) Southern blot analysis of SalI-digested genomic DNA of the H37Rv wild type and the Δ mosR mutant. (C) PCR analysis of cDNA synthesized from RNA samples purified from H37Rv (lanes 1, 3, and 5) or the Δ mosR mutant (lanes 2, 4, and 6). (D) Western blot analysis of different M. tuberculosis strains using polyclonal antibodies raised in rabbits against the MBP-MosR protein. Pellets from M. tuberculosis H37Rv (lane 1), the Δ mosR mutant (lane 2), the Δ mosR :: mosR complemented strain (lane 3), and the H37Rv:: mosR overexpression strain (lane 4) were subjected to immunoblotting. The blot for soluble fractions was negative (data not shown).
    Figure Legend Snippet: Deletion, complementation and overexpression of Rv0348. (A) Organization of the Rv0348 operon and our strategy for gene disruption. See Materials and Methods for details. (B) Southern blot analysis of SalI-digested genomic DNA of the H37Rv wild type and the Δ mosR mutant. (C) PCR analysis of cDNA synthesized from RNA samples purified from H37Rv (lanes 1, 3, and 5) or the Δ mosR mutant (lanes 2, 4, and 6). (D) Western blot analysis of different M. tuberculosis strains using polyclonal antibodies raised in rabbits against the MBP-MosR protein. Pellets from M. tuberculosis H37Rv (lane 1), the Δ mosR mutant (lane 2), the Δ mosR :: mosR complemented strain (lane 3), and the H37Rv:: mosR overexpression strain (lane 4) were subjected to immunoblotting. The blot for soluble fractions was negative (data not shown).

    Techniques Used: Over Expression, Southern Blot, Mutagenesis, Polymerase Chain Reaction, Synthesized, Purification, Western Blot

    8) Product Images from "New Alzheimer Amyloid ? Responsive Genes Identified in Human Neuroblastoma Cells by Hierarchical Clustering"

    Article Title: New Alzheimer Amyloid ? Responsive Genes Identified in Human Neuroblastoma Cells by Hierarchical Clustering

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0006779

    Experimental set up. Independent cell clones of the human neuroblastoma cell line SH-SY5Y, generating different amounts of Aβ 42 and Aβ 40 , were used for whole genome transcription analysis. Total-RNA was extracted from the cells, converted into cDNA, followed by conversion into cRNA (in the scheme simplified presented as m-RNA). The cRNA was hybridized onto the Chips, washed, scanned and the scanned images were used for data analysis. The means of triplicates (n = 3 per group) were calculated and the groups were compared in order to obtain information about the effects of Aβ 42 /Aβ 40 . C99WT, producing medium Aβ 42 /Aβ 40 levels, was compared with C99I45F (high Aβ 42 , low Aβ 40 levels) and with C99V50F (low Aβ 42 , high Aβ 40 levels). These comparisons resulted in A β -specific information. Comparisons between C99WT, C99I45F, C99V50F and mock-transfected cells resulted in information about effects caused by C99-overexpression combined with Aβ 42 /Aβ 40 effects, since C99 as well as Aβ 42 /Aβ 40 were overproduced compared to the mock-control in which only very low (endogenous) amounts of C99 and Aβ 42 /Aβ 40 were present ( Table 1 ).
    Figure Legend Snippet: Experimental set up. Independent cell clones of the human neuroblastoma cell line SH-SY5Y, generating different amounts of Aβ 42 and Aβ 40 , were used for whole genome transcription analysis. Total-RNA was extracted from the cells, converted into cDNA, followed by conversion into cRNA (in the scheme simplified presented as m-RNA). The cRNA was hybridized onto the Chips, washed, scanned and the scanned images were used for data analysis. The means of triplicates (n = 3 per group) were calculated and the groups were compared in order to obtain information about the effects of Aβ 42 /Aβ 40 . C99WT, producing medium Aβ 42 /Aβ 40 levels, was compared with C99I45F (high Aβ 42 , low Aβ 40 levels) and with C99V50F (low Aβ 42 , high Aβ 40 levels). These comparisons resulted in A β -specific information. Comparisons between C99WT, C99I45F, C99V50F and mock-transfected cells resulted in information about effects caused by C99-overexpression combined with Aβ 42 /Aβ 40 effects, since C99 as well as Aβ 42 /Aβ 40 were overproduced compared to the mock-control in which only very low (endogenous) amounts of C99 and Aβ 42 /Aβ 40 were present ( Table 1 ).

    Techniques Used: Clone Assay, Transfection, Over Expression

    Relative gene expression of NEUROG2 and KIAA0125 measured by real-time PCR and compared to relative Aβ 42 levels. Fig. 5A and 5B show an almost linear relationship of NEUROG2/KIAA0125 expression and relative Aβ 42 levels. It is noteworthy that these relationships are in opposite directions: While NEUROG2 expression increases with increasing relative Aβ 42 levels, KIAA0125 expression decreases with increasing relative Aβ 42 levels. Importantly, the same regulation pattern was confirmed by real-time PCR as previously observed by microarray analysis: The stronger the NEUROG2 up -regulation in certain cell clones (Fig. 5A), the stronger was the KIAA0125 down -regulation in the same cell clones (Fig. 5B) and vice versa. Total-RNA was originated from the same clones as the ones used for the microarrays. This total-RNA was converted into cDNA and used for real-time PCR. Cyclophilin A expression was used for normalisation. Error bars represent the standard error of the mean (S.E.M.) of three independent cell clones.
    Figure Legend Snippet: Relative gene expression of NEUROG2 and KIAA0125 measured by real-time PCR and compared to relative Aβ 42 levels. Fig. 5A and 5B show an almost linear relationship of NEUROG2/KIAA0125 expression and relative Aβ 42 levels. It is noteworthy that these relationships are in opposite directions: While NEUROG2 expression increases with increasing relative Aβ 42 levels, KIAA0125 expression decreases with increasing relative Aβ 42 levels. Importantly, the same regulation pattern was confirmed by real-time PCR as previously observed by microarray analysis: The stronger the NEUROG2 up -regulation in certain cell clones (Fig. 5A), the stronger was the KIAA0125 down -regulation in the same cell clones (Fig. 5B) and vice versa. Total-RNA was originated from the same clones as the ones used for the microarrays. This total-RNA was converted into cDNA and used for real-time PCR. Cyclophilin A expression was used for normalisation. Error bars represent the standard error of the mean (S.E.M.) of three independent cell clones.

    Techniques Used: Expressing, Real-time Polymerase Chain Reaction, Microarray, Clone Assay

    9) Product Images from "Gene expression analysis in cadmium-stressed roots of a low cadmium-accumulating solanaceous plant, Solanum torvum"

    Article Title: Gene expression analysis in cadmium-stressed roots of a low cadmium-accumulating solanaceous plant, Solanum torvum

    Journal: Journal of Experimental Botany

    doi: 10.1093/jxb/erp313

    A schematic diagram of the procedure for expression tag library preparation. Double-stranded cDNA was synthesized from mRNA using a biotinylated adaptor oligo(dT) primer. After a digestion with Nla III, the 3′ end cDNA fragments anchored to streptavidin magnetic beads were ligated to the adaptor 1_GT, the adaptor 1_CT, the adaptor 1_AC, and the adaptor 1_TC for Cd0, Cd3h, Cd1d, and Cd3d libraries, respectively. The adaptor 1-ligated cDNA fragments were digested with Eco P15I, and the released fragments were ligated to the adaptor 2. The adaptor 1-tag–adator 2 fragments were amplified using the GEX PCR primer set. The amplified fragments (∼104 bp) were separated by PAGE. Four independent library solutions (Cd0, Cd3h, Cd1d, and Cd3d) were mixed in an equal amount of DNA, and the blended library solution was subjected to high-throughput sequencing using an Illumina Genome Analyzer. Underlined characters indicate Nla III and Eco P15I recognition sites. Bold ‘XX’ indicates library coding nucleotides, and ‘GT’, ‘CT’, ‘AC’, and ‘TC’ were used for Cd0, Cd3h, Cd1d, and Cd3d libraries, respectively.
    Figure Legend Snippet: A schematic diagram of the procedure for expression tag library preparation. Double-stranded cDNA was synthesized from mRNA using a biotinylated adaptor oligo(dT) primer. After a digestion with Nla III, the 3′ end cDNA fragments anchored to streptavidin magnetic beads were ligated to the adaptor 1_GT, the adaptor 1_CT, the adaptor 1_AC, and the adaptor 1_TC for Cd0, Cd3h, Cd1d, and Cd3d libraries, respectively. The adaptor 1-ligated cDNA fragments were digested with Eco P15I, and the released fragments were ligated to the adaptor 2. The adaptor 1-tag–adator 2 fragments were amplified using the GEX PCR primer set. The amplified fragments (∼104 bp) were separated by PAGE. Four independent library solutions (Cd0, Cd3h, Cd1d, and Cd3d) were mixed in an equal amount of DNA, and the blended library solution was subjected to high-throughput sequencing using an Illumina Genome Analyzer. Underlined characters indicate Nla III and Eco P15I recognition sites. Bold ‘XX’ indicates library coding nucleotides, and ‘GT’, ‘CT’, ‘AC’, and ‘TC’ were used for Cd0, Cd3h, Cd1d, and Cd3d libraries, respectively.

    Techniques Used: Expressing, Synthesized, Magnetic Beads, Amplification, Polymerase Chain Reaction, Polyacrylamide Gel Electrophoresis, High Throughput Screening Assay, Sequencing

    10) Product Images from "Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery"

    Article Title: Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery

    Journal: The ISME Journal

    doi: 10.1038/ismej.2013.223

    Clostridial flagellin transcript and gene copies during colitis and recovery. RNA and DNA were recovered from the same nucleic acids preparation, RNA was reverse transcribed into single-stranded cDNA. Gene and transcript copies were determined with qPCR. The ratio of flagellin to gene copies was calculated for individual mice and log-transformed. Means were compared by One-Way ANOVA, different letters indicate significance ( P
    Figure Legend Snippet: Clostridial flagellin transcript and gene copies during colitis and recovery. RNA and DNA were recovered from the same nucleic acids preparation, RNA was reverse transcribed into single-stranded cDNA. Gene and transcript copies were determined with qPCR. The ratio of flagellin to gene copies was calculated for individual mice and log-transformed. Means were compared by One-Way ANOVA, different letters indicate significance ( P

    Techniques Used: Real-time Polymerase Chain Reaction, Mouse Assay, Transformation Assay

    11) Product Images from "Circular RNA Is Expressed across the Eukaryotic Tree of Life"

    Article Title: Circular RNA Is Expressed across the Eukaryotic Tree of Life

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0090859

    Circle-specific PCR and relative RNase R resistance. a) An example of circular and linear isoforms, in this case for the P. falciparum gene MAL13P1.337 , and circle- and linear-specific PCR design. PCR is performed on cDNA from total RNA that was mock-treated or RNase R-treated, or on P. falciparum genomic DNA. Circle-specific PCR amplifies from RNA but not genomic DNA; it amplifies the candidate junction (177 bp band) but also an unexpected band corresponding to a 4-1 circle. b) Quantitation of RNase R resistance. Plotted here is the relative RNase R resistance of a circular isoform compared to its counterpart linear isoform (ΔΔCt): RNase R resistance(circle) – RNase R resistance(linear); gray bars are standard errors. RNase R resistance (the log 2 fold-change in RNA isoform abundance with RNase R treatment) was measured by quantitative RT-PCR and taken as ΔCt = Ct(mock – treatment) – Ct(RNase R – treatment). RNase R resistance values for circular and linear isoforms are separately shown in Figure S1 . All linear isoforms were sensitive to RNase R, showing a greater than 32-fold drop in abundance after RNase R treatment (ΔCt
    Figure Legend Snippet: Circle-specific PCR and relative RNase R resistance. a) An example of circular and linear isoforms, in this case for the P. falciparum gene MAL13P1.337 , and circle- and linear-specific PCR design. PCR is performed on cDNA from total RNA that was mock-treated or RNase R-treated, or on P. falciparum genomic DNA. Circle-specific PCR amplifies from RNA but not genomic DNA; it amplifies the candidate junction (177 bp band) but also an unexpected band corresponding to a 4-1 circle. b) Quantitation of RNase R resistance. Plotted here is the relative RNase R resistance of a circular isoform compared to its counterpart linear isoform (ΔΔCt): RNase R resistance(circle) – RNase R resistance(linear); gray bars are standard errors. RNase R resistance (the log 2 fold-change in RNA isoform abundance with RNase R treatment) was measured by quantitative RT-PCR and taken as ΔCt = Ct(mock – treatment) – Ct(RNase R – treatment). RNase R resistance values for circular and linear isoforms are separately shown in Figure S1 . All linear isoforms were sensitive to RNase R, showing a greater than 32-fold drop in abundance after RNase R treatment (ΔCt

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

    12) Product Images from "An antisense promoter in mouse L1 retrotransposon open reading frame-1 initiates expression of diverse fusion transcripts and limits retrotransposition"

    Article Title: An antisense promoter in mouse L1 retrotransposon open reading frame-1 initiates expression of diverse fusion transcripts and limits retrotransposition

    Journal: Nucleic Acids Research

    doi: 10.1093/nar/gku091

    Contribution of an AS L1 RIFT to overall Arhgap15 gene expression in various mouse strains. ( A ) Schematic representation of Arhgap15 exons, including a polymorphic AS L1 integrant in the B6 reference genome but not in other strains. ( B ) AS L1 RIFT expression at Arhgap15 was detected in B6 mice, using the novel RIFT assay where we performed RT-PCR using AS L1 and oligo-d(T) primers, followed by hybridization of resulting cDNA products to an Affymetrix mouse exon microarray. We required five consecutive exon probes to be strongly positive to call RIFTs. Shown are genomic positions of probes within exons (x-axis) and hybridization signal intensities on a log scale (y-axis). Legend, inset : five mouse strains, different symbol colors and shapes. ( C ) Conventional assay for Arhgap15 expression in total RNAs (see legend, B). The AS L1 RIFT in B6 mice affects total RNA expression levels at the 3′ exons downstream of the polymorphic, initiating L1 integrant (see corresponding positions, A).
    Figure Legend Snippet: Contribution of an AS L1 RIFT to overall Arhgap15 gene expression in various mouse strains. ( A ) Schematic representation of Arhgap15 exons, including a polymorphic AS L1 integrant in the B6 reference genome but not in other strains. ( B ) AS L1 RIFT expression at Arhgap15 was detected in B6 mice, using the novel RIFT assay where we performed RT-PCR using AS L1 and oligo-d(T) primers, followed by hybridization of resulting cDNA products to an Affymetrix mouse exon microarray. We required five consecutive exon probes to be strongly positive to call RIFTs. Shown are genomic positions of probes within exons (x-axis) and hybridization signal intensities on a log scale (y-axis). Legend, inset : five mouse strains, different symbol colors and shapes. ( C ) Conventional assay for Arhgap15 expression in total RNAs (see legend, B). The AS L1 RIFT in B6 mice affects total RNA expression levels at the 3′ exons downstream of the polymorphic, initiating L1 integrant (see corresponding positions, A).

    Techniques Used: Expressing, Mouse Assay, Reverse Transcription Polymerase Chain Reaction, Hybridization, Microarray, RNA Expression

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