Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Arabidopsis RNA-Seq Differential Gene Expression profiling

ABSTRACT: RNA-Seq data from 17 wild-type biological replicates of Arabidopsis thaliana used to explore read count measurements across replicates along with the False Discovery Rate of Differential Gene Expression tools. Although A. thaliana has a relatively small genome, its transcriptome is similar in scale and complexity to that of model mammal species and its genome is extensively annotated and the conclusions presented here provide useful guidance for work in other complex eukaryotes. The findings show that the negative binomial and log-normal distributions are both good choices as models for the cross-replicate variability of RNA-seq read counts. 6 of 9 DGE tools controlled their identification of false positives well even with only 3 replicates. Our results reinforce the conclusions reached by Schurch et. al. (2015 RNA) in yeast.

INSTRUMENT(S): ERCC Spike-in Kit (Ambion) & Illumina TruSeq Stranded Total RNA with Ribo-Zero Plant kit, Illumina HiSeq 2000, RNeasy Plant Mini Kit & TURBOTM DNase (Ambion)

ORGANISM(S): Arabidopsis thaliana

SUBMITTER: Kimon Froussios

PROVIDER: E-MTAB-5446 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:This submission includes the sample data for a protocol covering differential expression analysis with TopHat and Cufflinks. The protocol also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-Seq analysis results. While the procedure assumes basic informatics skills, these tools assume little to no background with RNA-Seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The example data was generated in silico to closely resemble a real experiment in Drosophila melanogaster. First, expression values in cultured S2 cells were calculated for FlyBase 5.2 transcripts. These values were used to generate 3 sequencing replicates for condition "C1", with underlying variability in expression across replicates simulated by fitting a negative binomial model through the real S2 read count data. A second simulated condition "C2" was generated by perturbing expression for 300 randomly selected genes. Genes were perturbed by selecting the most highly expressed isoform and increasing its relative expression by three fold. Three replicates of this condtion were sequenced as above. Simulated sequencing was performed by picking a transcript from the FlyBase transcriptome with equal to its abundance, choosing a fragment length from a normal distribution with mean = 180bp and standard deviation = 20bp, and then choosing a start point for the fragment within the transcript uniformly at random. Total sequencing yield for each replicate was chosen to match that of the real S2 data. Each replicate was mapped to the fly genome with TopHat v 1.3.1 seperately. The replicates were assembled seperately with Cufflinks v 1.1.0. The replicate assemblies were merged with Cuffmerge. This merged assembly was then analysed for differentially expressed and regulated genes with Cuffdiff.

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Arabidopsis RNA-Seq Differential Gene Expression profiling

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