Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Arabidopsis tissue atlas

ABSTRACT: We used state of the art mass spectrometry and RNA sequencing (RNA-Seq) to provide the first integrated proteomic, phosphoproteomic and transcriptomic atlas of Arabidopsis. For this we measured 30 different Arabidopsis tissues from adult plants, seedlings, callus and cell culture samples to an average depth of 17,603 +/- 1,317 transcripts, 14,430 +/- 911 proteins and 14,689 +/- 2,509 phosphorylation sites. In total we provide protein expression data for 66 % and transcript expression data for 90 % of the annotated protein coding genes (Araport11). For four plant organs we additionally measured consecutive growth stages (rosette leaves, 13 stages; flower, 6 stages; silique, 5 stages; seed, 5 stages).

INSTRUMENT(S): Illumina HiSeq 2500

ORGANISM(S): Arabidopsis thaliana

SUBMITTER: Bernhard Kuster

PROVIDER: E-MTAB-7978 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Mass-spectrometry-based draft of the Arabidopsis proteome.

Mergner Julia J Frejno Martin M List Markus M Papacek Michael M Chen Xia X Chaudhary Ajeet A Samaras Patroklos P Richter Sandra S Shikata Hiromasa H Messerer Maxim M Lang Daniel D Altmann Stefan S Cyprys Philipp P Zolg Daniel P DP Mathieson Toby T Bantscheff Marcus M Hazarika Rashmi R RR Schmidt Tobias T Dawid Corinna C Dunkel Andreas A Hofmann Thomas T Sprunck Stefanie S Falter-Braun Pascal P Johannes Frank F Mayer Klaus F X KFX Jürgens Gerd G Wilhelm Mathias M Baumbach Jan J Grill Erwin E Schneitz Kay K Schwechheimer Claus C Kuster Bernhard B

Nature 20200311 7799

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities<sup>1</sup>. Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana. Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosp ...[more]

PMID: 32188942

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Project description:Next-generation RNA-sequencing (RNA-seq) is rapidly emerging as the technology of choice for whole-transcriptome studies. However, RNA-seq is not a bias free technique. It requires large amounts of RNA and library preparation can introduce multiple artifacts, compounded by problems from later stages in the process. Nevertheless, RNA-seq is increasingly used in multiple studies, including the characterization of tissue-specific transcriptomes from invertebrate models of human disease. The generation of samples in this context is complex, involving the establishment of mutant strains and the delicate contamination prone process of dissecting the target tissue. Moreover, in order achieve the required amount of RNA, multiple samples need to be pooled. Such datasets pose extra challenges due to the large variability that may occur between similar pools, mostly due to the presence of cells from surrounding tissues. Therefore, in addition to standard quality control of RNA-seq data, analytical procedures for control of 'biological quality’ are critical for successful comparison of gene expression profiles. In this study, the transcriptome of the central nervous system of a Drosophila transgenic strain with neuronal-specific RNAi of a ubiquitous gene was profiled using RNA-seq. While conducting our investigation, we observed the existence of an unusual variance in the libraries and showed that the expression profile of a small panel of genes was sufficient to identify libraries with low levels of contamination from neighboring tissues, enabling the selection of a robust dataset for differential expression analysis. We additionally analyzed the potential of profiling a complex tissue to identify cell-type specific changes in response to target gene down-regulation. Finally, we demonstrated that trimming 5’ ends of reads decreases nucleotide frequency biases, increasing the coverage of protein coding genes with a potential positive impact in the incurrence of sampling errors. Central Nervous System profiles of third instar larvae WT (N=6), C24 (N=7), and X7/C24 D. melanogaster were generated by sequencing using the Illumina Hiseq2000.

Dataset Information

Arabidopsis tissue atlas

Publications

Mass-spectrometry-based draft of the Arabidopsis proteome.

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