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Title: Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis

Journal Article · · The Plant Journal
DOI:https://doi.org/10.1111/tpj.13175· OSTI ID:1257945
 [1];  [2];  [3];  [4];  [5];  [4];  [6]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States); Univ. of Illinois at Urbana-Champaign, Champaign, IL (United States)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States); Stony Brook Univ., Stony Brook, NY (United States)
  4. Yale Univ., New Haven, CT (United States)
  5. Cold Spring Harbor Lab., Cold Spring Harbor, NY (United States)
  6. Cold Spring Harbor Lab., Cold Spring Harbor, NY (United States); USDA ARS NEA Plant, Ithaca, NY (United States)
+ Show Author Affiliations

Here, transcriptome datasets from thousands of samples of the model plant Arabidopsis thaliana have been collectively generated by multiple individual labs. Although integration and meta-analysis of these samples has become routine in the plant research community, it is often hampered by the lack of metadata or differences in annotation styles by different labs. In this study, we carefully selected and integrated 6,057 Arabidopsis microarray expression samples from 304 experiments deposited to NCBI GEO. Metadata such as tissue type, growth condition, and developmental stage were manually curated for each sample. We then studied global expression landscape of the integrated dataset and found that samples of the same tissue tend to be more similar to each other than to samples of other tissues, even in different growth conditions or developmental stages. Root has the most distinct transcriptome compared to aerial tissues, but the transcriptome of cultured root is more similar to those of aerial tissues as the former samples lost their cellular identity. Using a simple computational classification method, we showed that the tissue type of a sample can be successfully predicted based on its expression profile, opening the door for automatic metadata extraction and facilitating re-use of plant transcriptome data. As a proof of principle we applied our automated annotation pipeline to 708 RNA-seq samples from public repositories and verified accuracy of our predictions with samples’ metadata provided by authors.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
SC00112704
OSTI ID:
1257945
Report Number(s):
BNL-112108-2016-JA
Journal Information:
The Plant Journal, Journal Name: The Plant Journal; ISSN 0960-7412
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 24 works
Citation information provided by
Web of Science

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Cited By (10)

Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana journal January 2019
Shifting the limits in wheat research and breeding using a fully annotated reference genome journal August 2018
Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken journal August 2018
Identification of regulatory modules in genome scale transcription regulatory networks journal December 2017
Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken journal April 2018
PlaD: A Transcriptomics Database for Plant Defense Responses to Pathogens, Providing New Insights into Plant Immune System journal August 2018
CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping journal June 2017
Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection journal October 2016
Bioinformatics analysis to identify the critical genes, microRNAs and long noncoding RNAs in melanoma journal July 2017
Large-Scale Public Transcriptomic Data Mining Reveals a Tight Connection between the Transport of Nitrogen and Other Transport Processes in Arabidopsis journal August 2016

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