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The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data

Journal Article · · The Plant Journal
DOI:https://doi.org/10.1111/tpj.13940· OSTI ID:1616061
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  1. University of Marburg (Germany)
  2. University of Verona (Italy)
  3. USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
  4. Université Paris-Saclay, Versailles (France)
  5. Peking University, Beijing (China)
  6. University of Birmingham (United Kingdom)
  7. Hokkaido University, Sapporo (Japan)
  8. Helmholtz Zentrum München, Neuherberg (Germany)
  9. University of Missouri, Columbia, MO (United States)
  10. Clemente Estable Biological Research Institute, Montevideo (Uruguay)
  11. Washington University, St. Louis, MO (United States)
  12. Max Planck Institute for Plant Breeding Research, Köln (Germany)
  13. University of Freiburg (Germany)
  14. University of Zurich (Switzerland)
  15. HudsonAlpha Institute for Biotechnology, Huntsville, AL (United States)
  16. USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); HudsonAlpha Institute for Biotechnology, Huntsville, AL (United States)
  17. University of Marburg (Germany); University of Freiburg (Germany)

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Natural Science Foundation of China; German Federal and State Governments; UK Leverhulme Trust; Swiss National Science Foundation
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1616061
Alternate ID(s):
OSTI ID: 1441035
Journal Information:
The Plant Journal, Journal Name: The Plant Journal Journal Issue: 1 Vol. 95; ISSN 0960-7412
Publisher:
Society for Experimental BiologyCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (3)

Co-expression and Transcriptome Analysis of Marchantia polymorpha Transcription Factors Supports Class C ARFs as Independent Actors of an Ancient Auxin Regulatory Module journal October 2018
Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets journal November 2018
Gene Expression Maps in Plants: Current State and Prospects journal August 2019