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The Physcomitrella patens gene atlas project: large‐scale RNA ‐seq based expression data
Author(s) -
Perroud PierreFrançois,
Haas Fabian B.,
Hiss Manuel,
Ullrich Kristian K.,
Alboresi Alessandro,
Amirebrahimi Mojgan,
Barry Kerrie,
Bassi Roberto,
Bonhomme Sandrine,
Chen Haodong,
Coates Juliet C.,
Fujita Tomomichi,
GuyonDebast Anouchka,
Lang Daniel,
Lin Junyan,
Lipzen Anna,
Nogué Fabien,
Oliver Melvin J.,
Ponce de León Inés,
Quatrano Ralph S.,
Rameau Catherine,
Reiss Bernd,
Reski Ralf,
Ricca Mariana,
Saidi Younousse,
Sun Ning,
Szövényi Péter,
Sreedasyam Avinash,
Grimwood Jane,
Stacey Gary,
Schmutz Jeremy,
Rensing Stefan A.
Publication year - 2018
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.13940
Subject(s) - physcomitrella patens , biology , rna seq , gene , transcriptome , computational biology , protonema , genome , genetics , gene expression , moss , botany , mutant
Summary 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 ( DEG s) 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.