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

Authors: PERROUD, PIERRE-FRANCOIS - Philipps-Universität Marburg; HASS, FABIAN - Philipps-Universität Marburg; HISS, MANUEL - Philipps-Universität Marburg; ULLRICH, KRISTIAN - Philipps-Universität Marburg; ALBORESI, ALESSANDRO - University Of Verona; AMIREBRAHIMI, MOJGAN - US Department Of Energy; BARRY, KERRIE - US Department Of Energy; BASSI, ROBERTO - University Of Verona; BONHOMME, SANDRINE - University Of Paris; CHEN, HAODONG - Peking University; COATES, JULIET - University Of Birmingham; FUJITA, TOMOMICHI - Hokkaido University; GUYON-DEBAST, ANOUCHKA - University Of Paris; LANG, DANIEL - Helmholtz Centre; LIN, JUNYAN - US Department Of Energy; LIPZEN, ANNA - US Department Of Energy; NOGUE, FABIEN - University Of Paris; Oliver, Melvin; PONCE DE LEON, INES - Max Planck Institute Of Molecular Plant Physiology; QUATRANO, RALPH - Washington University; RAMEAU, CATHERINE - University Of Paris; REISS, BERND - Max Planck Institute Of Molecular Plant Physiology; RESKI, RALF - University Of Freiburg; RICCA, MARIANA - University Of Zurich; SAIDI, YOUNOUSSE - University Of Birmingham; SUN, NING - Peking University; SZOVENYI, PETER - University Of Zurich; SREEDASYAM, AVINASH - Hudsonalpha Institute For Biotechnology; GRIMWOOD, JANE - Hudsonalpha Institute For Biotechnology; STACEY, GARY - University Of Missouri; SCHMUTZ, JEREMY - Hudsonalpha Institute For Biotechnology; RENSING, STEFAN - Philipps-Universität Marburg

Submitted to: Plant Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/5/2018
Publication Date: 4/22/2018
Citation: Perroud, P., Hass, F., Hiss, M., Ullrich, K., Alboresi, A., Amirebrahimi, M., Barry, K., Bassi, R., Bonhomme, S., Chen, H., Coates, J., Fujita, T., Guyon-Debast, A., Lang, D., Lin, J., Lipzen, A., Nogue, F., Oliver, M.J., Ponce De Leon, I., Quatrano, R.S., Rameau, C., Reiss, B., Reski, R., Ricca, M., Saidi, Y., Sun, N., Szovenyi, P., Sreedasyam, A., Grimwood, J., Stacey, G., Schmutz, J., Rensing, S.A. 2018. The Physcomitrella patens gene atlas project: large scale RNA-seq based expression data. Plant Journal. 95:168-182. https://doi.org/10.1111/tpj.13940.
DOI: https://doi.org/10.1111/tpj.13940

Interpretive Summary: Physcomitrella patens, a moss that can be grown in lab cultures, has become the leading reference plant model for non-seed plants since the discovery of its intrinsically efficient gene targeting followed by its genome sequencing. It is also becoming the plant model of choice when assessing the value of novel genes for improvement of plant productivity and environmental stress tolerance. Many plant geneticists rely on this new model system and in this research many groups from around the world have joined together to produce a detailed gene expression resource for understanding how this plant model responds to developmental cues and exposure to various environmental conditions. Understanding these responses at the level of gene expression will aid future researchers in assessing the impact of added genes or new environmental cues on this important new laboratory model. This information will greatly aid in the assessment of the impact of the introduction of novel genes into plants, and ultimately into crops via breeding or biotechnology.

Technical Abstract: High through put RNA sequencing (RNA-seq) has recently become the method of choice to define and analyse transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help the analysis of specific perturbations, no overall reference dataset has been established yet. In the framework of its 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 stages and conditions. Upon dataset quality control and processing through read mapping, 28,509 of the 34,361 v3.3 gene models were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between specific growth conditions. The analysis of the three most distinct and abundant P. patens tissues, 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 protonema transcriptome. Finally, the cooperative nature of this project, 13 different laboratories around the world provided samples, allowed us to analyse inter-laboratory variation. We compare the differences between single laboratory experiment replication in contrast with the comparison of the same experiment between two different laboratories.