| Autor: |
Michel EJS; Boyce Thompson Institute, Ithaca, NY, USA.; Plant Biology Section, School of Integrative Plant Science, Cornell University, Ithaca NY, USA., Hotto AM; Boyce Thompson Institute, Ithaca, NY, USA., Strickler SR; Boyce Thompson Institute, Ithaca, NY, USA., Stern DB; Boyce Thompson Institute, Ithaca, NY, USA. ds28@cornell.edu., Castandet B; Boyce Thompson Institute, Ithaca, NY, USA. benoit.castandet@ips2.universite-paris-saclay.fr.; Centre National de la Recherche Scientifique, Institute of Plant Sciences Paris Saclay, Institut National de la Recherche Agronomique, Université Paris-Sud, Université Evry, Université Paris-Saclay, Orsay, France. benoit.castandet@ips2.universite-paris-saclay.fr.; Institute of Plant Sciences Paris-Saclay IPS2, Paris Diderot, Sorbonne Paris-Cité, Orsay, France. benoit.castandet@ips2.universite-paris-saclay.fr. |
| Abstrakt: |
Since its first use in plants in 2007, high-throughput RNA sequencing (RNA-Seq) has generated a vast amount of data for both model and nonmodel species. Organellar transcriptomes, however, are virtually always overlooked at the data analysis step. We therefore developed ChloroSeq, a bioinformatic pipeline aimed at facilitating the systematic analysis of chloroplast RNA metabolism, and we provide here a step-by-step user's manual. Following the alignment of quality-controlled data to the genome of interest, ChloroSeq measures genome expression level along with splicing and RNA editing efficiencies. When used in combination with the Tuxedo suite (TopHat and Cufflinks), ChloroSeq allows the simultaneous analysis of organellar and nuclear transcriptomes, opening the way to a better understanding of nucleus-organelle cross talk. We also describe the use of R commands to produce publication-quality figures based on ChloroSeq outputs. The effectiveness of the pipeline is illustrated through analysis of an RNA-Seq dataset covering the transition from growth to maturation to senescence of Arabidopsis thaliana leaves. |
