Journal Article

Retrogenes in Rice (<i>Oryza sativa</i> L. ssp. <i>japonica</i>) Exhibit Correlated Expression with Their Source Genes

Hiroaki Sakai, Hiroshi Mizuno, Yoshihiro Kawahara, Hironobu Wakimoto, Hiroshi Ikawa, Hiroyuki Kawahigashi, Hiroyuki Kanamori, Takashi Matsumoto, Takeshi Itoh and Brandon S. Gaut

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 1357-1368
Published in print January 2011 |
Published online October 2011 | e-ISSN: 1759-6653 | DOI: http://dx.doi.org/10.1093/gbe/evr111

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Gene duplication occurs by either DNA- or RNA-based processes; the latter duplicates single genes via retroposition of messenger RNA. The expression of a retroposed gene copy (retrocopy) is expected to be uncorrelated with its source gene because upstream promoter regions are usually not part of the retroposition process. In contrast, DNA-based duplication often encompasses both the coding and the intergenic (promoter) regions; hence, expression is often correlated, at least initially, between DNA-based duplicates. In this study, we identified 150 retrocopies in rice (Oryza sativa L. ssp japonica), most of which represent ancient retroposition events. We measured their expression from high-throughput RNA sequencing (RNAseq) data generated from seven tissues. At least 66% of the retrocopies were expressed but at lower levels than their source genes. However, the tissue specificity of retrogenes was similar to their source genes, and expression between retrocopies and source genes was correlated across tissues. The level of correlation was similar between RNA- and DNA-based duplicates, and they decreased over time at statistically indistinguishable rates. We extended these observations to previously identified retrocopies in Arabidopsis thaliana, suggesting they may be general features of the process of retention of plant retrogenes.

Keywords: retroposition; gene expression; gene duplication

Journal Article.  7431 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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