Selection on Synonymous Sites for Increased Accessibility around miRNA Binding Sites in Plants
Author(s) -
Wanjun Gu,
Xiaofei Wang,
Chuanying Zhai,
Xueying Xie,
Tong Zhou
Publication year - 2012
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/mss109
Subject(s) - biology , codon usage bias , gene , genetics , microrna , genome , synonymous substitution , natural selection , computational biology , function (biology) , negative selection , gc content , selection (genetic algorithm) , evolutionary biology , artificial intelligence , computer science
Synonymous codons are widely selected for various biological mechanisms in both prokaryotes and eukaryotes. Recent evidence suggests that microRNA (miRNA) function may affect synonymous codon choices near miRNA target sites. To better understand this, we perform genome-wide analysis on synonymous codon usage around miRNA target sites in four plant genomes. We observed a general trend of increased site accessibility around miRNA target sites in plants. Guanine-cytosine (GC)-poor codons are preferred in the flank region of miRNA target sites. Within-genome analyses show significant variation among miRNA targets in species. GC content of the target gene can partly explain the variation of site accessibility among miRNA targets. miRNA targets in GC-rich genes show stronger selection signals than those in GC-poor genes. Gene's codon usage bias and the conservation level of miRNA and its target also have some effects on site accessibility, but the expression level of miRNA or its target and the mechanism of miRNA activity do not contribute to site accessibility differences among miRNA targets. We suggest that synonymous codons near miRNA targets are selected for efficient miRNA binding and proper miRNA function. Our results present a new dimension of natural selection on synonymous codons near miRNA target sites in plants, which will have important implications of coding sequence evolution.
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