Open AccessCorrelation between gene expression levels under drought stress and synonymous codon usage in rice plant by in-silico study
Author(s) -
Fatemeh Chamani Mohasses,
Mahmood Solouki,
Behzad Ghareyazie,
Leila Fahmideh,
M Mohsenpour
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0237334
Subject(s) - in silico , biology , gene , genetics , codon usage bias , gene expression , correlation , computational biology , evolutionary biology , bioinformatics , genome , mathematics , geometry
We studied the correlation of synonymous codon usage (SCU) on gene expression levels under drought stress in rice. Sixty genes related to drought stress (with high, intermediate and low expression) were selected from rice meta-analysis data and various codon usage indices such as the effective number of codon usage (ENC), codon adaptation index (CAI) and relative synonymous codon usage (RSCU) were calculated. We found that in genes highly expressing under drought 1) GC content was higher, 2) ENC value was lower, 3) the preferred codons of some amino acids changed and 4) the RSCU ratio of GC-end codons relative to AT-end codons for 18 amino acids increased significantly compared with those in other genes. We introduce ARSCU as the A verage ratio of RSCU s of GC-end codons to AT-end codons in each gene that could significantly separate high-expression genes under drought from low-expression genes. ARSCU is calculated using the program ARSCU-Calculator developed by our group to help predicting expression level of rice genes under drought. An index above ARSCU threshold is expected to indicate that the gene under study may belong to the “high expression group under drought”. This information may be applied for codon optimization of genes for rice genetic engineering. To validate these findings, we further used 60 other genes (randomly selected subset of 43233 genes studied for their response to drought stress). ARSCU value was able to predict the level of expression at 88.33% of the cases. Using third set of 60 genes selected amongst high expressing genes not related to drought, only 31.65% of the genes showed ARSCU value of higher than the set threshold. This indicates that the phenomenon we described in this report may be unique for drought related genes. To justify the observed correlation between CUB and high expressing genes under drought, possible role of tRNA post transcriptional modification and tRFs was hypothesized as possible underlying biological mechanism.