Analysis of chromosomes and nucleotides in rice to predict gene expression through codon usage pattern

Amino acids are essential measurements for the potential growth stage because of connecting to protein structures and functions. The objective of this paper was to analyze chromosomes feature at plastid region of rice represented by nucleotide, synonymous codon, and amino acid usage to predict gene...

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Bibliographic Details
Main Author: Meshal M. Almutairi
Format: Article
Language:English
Published: Elsevier 2021-08-01
Series:Saudi Journal of Biological Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1319562X2100334X
Description
Summary:Amino acids are essential measurements for the potential growth stage because of connecting to protein structures and functions. The objective of this paper was to analyze chromosomes feature at plastid region of rice represented by nucleotide, synonymous codon, and amino acid usage to predict gene expression through codon usage pattern. The results showed that the values of the codon adaption index ranged from 0.733 in chromosome 9 to 0.631 in chromosome 8 with full length of these two chromosomes were 3738 and 1635 respectively. The higher value of guanine and cytosine content was 60% in chromosomes 9 while the lower values was 37% in chromosomes 11. Eight chromosomes (ch1, ch2, ch3, ch5, ch7, ch8, ch10, and ch12) were greater value of modified relative codon bias than threshold (threshold: 0.66) especially in cysteine for ch1, ch2, ch5, ch10, and ch12. While other remaining chromosomes were less than the threshold. Relative synonymous codon usage found that the over-represented of amino acids were asparagine, aspartate, cysteine, glutamate, and phenylalanine across all 12 chromosomes. These results would establish a platform for more and further projects concerning rice breeding and genetics and codon optimization in the amino acids for developing varieties. These results also will help breeders to select desirable genes through the genome for improve target traits.
ISSN:1319-562X