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Identifying Mutations by High Resolution Melting in a TILLING Population of Rice
Published on: September 2, 2019
Computational identification and sequence analysis of stop codon readthrough genes in Oryza sativa
1Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310029, China.
Abstract:
Using an approach based on the Readthrough Candidate Extraction System (RCES), we extracted 111 candidates from 9620 gene sequences of rice. The results of homology search and sequence analysis demonstrated that these candidates included actual readthrough genes that would be important for further investigating the mechanism of translation termination regulated by readthrough event, and could also give some useful clues for functional genome annotation. Between the candidates and non-candidates of gene sequences in rice, there exist significant base biases at the positions surrounding the stop codons. These positions, especially both -1 and +4, are referred to as part of an extended stop signal. In candidates, G at position -1, and G or C at position +4 are much more favored than that in non-candidates. Both stop sequence patterns, GUAGC and GUGAG, might drive high readthrough efficiency in rice. Secondary structure analysis revealed that the -1 and +1 amino acids around the first stop codon of candidates have a strong bias toward arginine, particularly the +1 position (20.7%), which indicated that the amino acids at the readthrough region being frequently located in the hydrophilic region of beta-turn might be a determinant for efficient translation termination or not.
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