Genome-wide prediction of stop codon readthrough during translation in the yeast Saccharomyces cerevisiae
Author(s) -
Ifor Williams
Publication year - 2004
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkh1004
Subject(s) - stop codon , open reading frame , biology , genetics , codon usage bias , context (archaeology) , orfs , saccharomyces cerevisiae , start codon , genome , translation (biology) , release factor , transfer rna , nucleotide , gene , messenger rna , peptide sequence , rna , paleontology
In-frame stop codons normally signal termination during mRNA translation, but they can be read as 'sense' (readthrough) depending on their context, comprising the 6 nt preceding and following the stop codon. To identify novel contexts directing readthrough, under-represented 5' and 3' stop codon contexts from Saccharomyces cerevisiae were identified by genome-wide survey in silico. In contrast with the nucleotide bias 3' of the stop codon, codon bias in the two codon positions 5' of the termination codon showed no correlation with known effects on stop codon readthrough. However, individually, poor 5' and 3' context elements were equally as effective in promoting stop codon readthrough in vivo, readthrough which in both cases responded identically to changes in release factor concentration. A novel method analysing specific nucleotide combinations in the 3' context region revealed positions +1,2,3,5 and +1,2,3,6 after the stop codon were most predictive of termination efficiency. Downstream of yeast open reading frames (ORFs), further in-frame stop codons were significantly over-represented at the +1, +2 and +3 codon positions after the ORF, acting to limit readthrough. Thus selection against stop codon readthrough is a dominant force acting on 3', but not on 5', nucleotides, with detectable selection on nucleotides as far downstream as +6 nucleotides. The approaches described can be employed to define potential readthrough contexts for any genome.
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