Evidence map›Paper›PMID 26248983›Full record

ArticleG3 (Bethesda, Md.)2015

GC-Content of Synonymous Codons Profoundly Influences Amino Acid Usage.

Jing Li, Jun Zhou, Ying Wu, Sihai Yang, Dacheng Tian

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Article
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  3. Methanogenic archaea encoding Pyrrolysine maintain ambiguous amber codon usage.Proceedings of the National Academy of Sciences of the United States of America · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jing LiState Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210093, China Institute for Research on Cancer and Aging, Nice (IRCAN), Nice, France.
Jun ZhouDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts dtian@nju.edu.cn jzhou@oeb.harvard.edu.
Ying WuState Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210093, China Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.
Sihai YangState Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210093, China.
Dacheng TianState Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210093, China dtian@nju.edu.cn jzhou@oeb.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amino acids typically are encoded by multiple synonymous codons that are not used with the same frequency. Codon usage bias has drawn considerable attention, and several explanations have been offered, including variation in GC-content between species. Focusing on a simple parameter-combined GC proportion of all the synonymous codons for a particular amino acid, termed GCsyn-we try to deepen our understanding of the relationship between GC-content and amino acid/codon usage in more details. We analyzed 65 widely distributed representative species and found a close association between GCsyn, GC-content, and amino acids usage. The overall usages of the four amino acids with the greatest GCsyn and the five amino acids with the lowest GCsyn both vary with the regional GC-content, whereas the usage of the remaining 11 amino acids with intermediate GCsyn is less variable. More interesting, we discovered that codon usage frequencies are nearly constant in regions with similar GC-content. We further quantified the effects of regional GC-content variation (low to high) on amino acid usage and found that GC-content determines the usage variation of amino acids, especially those with extremely high GCsyn, which accounts for 76.7% of the changed GC-content for those regions. Our results suggest that GCsyn correlates with GC-content and has impact on codon/amino acid usage. These findings suggest a novel approach to understanding the role of codon and amino acid usage in shaping genomic architecture and evolutionary patterns of organisms.

Indexed as

Amino AcidsBase CompositionCodonComputational BiologyDatabases, GeneticGenomicsAmino AcidsCodonamino acid usagecodon usageGC-contentsynonymous codon

Identifiers

PMID26248983
PMCPMC4592985

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.