Genomic factors shaping codon usage across the Saccharomycotina subphylum.

Codon Codon Usage Bias Machine-learning Saccharomycotina tRNA

Journal

G3 (Bethesda, Md.)
ISSN: 2160-1836
Titre abrégé: G3 (Bethesda)
Pays: England
ID NLM: 101566598

Informations de publication

Date de publication:
30 Aug 2024
Historique:
received: 13 06 2024
revised: 15 08 2024
accepted: 30 08 2024
medline: 31 8 2024
pubmed: 31 8 2024
entrez: 30 8 2024
Statut: aheadofprint

Résumé

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. We characterized codon usage across 1,154 strains from 1,051 species from the fungal subphylum Saccharomycotina to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns. We found a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is distinct between the 12 orders to such a degree that yeasts can be classified with an accuracy greater than 90% using a machine-learning algorithm. We also characterized the degree to which codon usage bias is impacted by translational selection. We found it was influenced by a combination of features, including the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that avoidance of the CGN codons is associated with a decline in arginine tRNA function. Consistent with previous findings, codon usage bias within the Saccharomycotina is shaped by genomic features and GC bias. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

Identifiants

pubmed: 39213398
pii: 7746026
doi: 10.1093/g3journal/jkae207
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.

Auteurs

Bryan Zavala (B)

Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, Kannapolis NC 28223, USA; U.S. Food and Drug Administration, Center for Biologics Evaluation and Research, Office of Vaccines Research and Review, Division of Bacterial Parasitic and Allergenic Products, Lab of Mucosal Pathogens and Cellular Immunology, Silver Spring MD 20993, USA.

Lauren Dineen (L)

Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, Kannapolis, NC 28081, USA.

Kaitlin J Fisher (KJ)

Department of Biological Sciences, SUNY Oswego, Oswego, NY 13126, USA; Laboratory of Genetics, Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53726, USA.

Dana A Opulente (DA)

Biology Department, Villianova University, Villanova, PA 19085, USA; Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53726, USA.

Marie-Claire Harrison (MC)

Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA.

John F Wolters (JF)

Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53726, USA.

Xing-Xing Shen (XX)

Institute of Insect Sciences and Centre for Evolutionary and Organismal Biology, Zhejiang University, Hangzhou 310058, China.

Xiaofan Zhou (X)

Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou 510642, China.

Marizeth Groenewald (M)

Westerdijk Fungal Biodiversity Institute, 3584 CT Utrecht, The Netherlands.

Chris Todd Hittinger (CT)

Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53726, USA.

Antonis Rokas (A)

Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA.

Abigail Leavitt LaBella (AL)

Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, Kannapolis NC 28081, USA; Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC, 28233, USA.

Classifications MeSH