Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts

Hittinger, Chris Todd

doi:10.6084/m9.figshare.c.6011956.v1

Title: Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts

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Abstract

Data accompanying Nalabothu et al. 2023 Molecular Biology and Evolution

Authors:

Hittinger, Chris Todd

GLBRC - University of Wisconsin

Publication Date:: Fri Jun 02 04:00:00 UTC 2023

DOE Contract Number:: SC0018409

Research Org.:: Great Lakes Bioenergy Research Center (GLBRC), Madison, WI (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject::  genome evolution;  metabolic evolution;  xylose;  yeasts; codon optimization

OSTI Identifier:: 3003547

DOI:: https://doi.org/10.6084/m9.figshare.c.6011956.v1

Citation Formats


                    Hittinger, Chris Todd. Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts.  United States: N. p., 2023. 
        Web.  doi:10.6084/m9.figshare.c.6011956.v1.

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                    Hittinger, Chris Todd. Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts.  United States.  doi:https://doi.org/10.6084/m9.figshare.c.6011956.v1

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                    Hittinger, Chris Todd. 2023.  
"Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts".  United States.  doi:https://doi.org/10.6084/m9.figshare.c.6011956.v1.  https://www.osti.gov/servlets/purl/3003547. Pub date:Fri Jun 02 04:00:00 UTC 2023

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@article{osti_3003547,

  title        = {Codon optimization improves the prediction of xylose metabolism from gene content in budding yeasts},

  author       = {Hittinger, Chris Todd},

  abstractNote = {Data accompanying Nalabothu et al. 2023 Molecular Biology and Evolution},

  doi          = {10.6084/m9.figshare.c.6011956.v1},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Jun 02 04:00:00 UTC 2023},

  month        = {Fri Jun 02 04:00:00 UTC 2023}

}

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DOI: https://doi.org/10.6084/m9.figshare.c.6011956.v1

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Codon Optimization Improves the Prediction of Xylose Metabolism from Gene Content in Budding Yeasts

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Xylose is the second most abundant monomeric sugar in plant biomass. Consequently, xylose catabolism is an ecologically important trait for saprotrophic organisms, as well as a fundamentally important trait for industries that hope to convert plant mass to renewable fuels and other bioproducts using microbial metabolism. Although common across fungi, xylose catabolism is rare within Saccharomycotina, the subphylum that contains most industrially relevant fermentative yeast species. The genomes of several yeasts unable to consume xylose have been previously reported to contain the full set of genes in the XYL pathway, suggesting the absence of a gene–trait correlation for xylose metabolism.more »« less
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Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. Wemore »« less
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