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Related Experiment Video

Updated: May 30, 2026

Microarray Analysis for Saccharomyces cerevisiae
13:17

Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

Mining for genotype-phenotype relations in Saccharomyces using partial least squares.

Tahir Mehmood1, Harald Martens, Solve Saebø

  • 1Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no

BMC Bioinformatics
|August 5, 2011
PubMed
Summary

A new multivariate method using BLAST and Soft-Thresholding Partial Least Squares (ST-PLS) reveals that few genes drive genotype-phenotype relationships in yeast. These key genes evolve rapidly and are crucial for adaptation.

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Last Updated: May 30, 2026

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Published on: August 12, 2019

Area of Science:

  • Genomics
  • Systems Biology
  • Evolutionary Biology

Background:

  • Multivariate approaches offer advantages over univariate analysis in diverse fields.
  • Genome-wide association studies (GWAS) often overlook multivariate genotype-phenotype relationships.
  • Existing methods require enhancement for comprehensive genotype-phenotype analysis.

Purpose of the Study:

  • To introduce a novel methodology for mapping genotype-phenotype relations.
  • To leverage BLAST for genomic sequence information extraction.
  • To employ Soft-Thresholding Partial Least Squares (ST-PLS) for multivariate analysis.

Main Methods:

  • A BLAST-based approach for genomic data mining.
  • Soft-Thresholding Partial Least Squares (ST-PLS) for genotype-phenotype mapping.
  • Application to the model yeast Saccharomyces cerevisiae.

Main Results:

  • A small fraction of genes (<1%) explains a large proportion of phenotypic variation.
  • Phenotype-influencing genes exhibit 20% faster evolution than non-influential genes.
  • Enrichment of these genes in cellular respiration, transposition, and known variations (paralogs, stop codon, copy number).

Conclusions:

  • The multivariate approach aligns with yeast phylogeny and gene ontology.
  • The methodology successfully identifies fast-evolving genes crucial for yeast phylogeny.
  • Further research is recommended to refine computational aspects and variable selection within the PLS framework.