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Updated: May 5, 2026

Microarray Analysis for Saccharomyces cerevisiae

Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

Refining the resolution of the yeast genotype-phenotype map using single-cell RNA-sequencing.

Arnaud N'Guessan¹, Wen Yuan Tong², Hamed Heydari^3,4

¹Department of Cell and Systems Biology, University of Toronto, Ramsay Wright Laboratories, Toronto, Canada.

|July 28, 2025

Summary

This summary is machine-generated.

This study uses large-scale single-cell RNA sequencing to map gene expression variations to traits in yeast. It reveals new insights into gene regulation and trait variation, highlighting the significant role of trans-regulation.

Keywords:

S. cerevisiae evolutionary biology genetics genomics genotype–phenotype map single-cell RNA sequencing transcriptome

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Microarray Analysis for Saccharomyces cerevisiae

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Published on: April 7, 2011

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

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High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing

High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing

Published on: May 21, 2020

Area of Science:

Genetics
Molecular Biology
Systems Biology

Background:

Genotype-phenotype mapping (GPM) traditionally struggles with dataset scale and transcriptome data integration.
Existing methods offer limited understanding of how selection modulates transcriptomes and the roles of cis- vs. trans-regulatory elements.

Purpose of the Study:

To overcome limitations in traditional GPM by leveraging single-cell RNA sequencing (scRNA-seq) for large-scale analysis.
To identify single-cell expression quantitative trait loci (eQTL) and map transcriptome variation to fitness variation in yeast.
To elucidate the relative importance of cis- and trans-regulation in trait variation.

Main Methods:

Collected scRNA-seq data from 18,233 yeast cells across 4489 F2 segregants.
Performed eQTL mapping on scRNA-seq data to identify single-cell eQTL.
Inferred fitness variation from segregant bulk fitness assays and associated it with transcriptome variation.

Main Results:

Successfully recapitulated established GPM findings from yeast bulk assays at an unprecedented scale.
Revealed novel associations between phenotypic and transcriptomic variations, identifying new regulatory hotspots.
Demonstrated a larger aggregate effect of trans-regulation compared to cis-regulation on trait variation.
Identified new gene functions with high expression heritability.

Conclusions:

Integrating large-scale scRNA-seq data significantly enhances GPM by providing a high-resolution view of transcriptomic regulation.
The study underscores the substantial contribution of trans-regulatory elements to phenotypic variation.
Findings pave the way for deeper understanding of the genetic basis of complex traits.