Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Abstract

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs inSaccharomyces cerevisiaeby single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the geneGPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

Adaptive Mating Among Natural Strains ofS. cerevisiae

“…Recently, it was shown that a single point mutation in the GPA1 gene (W82R) reduces fitness and induces a higher mating efficiency [50]. We found that 6 Mata strains (YAB1, YCH1, YCH2, AST1, CGL1, CPK1) and 1 Matα (AST) strain from our collection have this mutation.…”

“…In conditions where cell size is crucial for cell fitness, haploid cells tend to choose partners whose cell size aligns more closely with the optimal size for fitness in that particular condition [24]. A recent study by Boocock et al [50] showed that a single point mutation that changes a tryptophan to arginine in the GPA1 gene reduces fitness of the strains, but increases their mating efficiency. Moreover, this mutation was also associated with increased outbreeding tendency of natural strains.…”

Expression quantitative trait locus mapping in recombinant gametes using single nucleus RNA sequencing

“…Furthermore, eQTL mapping with snRNA-seq is also possible in F2 populations, provided sufficiently high numbers of individuals are used as input. This has been demonstrated in Caenorhabditis elegans (Ben-David et al, 2021) and Saccharyomyces cerevisiae (Boocock et al, 2023) using highly recombined F4 populations, opening up the possibility of mapping eQTLs using only single cell RNA-seq in cell-types other than haploid gametes. Furthermore, other single cell sequencing modalities, such as assay for accessible chromatin (ATAC) sequencing or DNA methylation sequencing (Heumos et al, 2023) also provide molecular phenotypes which could then be linked to haplotype information.…”

“…However, all cells derived from the same individual share the same genotype, meaning that the resolution and power of the eQTL analysis is limited to the number of individuals used in the pool, rather than the number of cells in the dataset. The use of cell populations with greater genetic heterogeneity, such as recombinant haplotypes in gametes, or large populations of segregants (Ben-David et al, 2021;Boocock et al, 2023), would therefore greatly improve the resolution of eQTL-mapping analysis with single-cell sequencing.…”

The rise of single‐cell transcriptomics in yeast

“…scRNA-seq can be used to recognize natural genetic variations allowing simultaneous genotyping and the acquisition of gene expression. This method has been recently reported as a preprint at the time of writing for S. cerevisiae to investigate allele-specific transcriptional heterogeneity and the complex interaction between eQTL and cell cycle phases (Boocock et al, 2023).…”