High-throughput functional analysis of natural variants in yeast

How natural variation affects phenotype is difficult to determine given our incomplete ability to deduce the functional impact of the polymorphisms detected in a population. Although current computational and experimental tools can predict and measure allele function, there has previously been no assay that does so in a high-throughput manner while also representing haplotypes derived from wild populations. Here, we present such an assay that measures the fitness of hundreds of natural alleles of a given gene without site-directed mutagenesis or DNA synthesis. With a large collection of diverse Saccharomyces cerevisiae natural isolates, we piloted this technique using the gene SUL1, which encodes a high-affinity sulfate permease that, at increased copy number, can improve the fitness of cells grown in sulfate-limited media. We cloned and barcoded all alleles from a collection of over 1000 natural isolates en masse and matched barcodes with their respective variants using PacBio long-read sequencing and a novel error-correction algorithm. We then transformed the reference S288C strain with this library and used barcode sequencing to track growth ability in sulfate limitation of lineages carrying each allele. We show that this approach allows us to measure the fitness conferred by each allele and stratify functional and nonfunctional alleles. Additionally, we pinpoint which polymorphisms in both coding and noncoding regions are detrimental to fitness or are of small effect and result in intermediate phenotypes. Integrating these results with a phylogenetic tree, we observe how often loss-of-function occurs and whether or not there is an evolutionary pattern to our observable phenotypic results. This approach is easily applicable to other genes. Our results complement classic genotype-phenotype mapping strategies and demonstrate a high-throughput approach for understanding the effects of polymorphisms across an entire species which can greatly propel future investigations into quantitative traits.

Differential paralog divergence modulates evolutionary outcomes in yeast

Evolutionary outcomes depend not only on the selective forces acting upon a species, but also on the genetic background. However, large timescales and uncertain historical selection pressures can make it difficult to discern such important background differences between species. Experimental evolution is one tool to compare evolutionary potential of known genotypes in a controlled environment. Here we utilized a highly reproducible evolutionary adaptation in Saccharomyces cerevisiae to investigate whether other yeast species would adopt similar evolutionary trajectories. We evolved populations of S. cerevisiae, S. paradoxus, S. mikatae, S. uvarum, and interspecific hybrids between S. uvarum and S. cerevisiae for ~200-500 generations in sulfate-limited continuous culture. Wild-type S. cerevisiae cultures invariably amplify the high affinity sulfate transporter gene, SUL1. However, while amplification of the SUL1 locus was detected in S. paradoxus and S. mikatae populations, S. uvarum cultures instead selected for amplification of the paralog, SUL2. We measured the relative fitness of strains bearing deletions and amplifications of both SUL genes from different species, confirming that, converse to S. cerevisiae, S. uvarum SUL2 contributes more to fitness in sulfate limitation than S. uvarum SUL1. By measuring the fitness and gene expression of chimeric promoter-ORF constructs, we were able to delineate the cause of this differential fitness effect primarily to the promoter of S. uvarum SUL1. Our data show evidence of differential sub-functionalization among the sulfur transporters across Saccharomyces species through recent changes in noncoding sequence. Furthermore, these results show a clear example of how such background differences due to paralog divergence can drive significant changes in evolutionary trajectories of eukaryotes.