Biology subjects

Yeh, C.-L. C.

Publications and source records attributed to Yeh, C.-L. C..

2 recordsLinked to original sources

bioRxiv2021

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.

genetics↗

bioRxiv2020

Multiplexing Mutation Rate Assessment: Determining Pathogenicity of Msh2 Variants in S. cerevisiae

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway (MMR). Loss-of-function (LOF) mutations in MSH2 are associated with hereditary non-polyposis colorectal cancer (HNPCC), an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbruck fluctuation tests using a collection of published MSH2 variants. Our pooled screen successfully identified previously-characterized non-functional alleles as high mutators. We then created an additional 185 human variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVars classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the rate of antibiotic resistance emergence.

genetics↗