부산대학교 도서관

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level. Synopsis: A diallel hybrid panel from diverse parental natural yeast isolates is used to investigate the effects of low- frequency single nucleotide polymorphisms (SNPs) and structural variants (SVs) on gene expression variation in a population. The impact of low-frequency and structural variants is assessed using a diallel panel. Diallel SVs are fully cataloged using long-read sequencing and combined parental types. SVs contribute less than SNPs to expression variation and exhibit lower effect size. Low-frequency variants are overrepresented in associations compared to common ones. A diallel hybrid panel from diverse parental natural yeast isolates is used to investigate the effects of low- frequency single nucleotide polymorphisms (SNPs) and structural variants (SVs) on gene expression variation in a population. [ABSTRACT FROM AUTHOR]