No abstract

Advanced-generation multiparent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than genome-wide association studies to detect rare variants and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from 18 genetically diverse founding strains. We carried out de novo assemblies of the genomes of the 18 founder strains, such that virtually all variation segregating between these strains is known, and represented those assemblies as Santa Cruz Genome Browser tracks. We discovered complex patterns of structural variation segregating among the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2. Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66 kb, demonstrating that the population is highly recombined. We pool-sequenced the two MPPs to 3270× and 2226× coverage and demonstrated that we can accurately estimate local haplotype frequencies using pooled data. We further downsampled the pool-sequenced data to ∼20–40× and showed that local haplotype frequency estimates remained accurate, with median error rates 0.8 and 0.6% at 20× and 40×, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that 10 or more founders are present at a detectable frequency for > 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

AbstractAdvanced generation multi-parent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than GWAS to detect rare variants, and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from eighteen genetically diverse founding strains. We carried out de novo assemblies of the genomes of the eighteen founder strains, such that virtually all variation segregating between these strains is known and represent those assemblies as Santa Cruz Genome Browser tracks. We discover complex patterns of structural variation segregating amongst the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2. Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66kb, demonstrating the population are highly recombined. We pool sequenced the two MPPs to 3270X and 2226X coverage and demonstrate that we can accurately estimate local haplotype frequencies using pooled data. We further down-sampled the poolseq data to ~20-40X and show that local haplotype frequency estimates remain accurate, with median error rate 0.8% and 0.6% at 20X and 40X, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that ten or more founders are present at a detectable frequency for over 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

Sixty‐four genomic loci and seven genes that contribute to heritable variation in a model quantitative trait—resistance to oxidative stress—are identified across three yeast strains. The high‐resolution understanding of this phenotype provides new insight into the genetic and molecular basis of quantitative traits.

Genetic heterogeneity occurs when individuals express similar phenotypes as a result of different underlying mechanisms. Although such heterogeneity is known to be a potential source of unexplained heritability in genetic mapping studies, its prevalence and molecular basis are not fully understood. Here we show that substantial genetic heterogeneity underlies a model phenotype-the ability to grow invasively-in a cross of two Saccharomyces cerevisiae strains. The heterogeneous basis of this trait across genotypes and environments makes it difficult to detect causal loci with standard genetic mapping techniques. However, using selective genotyping in the original cross, as well as in targeted backcrosses, we detected four loci that contribute to differences in the ability to grow invasively. Identification of causal genes at these loci suggests that they act by changing the underlying regulatory architecture of invasion. We verified this point by deleting many of the known transcriptional activators of invasion, as well as the gene encoding the cell surface protein Flo11 from five relevant segregants and showing that these individuals differ in the genes they require for invasion. Our work illustrates the extensive genetic heterogeneity that can underlie a trait and suggests that regulatory rewiring is a basic mechanism that gives rise to this heterogeneity.KEYWORDS complex traits; genetic mapping; invasive growth; regulatory networks; yeast G ENETIC studies in humans and model organisms have reported unexplained heritability for many traits (Manolio et al. 2009). A possible contributor to this "missing" heritability is genetic heterogeneity-individuals exhibiting similar phenotypes owing to different genetic and molecular mechanisms (Risch 2000;McClellan and King 2010;Wray and Maier 2014). Genetic heterogeneity can reduce the statistical power of mapping studies (Manchia et al. 2013;Wray and Maier 2014) and may involve multiple variants segregating in the same gene (allelic heterogeneity) or different genes (nonallelic heterogeneity) (Risch 2000). Work to date has shown that allelic heterogeneity is widespread (e.g., McClellan and King 2010;Ehrenreich et al. 2012;Long et al. 2014) and often involves two or more null or partial loss-of-function variants segregating in a single phenotypically important gene (e.g., Nogee et al. 2000;Sutcliffe et al. 2005;Will et al. 2010). However, the prominence and underlying mechanisms of nonallelic heterogeneity are less understood.In this paper we describe an example of nonallelic heterogeneity using heritable variation in the ability of Saccharomyces cerevisiae strains to undergo haploid invasive growth as our model. Invasive growth is a phenotype that is triggered by low carbon or nitrogen availability and is thought to be an adaptive response that allows yeast cells to adhere to and penetrate surfaces (Cullen and Sprague 2000). Invasion typically requires expression of FLO11, which encodes a cell surface glycoprotein that facilitates cell-cell and cell-surface adhes...