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Kruglyak, L.

Publications and source records attributed to Kruglyak, L..

27 records · Page 2Linked to original sources

Screening human embryos for polygenic traits has limited utility

Genome-wide association studies have led to the development of polygenic score (PS) predictors that explain increasing proportions of the variance in human complex traits. In parallel, progress in preimplantation genetic testing now allows genome-wide genotyping of embryos generated via in vitro fertilization (IVF). Jointly, these developments suggest the possibility of screening embryos for polygenic traits such as height or cognitive function. There are clear ethical, legal, and societal concerns regarding such a procedure, but these cannot be properly discussed in the absence of data on the expected outcomes of screening. Here, we use theory, simulations, and real data to evaluate the potential gain of PS-based embryo selection, defined as the expected difference in trait value between the top-scoring embryo and an average, unselected embryo. We observe that the gain increases very slowly with the number of embryos, but more rapidly with increased variance explained by the PS. Given currently available polygenic predictors and typical IVF yields, the average gain due to selection would be {approx}2.5cm if selecting for height, and {approx}2.5 IQ (intelligence quotient) points if selecting for cognitive function. These mean values are accompanied by wide confidence intervals; in real data drawn from nuclear families with up to 20 offspring each, we observe that the offspring with the highest PS for height was the tallest only in 25% of the families. We discuss prospects and limitations of PS-based embryo selection for the foreseeable future.

genetics↗

Rare variants contribute disproportionately to quantitative trait variation in yeast

A detailed understanding of the sources of heritable variation is a central goal of modern genetics. Genome-wide association studies (GWAS) in humans1 have implicated tens of thousands of DNA sequence variants in disease risk and quantitative trait variation, but these variants fail to account for the entire heritability of diseases and traits. GWAS have by design focused on common DNA sequence variants; however, recent studies underscore the likely importance of the contribution of rare variants to heritable variation2. Further, finding the genes that underlie the GWAS signals remains a major challenge. Here, we use a unique model system to disentangle the contributions of common and rare variants to a large number of quantitative traits. We generated large crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) that explain most of the heritable variation in 38 traits. We combined our results with sequencing data for 1,011 yeast isolates3 to decouple variant effect size estimation from allele frequency and showed that rare variants make a disproportionate contribution to trait variation as a consequence of their larger effect sizes. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, that such variants are more likely to decrease fitness, and that negative selection has shaped the relationship between variant frequency and effect size. Finally, we leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.

genetics↗

Fast genetic mapping of complex traits in C. elegans using millions of individuals in bulk

Genetic studies of complex traits in animals have been hindered by the need to generate, maintain, and phenotype large panels of recombinant lines. We developed a new method, C. elegans eXtreme Quantitative Trait Locus (ceX-QTL) mapping, that overcomes this obstacle via bulk selection on millions of unique recombinant individuals. We used ceX-QTL to map a drug resistance locus with high resolution. We also mapped differences in gene expression in live worms and discovered a regulatory feedback loop that responds to changes in HSP-90 chaperone activity. Lastly, we used ceX-QTL to map loci that influence fitness and discovered that one such locus is caused by a deletion in a highly conserved chromatin reader in the N2 reference strain. ceX-QTL is fast, powerful and cost-effective, and will accelerate the study of complex traits in animals.

genetics↗

The genetic basis of mutation rate variation in yeast

Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis of these differences. Here we leveraged the power of the yeast Saccharomyces cerevisiae as a model system to uncover natural genetic variants that underlie variation in mutation rate. We developed a high-throughput fluctuation assay and used it to quantify mutation rates in natural yeast isolates and in 1040 segregant progeny from a cross between BY, a lab strain, and RM, a wine strain. We observed that mutation rate varies among yeast strains and is highly heritable (H2=0.46). We performed linkage mapping in the segregants and identified four quantitative trait loci (QTLs) underlying mutation rate variation in the cross. We fine-mapped two QTLs to the underlying causal genes, RAD5 and MKT1, that contribute to mutation rate variation. These genes also underlie sensitivity to the DNA damaging agents 4NQO and MMS, suggesting a connection between spontaneous mutation rate and mutagen sensitivity.

genetics↗

Analysis of the genetic basis of height in large Jewish nuclear families

Despite intensive study, most genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. We identified loci that together explain an estimated 6% of the variance in height. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population.

genetics↗

Genetics of trans-regulatory variation in gene expression

Heritable variation in gene expression provides a critical bridge between differences in genome sequence and the biology of many traits, including common human diseases. However, the sources of most regulatory genetic variation remain unknown. Here, we used transcriptome profiling in 1,012 yeast segregants to map the genetic basis of variation in gene expression with high statistical power. We identified expression quantitative trait loci (eQTL) that together account for over 70% of the total genetic contribution to variation in mRNA levels, allowing us to examine the sources of regulatory variation comprehensively. We found that variation in the expression of a typical gene has a complex genetic architecture involving multiple eQTL. We also detected hundreds of eQTL pairs with significant non-additive interactions in an unbiased genome-wide scan. Although most genes were influenced by a local eQTL located close to the gene, most expression variation arose from distant, trans-acting eQTL located far from their target genes. Nearly all distant eQTL clustered at 102 \"hotspot\" locations, some of which influenced the expression of thousands of genes. Hotspot regions were enriched for transcription factor genes and altered expression of their target genes though both direct and indirect mechanisms. Many local eQTL had no detectable effects on the expression of other genes in trans. These results reveal the complexity of genetic influences on transcriptome variation in unprecedented depth and detail.

genetics↗

Highly parallel genome variant engineering with CRISPR/Cas9 in eukaryotic cells

Direct measurement of functional effects of DNA sequence variants throughout a genome is a major challenge. We developed a method that uses CRISPR/Cas9 to engineer many specific variants of interest in parallel in the budding yeast Saccharomyces cerevisiae, and to screen them for functional effects. We used the method to examine the functional consequences of premature termination codons (PTCs) at different locations within all annotated essential genes in yeast. We found that most PTCs were highly deleterious unless they occurred close to the C-terminal end and did not interrupt an annotated protein domain. Surprisingly, we discovered that some putatively essential genes are dispensable, while others have large dispensable regions. This approach can be used to profile the effects of large classes of variants in a high-throughput manner.

genomics↗

Genetic Variation In Adaptability And Pleiotropy In Budding Yeast

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

evolutionary biology↗

A maternal-effect genetic incompatibility in Caenorhabditis elegans

Selfish genetic elements spread in natural populations and have an important role in genome evolution. We discovered a selfish element causing a genetic incompatibility between strains of the nematode Caenorhabditis elegans. The element is made up of sup-35, a maternal-effect toxin that kills developing embryos, and pha-1, its zygotically expressed antidote. pha-1 has long been considered essential for pharynx development based on its mutant phenotype, but this phenotype in fact arises from a loss of suppression of sup-35 toxicity. Inactive copies of the sup-35/pha-1 element show high sequence divergence from active copies, and phylogenetic reconstruction suggests that they represent ancestral stages in the evolution of the element. Our results suggest that other essential genes identified by genetic screens may turn out to be components of selfish elements.

evolutionary biology↗