Leonid Kruglyak, Ph.D. - US grants

The goals of this project are to develop improved quantitative methods for analysis of genetic data gathered in family and population studies of complex diseases, and to implement these methods in easy to use computer programs. Such methods are required to unravel the complex genetic basis of common diseases. New methods will be developed for the following tasks: Faster and more memory-efficient multi-point analysis of both qualitative and quantitative traits in arbitrarily large and complex pedigrees;Testing haplotypes for association with disease;Multipoint linkage disequilibrium analysis; SNP-based association studies. New technologies are allowing collection of increasingly large amounts of polymorphism data on common disease samples drawn from both families and populations. The new methods developed for this project will enable efficient use of these data, and will improve researchers'ability to detect true genetic effects on disease susceptibility and to distinguish them from statistical noise. The computer programs will be freely distributed to the broader research community to ensure that the methods are widely and readily applied to real-world problems.

DESCRIPTION (provided by applicant): The broad objective of the proposed research is high-resolution genetic dissection of a large number of complex and quantitative traits in the nematode worm C. elegans. Success in understanding the genetic basis of phenotypic variation in a metazoan will provide critical guidance for the design of genotype- phenotype studies in humans and other organisms of medical, biological, and agricultural interest, as well as supply insights into regulatory networks that connect genetic and phenotypic variation and into the evolution of phenotypic variation. Specifically, we will develop and genotype a large set of high-resolution recombinant inbred lines (RILs) from a cross between Bristol and Hawaiian isolates, and genotype a diverse collection of wild isolates. We will then use microarrays to generate expression profiles for the RILs and wild isolates, and carry out linkage and association analysis to define loci that affect gene expression. We will identify individual loci as well as pairs of interacting loci. We will determine which loci affect expression through polymorphisms in the encoding gene or its nearby control regions, and which affect expression of genes at distant locations. We will identify "hot spots"-loci that affect the expression of many genes, and use bioinformatic approaches to integrate the results with regulatory networks. We will also assay behavioral and age-related phenotypes in the RILs, map loci that affect these phenotypes, and integrate these phenotypes with transcript data. Finally, we will identify the genes and polymorphisms that underlie several transcriptional, behavioral and age-related phenotypes and confirm their roles through transgenic and RNAi experiments. We have already successfully carried out similar studies in yeast, and expect that the results will be even richer in C. elegans, given its more complex regulation in the context of multicellularity and development. Relevance to public health: Genetic factors underlie susceptibility to virtually every human disease. Much of current biomedical research is based on the expectation that identifying these factors is a crucial step in improving diagnosis, prevention, and treatment. Identification is difficult because the genetic basis of common disorders is complex, with disease susceptibility influenced by multiple genes in interaction with each other and with environmental factors. The proposed research will improve our understanding of such interactions and will provide critical guidance for studies of the genetic basis of common human diseases.

DESCRIPTION (provided by applicant): The broad objective of the proposed research is the genetic dissection of a large number of complex and quantitative traits in the nematode worm and model organism C. elegans, with a focus on two classes of traits with relevance to human health: responses to pathogens and drugs. Success in understanding the genetic basis of phenotypic variation in a metazoan will provide critical guidance for the design of genotype-phenotype studies in humans and other organisms of medical, biological, and agricultural interest. The methods and resources developed will be broadly applicable to other phenotypes in C. elegans. The results will improve our understanding of the genes and pathways involved in susceptibility to pathogens, and in the mechanisms of action, resistance, and off-target effects of chemotherapeutics, anthelmintics, pesticides, and other compounds. Specifically, we will develop high-throughput quantitative phenotyping assays for these traits and apply them to genetic resources developed during the previous project period: a large set of high-resolution advanced intercross recombinant inbred lines from a cross between Bristol and Hawaii isolates, and a diverse collection of wild isolates extensively characterized for sequence variation. We will also apply these assays to new genetic resources that we will develop as part of the proposed research: we will build and genotype mapping populations from a maximally diverse subset of wild isolates. We will also develop new approaches for rapid identification of quantitative trait loci for any starting set of parent strains. We expect these efforts to produce:(i) a set of well-characterized diverse wild isolates and a broadly useful multiparent mapping population that will be shared with the C. elegans research community; (ii) new mapping methods applicable to C. elegans and other species; and (iii) a large set of loci for further investigation. We then propose to identify the genes and polymorphisms that underlie these loci, and to investigate the genetic architectures of the traits, including the population frequencies of the relevant alleles. We will confirm candidate genes and regions by using RNAi and transgenics to knock down or express genes in the appropriate strains. We will measure the frequencies of the identified alleles in the full diverse collection of wild isolates, and answer questions about rare vs. common alleles, additivity vs. dominance, and the role of genetic interactions. We expect to elucidate key principles of genetic architecture that will guide study design in C. elegans and other species. The pathways C. elegans uses to respond to biotic and abiotic stresses are conserved in humans and involved in a variety of diseases, including cancer and diabetes. Thus, we will leverage the power of the worm to better understand human biology.

DESCRIPTION (provided by applicant): PROJECT SUMMARY The broad objective of the proposed research is to achieve comprehensive dissection of the genetic basis of many complex phenotypes in the yeast S. cerevisiae, arguably the most powerful eukaryotic model system due to its small genome, ease of genetic manipulation, and the ability to generate very large sample sizes. Evolutionary conservation has also ensured that many yeast traits have direct parallels to biomedically important human phenotypes. We seek to answer many of the basic questions about the genetic architecture of complex traits, including the number of loci underlying a trait, the distribution of allelic effect sizes, the prevalence of genetic interactions, and the distribution f allele frequencies in a population. Success in answering these questions will provide critical guidance for the design of genotype-phenotype studies in humans and other organisms of medical, biological, and agricultural interest. Our proposal focuses on biomedically relevant traits, and will therefore allow us to leverage the power of yeast genetics to better understand human biology and disease. Specifically, will generate a mapping panel of 4000 individual segregants for the well-studied BYxRM cross, as well as panels of 1000 segregants for 20 other crosses, chosen with a modified round-robin design in which each of 20 strains will be crossed to two other strains. We will genotype these panels by very highly multiplexed low-coverage whole-genome sequencing. We will then phenotype the panels using colony growth assays probing an extensive space of cell physiology. We have developed high-throughput automated phenotyping assays that will enable us to measure growth of tens of thousands of strains in hundreds of conditions over the proposed project period. The growth conditions we propose to test include antifungals, chemotherapeutics, nutrient depletion, small molecules that target specific cellular processes, and treatments that have been shown to be yeast phenologs of disease-related human phenotypes. We will use these data to estimate broad-sense and narrow-sense heritability of each trait, carry out linkage analysis to detect loci with additive an epistatic effects, measure the distribution of effect sizes, and compute the fraction of heritabiliy explained by the detected loci. We will attempt to identify candidate genes and variants underlying the detected loci, and validate a subset of these with molecular genetics techniques such as allele replacements. We will select 10 highly heritable traits with substantial missing heritability, and use X-QTL to detect loci with smaller effects than possible with other approaches, and to improve the mapping resolution of already identified loci. We will examine the additive and interaction effect sizes of the new loci detected by X-QTL, build multiple-QTL models, and assess the fraction of heritability that can be explained by loci with effects as small as 0.1% of phenotypic variance. Quantitative trait genes and nucleotides we identify will also be resequenced across a large panel of diverse yeast strains in order to determine the relative contributions of common and rare polymorphisms to complex trait variation in yeast, as well as to examine the allelic complexity of functional variation in these genes. Our studies will provide a broad view of genetic architectures of many complex traits and a very deep understanding of a subset of traits. PUBLIC HEALTH RELEVANCE: NARRATIVE Relevance to public health: Genetic factors underlie susceptibility to virtually every human disease, and much of current biomedical research is based on the expectation that identifying these factors is a crucial step in improving diagnosis, prevention, and treatment. Identification is difficult because the genetic basis of common disorders is complex, with disease susceptibility influenced by multiple genes. The proposed research will improve our understanding of genetic complexity and provide critical guidance for studies of the genetic basis of common human diseases. The proposed research will also provide insights into the genetic basis of responses to drugs and stressful conditions.

PROJECT SUMMARY / ABSTRACT The broad objective of the proposed research is to achieve comprehensive dissection of the genetic basis of many complex phenotypes in the yeast S. cerevisiae, arguably the most powerful eukaryotic model system due to its small genome, ease of genetic manipulation, and the ability to generate very large sample sizes. Evolutionary conservation has also ensured that many yeast traits have direct parallels to biomedically important human phenotypes. We seek comprehensively identify the DNA sequence variants underlying a variety of traits, study the distribution of their effect sizes and their frequencies in a population, and build rules for predicting the functional effects of variants of unknown significance. Success in answering these questions will provide critical guidance for the design of genotype-phenotype studies in humans and other organisms of medical, biological, and agricultural interest, and enable improved diagnostic accuracy based on genome sequencing of patients. Specifically, will use a resource we built that consists of nearly 15,000 genotyped and phenotyped segregants from crosses between 16 diverse yeast strains to identify causal genes and prioritize individual putative causal genetic variants. We will then identify specific causal variants by directly engineering thousands of candidate variants in bulk. We will use methods we have developed for massively parallel targeted editing by CRISPR/Cas9 to engineer pools of yeast cells, each carrying one of 2000 natural variants. We will subject the edited pools of yeast cells to selective conditions and track the phenotypic consequences of the introduced variants over time by short read sequencing of DNA barcodes identifying each edit. We will then extend massively parallel targeted editing to generate all variants discovered in the panel of 16 diverse yeast strains. We will assay the effects of single nucleotide polymorphisms (SNPs), small scale insertions or deletions (indels), and haplotype effects of closely linked variants. We will include non-coding variants to better understand their effects on fitness. We will extend our engineering toolkit to employ versions of Cas9 and related enzymes that have different recognition sites, and by using Cas9-based ?base editors? that allow generation of specific classes of mutations. Ultimately, we will edit and measure the phenotypic consequences of hundreds of thousands of natural genetic variants, which will provide a deep understanding of the genetic basis of many traits and enable us to develop accurate algorithms that predict the functional effect of any genetic variant.