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Biomedical subjects

Leonid Kruglyak

Publications and source records attributed to Leonid Kruglyak.

At least 19 recordsLinked to original sources

Population genomic analysis of outcrossing and recombination in yeast.

The budding yeast Saccharomyces cerevisiae has been used by humans for millennia to make wine, beer and bread. More recently, it became a key model organism for studies of eukaryotic biology and for genomic analysis. However, relatively little is known about the natural lifestyle and population genetics of yeast. One major question is whether genetically diverse yeast strains mate and recombine in the wild. We developed a method to infer the evolutionary history of a species from genome sequences of multiple individuals and applied it to whole-genome sequence data from three strains of Saccharomyces cerevisiae and the sister species Saccharomyces paradoxus. We observed a pattern of sequence variation among yeast strains in which ancestral recombination events lead to a mosaic of segments with shared genealogy. Based on sequence divergence and the inferred median size of shared segments (approximately 2,000 bp), we estimated that although any two strains have undergone approximately 16 million cell divisions since their last common ancestor, only 314 outcrossing events have occurred during this time (roughly one every 50,000 divisions). Local correlations in polymorphism rates indicate that linkage disequilibrium in yeast should extend over kilobases. Our results provide the initial foundation for population studies of association between genotype and phenotype in S. cerevisiae.

Crosses, Genetic↗

Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome.

Significant interest has emerged in mapping genetic susceptibility for complex traits through whole-genome association studies. These studies rely on the extent of association, i.e., linkage disequilibrium (LD), between single nucleotide polymorphisms (SNPs) across the human genome. LD describes the nonrandom association between SNP pairs and can be used as a metric when designing maximally informative panels of SNPs for association studies in human populations. Using data from the 1.58 million SNPs genotyped by Perlegen, we explored the allele frequency dependence of the LD statistic r(2) both empirically and theoretically. We show that average r(2) values between SNPs unmatched for allele frequency are always limited to much less than 1 (theoretical approximately 0.46 to 0.57 for this dataset). Frequency matching of SNP pairs provides a more sensitive measure for assessing the average decay of LD and generates average r(2) values across nearly the entire informative range (from 0 to 0.89 through 0.95). Additionally, we analyzed the extent of perfect LD (r(2) = 1.0) using frequency-matched SNPs and found significant differences in the extent of LD in genic regions versus intergenic regions. The SNP pairs exhibiting perfect LD showed a significant bias for derived, nonancestral alleles, providing evidence for positive natural selection in the human genome.

Animals↗

Natural malaria infection in Anopheles gambiae is regulated by a single genomic control region.

We surveyed an Anopheles gambiae population in a West African malaria transmission zone for naturally occurring genetic loci that control mosquito infection with the human malaria parasite, Plasmodium falciparum. The strongest Plasmodium resistance loci cluster in a small region of chromosome 2L and each locus explains at least 89% of parasite-free mosquitoes in independent pedigrees. Together, the clustered loci form a genomic Plasmodium-resistance island that explains most of the genetic variation for malaria parasite infection of mosquitoes in nature. Among the candidate genes in this chromosome region, RNA interference knockdown assays confirm a role in Plasmodium resistance for Anopheles Plasmodium-responsive leucine-rich repeat 1 (APL1), encoding a leucine-rich repeat protein that is similar to molecules involved in natural pathogen resistance mechanisms in plants and mammals.

Alleles↗

Telomere length as a quantitative trait: genome-wide survey and genetic mapping of telomere length-control genes in yeast.

Telomere length-variation in deletion strains of Saccharomyces cerevisiae was used to identify genes and pathways that regulate telomere length. We found 72 genes that when deleted confer short telomeres, and 80 genes that confer long telomeres relative to those of wild-type yeast. Among identified genes, 88 have not been previously implicated in telomere length control. Genes that regulate telomere length span a variety of functions that can be broadly separated into telomerase-dependent and telomerase-independent pathways. We also found 39 genes that have an important role in telomere maintenance or cell proliferation in the absence of telomerase, including genes that participate in deoxyribonucleotide biosynthesis, sister chromatid cohesion, and vacuolar protein sorting. Given the large number of loci identified, we investigated telomere lengths in 13 wild yeast strains and found substantial natural variation in telomere length among the isolates. Furthermore, we crossed a wild isolate to a laboratory strain and analyzed telomere length in 122 progeny. Genome-wide linkage analysis among these segregants revealed two loci that account for 30%-35% of telomere length-variation between the strains. These findings support a general model of telomere length-variation in outbred populations that results from polymorphisms at a large number of loci. Furthermore, our results laid the foundation for studying genetic determinants of telomere length-variation and their roles in human disease.

Chromosome Mapping↗

Molecular genetics: DNA analysis of a putative dog clone.

In August 2005, Lee et al. reported the first cloning of a domestic dog from adult somatic cells. This putative dog clone was the result of somatic-cell nuclear transfer from a fibroblast cell of a three-year-old male Afghan hound into a donor oocyte provided by a dog of mixed breed. In light of recent concerns regarding the creation of cloned human cell lines from the same institution, we have undertaken an independent test to determine the validity of the claims made by Lee et al..

Afghanistan↗

Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray.

A central challenge of genomics is to detect, simply and inexpensively, all differences in sequence among the genomes of individual members of a species. We devised a system to detect all single-nucleotide differences between genomes with the use of data from a single hybridization to a whole-genome DNA microarray. This allowed us to detect a variety of spontaneous single-base pair substitutions, insertions, and deletions, and most (>90%) of the approximately 30,000 known single-nucleotide polymorphisms between two Saccharomyces cerevisiae strains. We applied this approach to elucidate the genetic basis of phenotypic variants and to identify the small number of single-base pair changes accumulated during experimental evolution of yeast.

Directed Molecular Evolution↗

Revealing complex traits with small molecules and naturally recombinant yeast strains.

Here we demonstrate that natural variants of the yeast Saccharomyces cerevisiae are a model system for the systematic study of complex traits, specifically the response to small molecules. As a complement to artificial knockout collections of S. cerevisiae widely used to study individual gene function, we used 314- and 1932-member libraries of mutant strains generated by meiotic recombination to study the cumulative, quantitative effects of natural mutations on phenotypes induced by 23 small-molecule perturbagens (SMPs). This approach reveals synthetic lethality between SMPs, and genetic mapping studies confirm the involvement of multiple quantitative trait loci in the response to two SMPs that affect respiratory processes. The systematic combination of natural variants of yeast and small molecules that modulate evolutionarily conserved cellular processes can enable a better understanding of the general features of complex traits.

Biosensing Techniques↗

Genetics of global gene expression.

A new field of genetic analysis of global gene expression has emerged in recent years, driven by the realization that traditional techniques of linkage and association analysis can be applied to thousands of transcript levels measured by microarrays. Genetic dissection of transcript abundance has shed light on the architecture of quantitative traits, provided a new approach for connecting DNA sequence variation with phenotypic variation, and improved our understanding of transcriptional regulation and regulatory variation.

Amino Acid Sequence↗

Local regulatory variation in Saccharomyces cerevisiae.

Naturally occurring sequence variation that affects gene expression is an important source of phenotypic differences among individuals within a species. We and others have previously shown that such regulatory variation can occur both at the same locus as the gene whose expression it affects (local regulatory variation) and elsewhere in the genome at trans-acting factors. Here we present a detailed analysis of genome-wide local regulatory variation in Saccharomyces cerevisiae. We used genetic linkage analysis to show that nearly a quarter of all yeast genes contain local regulatory variation between two divergent strains. We measured allele-specific expression in a diploid hybrid of the two strains for 77 genes showing strong self-linkage and found that in 52%-78% of these genes, local regulatory variation acts directly in cis. We also experimentally confirmed one example in which local regulatory variation in the gene AMN1 acts in trans through a feedback loop. Genome-wide sequence analysis revealed that genes subject to local regulatory variation show increased polymorphism in the promoter regions, and that some but not all of this increase is due to polymorphisms in predicted transcription factor binding sites. Increased polymorphism was also found in the 3' untranslated regions of these genes. These findings point to the importance of cis-acting variation, but also suggest that there is a diverse set of mechanisms through which local variation can affect gene expression levels.

3' Untranslated Regions↗

Genetic interactions between polymorphisms that affect gene expression in yeast.

Interactions between polymorphisms at different quantitative trait loci (QTLs) are thought to contribute to the genetics of many traits, and can markedly affect the power of genetic studies to detect QTLs. Interacting loci have been identified in many organisms. However, the prevalence of interactions, and the nucleotide changes underlying them, are largely unknown. Here we search for naturally occurring genetic interactions in a large set of quantitative phenotypes--the levels of all transcripts in a cross between two strains of Saccharomyces cerevisiae. For each transcript, we searched for secondary loci interacting with primary QTLs detected by their individual effects. Such locus pairs were estimated to be involved in the inheritance of 57% of transcripts; statistically significant pairs were identified for 225 transcripts. Among these, 67% of secondary loci had individual effects too small to be significant in a genome-wide scan. Engineered polymorphisms in isogenic strains confirmed an interaction between the mating-type locus MAT and the pheromone response gene GPA1. Our results indicate that genetic interactions are widespread in the genetics of transcript levels, and that many QTLs will be missed by single-locus tests but can be detected by two-stage tests that allow for interactions.

Crosses, Genetic↗

Multiple locus linkage analysis of genomewide expression in yeast.

With the ability to measure thousands of related phenotypes from a single biological sample, it is now feasible to genetically dissect systems-level biological phenomena. The genetics of transcriptional regulation and protein abundance are likely to be complex, meaning that genetic variation at multiple loci will influence these phenotypes. Several recent studies have investigated the role of genetic variation in transcription by applying traditional linkage analysis methods to genomewide expression data, where each gene expression level was treated as a quantitative trait and analyzed separately from one another. Here, we develop a new, computationally efficient method for simultaneously mapping multiple gene expression quantitative trait loci that directly uses all of the available data. Information shared across gene expression traits is captured in a way that makes minimal assumptions about the statistical properties of the data. The method produces easy-to-interpret measures of statistical significance for both individual loci and the overall joint significance of multiple loci selected for a given expression trait. We apply the new method to a cross between two strains of the budding yeast Saccharomyces cerevisiae, and estimate that at least 37% of all gene expression traits show two simultaneous linkages, where we have allowed for epistatic interactions. Pairs of jointly linking quantitative trait loci are identified with high confidence for 170 gene expression traits, where it is expected that both loci are true positives for at least 153 traits. In addition, we are able to show that epistatic interactions contribute to gene expression variation for at least 14% of all traits. We compare the proposed approach to an exhaustive two-dimensional scan over all pairs of loci. Surprisingly, we demonstrate that an exhaustive two-dimensional scan is less powerful than the sequential search used here. In addition, we show that a two-dimensional scan does not truly allow one to test for simultaneous linkage, and the statistical significance measured from this existing method cannot be interpreted among many traits.

Chromosome Mapping↗

The landscape of genetic complexity across 5,700 gene expression traits in yeast.

Many studies have identified quantitative trait loci (QTLs) that contribute to continuous variation in heritable traits of interest. However, general principles regarding the distribution of QTL numbers, effect sizes, and combined effects of multiple QTLs remain to be elucidated. Here, we characterize complex genetics underlying inheritance of thousands of transcript levels in a cross between two strains of Saccharomyces cerevisiae. Most detected QTLs have weak effects, with a median variance explained of 27% for highly heritable transcripts. Despite the high statistical power of the study, no QTLs were detected for 40% of highly heritable transcripts, indicating extensive genetic complexity. Modeling of QTL detection showed that only 3% of highly heritable transcripts are consistent with single-locus inheritance, 17-18% are consistent with control by one or two loci, and half require more than five loci under additive models. Strikingly, analysis of parent and progeny trait distributions showed that a majority of transcripts exhibit transgressive segregation. Sixteen percent of highly heritable transcripts exhibit evidence of interacting loci. Our results will aid design of future QTL mapping studies and may shed light on the evolution of quantitative traits.

Computer Simulation↗

Simultaneous genotyping, gene-expression measurement, and detection of allele-specific expression with oligonucleotide arrays.

Oligonucleotide microarrays provide a high-throughput method for exploring genomes. In addition to their utility for gene-expression analysis, oligonucleotide-expression arrays have also been used to perform genotyping on genomic DNA. Here, we show that in segregants from a cross between two unrelated strains of Saccharomyces cerevisiae, high-quality genotype data can also be obtained when mRNA is hybridized to an oligonucleotide-expression array. We were able to identify and genotype nearly 1000 polymorphisms at an error rate close to 3% in segregants and at an error rate of 7% in diploid strains, a performance comparable to methods using genomic DNA. In addition, we demonstrate how simultaneous genotyping and gene-expression profiling can reveal cis-regulatory variation by screening hundreds of genes for allele-specific expression. With this method, we discovered 70 ORFs with evidence for preferential expression of one allele in a diploid hybrid of two S. cerevisiae strains.

Alleles↗

Extensive and breed-specific linkage disequilibrium in Canis familiaris.

The 156 breeds of registered dogs in the United States offer a unique opportunity to map genes important in disease susceptibility, morphology, and behavior. Linkage disequilibrium (LD) is of current interest for its application in whole genome association mapping, since the extent of LD determines the feasibility of such studies. We have measured LD at five genomic intervals, each 5 Mb in length and composed of five clusters of sequence variants spaced 800 kb-1.6 Mb apart. These intervals are located on canine chromosomes 1, 2, 3, 34, and 37, and none is under obvious selective pressure. Approximately 20 unrelated dogs were assayed from each of five breeds: Akita, Bernese Mountain Dog, Golden Retriever, Labrador Retriever, and Pekingese. At each genomic interval, SNPs and indels were discovered and typed by resequencing. Strikingly, LD in canines is much more extensive than in humans: D' falls to 0.5 at 400-700 kb in Golden Retriever and Labrador Retriever, 2.4 Mb in Akita, and 3-3.2 Mb in Bernese Mountain Dog and Pekingese. LD in dog breeds is up to 100x more extensive than in humans, suggesting that a correspondingly smaller number of markers will be required for association mapping studies in dogs compared to humans. We also report low haplotype diversity within regions of high LD, with 80% of chromosomes in a breed carrying two to four haplotypes, as well as a high degree of haplotype sharing among breeds.

Animals↗

Population history and natural selection shape patterns of genetic variation in 132 genes.

Identifying regions of the human genome that have been targets of natural selection will provide important insights into human evolutionary history and may facilitate the identification of complex disease genes. Although the signature that natural selection imparts on DNA sequence variation is difficult to disentangle from the effects of neutral processes such as population demographic history, selective and demographic forces can be distinguished by analyzing multiple loci dispersed throughout the genome. We studied the molecular evolution of 132 genes by comprehensively resequencing them in 24 African-Americans and 23 European-Americans. We developed a rigorous computational approach for taking into account multiple hypothesis tests and demographic history and found that while many apparent selective events can instead be explained by demography, there is also strong evidence for positive or balancing selection at eight genes in the European-American population, but none in the African-American population. Our results suggest that the migration of modern humans out of Africa into new environments was accompanied by genetic adaptations to emergent selective forces. In addition, a region containing four contiguous genes on Chromosome 7 showed striking evidence of a recent selective sweep in European-Americans. More generally, our results have important implications for mapping genes underlying complex human diseases.

Black People↗

Sequence-based linkage analysis.

The rapid decrease in the cost of DNA sequencing will enable its use for novel applications. Here, we investigate the use of DNA sequencing for simultaneous discovery and genotyping of polymorphisms in family linkage studies. In the proposed approach, short contiguous segments of genomic DNA, regularly spaced across the genome, are resequenced in each pedigree member, and all sequence polymorphisms discovered within a pedigree are used as genetic markers. We use computer simulations consistent with observed human sequence diversity to show that segments of 500-1,000 base pairs, spaced at intervals of 1-2 Mb across the genome, provide linkage information that equals or exceeds that of traditional marker-based approaches. We validate these results experimentally by implementing the sequence-based linkage approach for chromosome 19 in CEPH pedigrees.

Chromosome Mapping↗