James Ronald

Gene-Expression Variation Within and Among Human Populations

Understanding patterns of gene-expression variation within and among human populations will provide important insights into the molecular basis of phenotypic diversity and the interpretation of patterns of expression variation in disease. However, little is known about how gene-expression variation is apportioned within and among human populations. Here, we characterize patterns of natural gene-expression variation in 16 individuals of European and African ancestry. We find extensive variation in gene-expression levels and estimate that approximately 83% of genes are differentially expressed among individuals and that approximately 17% of genes are differentially expressed among populations. By decomposing total gene-expression variation into within- versus among-population components, we find that most expression variation is due to variation among individuals rather than among populations, which parallels observations of extant patterns of human genetic variation. Finally, we performed allele-specific quantitative polymerase chain reaction to demonstrate that cis-regulatory variation in the lymphocyte adaptor protein (SH2B adapter protein 3) contributes to differential expression between European and African samples. These results provide the first insight into how human population structure manifests itself in gene-expression levels and will help guide the search for regulatory quantitative trait loci.

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.

Inherited Variation in Gene Expression

Variation in gene expression constitutes an important source of biological variability within and between populations that is likely to contribute significantly to phenotypic diversity. Recent conceptual, technical, and methodological advances have enabled the genome-scale dissection of transcriptional variation. Here, we outline common approaches for detecting gene expression quantitative trait loci, and summarize the insights gleaned from these studies regarding the genetic architecture of transcriptional variation and the nature of regulatory alleles. Particular emphasis is placed on human studies, and we discuss experimental designs that ensure that increasingly large and complex studies continue to advance our understanding of gene expression variation. We conclude by discussing the evolution of gene expression levels, and we explore prospects for leveraging new technological developments to investigate inherited variation in gene expression in even greater depth.

The Evolution of Gene Expression QTL in Saccharomyces cerevisiae

Understanding the evolutionary forces that influence patterns of gene expression variation will provide insights into the mechanisms of evolutionary change and the molecular basis of phenotypic diversity. To date, studies of gene expression evolution have primarily been made by analyzing how gene expression levels vary within and between species. However, the fundamental unit of heritable variation in transcript abundance is the underlying regulatory allele, and as a result it is necessary to understand gene expression evolution at the level of DNA sequence variation. Here we describe the evolutionary forces shaping patterns of genetic variation for 1206 cis-regulatory QTL identified in a cross between two divergent strains of Saccharomyces cerevisiae. We demonstrate that purifying selection against mildly deleterious alleles is the dominant force governing cis-regulatory evolution in S. cerevisiae and estimate the strength of selection. We also find that essential genes and genes with larger codon bias are subject to slightly stronger cis-regulatory constraint and that positive selection has played a role in the evolution of major trans-acting QTL.

Genome-wide scans for loci under selection in humans

Natural selection, which can be defined as the differential contribution of genetic variants to future generations, is the driving force of Darwinian evolution. Identifying regions of the human genome that have been targets of natural selection is an important step in clarifying human evolutionary history and understanding how genetic variation results in phenotypic diversity, it may also facilitate the search for complex disease genes. Technological advances in high-throughput DNA sequencing and single nucleotide polymorphism genotyping have enabled several genome-wide scans of natural selection to be undertaken. Here, some of the observations that are beginning to emerge from these studies will be reviewed, including evidence for geographically restricted selective pressures (ie local adaptation) and a relationship between genes subject to natural selection and human disease. In addition, the paper will highlight several important problems that need to be addressed in future genome-wide studies of natural selection.

Genetic Variation in LPAL2, LPA, and PLG Predicts Plasma Lipoprotein(a) Level and Carotid Artery Disease Risk

Background and Purpose— Lipoprotein(a) [Lp(a)] level is an established risk factor for coronary artery disease and has been implicated in carotid artery disease (CAAD). The relationship between genetic variation in the LPA gene region and CAAD risk remains unknown. Methods— We genotyped single nucleotide polymorphisms (SNPs) in the LPAL2, LPA, and PLG regions in 530 individuals with severe CAAD and 770 controls and kringle IV type 2 (KIV2) repeat length in a subset of 90 individuals. Results— Nine SNPs collectively accounted for 30% of the variance in Lp(a) level. Six SNPs were associated with Lp(a) level after accounting for KIV2 copy number, and the dominant KIV2 allele combined with these markers explained 60% of the variance in Lp(a) level. Five SNPs, including rs10455872, which had an odds ratio of 2.1 per minor allele and haplotypes formed by rs10455872, rs6919346, and rs3123629, were significant predictors of CAAD. After accounting for Lp(a) level, all evidence of CAAD-genotype association in the LPA region was eliminated. Conclusions— LPA region SNPs capture some but not all of the effect of KIV2 repeat length on Lp(a) level. There are associations between LPA region SNPs and CAAD that appear to be attributable to effects on Lp(a) level.

Analysis of recently identified dyslipidemia alleles reveals two loci that contribute to risk for carotid artery disease

BackgroundGenome-wide association studies have identified numerous single nucleotide polymorphisms (SNPs) affecting high density lipoprotein (HDL) or low density lipoprotein (LDL) cholesterol levels; these SNPs may contribute to the genetic basis of vascular diseases.ResultsWe assessed the impact of 34 SNPs at 23 loci on dyslipidemia, key lipid sub-phenotypes, and severe carotid artery disease (CAAD) in a case-control cohort. The effects of these SNPs on HDL and LDL were consistent with those previously reported, and we provide unbiased estimates of the percent variance in HDL (3.9%) and LDL (3.3%) explained by genetic risk scores. We assessed the effects of these SNPs on HDL subfractions, apolipoprotein A-1, LDL buoyancy, apolipoprotein B, and lipoprotein (a) and found that rs646776 predicts apolipoprotein B level while rs2075650 predicts LDL buoyancy. Finally, we tested the role of these SNPs in conferring risk for ultrasonographically documented CAAD stenosis status. We found that two loci, chromosome 1p13.3 near CELSR2 and PSRC1 which contains rs646776, and 19q13.2 near TOMM40 and APOE which contains rs2075650, harbor risk alleles for CAAD.ConclusionOur analysis of 34 SNPs contributing to dyslipidemia at 23 loci suggests that genetic variation in the 1p13.3 region may increase risk of CAAD by increasing LDL particle number, whereas variation in the 19q13.2 region may increase CAAD risk by promoting formation of smaller, denser LDL particles.

Genomewide Evolutionary Rates in Laboratory and Wild Yeast

As wild organisms adapt to the laboratory environment, they become less relevant as biological models. It has been suggested that a commonly used S. cerevisiae strain has rapidly accumulated mutations in the lab. We report a low-to-intermediate rate of protein evolution in this strain relative to wild isolates.

Linkage and association of phospholipid transfer protein activity to LASS4

Phospholipid transfer protein activity (PLTPa) is associated with insulin levels and has been implicated in atherosclerotic disease in both mice and humans. Variation at the PLTP structural locus on chromosome 20 explains some, but not all, heritable variation in PLTPa. In order to detect quantitative trait loci (QTLs) elsewhere in the genome that affect PLTPa, we performed both oligogenic and single QTL linkage analysis on four large families (n = 227 with phenotype, n = 330 with genotype, n = 462 total), ascertained for familial combined hyperlipidemia. We detected evidence of linkage between PLTPa and chromosome 19p (lod = 3.2) for a single family and chromosome 2q (lod = 2.8) for all families. Inclusion of additional marker and exome sequence data in the analysis refined the linkage signal on chromosome 19 and implicated coding variation in LASS4, a gene regulated by leptin that is involved in ceramide synthesis. Association between PLTPa and LASS4 variation was replicated in the other three families (P = 0.02), adjusting for pedigree structure. To our knowledge, this is the first example for which exome data was used in families to identify a complex QTL that is not the structural locus.

Population Genomics of Intron Splicing in 38 Saccharomyces cerevisiae Genome Sequences

Introns are a ubiquitous feature of eukaryotic genomes, and the dynamics of intron evolution between species has been extensively studied. However, comparatively few analyses have focused on the evolutionary forces shaping patterns of intron variation within species. To better understand the population genetic characteristics of introns, we performed an extensive population genetics analysis on key intron splice sequences obtained from 38 strains of Saccharomyces cerevisiae. As expected, we found that purifying selection is the dominant force governing intron splice sequence evolution in yeast, formally confirming that intron-containing alleles are a mutational liability. In addition, through extensive coalescent simulations, we obtain quantitative estimates of the strength of purifying selection (2Nes ≈ 19) and use diffusion approximations to provide insights into the evolutionary dynamics and sojourn times of newly arising splice sequence mutations in natural yeast populations. In contrast to previous functional studies, evolutionary analyses comparing the prevalence of introns in essential and nonessential genes suggest that introns in nonribosomal protein genes are functionally important and tend to be actively maintained in natural populations of S. cerevisiae. Finally, we demonstrate that heritable variation in splicing efficiency is common in intron-containing genes with splice sequence polymorphisms. More generally, our study highlights the advantages of population genomics analyses for exploring the forces that have generated extant patterns of genome variation and for illuminating basic biological processes.