Prof Gil McVean

Research Area: Genetics and Genomics
Technology Exchange: Bioinformatics, SNP typing and Statistical genetics
Scientific Themes: Genetics & Genomics
Keywords: Population genetics, Coalescent modelling, HLA imputation, de novo assembly and Statistical Genetics
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My research covers several areas in the analysis of genetic variation, combining the development of methods for analysing high throughput sequencing data, theoretical work and empirical analysis. Of particular interest are: the analysis of recombination from population genetic data, dissecting signals of disease association within the HLA, methods for inferring genealogical history from DNA sequence data and de novo sequence assemblyfor the discovery of genetic variation. I am a member of the Mathematical Genetics Group in the Department of Statistics and Acting Director of the new Oxford Big Data Institute.

Name Department Institution Country
Prof Peter Donnelly FRS Wellcome Trust Centre for Human Genetics University of Oxford United Kingdom
Prof Dominic Kwiatkowski Wellcome Trust Centre for Human Genetics University of Oxford United Kingdom
Dr Simon Myers Wellcome Trust Centre for Human Genetics University of Oxford United Kingdom
Prof Andrew OM Wilkie FRS FMedSci FRCP (RDM) Nuffield Division of Clinical Laboratory Sciences University of Oxford United Kingdom
Prof Lars Fugger (RDM) Weatherall Institute of Molecular Medicine University of Oxford United Kingdom
Prof Jonathan Flint Wellcome Trust Centre for Human Genetics University of Oxford United Kingdom
Prof Molly Przeworski Department of Human Genetics and Department of Ecology and Evolution Columbia University United States
The 1000 Genomes Project Wellcome Trust United Kingdom

Zilversmit MM, Chase EK, Chen DS, Awadalla P, Day KP, McVean G. 2013. Hypervariable antigen genes in malaria have ancient roots. BMC Evol Biol, 13 (1), pp. 110. Read abstract | Read more

BACKGROUND: The var genes of the human malaria parasite Plasmodium falciparum are highly polymorphic loci coding for the erythrocyte membrane proteins 1 (PfEMP1), which are responsible for the cytoaherence of P. falciparum infected red blood cells to the human vasculature. Cytoadhesion, coupled with differential expression of var genes, contributes to virulence and allows the parasite to establish chronic infections by evading detection from the host's immune system. Although studying genetic diversity is a major focus of recent work on the var genes, little is known about the gene family's origin and evolutionary history. RESULTS: Using a novel hidden Markov model-based approach and var sequences assembled from additional isolates and species, we are able to reveal elements of both the early evolution of the var genes as well as recent diversifying events. We compare sequences of the var gene DBLα domains from divergent isolates of P. falciparum (3D7 and HB3), and a closely-related species, Plasmodium reichenowi. We find that the gene family is equally large in P. reichenowi and P. falciparum -- with a minimum of 51 var genes in the P. reichenowi genome (compared to 61 in 3D7 and a minimum of 48 in HB3). In addition, we are able to define large, continuous blocks of homologous sequence among P. falciparum and P. reichenowi var gene DBLα domains. These results reveal that the contemporary structure of the var gene family was present before the divergence of P. falciparum and P. reichenowi, estimated to be between 2.5 to 6 million years ago. We also reveal that recombination has played an important and traceable role in both the establishment, and the maintenance, of diversity in the sequences. CONCLUSIONS: Despite the remarkable diversity and rapid evolution found in these loci within and among P. falciparum populations, the basic structure of these domains and the gene family is surprisingly old and stable. Revealing a common structure as well as conserved sequence among two species also has implications for developing new primate-parasite models for studying the pathology and immunology of falciparum malaria, and for studying the population genetics of var genes and associated virulence phenotypes. Hide abstract

Leffler EM, Gao Z, Pfeifer S, Ségurel L, Auton A, Venn O, Bowden R, Bontrop R et al. 2013. Multiple instances of ancient balancing selection shared between humans and chimpanzees. Science, 339 (6127), pp. 1578-1582. Read abstract | Read more

Instances in which natural selection maintains genetic variation in a population over millions of years are thought to be extremely rare. We conducted a genome-wide scan for long-lived balancing selection by looking for combinations of SNPs shared between humans and chimpanzees. In addition to the major histocompatibility complex, we identified 125 regions in which the same haplotypes are segregating in the two species, all but two of which are noncoding. In six cases, there is evidence for an ancestral polymorphism that persisted to the present in humans and chimpanzees. Regions with shared haplotypes are significantly enriched for membrane glycoproteins, and a similar trend is seen among shared coding polymorphisms. These findings indicate that ancient balancing selection has shaped human variation and point to genes involved in host-pathogen interactions as common targets. Hide abstract

Gregory AP, Dendrou CA, Attfield KE, Haghikia A, Xifara DK, Butter F, Poschmann G, Kaur G et al. 2012. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis. Nature, 488 (7412), pp. 508-511. Read abstract | Read more

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation. Hide abstract

Mathieson I, McVean G. 2012. Differential confounding of rare and common variants in spatially structured populations. Nat Genet, 44 (3), pp. 243-246. Read abstract | Read more

Well-powered genome-wide association studies, now made possible through advances in technology and large-scale collaborative projects, promise to characterize the contribution of rare variants to complex traits and disease. However, while population structure is a known confounder of association studies, it remains unknown whether methods developed to control stratification are equally effective for rare variants. Here, we demonstrate that rare variants can show a stratification that is systematically different from, and typically stronger than, common variants, and this is not necessarily corrected by existing methods. We show that the same process leads to inflation for load-based tests and can obscure signals at truly associated variants. Furthermore, we show that populations can display spatial structure in rare variants, even when Wright's fixation index F(ST) is low, but that allele frequency-dependent metrics of allele sharing can reveal localized stratification. These results underscore the importance of collecting and integrating spatial information in the genetic analysis of complex traits. Hide abstract

Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G. 2012. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat Genet, 44 (2), pp. 226-232. Read abstract | Read more

Detecting genetic variants that are highly divergent from a reference sequence remains a major challenge in genome sequencing. We introduce de novo assembly algorithms using colored de Bruijn graphs for detecting and genotyping simple and complex genetic variants in an individual or population. We provide an efficient software implementation, Cortex, the first de novo assembler capable of assembling multiple eukaryotic genomes simultaneously. Four applications of Cortex are presented. First, we detect and validate both simple and complex structural variations in a high-coverage human genome. Second, we identify more than 3 Mb of sequence absent from the human reference genome, in pooled low-coverage population sequence data from the 1000 Genomes Project. Third, we show how population information from ten chimpanzees enables accurate variant calls without a reference sequence. Last, we estimate classical human leukocyte antigen (HLA) genotypes at HLA-B, the most variable gene in the human genome. Hide abstract

Auton A, Fledel-Alon A, Pfeifer S, Venn O, Ségurel L, Street T, Leffler EM, Bowden R et al. 2012. A fine-scale chimpanzee genetic map from population sequencing. Science, 336 (6078), pp. 193-198. Read abstract | Read more

To study the evolution of recombination rates in apes, we developed methodology to construct a fine-scale genetic map from high-throughput sequence data from 10 Western chimpanzees, Pan troglodytes verus. Compared to the human genetic map, broad-scale recombination rates tend to be conserved, but with exceptions, particularly in regions of chromosomal rearrangements and around the site of ancestral fusion in human chromosome 2. At fine scales, chimpanzee recombination is dominated by hotspots, which show no overlap with those of humans even though rates are similarly elevated around CpG islands and decreased within genes. The hotspot-specifying protein PRDM9 shows extensive variation among Western chimpanzees, and there is little evidence that any sequence motifs are enriched in hotspots. The contrasting locations of hotspots provide a natural experiment, which demonstrates the impact of recombination on base composition. Hide abstract

1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA. 2012. An integrated map of genetic variation from 1,092 human genomes. Nature, 491 (7422), pp. 56-65. Read abstract | Read more

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. Hide abstract

Dilthey AT, Moutsianas L, Leslie S, McVean G. 2011. HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes. Bioinformatics, 27 (7), pp. 968-972. Read abstract | Read more

MOTIVATION: Genetic variation at classical HLA alleles influences many phenotypes, including susceptibility to autoimmune disease, resistance to pathogens and the risk of adverse drug reactions. However, classical HLA typing methods are often prohibitively expensive for large-scale studies. We previously described a method for imputing classical alleles from linked SNP genotype data. Here, we present a modification of the original algorithm implemented in a freely available software suite that combines local data preparation and QC with probabilistic imputation through a remote server. RESULTS: We introduce two modifications to the original algorithm. First, we present a novel SNP selection function that leads to pronounced increases (up by 40% in some scenarios) in call rate. Second, we develop a parallelized model building algorithm that allows us to process a reference set of over 2500 individuals. In a validation experiment, we show that our framework produces highly accurate HLA type imputations at class I and class II loci for independent datasets: at call rates of 95-99%, imputation accuracy is between 92% and 98% at the four-digit level and over 97% at the two-digit level. We demonstrate utility of the method through analysis of a genome-wide association study for psoriasis where there is a known classical HLA risk allele (HLA-C*06:02). We show that the imputed allele shows stronger association with disease than any single SNP within the region. The imputation framework, HLA*IMP, provides a powerful tool for dissecting the architecture of genetic risk within the HLA. AVAILABILITY: HLA*IMP, implemented in C++ and Perl, is available from and is free for academic use. Hide abstract

International Multiple Sclerosis Genetics Consortium, Wellcome Trust Case Control Consortium 2, Sawcer S, Hellenthal G, Pirinen M, Spencer CC, Patsopoulos NA, Moutsianas L et al. 2011. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature, 476 (7359), pp. 214-219. Read abstract | Read more

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis. Hide abstract

1000 Genomes Project Consortium, Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, Gibbs RA, Hurles ME, McVean GA. 2010. A map of human genome variation from population-scale sequencing. Nature, 467 (7319), pp. 1061-1073. Read abstract | Read more

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research. Hide abstract

Myers S, Bowden R, Tumian A, Bontrop RE, Freeman C, MacFie TS, McVean G, Donnelly P. 2010. Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic recombination. Science, 327 (5967), pp. 876-879. Read abstract | Read more

Although present in both humans and chimpanzees, recombination hotspots, at which meiotic crossover events cluster, differ markedly in their genomic location between the species. We report that a 13-base pair sequence motif previously associated with the activity of 40% of human hotspots does not function in chimpanzees and is being removed by self-destructive drive in the human lineage. Multiple lines of evidence suggest that the rapidly evolving zinc-finger protein PRDM9 binds to this motif and that sequence changes in the protein may be responsible for hotspot differences between species. The involvement of PRDM9, which causes histone H3 lysine 4 trimethylation, implies that there is a common mechanism for recombination hotspots in eukaryotes but raises questions about what forces have driven such rapid change. Hide abstract

McVean G. 2009. A genealogical interpretation of principal components analysis. PLoS Genet, 5 (10), pp. e1000686. Read abstract | Read more

Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to inform about historical demographic processes, little is known about the relationship between fundamental demographic parameters and the projection of samples onto the primary axes. Here I show that for SNP data the projection of samples onto the principal components can be obtained directly from considering the average coalescent times between pairs of haploid genomes. The result provides a framework for interpreting PCA projections in terms of underlying processes, including migration, geographical isolation, and admixture. I also demonstrate a link between PCA and Wright's f(st) and show that SNP ascertainment has a largely simple and predictable effect on the projection of samples. Using examples from human genetics, I discuss the application of these results to empirical data and the implications for inference. Hide abstract

Myers S, Freeman C, Auton A, Donnelly P, McVean G. 2008. A common sequence motif associated with recombination hot spots and genome instability in humans. Nat Genet, 40 (9), pp. 1124-1129. Read abstract | Read more

In humans, most meiotic crossover events are clustered into short regions of the genome known as recombination hot spots. We have previously identified DNA motifs that are enriched in hot spots, particularly the 7-mer CCTCCCT. Here we use the increased hot-spot resolution afforded by the Phase 2 HapMap and novel search methods to identify an extended family of motifs based around the degenerate 13-mer CCNCCNTNNCCNC, which is critical in recruiting crossover events to at least 40% of all human hot spots and which operates on diverse genetic backgrounds in both sexes. Furthermore, these motifs are found in hypervariable minisatellites and are clustered in the breakpoint regions of both disease-causing nonallelic homologous recombination hot spots and common mitochondrial deletion hot spots, implicating the motif as a driver of genome instability. Hide abstract

Leslie S, Donnelly P, McVean G. 2008. A statistical method for predicting classical HLA alleles from SNP data. Am J Hum Genet, 82 (1), pp. 48-56. Read abstract | Read more

Genetic variation at classical HLA alleles is a crucial determinant of transplant success and susceptibility to a large number of infectious and autoimmune diseases. However, large-scale studies involving classical type I and type II HLA alleles might be limited by the cost of allele-typing technologies. Although recent studies have shown that some common HLA alleles can be tagged with small numbers of markers, SNP-based tagging does not offer a complete solution to predicting HLA alleles. We have developed a new statistical methodology to use SNP variation within the region to predict alleles at key class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) loci. Our results indicate that a single panel of approximately 100 SNPs typed across the region is sufficient for predicting both rare and common HLA alleles with up to 95% accuracy in both African and non-African populations. Furthermore, we show that HLA alleles can be successfully predicted by using previously genotyped SNPs that are within the MHC and that had not been chosen for their ability to predict HLA alleles, such as those included on genome-wide products. These results indicate that our methodology, combined with an extended database of reference haplotypes, will facilitate large-scale experiments, including disease-association studies and vaccine trials, in which detailed information about HLA type is valuable. Hide abstract

International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW et al. 2007. A second generation human haplotype map of over 3.1 million SNPs. Nature, 449 (7164), pp. 851-861. Read abstract | Read more

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations. Hide abstract

Spencer CC, Deloukas P, Hunt S, Mullikin J, Myers S, Silverman B, Donnelly P, Bentley D, McVean G. 2006. The influence of recombination on human genetic diversity. PLoS genetics, 2 (9), Read abstract | Read more

In humans, the rate of recombination, as measured on the megabase scale, is positively associated with the level of genetic variation, as measured at the genic scale. Despite considerable debate, it is not clear whether these factors are causally linked or, if they are, whether this is driven by the repeated action of adaptive evolution or molecular processes such as double-strand break formation and mismatch repair. We introduce three innovations to the analysis of recombination and diversity: fine-scale genetic maps estimated from genotype experiments that identify recombination hotspots at the kilobase scale, analysis of an entire human chromosome, and the use of wavelet techniques to identify correlations acting at different scales. We show that recombination influences genetic diversity only at the level of recombination hotspots. Hotspots are also associated with local increases in GC content and the relative frequency of GC-increasing mutations but have no effect on substitution rates. Broad-scale association between recombination and diversity is explained through covariance of both factors with base composition. To our knowledge, these results are the first evidence of a direct and local influence of recombination hotspots on genetic variation and the fate of individual mutations. However, that hotspots have no influence on substitution rates suggests that they are too ephemeral on an evolutionary time scale to have a strong influence on broader scale patterns of base composition and long-term molecular evolution. Hide abstract


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