Wellcome Trust Centre for Human Genetics

About: Wellcome Trust Centre for Human Genetics is a facility organization based out in Oxford, United Kingdom. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 2122 authors who have published 4269 publications receiving 433899 citations.

HLA*IMP—an integrated framework for imputing classical HLA alleles from SNP genotypes

Abstract: 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 http://oxfordhla.well.ox.ac.uk and is free for academic use. Contact: ku.ca.xo.stats@naevcm Supplementary information: Supplementary data are available at Bioinformatics online.

Cardiac malformations and midline skeletal defects in mice lacking filamin A

Abstract: The X-linked gene filamin A (FIna) encodes a widely expressed actin-binding protein that crosslinks actin into orthogonal networks and interacts with a variety of other proteins including membrane proteins, integrins, transmembrane receptor complexes and second messengers, thus forming an important intracellular signalling scaffold. Heterozygous loss of function of human FLNA causes periventricular nodular heterotopia in females and is generally lethal (cause unknown) in hemizygous males. Missense FLNA mutations underlie a spectrum of disorders affecting both sexes that feature skeletal dysplasia accompanied by a variety of other abnormalities. Dilp2 is an X-linked male-lethal mouse mutation that was induced by N-ethyl-N-nitro-sourea. We report here that Dilp2 is caused by a T-to-A transversion that converts a tyrosine codon to a stop codon in the FIna gene (Y2388X), leading to absence of the FIna protein and male lethality because of incomplete septation of the outflow tract of the heart, which produces common arterial trunk. A proportion of both male and female mutant mice have other cardiac defects including ventricular septal defect. In addition, mutant males have midline fusion defects manifesting as sternum and palate abnormalities. Carrier females exhibit milder sternum and palate defects and misshapen pupils. These results define crucial roles for FIna in development, demonstrate that X-linked male lethal mutations can be recovered from ENU mutagenesis screens and suggest possible explanations for lethality of human males hemizygous for null alleles of FLNA.

A radiation hybrid map of 506 STS markers spanning human chromosome 11.

Abstract: We present a high resolution radiation hybrid map of human chromosome 11 using 506 sequence tagged sites (STSs) scored on a panel of 86 radiation hybrids. The 506 STSs fall into 299 unique positions (average resolution of about 480 kilobases (kb)) that span the whole chromosome. A subset of 260 STSs (143 positions) form a framework map that has a resolution of approximately 1 megabase between adjacent positions and is ordered with odds of at least 1,000:1. The centromere was clearly defined with pericentric markers unambiguously assigned to the short or long arm. The map contains most genes (125) and expressed sequence tags (26) currently assigned to chromosome 11 and more than half of the STSs are polymorphic microsatellite loci. These markers and the map can be used for high resolution physical and genetic mapping.

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites.

Abstract: Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now prioritized for functional study.

Rapid genotype imputation from sequence without reference panels

Abstract: Inexpensive genotyping methods are essential to modern genomics. Here we present QUILT, which performs diploid genotype imputation using low-coverage whole-genome sequence data. QUILT employs Gibbs sampling to partition reads into maternal and paternal sets, facilitating rapid haploid imputation using large reference panels. We show this partitioning to be accurate over many megabases, enabling highly accurate imputation close to theoretical limits and outperforming existing methods. Moreover, QUILT can impute accurately using diverse technologies, including long reads from Oxford Nanopore Technologies, and a new form of low-cost barcoded Illumina sequencing called haplotagging, with the latter showing improved accuracy at low coverages. Relative to DNA genotyping microarrays, QUILT offers improved accuracy at reduced cost, particularly for diverse populations that are traditionally underserved in modern genomic analyses, with accuracy nearly doubling at rare SNPs. Finally, QUILT can accurately impute (four-digit) human leukocyte antigen types, the first such method from low-coverage sequence data.