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.

Differential Immunogenicity of Various Heterologous Prime-Boost Vaccine Regimens Using DNA and Viral Vectors in Healthy Volunteers

Abstract: Heterologous prime-boost vaccination has been shown to be an efficient way of inducing T cell responses in animals and in humans. We have used three vaccine vectors, naked DNA, modified vaccinia virus Ankara (MVA), and attenuated fowlpox strain, FP9, for prime-boost vaccination approaches against Plasmodium falciparum malaria in humans. In this study, we characterize, using two types of ELISPOT assays and FACS analysis, cell-mediated immune responses induced by different prime-boost combinations where all vectors encode a multiepitope string fused to the pre-erythrocytic Ag thrombospondin-related adhesion protein. We show that these different vectors need to be used in a specific order for an optimal ex vivo IFN-gamma response. From the different combinations, DNA priming followed by MVA boosting and FP9 priming followed by MVA boosting were most immunogenic and in both cases the IFN-gamma response was of broad specificity and cross-reactive against two P. falciparum strains (3D7 and T9/96). Immunization with all three vectors showed no improvement over optimal two vector regimes. Strong ex vivo IFN-gamma responses peaked 1 wk after the booster dose, but cultured ELISPOT assays revealed longer-lasting T cell memory responses for at least 6 mo. In the DNA-primed vaccinees the IFN-gamma response was mainly due to CD4(+) T cells, whereas in the FP9-primed vaccinees it was mainly due to CD4-dependent CD8(+) T cells. This difference may be of importance for the protective efficacy of these vaccination approaches against various diseases.

Guidelines for Genotyping in Genomewide Linkage Studies: Single-Nucleotide–Polymorphism Maps Versus Microsatellite Maps

Abstract: Genomewide linkage scans have traditionally employed panels of microsatellite markers spaced at intervals of ∼10 cM across the genome. However, there is a growing realization that a map of closely spaced single-nucleotide polymorphisms (SNPs) may offer equal or superior power to detect linkage, compared with low-density microsatellite maps. We performed a series of simulations to calculate the information content associated with microsatellite and SNP maps across a range of different marker densities and heterozygosities for sib pairs (with and without parental genotypes), sib trios, and sib quads. In the case of microsatellite markers, we varied density across 11 levels (1 marker every 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cM) and marker heterozygosity across 6 levels (2, 3, 4, 5, 10, or 20 equally frequent alleles), whereas, in the case of SNPs, we varied marker density across 4 levels (1 marker every 0.1, 0.2, 0.5, or 1 cM) and minor-allele frequency across 7 levels (0.5, 0.4, 0.3, 0.2, 0.1, 0.05, and 0.01). When parental genotypes were available, a map consisting of microsatellites spaced every 2 cM or a relatively sparse map of SNPs (i.e., at least 1 SNP/cM) was sufficient to extract most of the inheritance information from the map (>95% in most cases). However, when parental genotypes were unavailable, it was important to use as dense a map of markers as possible to extract the greatest amount of inheritance information. It is important to note that the information content associated with a traditional map of microsatellite markers (i.e., 1 marker every ∼10 cM) was significantly lower than the information content associated with a dense map of SNPs or microsatellites. These results strongly suggest that previous linkage studies that employed sparse microsatellite maps could benefit substantially from reanalysis by use of a denser map of markers.

Genomic analysis of local variation and recent evolution in Plasmodium vivax

Abstract: The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax.

Shared and Unique Components of Human Population Structure and Genome-Wide Signals of Positive Selection in South Asia

Abstract: South Asia harbors one of the highest levels genetic diversity in Eurasia, which could be interpreted as a result of its long-term large effective population size and of admixture during its complex demographic history. In contrast to Pakistani populations, populations of Indian origin have been underrepresented in previous genomic scans of positive selection and population structure. Here we report data for more than 600,000 SNP markers genotyped in 142 samples from 30 ethnic groups in India. Combining our results with other available genome-wide data, we show that Indian populations are characterized by two major ancestry components, one of which is spread at comparable frequency and haplotype diversity in populations of South and West Asia and the Caucasus. The second component is more restricted to South Asia and accounts for more than 50% of the ancestry in Indian populations. Haplotype diversity associated with these South Asian ancestry components is significantly higher than that of the components dominating the West Eurasian ancestry palette. Modeling of the observed haplotype diversities suggests that both Indian ancestry components are older than the purported Indo-Aryan invasion 3,500 YBP. Consistent with the results of pairwise genetic distances among world regions, Indians share more ancestry signals with West than with East Eurasians. However, compared to Pakistani populations, a higher proportion of their genes show regionally specific signals of high haplotype homozygosity. Among such candidates of positive selection in India are MSTN and DOK5, both of which have potential implications in lipid metabolism and the etiology of type 2 diabetes.