Biology subjects

Donnelly, P.

Publications and source records attributed to Donnelly, P..

7 recordsLinked to original sources

bioRxiv2018

Long-read whole genome sequencing and comparative analysis of six strains of the human pathogen Orientia tsutsugamushi

BackgroundOrientia tsutsugamushi is a clinically important but neglected obligate intracellular bacterial pathogen of the Rickettsiaceae family that causes the potentially life-threatening human disease scrub typhus. In contrast to the genome reduction seen in many obligate intracellular bacteria, early genetic studies of Orientia have revealed one of the most repetitive bacterial genomes sequenced to date. The dramatic expansion of mobile elements has hampered efforts to generate complete genome sequences using short read sequencing methodologies, and consequently there have been few studies of the comparative genomics of this neglected species.\n\nResultsWe report new high-quality genomes of Orientia tsutsugamushi, generated using PacBio single molecule long read sequencing, for six strains: Karp, Kato, Gilliam, TA686, UT76 and UT176. In comparative genomics analyses of these strains together with existing reference genomes from Ikeda and Boryong strains, we identify a relatively small core genome of 657 genes, grouped into core gene islands and separated by repeat regions, and use the core genes to infer the first whole-genome phylogeny of Orientia.\n\nConclusionsComplete assemblies of multiple Orientia genomes verify initial suggestions that these are remarkable organisms. They have large genomes with widespread amplification of repeat elements and massive chromosomal rearrangements between strains. At the gene level, Orientia has a relatively small set of universally conserved genes, similar to other obligate intracellular bacteria, and the relative expansion in genome size can be accounted for by gene duplication and repeat amplification. Our study demonstrates the utility of long read sequencing to investigate complex bacterial genomes and characterise genomic variation.

genomics↗

bioRxiv2018

Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula

Genetic differences within or between human populations (population structure) has been studied using a variety of approaches over many years. Recently there has been an increasing focus on studying genetic differentiation at fine geographic scales, such as within countries. Identifying such structure allows the study of recent population history, and identifies the potential for confounding in association studies, particularly when testing rare, often recently arisen variants. The Iberian Peninsula is linguistically diverse, has a complex demographic history, and is unique among European regions in having a centuries-long period of Muslim rule. Previous genetic studies of Spain have examined either a small fraction of the genome or only a few Spanish regions. Thus, the overall pattern of fine-scale population structure within Spain remains uncharacterised. Here we analyse genome-wide genotyping array data for 1,413 Spanish individuals sampled from all regions of Spain. We identify extensive fine-scale structure, down to unprecedented scales, smaller than 10 Km in some places. We observe a major axis of genetic differentiation that runs from east to west of the peninsula. In contrast, we observe remarkable genetic similarity in the north-south direction, and evidence of historical north-south population movement. Finally, without making particular prior assumptions about source populations, we show that modern Spanish people have regionally varying fractions of ancestry from a group most similar to modern north Moroccans. The north African ancestry results from an admixture event, which we date to 860 - 1120 CE, corresponding to the early half of Muslim rule. Our results indicate that it is possible to discern clear genetic impacts of the Muslim conquest and population movements associated with the subsequent Reconquista.

genomics↗

bioRxiv2017

Insights into platypus population structure and history from whole-genome sequencing

The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly-improved reference genome, we called over 6.7M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative amongst other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0x10-9/bp/generation (95% CI 4.1x10-9 - 1.2x10-8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.

genomics↗

bioRxiv2017

Phenome-wide association studies (PheWAS) across large "real-world data" population cohorts support drug target validation

Phenome-wide association studies (PheWAS), which assess whether a genetic variant is associated with multiple phenotypes across a phenotypic spectrum, have been proposed as a possible aid to drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we evaluate whether PheWAS can inform target validation during drug development. We selected 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease therapeutic indications. We independently interrogated these SNPs through PheWAS in four large \"real-world data\" cohorts (23andMe, UK Biobank, FINRISK, CHOP) for association with a total of 1,892 binary endpoints. We then conducted meta-analyses for 145 harmonized disease endpoints in up to 697,815 individuals and joined results with summary statistics from 57 published GWAS. Our analyses replicate 70% of known GWAS associations and identify 10 novel associations with study-wide significance after multiple test correction (P<1.8x10-6; out of 72 novel associations with FDR<0.1). By leveraging directionality and point estimate of the effect sizes, we describe new associations that may predict ADEs, e.g., acne, high cholesterol, gout and gallstones for rs738409 (p.I148M) in PNPLA3; or asthma for rs1990760 (p.T946A) in IFIH1. We further propose how quantitative estimates of genetic safety/efficacy profiles can be used to help prioritize candidate targets for a specific indication. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.\n\nOne Sentence SummaryMatching genetics with phenotypes in 800,000 individuals predicts efficacy and on-target safety of future drugs.

genetics↗

bioRxiv2017

Genome-wide genetic data on ~500,000 UK Biobank participants

The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data - such as population structure and relatedness - that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

genetics↗

bioRxiv2017

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data has the ability to radically transform our understanding of the human phenome, thereby accelerating progress towards precision medicine. However, a critical question when analysing high-dimensional and heterogeneous data is how to interrogate increasingly specific subphenotypes whilst retaining statistical power to detect genetic associations. Here we develop and employ a novel Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to jointly analyse genetic variants against UK Biobank healthcare phenotypes. Our method displays a more than 20% increase in power to detect genetic effects over other approaches, such that we uncover the broader burden of genetic variation: we identify associations with over 2,000 diagnostic terms. We find novel associations with common immune-mediated diseases (IMD), we reveal the extent of genetic sharing between specific IMDs, and we expose differences in disease perception or diagnosis with potential clinical implications.

genetics↗

bioRxiv2016

Practical Use of Methods for Imputation of HLA Alleles from SNP Genotype Data

The human leukocyte antigen (HLA) genes play an essential role in immune function. Typing of HLA alleles is critical for transplantation and is informative for many disease associations. The high cost of accurate lab-based HLA typing has precluded its use in large-scale disease-association studies. The development of statistical methods to type alleles using linkage disequilibrium with nearby SNPs, called HLA imputation, has allowed large cohorts of individuals to be typed accurately, so that massive numbers of affected individuals and controls may be studied. This has resulted in many important findings. Several HLA imputation methods have been widely used, however their relative performance has not been adequately addressed. We have conducted a comprehensive study to evaluate the most widely used HLA imputation methods. We assembled a multi-ethnic panel of 10,561 individuals with SNP genotype data and lab-based typing of alleles at 11 HLA genes at two-field resolution, and used it to train and validate each method. Use of this panel leads to imputation accuracy far superior to what is currently publicly available. We present a highly-accurate new imputation method, HLA*IMP:03. We address the question of optimal use of HLA imputations in tests of genetic association, showing that it is usually not necessary to apply a probability threshold to achieve maximal power. We also investigated the effect on accuracy of SNP density and population stratification at the continental level and show that neither of these are a significant concern.

genetics↗