Biology subjects

Rawlik, K.

Publications and source records attributed to Rawlik, K..

12 recordsLinked to original sources

bioRxiv2022

A compendium of genetic regulatory effects across pig tissues

The Farm animal Genotype-Tissue Expression (FarmGTEx, https://www.farmgtex.org/) project has been established to develop a comprehensive public resource of genetic regulatory variants in domestic animal species, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. Here we present results from the pilot phase of PigGTEx (http://piggtex.farmgtex.org/), where we processed 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs. We build a pig genotype imputation panel, characterize the transcriptional landscape across over 100 tissues, and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We study interactions between genotype and breed/cell type, evaluate tissue specificity of regulatory effects, and elucidate the molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes, and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, corroborating the importance of pigs as a human biomedical model.

genomics↗

bioRxiv2022

Expanded Analysis of Pigmentation Genetics in UK Biobank

The genetics of pigmentation is an excellent model for understanding gene interactions in a trait almost entirely unaffected by environment. We have analysed pigmentation phenotypes in UK Biobank using DISSECT, a tool which enables genome-wide association studies (GWAS) whilst accounting for relatedness between individuals, and thus allows a much larger cohort to be studied. We have increased the number of candidate genes associated with red and blonde hair colour, basal skin colour and tanning response to UV radiation. As previously described, we find almost all red hair individuals have two variant MC1R alleles; exome sequence data expands the number of associated coding variants. Rare red-headed individuals with only a single MC1R variant are enriched for an associated eQTL at the ASIP gene. We find that females are most likely to self-report red or blonde hair, paler skin and less tanning ability than men, and that variants at KITLG, MC1R, OCA2 and IRF4 show significant sex differences in effect. After taking sex into account, pigmentation phenotypes are not correlated with sex hormone levels, except for tanning ability, which shows a positive correlation with testosterone in men. Across the UK there is a correlation between place of birth and hair colour; red hair being more common in the north and west, whilst blonde hair is more common in the east. Combining GWAS with transcriptome data to generate a transcriptome wide association study identifies candidate genes whose expression in skin or melanocytes shows association with pigmentation phenotypes. A comparison of candidates associated with different pigmentation phenotypes finds that candidates for blonde hair, but not skin colour, are enriched for skin and hair genes suggesting that it may be hair shape and structure that impacts hair colour, rather than the melanocyte/keratinocyte interaction.

genetics↗

bioRxiv2020

A comprehensive catalogue of regulatory variants in the cattle transcriptome

Characterization of genetic regulatory variants acting on the transcriptome of livestock is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here, we build a cattle Genotype-Tissue Expression atlas (cattle GTEx, http://cgtex.roslin.ed.ac.uk/) as part of the pilot phase of Farm animal GTEx (FarmGTEx) project for the research community based on publicly available 11,642 RNA-Seq datasets. We describe the landscape of the transcriptome across over 100 tissues and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 24 major tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multi-omics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association study (TWAS) and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.

genomics↗

bioRxiv2020

SNP heritability: What are we estimating?

The SNP heritability [Formula] has become a central concept in the study of complex traits. Estimation of [Formula] based on genomic variance components in a linear mixed model using restricted maximum likelihood has been widely adopted as the method of choice were individual level data are available. Empirical results have suggested that this approach is not robust if the population of interest departs from the assumed statistical model. Prolonged debate of the appropriate model choice has yielded a number of approaches to account for frequency- and linkage disequilibrium dependent genetic architectures. Here we analytically resolve the question of how these estimates relate to [Formula] of the population from which samples are drawn. In particular, we show that the correct model for the purpose of inference about [Formula] does not require knowledge of the true genetic architecture of a trait. More generally, our results provide a complete perspective of these class of estimators of [Formula], highlighting practical shortcomings of current practise. We illustrate our theoretical results using simulations and data from UK Biobank.

genetics↗

bioRxiv2020

Sexual differences in genetic architecture in UK Biobank

Sex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Gene by sex interactions (GxS) are thought to account for some of this sexual dimorphism. However, the extent and basis of these interactions are poorly understood. Here we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We also found that, in some cases, sex-agnostic GWAS efforts might be missing loci of interest, and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the dimorphism observed through sex-biased eQTL and gene-level analyses. This study marks a broad examination of the genetics of sexual dimorphism. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Our results suggest the need to consider sex-stratified analyses for future studies in order to shed light into possible sex-specific molecular mechanisms.

genomics↗

bioRxiv2019

Assessment of DNA methylation differences between carriers of APOE ε4 and APOE ε2

BACKGROUNDThe Apolipoprotein E (APOE) {varepsilon}4 allele is the strongest genetic risk factor for late onset Alzheimers disease, while the {varepsilon}2 allele confers protection. Previous studies report differential DNA methylation of APOE between {varepsilon}4 and {varepsilon}2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODSUsing the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimers disease-free APOE {varepsilon}4 (n=2469) and {varepsilon}2 (n=1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTSWe obtained replicated evidence for DNA methylation differences in a ~169kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 x 10-100[≤]P[≤]2.44 x 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 x 10-4[≤]P[≤]3.01 x 10-2). Pathway and meQTL analyses implicated lipid-related processes and high density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONSAPOE {varepsilon}4 vs. {varepsilon}2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

genetics↗

bioRxiv2019

Birth weight predicts psychiatric and physical health, cognitive function, and DNA methylation differences in an adult population

BackgroundThe Developmental Origins of Adult Disease (DOAD) theory predicts that prenatal and early life events shape adult health outcomes. Birth weight is a useful indicator of the foetal experience, and has been associated with multiple adult health outcomes. DNA methylation (DNAm) is one plausible mechanism behind the relationship of birth weight to adult health. MethodsThe Generation Scotland study allows data linkage to historic Scottish birth cohorts, and birth records held through the NHS Information and Statistics Division. Data linkage with these sources yielded a sample of 4, 710 individuals. Health measures were related to birth weight in regression models. An epigenome-wide association study (EWAS) was performed in a subgroup (n=1, 395), relating adult DNAm from whole blood to birth weight, with replication in an independent sample (n=362). Associations between birth weight and epigenetic clocks were also assessed. FindingsHigher birth weight was significantly associated with reduced incidence of depression and osteoarthritis, higher body mass index, and higher general intelligence (absolute standardised effect size range 0{middle dot}04 to 0{middle dot}30, p(FDR)<0{middle dot}05). Meta-analysis of discovery and replication EWAS studies yielded one genome-wide significant CpG site (p=5{middle dot}97x10-9), cg00966482. Significant associations between birth weight and Grim Age (p=0{middle dot}0014) and DNAm-derived telomere length (p=3{middle dot}3x10-4) are also described. InterpretationOur results demonstrate associations between birth weight and adult health outcomes, with particularly striking effects for depression risk. It also provides support for an association between birth weight and DNAm, describing the first significant EWAS site associated with birth weight in an adult sample. FundingWellcome Trust Strategic Award 104036/Z/14/Z Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSThe associations between birth weight and various adult health outcomes have been well established. DNA methylation is a plausible mechanism through which early life experiences may continue to affect health throughout the lifecourse; however, evidence for birth weight associations with DNA methylation in adulthood has not yet been robustly established. This is likely due to small sample sizes of previous samples, as well as the use of poor-quality birth weight data, such as binary low/normal variables or retrospective self-report. Alternatively, work has attempted to describe the persistence into adulthood of DNA methylation at sites identified at birth. Added value of this studyWe investigated genome-wide differential DNA methylation patterns from whole blood using data linkage-derived, continuous birth weight data, in the largest reported adult sample (n=1, 395) with replication (n=362) and meta-analysis. Meta-analysis revealed one epigenome-wide significant CpG site, to our knowledge the first significant EWAS result reported for birth weight in a an adult sample. In addition, we found associations between birth weight and GrimAge and a DNA methylation-derived measure of telomere length, demonstrating accelerated biological ageing in lower birth weight individuals. Together, these results suggest differential methylation exists in adulthood related to birth weight, and this may be relevant to health and mortality. Implications of all the available evidenceAlthough CpG sites differentially methylated with birth weight at parturition may not remain so throughout life, the adult epigenome may still provide information on the impact of birth weight on health outcomes. The adult epigenome, therefore, may represent a useful archive of the foetal experience which results in birth weight variability, and this information may provide clinically useful information in mid-life.

genomics↗

bioRxiv2019

Proteome-by-phenome Mendelian Randomisation detects 38 proteins with causal roles in human diseases and traits

Target identification remains a crucial challenge in drug development. To enable unbiased detection of proteins and pathways that have a causal role in disease pathogenesis or progression, we propose proteome-by-phenome Mendelian Randomisation (P2MR). We first detected genetic variants associated with plasma concentration of 249 proteins. We then used 64 replicated variants in two-sample Mendelian Randomisation to quantify evidence of a causal role for each protein across 846 phenotypes: this yielded 509 robust protein-outcome links. P2MR provides substantial promise for drug target prioritisation. We provide confirmatory evidence for a causal role for the proteins encoded at multiple cardiovascular disease risk loci (FGF5, IL6R, LPL, LTA), and discovered that intestinal fatty acid binding protein (FABP2) contributes to disease pathogenesis. Additionally, we find and replicate evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia. Our results provide specific prediction of the effects of changes of plasma protein concentration on complex phenotypes in humans.

genomics↗

bioRxiv2018

Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD

BackgroundThe causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850K Illumina EPIC array in the largest single population sample to date.\n\nMethodsEpigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (N=3,791; 274 COPD cases and 2,928 controls). In independent COPD incidence data (N=150), significantly differentially methylated sites (DMSs; p<3.6x10-8) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (N=895) and prediction (N=178) results.\n\nFindingsWe identified 29 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p<0.05) in independent GS:SFHS (p=0.014) and LBC1936 (p=0.018) datasets by adding DMSs to a clinical model.\n\nInterpretationIdentification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk.\n\nFundingWellcome Trust Strategic Award 10436/Z/14/Z.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched for articles in PubMed published in English up to July 25, 2018, with the search terms \"DNA methylation\" and \"respiratory function\", or \"COPD\". We found some evidence for association between differential DNA methylation and both respiratory function and COPD. Of the twelve previous studies identified, eight used peripheral blood samples (sample size [N] range = 100-1,085) and four used lung tissue samples (N range = 24-160). The number of CpG loci analysed range from 27,578 to 485,512. These studies have not identified consistent changes in methylation, most likely due to a combination of factors including small sample sizes, technical issues, phenotypic definitions, and study design. In addition, no previous study has: analysed a sample from a large single cohort; used the recently released Illumina EPIC array (which assesses ~850,000 CpG loci); adjusted methylation data and phenotype for smoking history, or used both prevalent and incident COPD electronic health record data.\n\nAdded value of this studyTo our knowledge, this is the largest single cohort epigenome-wide association study (EWAS) of respiratory function and COPD to date (N=3,791). After applying stringent genome-wide significance criteria (P <3.6x10-8), we found that DNA methylation levels at 29 CpG sites in peripheral blood were associated with respiratory function or COPD. Of these 29, seven were testable in an independent population sample: all seven showed consistent direction of effect between the two samples and three showed replication (p<0.007 [0.05/7 CpG sites tested]). Our results suggest that adjustment of both the phenotypic and the DNA methylation probe data for smoking history, which has not been carried out in previous studies, reduces the confounding effects of smoking, identifies larger numbers of associations, and reduces the heterogeneity of effects across smoking strata. We used gene set enrichment and pathway analyses, together with an approach that combines DNA methylation results with gene expression data to provide evidence for enrichment of differentially methylated sites in genes linked to alternative splicing, and JAK-STAT signalling and axon guidance. Finally, we demonstrated that the inclusion of DNA methylation data improves COPD risk prediction over established clinical variables alone in two independent datasets.\n\nImplications of all the available evidenceThere is now accumulating evidence that DNA methylation in peripheral blood is associated with respiratory function and COPD.\n\nOur study has shown that DNA methylation levels at 29 CpG sites are robustly associated with respiratory function and COPD, provide mechanistic insights, and can improve prediction of COPD risk. Further studies are warranted to improve understanding of the aetiology of COPD and to assess the utility of DNA methylation profiling in the clinical management of this condition.

genomics↗

bioRxiv2018

The genetic architecture of hair colour in the UK population

We have extensively mapped the genes responsible for hair colour in the UK population. MC1R mutations are well established as the principal genetic cause of red hair colour, but with variable penetrance. We find variation at genes encoding its agonist (POMC), inverse agonist (ASIP) and other loci contribute to red hair and demonstrate epistasis between MC1R and some of these loci. Blonde hair is associated with over 200 loci, and we find a genetic continuum from black through dark and light brown to blonde. Many of the associated genes are involved in hair growth or texture, emphasising the cellular connections between keratinocytes and melanocytes in the determination of hair colour.

genetics↗

bioRxiv2017

Indirect assortative mating for human disease and longevity

Phenotypic correlations of couples for phenotypes evident at the time of mate choice, like height, are well documented. Similarly, phenotypic correlations among partners for traits not directly observable at the time of mate choice, like longevity or late-onset disease status, have been reported. Partner correlations for longevity and late-onset disease are comparable in magnitude to correlations in 1st degree relatives. These correlations could arise as a consequence of convergence after mate choice, due to initial assortment on observable correlates of one or more risk factors (e.g. BMI), referred to as indirect assortative mating, or both. Using couples from the UK Biobank cohort, we show that longevity and disease history of the parents of white British couples is correlated. The correlations in parental longevity are replicated in the FamiLinx cohort. These correlations exceed what would be expected due to variations in lifespan based on year and location of birth. This suggests the presence of assortment on factors correlated with disease and lifespan, which show correlations across generations. Birth year, birth location, Townsend Deprivation Index, height, waist to hip ratio, BMI and smoking history of UK Biobank couples explained ~70% of the couple correlation in parental lifespan. For cardiovascular diseases, in particular hypertension, we find significant correlations in genetic values among partners, which support a model where partners assort for risk factors genetically correlated with cardiovascular disease. Identifying the factors that mediate indirect assortment on longevity and human disease risk will help to unravel what factors affect human disease and ultimately longevity.

genetics↗

bioRxiv2017

An atlas of genetic associations in UK Biobank

Genome-wide association studies have revealed many loci contributing to the variation of complex traits, yet the majority of loci that contribute to the heritability of complex traits remain elusive. Large study populations with sufficient statistical power are required to detect the small effect sizes of the yet unidentified genetic variants. However, the analysis of huge cohorts, like UK Biobank, is complicated by incidental structure present when collecting such large cohorts. For instance, UK Biobank comprises 107,162 third degree or closer related participants. Traditionally, GWAS have removed related individuals because they comprised an insignificant proportion of the overall sample size, however, removing related individuals in UK Biobank would entail a substantial loss of power. Furthermore, modelling such structure using linear mixed models is computationally expensive, which requires a computational infrastructure that may not be accessible to all researchers. Here we present an atlas of genetic associations for 118 non-binary and 599 binary traits of 408,455 related and unrelated UK Biobank participants of White-British descent. Results are compiled in a publicly accessible database that allows querying genome-wide association summary results for 623,944 genotyped and HapMap2 imputed SNPs, as well downloading whole GWAS summary statistics for over 30 million imputed SNPs from the Haplotype Reference Consortium panel. Our atlas of associations (GeneATLAS, http://geneatlas.roslin.ed.ac.uk) will help researchers to query UK Biobank results in an easy way without the need to incur in high computational costs.

genomics↗