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Canela-Xandri, O.

Publications and source records attributed to Canela-Xandri, O..

10 recordsLinked to original sources

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↗

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↗

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↗

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↗

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↗

TiFoSi: an Efficient Tool for Mechanobiology Simulations of Epithelia

AboutThis document is an extended version of the main text where some details and results are fleshed out. Further details can be also found in the manual of the code and at TiFoSis website: http://tifosi.thesimbiosys.com. MotivationEmerging phenomena in developmental biology and tissue engineering are the result of feedbacks between gene expression and cell biomechanics. In that context, in silico experiments are a powerful tool to understand fundamental mechanisms and to formulate and test hypotheses. ResultsHere we present TiFoSi, a computational tool to simulate the cellular dynamics of planar epithelia. TiFoSi allows to model feedbacks between cellular mechanics and gene expression (either in a deterministic or a stochastic way), the interaction between different cell populations, the custom design of the cell cycle and cleavage properties, the protein number partitioning upon cell division, and the modeling of cell communication (juxtacrine and paracrine signalling). TiFoSi fills a niche in the field of software solutions to simulate the mechanobiology of epithelia because of its functionalities, computational efficiency, and its user-friendly approach to design in silico experiments using XML configuration files. Availabilityhttp://tifosi.thesimbiosys.com Contactjbuceta@lehigh.edu

systems biology↗

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↗

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↗

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↗

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↗