Biology subjects

Lawson, D. J.

Publications and source records attributed to Lawson, D. J..

13 recordsLinked to original sources

bioRxiv2023

Heritability of complex traits in sub-populations experiencing bottlenecks and growth

1Populations that have experienced a bottleneck are regularly used in Genome Wide Association Studies (GWAS) to investigate variants associated with complex traits. It is generally understood that these isolated sub-populations may experience high frequency of otherwise rare variants with large effect size, and therefore provide a unique opportunity to study said trait. However, the demographic history of the population under investigation affects all SNPs that determine the complex trait genome-wide, changing its heritability and genetic architecture. We use a simulation based approach to identify the impact of the demographic processes of drift, expansion, and migration on the heritability of complex trait. We show that demography has considerable impact on complex traits. We then investigate the power to resolve heritability of complex traits in GWAS studies subjected to demographic effects. We find that demography is an important component for interpreting inference of complex traits and has a nuanced impact on the power of GWAS. We conclude that demographic histories need to be explicitly modelled to properly quantify the history of selection on a complex trait.

genetics↗

bioRxiv2023

Leveraging fine-scale population structure reveals conservation in genetic effect sizes between human populations across a range of human phenotypes

An understanding of genetic differences between populations is essential for avoiding confounding in genome-wide association studies (GWAS) and understanding the evolution of human traits. Polygenic risk scores constructed in one group perform poorly in highly genetically-differentiated populations, for reasons which remain controversial. We developed a statistical ancestry inference pipeline able to decompose ancestry both within and between countries, and applied it to the UK Biobank data. This identifies fine-scale patterns of genetic relatedness not captured by standard and widely used principal components (PCs), and allows fine-scale population stratification correction that removes both false positive and false negative associations for traits with geographic correlations. We also develop and apply ANCHOR, an approach leveraging segments of distinct ancestries within individuals to estimate similarity in underlying causal effect sizes between groups, using an existing PGS. Applying ANCHOR to >8000 people of mixed African and European ancestry, we demonstrate that estimated causal effect sizes are highly similar across these ancestries for 26 of 29 quantitative molecular and non-molecular phenotypes (mean correlation 0.98 +/-0.08), providing evidence that gene-environment and gene-gene interactions do not play major roles in the poor prediction of European-ancestry PRS scores in African populations for these traits, contradicting previous findings. Instead our results provide optimism that shared causal mutations operate similarly in different groups, focussing the challenge of improving GWAS "portability" between groups on joint fine-mapping.

genetics↗

bioRxiv2023

To unscramble an egg: admixed captive breeding populations can be rescued using local ancestry information

This paper asks the question: can genomic information recover a species that is already on the pathway to extinction due to genetic swamping from a related and more numerous population? We show that whole genome sequencing can be used to identify and remove hybrid segments of DNA, when used as part of the breeding policy in a captive breeding program. The proposed policy uses a generalised measure of kinship or heterozygosity accounting for local ancestry, that is, whether a specific genetic location was inherited from from the target of conservation. We then show that optimising these measures would minimise undesired ancestry whilst also controlling undesired kinship or heterozygosity respectively, in a simulated breeding population. The process is applied to real data representing the hybridized Scottish wildcat breeding population, with the result that it should be possible to breed out the domestic cat ancestry. The ability to reverse introgression is a powerful new tool brought about from both sequencing and computational advances in ancestry estimation. Since it works best when applied early in the process, important decisions need to be made about which genetically distinct populations should benefit from it and which should be left to reform into a single population.

genetics↗

bioRxiv2022

HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype

SummaryHaplotype Trend Regression with eXtra flexibility (HTRX) is an R package which uses cross-validation to learn sets of interacting features for a prediction. HTRX identifies haplotypes composed of non-contiguous single nucleotide polymorphisms (SNPs) associated with a phenotype. To reduce the space and computational complexity when investigating many features, we constrain the search by growing good feature sets using Cumulative HTRX, and limit the maximum complexity of a feature set. AvailabilityHTRX is implemented in R and is available under GPL-3 license from CRAN and Github at: https://github.com/YaolingYang/HTRX. Contactyaoling.yang@bristol.ac.uk

bioinformatics↗

bioRxiv2022

Genetic risk for Multiple Sclerosis originated in Pastoralist Steppe populations

Multiple sclerosis (MS) is a modern neuro-inflammatory and -degenerative disease, which is most prevalent in Northern Europe. Whilst it is known that inherited risk to MS is located within or within close proximity to immune genes, it is unknown when, where and how this genetic risk originated 1. By using the largest ancient genome dataset from the Stone Age 2, along with new Medieval and post-Medieval genomes, we show that many of the genetic risk variants for MS rose to higher frequency among pastoralists located on the Pontic Steppe, and were brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the Steppe population, and later in Europe, likely driven by pathogenic challenges coinciding with dietary, lifestyle, and population density changes. This study highlights the critical importance of this period as a determinant of modern immune responses and its subsequent impact on the risk of developing MS in a changing environment.

evolutionary biology↗

bioRxiv2022

The Selection Landscape and Genetic Legacy of Ancient Eurasians

The Holocene (beginning [~]12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical, and mental health of present-day populations. Using a dataset of >1600 imputed ancient genomes 1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify major selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported, and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in >400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic, and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, while risk alleles for diabetes and Alzheimers disease are enriched for Western Hunter-gatherer ancestry. Our results suggest that ancient selection and migration were major contributors to the distribution of phenotypic diversity in present-day Europeans.

evolutionary biology↗

bioRxiv2021

Evidence of positive and negative selection associated with DNA methylation

Signatures of negative selection are pervasive amongst complex traits and diseases. However, it is unclear whether such signatures exist for DNA methylation (DNAm) that has been proposed to have a functional role in disease. We estimate polygenicity, SNP-based heritability and model the joint distribution of effect size and minor allele frequency (MAF) to estimate a selection coefficient (S) for 2000 heritable DNAm sites in 1774 individuals from the Avon Longitudinal Study of Parents and Children. Additionally, we estimate S for meta stable epi alleles and DNAm sites associated with aging and mortality, birthweight and body mass index. Quantification of MAF-dependent genetic architectures estimated from genotype and DNAm reveal evidence of positive (S > 0) and negative selection (S < 0) and confirm previous evidence of negative selection for birthweight. Evidence of both negative and positive selection highlights the role of DNAm as an intermediary in multiple biological pathways with competing function.

genetics↗

bioRxiv2020

Population stratification in GWAS meta-analysis should be standardized to the best available reference datasets

Population stratification has recently been demonstrated to bias genetic studies even in relatively homogeneous populations such as within the British Isles. A key component to correcting for stratification in genome-wide association studies (GWAS) is accurately identifying and controlling for the underlying structure present in the sample. Meta-analysis across cohorts is increasingly important for achieving very large sample sizes, but comes with the major disadvantage that each individual cohort corrects for different population stratification. Here we demonstrate that correcting for structure against an external reference adds significant value to meta-analysis. We treat the UK Biobank as a collection of smaller studies, each of which is geographically localised. We provide software to standardize an external dataset against a reference, provide the UK Biobank principal component loadings for this purpose, and demonstrate the value of this with an analysis of the geographically sampled ALSPAC cohort.

genetics↗

bioRxiv2020

Genetic drift from the out-of-Africa bottleneck leads to biased estimation of genetic architecture and selection

Most complex traits evolved in the ancestors of all modern humans and have been under negative or balancing selection to maintain the distribution of phenotypes observed today. Yet all large studies mapping genomes to complex traits occur in populations that have experienced the Out-of-Africa bottleneck. Does this bottleneck affect the way we characterise complex traits? We demonstrate using the 1000 Genomes dataset and hypothetical complex traits that genetic drift can strongly affect the joint distribution of effect size and SNP frequency, and that the bias can be positive or negative depending on subtle details. Characterisations that rely on this distribution therefore conflate genetic drift and selection. We provide a model to identify the underlying selection parameter in the presence of drift, and demonstrate that a simple sensitivity analysis may be enough to validate existing characterisations. We conclude that biobanks characterising more worldwide diversity would benefit studies of complex traits.

genetics↗

bioRxiv2019

Population genomics of the Viking world

The Viking maritime expansion from Scandinavia (Denmark, Norway, and Sweden) marks one of the swiftest and most far-flung cultural transformations in global history. During this time (c. 750 to 1050 CE), the Vikings reached most of western Eurasia, Greenland, and North America, and left a cultural legacy that persists till today. To understand the genetic structure and influence of the Viking expansion, we sequenced the genomes of 442 ancient humans from across Europe and Greenland ranging from the Bronze Age (c. 2400 BC) to the early Modern period (c. 1600 CE), with particular emphasis on the Viking Age. We find that the period preceding the Viking Age was accompanied by foreign gene flow into Scandinavia from the south and east: spreading from Denmark and eastern Sweden to the rest of Scandinavia. Despite the close linguistic similarities of modern Scandinavian languages, we observe genetic structure within Scandinavia, suggesting that regional population differences were already present 1,000 years ago. We find evidence for a majority of Danish Viking presence in England, Swedish Viking presence in the Baltic, and Norwegian Viking presence in Ireland, Iceland, and Greenland. Additionally, we see substantial foreign European ancestry entering Scandinavia during the Viking Age. We also find that several of the members of the only archaeologically well-attested Viking expedition were close family members. By comparing Viking Scandinavian genomes with present-day Scandinavian genomes, we find that pigmentation-associated loci have undergone strong population differentiation during the last millennia. Finally, we are able to trace the allele frequency dynamics of positively selected loci with unprecedented detail, including the lactase persistence allele and various alleles associated with the immune response. We conclude that the Viking diaspora was characterized by substantial foreign engagement: distinct Viking populations influenced the genomic makeup of different regions of Europe, while Scandinavia also experienced increased contact with the rest of the continent.

genetics↗

bioRxiv2018

Alcohol consumption and mate choice in UK Biobank: comparing observational and Mendelian randomization estimates

Alcohol use is correlated within spouse-pairs, but it is difficult to disentangle the effects of alcohol consumption on mate-selection from social factors or cohabitation leading to spouses becoming more similar over time. We hypothesised that genetic variants related to alcohol consumption may, via their effect on alcohol behaviour, influence mate selection. Therefore, in a sample of over 47,000 spouse-pairs in the UK Biobank we utilised a well-characterised alcohol related variant, rs1229984 in ADH1B, as a genetic proxy for alcohol use. We compared the phenotypic concordance between spouses for self-reported alcohol use with the association between an individuals self-reported alcohol use and their partners rs1229984 genotype using Mendelian randomization. This was followed up by an exploration of the spousal genotypic concordance for the variant and an analysis determining if relationship length may be related to spousal alcohol behaviour similarities. We found strong evidence that both an individuals self-reported alcohol consumption and rs1229984 genotype are associated with their partners self-reported alcohol use. The Mendelian randomization analysis found that each unit increase in an individuals weekly alcohol consumption increased their partners alcohol consumption by 0.26 units (95% C.I. 0.15, 0.38; P=1.10x10-5). Furthermore, the rs1229984 genotype was concordant within spouse-pairs, suggesting that some spousal concordance for alcohol consumption existed prior to cohabitation. Although the SNP is strongly associated with ancestry, our results suggest that this concordance is unlikely to be explained by population stratification. Overall, our findings suggest that alcohol behaviour directly influences mate selection.

genetics↗

bioRxiv2018

A machine learning approach to intensive care discharge.

ObjectiveThe primary objective is to develop an automated method for detecting patients that are ready for discharge from intensive care. DesignWe used two datasets of routinely collected patient data to test and improve upon a set of previously proposed discharge criteria. SettingBristol Royal Infirmary general intensive care unit (GICU). PatientsTwo cohorts derived from historical datasets: 1870 intensive care patients from GICU in Bristol, and 7592 from MIMIC-III (a publicly available intensive care dataset). ResultsIn both cohorts few successfully discharged patients met all of the discharge criteria. Both a random forest and a logistic classifier, trained using multiple-source cross-validation, demonstrated improved performance over the original criteria and generalised well between the cohorts. The classifiers showed good agreement on which features were most predictive of readiness-for-discharge, and these were generally consistent with clinical experience. By weighting the discharge criteria according to feature importance from the logistic model we showed improved performance over the original criteria, while retaining good interpretability. ConclusionsOur findings indicate the feasibility of the proposed approach to ready-for-discharge classification, which could complement other risk models of specific adverse outcomes in a future decision support system. Avenues for improvement to produce a clinically useful tool are identified. Strengths and Limitations of this studyO_LITraining data from multiple source domains is leveraged to produce general classifiers. C_LIO_LIThe restrictive feature representation tested could be expanded to better exploit the richness of available data and boost performance. C_LIO_LIOur approach has the potential to streamline the discharge process in cases where patient C_LIO_LIphysiology makes them clear candidates for a de-escalation of care. C_LIO_LIHigh-risk patients would require additional levels of decision support to facilitate complex discharge planning. C_LI

physiology↗

bioRxiv2017

Population Genomics Of Cryptococcus neoformans var. grubii Reveals New Biogeographic Relationships And Finely Maps Hybridization

Cryptococcus neoformans var. grubii is the causative agent of cryptococcal meningitis, a significant source of mortality in immunocompromised individuals, typically HIV/AIDS patients from developing countries. Despite the worldwide emergence of this ubiquitous infection, little is known about the global molecular epidemiology of this fungal pathogen. Here we sequence the genomes of 188 diverse isolates and characterized the major subdivisions, their relative diversity and the level of genetic exchange between them. While most isolates of C. neoformans var. grubii belong to one of three major lineages (VNI, VNII, and VNB), some haploid isolates show hybrid ancestry including some that appear to have recently interbred, based on the detection of large blocks of each ancestry across each chromosome. Many isolates display evidence of aneuploidy, which was detected for all chromosomes. In diploid isolates of C. neoformans var. grubii (serotype A/A) and of hybrids with C. neoformans var. neoformans (serotype A/D) such aneuploidies have resulted in loss of heterozygosity, where a chromosomal region is represented by the genotype of only one parental isolate. Phylogenetic and population genomic analyses of isolates from Brazil revealed that the previously African VNB lineage occurs naturally in the South American environment. This suggests migration of the VNB lineage between Africa and South America prior to its diversification, supported by finding ancestral recombination events between isolates from different lineages and regions. The results provide evidence of substantial population structure, with all lineages showing multi-continental distributions demonstrating the highly dispersive nature of this pathogen.\n\nAuthor SummaryCryptococcus neoformans var. grubii is a human fungal pathogen of immunocompromised individuals that has global clinical impact, causing half a million deaths per year. Substantial genetic substructure exists for this pathogen, with two lineages found globally (VNI, VNII) whereas a third has appeared confined to sub-Saharan Africa (VNB). Here, we utilized genome sequencing of a large set of global isolates to examine the genetic diversity, hybridization, and biogeography of these lineages. We found that while the three major lineages are well separated, recombination between the lineages has occurred, notably resulting in hybrid isolates with segmented ancestry across the genome. In addition, we showed that isolates from South America are placed within the VNB lineage, formerly thought to be confined to Africa, and that there is phylogenetic separation between these geographies that substantially expands the diversity of these lineages. Our findings provide a new framework for further studies of the dynamics of natural populations of C. neoformans var. grubii.

genomics↗