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Salter-Townshend, M.

Publications and source records attributed to Salter-Townshend, M..

11 recordsLinked to original sources

Detecting genomic regions enriched for reciprocal recombination in autism spectrum disorder

Meiotic recombination is an important means of increasing genetic diversity by generating novel haplotypes in a population. Recombination separates linked loci extremely slowly in some regions, therefore genetic variants in high linkage disequilibrium may become co-adapted. Reciprocal recombination that separates co-adapted variants may generate a deleterious de novo haplotype that contributes to disease. We developed statistical methods to detect genomic regions of recombination excess in two different family-based study designs. We identified recombination in the Simons Simplex Collection in 273 simplex families with one child with autism spectrum disorder (ASD) and at least two unaffected children, in which recombinations can be mapped to the proband and contrasted with the recombination counts in unaffected siblings; and in 1,802 families with two children, where the number of recombinations identified can be contrasted with the expectation from a reference recombination map. Both strategies revealed a tail of low p-values for loci of interest that contrasted with the rest of the distribution. Permutation and bootstrap tests did not identify genome-wide primary findings in either cohort, but the most significant three-child cohort locus of recombination excess (between cadherin genes CDH4 and CDH26) replicated in the two-child cohort (p=0.01). While this replication strategy was not defined a priori, five of the most recombination enriched bins identified candidate ASD genes (p=0.02; WWOX, ADAMTS16, INSR, ADARB2, and HS6ST1). Since the six identified loci were not identified as regions of high de novo copy number variation in the study cohort and no CNVs were detected in any of the recombinant probands in the identified regions, they represent candidates for reciprocal recombinations generating unfavourable haplotypes for these genes. This study highlights a previously unidentified source of clinical genetic variability contributing to the molecular aetiology of ASD. AUTHOR SUMMARYAutism spectrum disorder (ASD) is a constellation of neurodevelopmental disabilities characterised by deficits in social communication and repetitive patterns of behaviour. While ASD is highly heritable, its genetic basis is complex and poorly understood. While some highly penetrant types of genetic variation have been identified, most people with ASD carry a large number of variants that each contribute a small amount to their overall phenotype. In addition to mutations in individual genes, changes in the configuration of genes along a chromosome may contribute to ASD. Here, we describe a method for identifying regions where such new configurations have occurred through recombination and attempt to find regions where such changes are more common in autistic children than in their non-autistic siblings. We explore recombination as a source of genetic variation contributing to autism, which has potential to inform clinicians in providing services to autistic people and their families.

genetics↗

Integrative genomics identifies candidate genes underlying trypanotolerance in hybrid African cattle

Integrative genomics combines data from different omic sources to link genotypes and phenotypes with the aim of unravelling biological networks and pathways that undergird complex traits, particularly with respect to disease. In this respect, integrative genomics using population and functional genomic data can be employed to understand evolutionary processes that have shaped adaptation to infectious diseases in domestic cattle. This approach can be particularly informative for African cattle, which exhibit a complex mosaic of Bos taurus (taurine) and Bos indicus (indicine) genomic ancestry. Some African taurine populations have an important evolutionary adaptation known as trypanotolerance, a genetically determined tolerance of infection by trypanosome parasites (Trypanosoma spp.) that cause African animal trypanosomiasis (AAT) disease. AAT is one of the largest constraints to livestock production in sub-Saharan Africa and causes a financial burden of approximately $4.5 billion annually. In this study we identified putative candidate genes underlying trypanotolerance through the integration of local ancestry inference (LAI) from genome-wide SNP data for multiple trypanotolerant and trypanosusceptible hybrid cattle populations with RNA-seq and expression microarray transcriptomics data from multiple tissues collected across time course trypanosome infection experiments. These candidate genes included AGO2, CBL, CNOT1, EDN1, IL1B, NFKB1, RIPK1, and TRAF2. Functional analysis of the gene set outputs from this work highlighted GO terms associated with the immune system (including the major histocompatibility complex - MHC) and cell signalling processes. These results signpost future work to elucidate the cellular networks and pathways that drive trypanotolerance. Author SummaryIntegrative genomics combines different types of data to identify links between genes and traits, particularly with respect to disease. In this respect, integrative genomics can be used to understand the admixture and adaptation to infectious diseases that have shaped the genomes of domestic cattle. This is particularly noticeable in the case of African cattle, which form a complex mosaic of Bos taurus (taurine) and Bos indicus (indicine) ancestry. Some African taurine populations exhibit an evolutionary adaptation known as trypanotolerance, a genetically determined tolerance of infection by trypanosome parasites (Trypanosoma spp.) that cause African animal trypanosomiasis (AAT) disease. AAT is one of the largest constraints to livestock production in sub-Saharan Africa and causes a financial burden of approximately $4.5 billion annually. In this study we identify potential candidate genes underlying trypanotolerance through integration of subchromosomal genomic ancestry data from multiple trypanotolerant and trypanosusceptible hybrid cattle populations with gene expression data from multiple tissues collected across time course trypanosome infection experiments.

genomics↗

Random subsamples of animal populations can reveal intrinsic differences in sociality with key implications in ecology, conservation and disease transmission

Animal populations are under mounting stress from the dual threats of climate change and rapid global human population growth, raising significant concerns about declining wildlife and the rising risk of zoonotic diseases. In many species, social interactions can be a highly plastic suite of behaviours that are responsive to these disturbances and are consequential to other processes like disease transmission and population dynamics. Studying social interactions can be challenging in that researchers often rely on wildlife population subsamples due to practical constraints and costs, which can introduce biases in the reliability of social network metrics. We investigated the extent to which subsamples can depict intrinsic characteristics of wildlife populations using data from three distinct species: peri-urban fallow deer, Alpine ibex and Angolan giraffe. We showed that random subsamples of these populations could still reveal differences in their social behaviour, indicating that, as long as researchers have a reliable estimate of population size, subsampling animal populations can be an effective and precise method to infer their sociality and offer valuable empirical data for management, conservation and zoonotic disease ecology. Furthermore, we demonstrate that non-random sampling, influenced for instance by animal personality and related trappability, can introduce significant biases in social network estimates. These findings underscore the importance of accounting for sampling biases in social network analysis and offer a robust framework for using partial networks in ecological studies and conservation management.

ecology↗

Genome-wide local ancestry and the functional consequences of admixture in African and European cattle populations

Bos taurus (taurine) and Bos indicus (indicine) cattle diverged at least 150,000 years ago and, since that time, substantial genomic differences have evolved between the two lineages. During the last two millennia, genetic exchange in Africa has resulted in a complex tapestry of taurine-indicine ancestry, with most cattle populations exhibiting varying levels of admixture. Similarly, there are several Southern European cattle populations that also show evidence for historical gene flow from indicine cattle, the highest levels of which are found in the Central Italian White breeds. Here we use two different software tools (MOSAIC and ELAI) for local ancestry inference (LAI) with genome-wide high-and low-density SNP array data sets in hybrid African and Italian cattle populations and obtained broadly similar results despite critical differences in the two LAI methodologies used. Our analyses identified genomic regions with elevated levels of retained or introgressed ancestry from the African taurine, European taurine, Asian indicine lineages. Functional enrichment of genes underlying these ancestry peaks highlighted biological processes relating to immunobiology and olfaction, some of which may relate to differing susceptibilities to infectious diseases, including bovine tuberculosis, East Coast fever, and tropical theileriosis. Notably, for retained African taurine ancestry in admixed trypanotolerant cattle we observed enrichment of genes associated with haemoglobin and oxygen transport. This may reflect positive selection of genomic variants that enhance control of severe anaemia, a debilitating feature of trypanosomiasis disease, which severely constrains cattle agriculture across much of sub-Saharan Africa.

genomics↗

Using an agent based model to inform sampling design for animal social network analysis

Producing accurate and reliable inference from animal social network analysis depends on the sampling strategy during data collection. An increasing number of studies now use large-scale deployment of GPS tags to collect data on social behaviour. However, these can rarely capture whole populations or sample at very high frequencies. To date, little guidance exists when making prior decisions about how to maximise sampling effort to ensure that the data collected can be used to construct reliable social networks. We use a simulation-based approach to generate a functional understanding of how the accuracy of various network metrics is affected by decisions along three fundamental axes of sampling effort: coverage, frequency and duration. Researchers often face trade-offs between these three sampling axes, for example due to resource limitations, and thus we identify which axes need to be prioritised as well as the effectiveness of different deployment and analytical strategies. We found that the sampling level across the three axes has different consequences depending on the social network metrics that are estimated. For example, global metrics are more sensitive than local metrics to the proportion of the population tracked, and that among local metrics some are more sensitive to sampling duration than others. Our research demonstrates the importance of establishing an optimal sampling configuration for drawing relevant and robust inferences, and presents a range of practical advice for designing GPS based sampling strategies in accordance with the research objectives.

ecology↗

aniSNA : An R package to assess bias and uncertainty in social networks obtained from animals sampled via direct observations or satellite telemetry

Animal social network analysis using GPS telemetry datasets provides insights into group dynamics, social structure, and interactions of the animal communities. It aids conservation by characterizing key aspects of animal sociality - including spatially explicit information on where sociality occurs (e.g., habitats, migratory corridors), contributing to informed management strategies for wildlife populations. The aniSNA package provides functions to assess and leverage data collected by sampling a subset of an animal population to perform social network analysis. The methodologies offered in this package are compatible with a variety of location and grouping data, collected through various means (e.g., direct observations, biologgers), however, they are particularly well suited to autocorrelated data streams such as data collected through GPS telemetry radio collars. The techniques assess the datas suitability to extract reliable statistical inferences from social networks and compute uncertainty estimates around the network metrics in the scenario where a fraction of the population is monitored. The package functions are user-friendly and allow for the implementation of pre-network data permutations for auto-correlated data streams, sensitivity analysis under downsampling, bootstrapping to establish confidence intervals for global and node-level network metrics, and correlation and regression analysis to assess the robustness of node-level network metrics. Using this package, animal ecologists will be able to compute social network metrics, both at the population and individual level, assess their reliability, and use such metrics in further analyses, e.g., to study social network variation within and across populations or link individual sociality to life history. This software also has plotting features that allow for visual interpretation of the findings.

animal behavior and cognition↗

Genomic Insights into the Population History and Adaptive Traits of Latin American Criollo Cattle

Criollo cattle, descendants of animals brought by Iberian colonists to the Americas, have been subject to centuries of natural and human-mediated selection in novel tropical agroecological zones. Consequently, these breeds have evolved distinct characteristics such as resistance to disease and exceptional heat tolerance. In addition to European taurine (Bos taurus) ancestry, it has been proposed that gene flow from African taurine and Asian indicine (Bos indicus) cattle has shaped the ancestry of Criollo cattle. In this study, we analysed Criollo breeds from Colombia and Venezuela using whole-genome sequencing (WGS) and single-nucleotide polymorphism (SNP) array data to examine population structure and admixture at high resolution. Analysis of genetic structure and ancestry components provided evidence for African taurine and Asian indicine admixture in Criollo cattle. In addition, using WGS data, we detected selection signatures associated with a myriad of adaptive traits, revealing genes linked to thermotolerance, reproduction, fertility, immunity, and distinct coat and skin coloration traits. This study underscores the remarkable adaptability of Criollo cattle and highlights the genetic richness and potential of these breeds in the face of climate change, habitat flux, and disease challenges. Further research is warranted to leverage these findings for more effective and sustainable cattle breeding programmes.

genomics↗

Curbing zoonotic disease spread in multi-host-species systems will require integrating novel data streams and analytical approaches: evidence from a scoping review of bovine tuberculosis

BackgroundZoonotic diseases represent a significant societal challenge in terms of their health and economic impacts. One Health approaches to managing zoonotic diseases are becoming more prevalent, but require novel thinking, tools and cross-disciplinary collaboration. Bovine tuberculosis (bTB) is one example of a costly One Health challenge with a complex epidemiology involving human, domestic animal, wildlife and environmental factors, which require sophisticated collaborative approaches. ObjectiveWe undertook a scoping review of multi-host bTB epidemiology to identify recent trends in species publication focus, methodologies, scales and One Health approaches. We aimed to identify research gaps where novel research could provide insights to inform control policy, for bTB and other zoonoses. ResultsThe review included 167 articles. We found different levels of research attention across episystems, with a significant proportion of the literature focusing on the badger-cattle-TB episystem, with far less attention given to the multi-host episystems of southern Africa. We found a limited number of studies focusing on management solutions and their efficacy, with very few studies looking at modelling exit strategies. Surprisingly, only a small number of studies looked at the effect of human disturbances on the spread of bTB involving wildlife hosts. Most of the studies we reviewed focused on the effect of badger vaccination and culling on bTB dynamics with few looking at how roads, human perturbations and habitat change may affect wildlife movement and disease spread. Finally, we observed a lack of studies considering the effect of weather variables on bTB spread, which is particularly relevant when studying zoonoses under climate change scenarios. ConclusionsSignificant technological and methodological advances have been applied to bTB episystems, providing explicit insights into its spread and maintenance across populations. We identified a prominent bias towards certain species and locations. Generating more high-quality empirical data on wildlife host distribution and abundance, high-resolution individual behaviours and greater use of mathematical models and simulations are key areas for future research. Integrating data sources across disciplines, and a "virtuous cycle" of well-designed empirical data collection linked with mathematical and simulation modelling could provide additional gains for policy-makers and managers, enabling optimised bTB management with broader insights for other zoonoses.

ecology↗

Assessing bias and robustness of social network metrics using GPS based radio-telemetry data

O_LISocial network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, dynamical processes, and transmission events such as the spread of disease. However, the accuracy of estimated social network metrics depends on the proportion of individuals sampled, actual sample size, and frequency of observations. Robustness of network metrics derived from a sample has thus far been examined through various simulation studies. However, simulated data do not necessarily reflect the nuances of real empirical data. C_LIO_LIWe used some of the largest available GPS telemetry relocation datasets from five species of ungulates characterised by different behavioural and ecological traits and living in distinct environmental contexts to study the bias and robustness of social network metrics. We introduced novel statistical methods to quantify the uncertainty in network metrics obtained from a partial population suited to autocorrelated data such as telemetry relocations. We analysed how social network metrics respond to down-sampling from the observed data and applied pre-network data permutation techniques, a bootstrapping approach, correlation, and regression analyses to assess the stability of network metrics when based on samples of a population. C_LIO_LIWe found that global network metrics like density remain robust when the sample size is lowered, whereas some local network metrics, such as eigenvector centrality, are entirely unreliable when a large proportion of the population is not monitored. We show how to construct confidence intervals around the point estimates of these metrics representing the uncertainty as a function of the number of nodes in the network. C_LIO_LIOur uncertainty estimates enable the statistical comparison of social network metrics under different conditions, such as analysing daily and seasonal changes in the density of a network. Despite the striking differences in the ecology and sociality among the five different ungulate species, the various social network metrics behave similarly under downsampling, suggesting that our approach can be applied to a wider range of species across vertebrates. Our methods can guide methodological decisions about animal social network research (e.g., sampling design and sample sizes) and allow more accurate ecological inferences from the available data. C_LI

animal behavior and cognition↗

Genome-wide local ancestry and direct evidence for mitonuclear co-adaptation in African hybrid cattle populations (Bos taurus/indicus)

The phenotypic diversity of African cattle reflects adaptation to a wide range of agroecological conditions, human-mediated selection preferences, and complex patterns of admixture between the humpless Bos taurus (taurine) and humped Bos indicus (zebu) subspecies, which diverged 150-500 thousand years ago. Despite extensive admixture, all African cattle possess taurine mitochondrial haplotypes, even populations with significant zebu biparental and male uniparental nuclear ancestry. This has been interpreted as the result of a human-mediated dispersal ultimately stemming from zebu bulls imported from South Asia during the last three millennia. Here we assess whether ancestry at mitochondrially-targeted nuclear genes in African admixed cattle is impacted by mitonuclear functional interactions. Using high-density SNP data, we find evidence for mitonuclear coevolution across hybrid African cattle populations with a significant increase of taurine ancestry at mitochondrially-targeted nuclear genes. Our results, therefore, support the hypothesis of incompatibility between the taurine mitochondrial genome and the zebu nuclear genome. GRAPHICAL SUMMARY O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/457829v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1031fb0org.highwire.dtl.DTLVardef@1575faorg.highwire.dtl.DTLVardef@f4795corg.highwire.dtl.DTLVardef@4ba74e_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights* Using high-density genome-wide SNP data, we present evidence for mitonuclear coevolution in hybrid African cattle. * We observe a significant increase of taurine ancestry across multiple hybrid populations at mitochondrially-targeted nuclear genes. * Our results provide support for the hypothesis of mitonuclear incompatibility between the zebu nuclear genome and the taurine mitochondrial genome.

evolutionary biology↗

Fine-scale Inference of Ancestry Segments without Prior Knowledge of Admixing Groups

We present an algorithm for inferring ancestry segments and characterizing admixture events, which involve an arbitrary number of genetically differentiated groups coming together. This allows inference of the demographic history of the species, properties of admixing groups, identification of signatures of natural selection, and may aid disease gene mapping. The algorithm employs nested hidden Markov models to obtain local ancestry estimation along the genome for each admixed individual. In a range of simulations, the accuracy of these estimates equals or exceeds leading existing methods that return local ancestry. Moreover, and unlike these approaches, we do not require any prior knowledge of the relationship between sub-groups of donor reference haplotypes and the unseen mixing ancestral populations. Instead, our approach infers these in terms of conditional \"copying probabilities\". In application to the Human Genome Diversity Panel we corroborate many previously inferred admixture events (e.g. an ancient admixture event in the Kalash). We further identify novel events such as complex 4-way admixture in San-Khomani individuals, and show that Eastern European populations possess 1 - 5% ancestry from a group resembling modern-day central Asians. We also identify evidence of recent natural selection favouring sub-Saharan ancestry at the HLA region, across North African individuals. We make available an R and C++ software library, which we term MOSAIC (which stands for MOSAIC Organises Segments of Ancestry In Chromosomes).

genomics↗