Biology subjects

Talenti, A.

Publications and source records attributed to Talenti, A..

16 recordsLinked to original sources

bioRxiv2026

Linking geography and mutation profiles across goat species

Recent studies have characterised the mutational profile across multiple mammalian species, highlighting substantial differences across lineages. However, none of these studies investigated whether mutation profiles and geography are significantly correlated. In this study, we present a multi-genome alignment spanning several Capra taxa, reconstruct the ancestral genome of Capra hircus and use it to characterize the mutational profiles across multiple Capra species by using the 1000 genomes VarGoats dataset. Results confirmed that the scale of differences among Capra species largely reflects their phylogenetic relationships, in particular with the Bezoar being genetically closer to domestic goats than to other wild species. Subsequently, we correlated the mutational profile and the geographical origin of the different individuals. In particular, ACG>ATG changes have the strongest correlation with longitude (r = -0.79, P-value = 3.02*10-204), while TCA>TGA are strongly correlated with latitude (r = -0.51, P-value = 4.30*10-63). We highlight how sequential dinucleotide mutations (SDMs) place cosmopolitan breeds closer to the sampling location, rather than the country of origin, showing how the recent relocation of cosmopolitan breeds to new continents is reshaping the genome of these animals. Finally, we used the mutational profile to predict the coordinate of origin of each animal in the dataset. In conclusion, we show the important role that geography had in shaping the genomes of domestic goats.

genomics↗

bioRxiv2026

A high-resolution atlas of cattle regulatory variants and their cross-species activity in matched human cells

Identifying causal noncoding variants underlying complex traits in cattle remains challenging because high-resolution functional maps of regulatory variation are lacking. Here we combine massively parallel reporter assays with graph genomics to measure autonomous transcriptional activity from >1.5 billion DNA fragments spanning both cattle subspecies. In primary bovine cells, we assay >15 million variants and identify >150,000 expression-modulating variants enriched at cattle eQTL and GWAS loci. This enables the refinement of broad association signals to small sets of candidate functional regulatory variants. Our haplotype-aware framework captures rare, multi-allelic and tightly linked variants poorly resolved by conventional eQTL studies, and quantifies the disproportionate impact of larger variants on transcription. Furthermore, we use these data to train a deep-learning model that successfully predicts bovine promoter activity directly from sequence. Profiling the same cattle DNA in matched primary human cells reveals widespread conservation of promoter and enhancer activity, allelic effects and regulatory grammar, supporting the transfer of annotations and models across species. However, species-dependent effects are enriched in evolutionarily young sequences and p53-family motifs, highlighting the limits to simple cross-species extrapolation. Together, these data provide a high-resolution atlas of cattle regulatory variation and a framework for prioritising causal noncoding variants for cattle trait improvement.

genetics↗

bioRxiv2026

XPCLRS: fast selection signature detection using cross-population composite likelihood ratio

SummaryThe growing size of genomic datasets poses serious computational challenges, especially for laboratories and groups with limited access to high-performance compute facilities. This problem affects a broad range of analysis, including selection signature methods used to identify genomic regions undergoing selective pressure. Many of these methods were developed with SNP arrays in mind and are often not designed with scalability as a priority. Cross-population composite likelihood ratio (XP-CLR) is one such approaches, intended to detect hard selective sweeps by comparing two groups of individuals. In this paper I introduce XPCLRS, a rust implementation of the XP-CLR selection signatures method. It can be hundreds of times faster, supports multithreading natively and produces results comparable to its original counterpart (R = 0.976). lowers the computational barrier to applying XP-CLR alongside other statistics, helping detect regions of interest, reduce false positives, and ultimately improve the robustness of genomic studies. Availability and implementationThe source code for the software freely accessible in GitHub (https://www.github.com/RenzoTale88/xpclrs). Additionally, the software is also distributed via crates.io (https://crates.io/crates/xpclrs) and docker container (https://hub.docker.com/r/tale88/xpclrs) for ease of installation. The software is released under MIT open source license. ContactE-mail: Andrea.Talenti@glasgow.ac.uk

genomics↗

bioRxiv2025

A tailored variant filtering procedure for multi-breed and multi-species unbalanced animal SNP collections

Technological advancements and decreasing costs of whole-genome sequencing have generated a huge amount of resequencing data. Large-sized datasets, spanning several species and/or populations can now be assembled easily. However, they vary widely in geographical provenance, and sample sizes, with taxonomic groups varying from single to hundreds of entries. Consequently, standard filtering approaches may bias the representation of groups or gene pools. Commonly adopted variant filters relying on minor allele frequency (MAF) and linkage disequilibrium (LD) are not adequate because LD patterns and allele frequencies differ substantially within datasets representing both local and global diversity of multiple populations and species. Thus, by using the VarGoats 1000 goat genome project, we devised a novel approach which avoids the biases of the standard filtering procedures by adopting within-population subsampling, minor allele count (MAC) and marker spacing (bp-space) as filters. Starting from a quality-filtered dataset of >28M SNPs from 1372 animals, we generated a dataset of <14M markers and 750 individuals, complying with the initial requirements and facilitating further computational steps.

bioinformatics↗

bioRxiv2025

A comprehensive water buffalo pangenome reveals extensive structural variation linked to population specific signatures of selection

Water buffalo is a cornerstone livestock species in many low- and middle-income countries, yet major gaps persist in its genomic characterization--complicated by the divergent karyotypes of its two sub-species (swamp and river). Such genomic complexity makes water buffalo a particularly good candidate for the use of graph genomics, which can capture variation missed by linear reference approaches. However, the utility of this approach to improve water buffalo has been largely unexplored. We present a comprehensive pangenome that integrates four newly generated, highly contiguous assemblies of Pakistani river buffalo with available assemblies from both sub- species. This doubles the number of accessible high-quality river buffalo genomes and provides the most contiguous assemblies for the sub-species to date. Using the pangenome to assay variation across 711 global samples, we uncovered extensive genomic diversity, including thousands of large structural variants absent from the reference genome, spanning over 140 Mb of additional sequence. We demonstrate the utility of these data by identifying putative functional indels and structural variants linked to selective sweeps in key genes involved in productivity and immune response across 26 populations. This study represents one of the first successful applications of graph genomics in water buffalo and offers valuable insights into how integrating assemblies can transform analyses of water buffalo and other species with complex evolutionary histories. We anticipate that these assemblies, and the pangenome and putative functional structural variants we have released, will accelerate efforts to unlock water buffalos genetic potential, improving productivity and resilience in this economically important species.

genomics↗

bioRxiv2025

Inferring domestic goat demographic history through ancient genome imputation

Goats were among the earliest managed animals, making them a natural model to explore the genetic consequences of domestication. However, a challenge in ancient genomic analysis is the relatively low genome coverage for most samples, limiting analysis to pseudohaploid genotypes. Genotype imputation offers potential to alleviate this limitation by improving information content and accuracy in low coverage genomes. To test this we used published high coverage (>8x) goat palaeogenomes, imputing downsampled genomes using the VarGoats dataset (1,372 individuals) as a reference panel. Measuring concordance between imputed and high coverage genotypes, we find high concordance after filtering for common (>5%), high confidence variants, with 0.5x genomes reaching >0.97 concordance. There is a trade-off between coverage, genotype probability (GP) thresholds, and genotype recovery, where higher coverage and more lenient GP thresholds result in higher recovery, and a reduction in heterozygous false-positive rates with stricter thresholds. We then imputed 36 goat palaeogenomes with [≥]0.5x coverage to examine runs-of-homozygosity (ROH) and identity-by-descent (IBD) patterns. Using a novel approach combining ROH profiles across tools, we find that among Neolithic goats, ROH increases with distance from the Zagros Mountains, suggesting a large effect of the initial dispersal of managed herds. Inbreeding levels decrease across Southwest Asia in more recent periods. IBD mirrored this pattern, with less relatedness in the early herding site of Ganj Dareh compared to higher relatedness in goats from later in the dispersal process. These findings provide insights into the genetic consequences of early goat management on demography, and confirm the utility of imputation in leveraging low coverage palaeogenomes. SignificancePaleogenomics offers crucial insight into how animals were domesticated, but poor DNA preservation in ancient remains often limits the reach of genetic analyses. We utilise a cutting-edge technique, genotype imputation, to recover missing genetic information from ancient low coverage goat genomes and shine light on their domestication process. Early domestic goats showed low overall runs-of-homozygosity (ROH) and relatedness. We find that during the Neolithic, runs-of-homozygosity (ROH) and relatedness among goats increased, likely a consequence of the movement of herds beyond their natural range by humans. Inbreeding levels decline in more recent periods, potentially due to expanded herd sizes, animal trade networks, or improved husbandry practices. These findings challenge long-standing assumptions about domestication bottlenecks and highlight how ancient DNA can be used to uncover complex evolutionary histories, even from low coverage ancient samples.

genomics↗

bioRxiv2024

The potential of regulatory variant prediction AI models to improve cattle traits

Considerable progress has been made in developing machine learning models for predicting human functional variants, but progress in livestock species has been more limited. This is despite the disproportionate potential benefits such models could have to livestock research, from improving breeding values to prioritising functional variants at trait-associated loci. A key open question is what datasets and modelling approaches are most important to close this performance gap between species. In this work we have developed a new framework for predicting regulatory variants, that includes deriving key conservation metrics in cattle for the first time, variant annotation and model training. When trained on expression quantitative trait loci (eQTL) and massively parallel reporter assay (MPRA) data for human and cattle we show that this framework has a high performance at predicting regulatory variants, with a maximum area under the receiver operating characteristic curve (AUROC) score of 0.86 in human and 0.81 in cattle. We explore various approaches to further close this performance gap, including integrating advanced DNA sequence models and generating extra chromatin data, but illustrate that the best approach would be generating improved gold-standard sets of known cattle regulatory variants. Importantly we demonstrate both the human and cattle models substantially enrich for variants linked to important traits, with up to 18-fold enrichments for functional variants observed. Consequently, with our framework developed to be applicable across species these results not only demonstrate its potential utility for fine-mapping functional variants and improving breeding values in cattle, but also its potential for wider use across animal species.

genomics↗

bioRxiv2023

The evolution and convergence of mutation spectra across mammals

Despite the key role genetic mutations play in shaping phenotypic differences between species, little is currently known about the evolution of germline mutation spectra across mammals. Domesticated species are likely particularly interesting case studies because of their high mutation rates and complex evolutionary histories, which can span multiple founding events and genetic bottlenecks. Here we have developed a new reusable workflow, nSPECTRa, that can undertake the key steps in characterising mutation spectra, from determining ancestral alleles to characterising multiple forms of variation. We apply nSPECTRa to seven species, including several that have undergone domestication, and highlight how nSPECTRa can provide important novel insights into mutation rate evolution. While mutation spectra most often show marked differences between species and even breeds, certain mutation types have risen to a high frequency in subpopulations of different species, indicative of convergent evolution in mutation rates. This includes the previously characterized TCC->TTC change enriched among European humans, which is also enriched among East Asian cattle. We show Indicine cattle are particularly interesting examples of how different mutation spectra segregate within a population and subsequently spread across the globe. Together, this work has important implications for understanding the control and evolution of mammalian mutation rates.

genetics↗

bioRxiv2023

Continent-wide genomic analysis of the African buffalo (Syncerus caffer).

The African buffalo (Syncerus caffer) is a wild bovid with a historical distribution across much of sub-Saharan Africa. Genomic analysis can provide insights into the evolutionary history of the species, and the key selective pressures shaping populations, including assessment of population level differentiation, population fragmentation, and population genetic structure. In this study we generated the highest quality de novo genome assembly (2.65 Gb, scaffold N50 69.17 Mb) of African buffalo to date, and sequenced a further 195 genomes from across the species distribution. Principal component and admixture analyses provided surprisingly little support for the currently described four subspecies, but indicated three main lineages, in Western/Central, Eastern and Southern Africa, respectively. Estimating Effective Migration Surfaces analysis suggested that geographical barriers have played a significant role in shaping gene flow and the population structure. Estimated effective population sizes indicated a substantial drop occurring in all populations 5-10,000 years ago, coinciding with the increase in human populations. Finally, signatures of selection were enriched for key genes associated with the immune response, suggesting infectious disease exert a substantial selective pressure upon the African buffalo. These findings have important implications for understanding bovid evolution, buffalo conservation and population management.

genomics↗

bioRxiv2022

Optical mapping compendium of structural variants across global cattle breeds

Structural variants (SV) have been linked to important bovine disease phenotypes, but due to the difficulty of their accurate detection with standard sequencing approaches, their role in shaping important traits across cattle breeds is largely unexplored. Optical mapping is an alternative approach for mapping SVs that has been shown to have higher sensitivity than DNA sequencing approaches. The aim of this project was to use optical mapping to develop a high-quality database of structural variation across cattle breeds from different geographical regions, to enable further study of SVs in cattle. To do this we generated 100X Bionano optical mapping data for 18 cattle of nine different ancestries, three continents and both cattle sub-species. In total we identified 13,457 SVs, of which 1,200 putatively overlap coding regions. This resource provides a high-quality set of optical mapping-based SV calls that can be used across studies, from validating DNA sequencing-based SV calls to prioritising candidate functional variants in genetic association studies and expanding our understanding of the role of SVs in cattle evolution.

genomics↗

bioRxiv2022

The conservation of human functional variants and their effects across mammals

Despite the clear potential of livestock models of human functional variants to provide important insights into the biological mechanisms driving human diseases and traits, their use to date has been limited. Generating such models via genome editing is costly and time consuming, and it is unclear which variants will have conserved effects across species. In this study we address these issues by studying naturally occurring livestock models of human functional variants. We show that orthologues of over 1.6 million human variants are already segregating in domesticated mammalian species, including several hundred previously directly linked to human traits and diseases. Models of variants linked to particular phenotypes, including metabolomic disorders and height, have been preferentially maintained across species, meaning studying the genetic basis of these phenotypes is particularly tractable in livestock. Using machine learning we demonstrate it is possible to identify human variants that are more likely to have an existing livestock orthologue, and, importantly, we show that the effects of functional variants are often conserved in livestock, acting on orthologous genes with the same direction of effect. Consequently, this work demonstrates the substantial potential of naturally occurring livestock carriers of orthologues of human functional variants to disentangle their functional impacts.

genetics↗

bioRxiv2021

Structure, receptor recognition and antigenicity of the human coronavirus CCoV-HuPn-2018 spike glycoprotein

The recent isolation of CCoV-HuPn-2018 from a child respiratory swab indicates that more coronaviruses are spilling over to humans than previously appreciated. Here, we determined cryo-electron microscopy structures of the CCoV-HuPn-2018 spike glycoprotein trimer in two distinct conformational states and identified that it binds canine, feline and porcine aminopeptidase N (APN encoded by ANPEP) orthologs which serve as entry receptors. Introduction of an oligosaccharide at position N739 of human APN renders cells susceptible to CCoV-HuPn-2018 spike-mediated entry, suggesting that single nucleotide polymorphisms could account for the detection of this virus in some individuals. Human polyclonal plasma antibodies elicited by HCoV-229E infection and a porcine coronavirus monoclonal antibody inhibit CCoV-HuPn-2018 S-mediated entry, indicating elicitation of cross-neutralizing activity among -coronaviruses. These data provide a blueprint of the CCoV-HuPn-2018 infection machinery, unveil the viral entry receptor and pave the way for vaccine and therapeutic development targeting this zoonotic pathogen.

microbiology↗

bioRxiv2021

A locus conferring tolerance to Theileria infection in African cattle

East Coast fever, a tick-borne cattle disease caused by the Theileria parva parasite, is among the biggest natural killers of cattle in East Africa, leading to over 1 million deaths annually. Here we report on the genetic analysis of a cohort of Boran cattle demonstrating heritable tolerance to infection by T. parva (h2 = 0.65, s.e. 0.57). Through a linkage analysis we identify a 6 Mb genomic region on Bos taurus chromosome 15 that is significantly associated with survival outcome following T. parva exposure. Testing this locus in an independent cohort of animals replicates this association with survival following T. parva infection. A stop gained polymorphism in this region was found to be highly associated with survival across both related and unrelated animals, with only one of the 20 homozygote carriers (T/T) of this change succumbing to the disease in contrast to 44 out of 97 animals homozygote for the reference allele (C/C). Consequently, we present a genetic locus linked to tolerance of one of Africas most important cattle diseases, raising the promise of marker-assisted selection for cattle that are less susceptible to infection by T. parva. Author SummaryMore than a million cattle die of East Coast fever in Africa each year, the impact of which disproportionately falls onto low-income, smallholder farmers. The lack of a widely accessible vaccine, heavy reliance on chemicals to control the tick vector and inadequate drug treatments means that new approaches for controlling the disease are urgently required. Through a genetic study of an extended pedigree of Boran cattle that are more than three times less likely to succumb to the disease than matched controls, we identify a region on chromosome 15 of the cattle genome associated with a high level of tolerance to the disease. We show that a variant in this region is also associated with survival in an independent cohort, and is linked to rates of cell expansion during infection. This genetic variant can therefore support marker-assisted selection, allowing farmers to breed tolerant cattle and offers a route to introduce this beneficial DNA to non-native breeds, enabling reduced disease incidence and increased productivity, which would be of benefit to millions of rural smallholder farmers across Africa.

genetics↗

bioRxiv2021

A cattle graph genome incorporating global breed diversity

Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds. To mitigate this issue, we have generated the first assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into the first graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.

genomics↗

bioRxiv2021

nf-LO: A scalable, containerised workflow for genome-to-genome lift over

The increasing availability of new genome assemblies often comes with an impaired amount of associated genomic annotations, limiting the range of studies that can be performed. A common workaround is to lift over annotations from better annotated genomes. However, generating the files required to perform a liftover is computationally and labour intensive and only a limited number are currently publicly available. Here we present nf-LO (nextflow-LiftOver), a containerised and scalable Nextflow pipeline that enables liftovers within and between any species for which assemblies are available. nf-LO will consequently facilitates data interpretation across a broad range of genomic studies.

bioinformatics↗

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↗