Biology subjects

Speidel, L.

Publications and source records attributed to Speidel, L..

12 recordsLinked to original sources

bioRxiv2026

Joint dog and wolf genealogies reveal the evolution of the canine genome

Dogs and their closest extant relative, the grey wolf, diverged around 30k years ago, but have since experienced complex histories of gene flow involving other canids, adaptive pressures due to close association with humans, and changing climates. We infer joint genealogies of dogs, grey wolves, and a coyote using available whole genomes to reconstruct the evolutionary forces shaping the dog genome. These genealogies reveal multiple strong mutation-rate pulses unique to dogs, including signals detectable across ancient dogs from the past 10,000 years. We further detect pervasive genealogical signatures of purifying selection and find that GC-biased gene conversion is a major driver of diversity patterns around gene promoters in dogs. We introduce a new genealogy-based selection scan, TwigScan, that computes time-stratified differentiation, increasing power over traditional FST-based approaches. Applying this framework, alongside a second single-population test for detecting more recent selection within dogs, we identify multiple known and novel loci with signatures of positive selection. Among these, the region surrounding the amylase 2B locus shows evidence of introgression from a deeply divergent, unsampled canid lineage with divergence comparable to that of dholes. AMY2B duplications appear to occur exclusively on this introgressed haplotype which increased in frequency approximately 7,000-8,000 years ago, coinciding with increased reliance on starch-rich diets in human populations. Together, these results show how mutation-rate variation, gene conversion, selection, and inter-species gene flow have jointly shaped the dog genome, highlighting the power of genealogical approaches for resolving complex evolutionary histories.

evolutionary biology↗

bioRxiv2026

Genome-wide genealogies reveal deep admixtures forming modern humans

Over the past decade, genomic modelling has revealed a rich tapestry of admixtures shaping present-day human populations. These have largely focused on the past few thousand years, when ancestral populations are either well characterised by present-day genomic diversity or directly observed through ancient DNA. Genomic modelling and fossil evidence have so far only provided a fragmented picture of the coexistence and mixing of human groups in the deeper past. Here, we propose a new method, GhostBuster, that leverages inferred genome-wide genealogies to detect admixture events of unsampled ghost populations, while simultaneously inferring accurate local ancestry. Local ancestry enables us to identify ancestry-specific genomic signatures that independently corroborate the events. We identify at least three waves of "back-to-Africa" migrations starting [~]14,000 years ago. Applying GhostBuster to deeper timescales reveals that modern humans were shaped by repeated episodes of mixture. Around 50,000 years ago, we identify a human lineage that expanded to form present-day non-Africans, while also expanding within Africa, mixing with the other local African group in varying proportions. These ancient groups help explain polygenic score portability differences within Africa, and exhibit differences in population size and recombination landscapes. Extending our analysis further back to between 300,000 and 1 million years ago reveals two deeply diverged ancestral lineages. These lineages evolved profoundly different recombination landscapes, with different PRDM9 alleles (PRDM9-A and C) and recombination hotspots. We demonstrate that both Neanderthals and ancestral modern humans are formed through a mixture of these two lineages, with no evidence of gene flow from the PRDM9-A-carrying group into Denisovans.

evolutionary biology↗

bioRxiv2026

Ancient Ryukyu Jomon contributed to past and current genetic structure of Japanese populations

Characterized by the earliest use of pottery, the Jomon culture was a unique Neolithic culture that spread throughout the Japanese Archipelago. Previous archaeological evidence suggests that Jomon hunter-gatherers colonized the southernmost islands, the Ryukyu Archipelago, by approximately 7,000 years before present (YBP). However, genetic characteristics of the Ryukyu Jomon population and its contribution to the modern population have not been elucidated yet. In this study, we newly sequenced 273 modern and 25 ancient (6,700-900 YBP) whole genomes collected across the Ryukyu Archipelago. Our analysis demonstrated a genetic differentiation between the Hondo (Japanese mainland) and Ryukyu Jomon, dating back to [~]6,900 YBP. After the divergence from the Hondo Jomon, the Ryukyu Jomon experienced severe bottlenecks, with an effective population size of [~]2,000. Admixture between the Ryukyu Jomon and migrants from the historic Hondo population occurred [~]1,000 YBP, which corresponds to the widespread adoption of iron tools and agriculture in the Central Ryukyus. Different demographic histories between modern Hondo and Ryukyu populations resulted in different rates of Jomon ancestry in these populations. By providing a new perspective on the peopling of the Ryukyu Archipelago, this study significantly enhances our understanding of cultural transitions in the region.

evolutionary biology↗

bioRxiv2025

Inference of complex demographic history using composite likelihood based on whole-genome genealogies

Accurate parametric inference on complex demographic models is a continuing challenge in population genetics. Ancestral recombination graphs (ARGs) provide richer information than simple population genetic summary statistics and can potentially improve the power and accuracy of such inference. We present mrpast, a tool for inferring complex demographic history from ARGs. mrpast uses a composite likelihood formulation based on the pairwise sample coalescence time, observable in an ARG, and the coalescence probabilities from a continuous-time Markov process. We have evaluated mrpasts accuracy on a variety of models, including stepping-stone models with asymmetric migrations, changes in effective population sizes, out-of-Africa, and American admixture. We demonstrated mrpasts accuracy using simulated ARGs and inferred ARGs, and its high versatility in jointly inferring all parameters in complex models, including time of demographic events (e.g., population split, admixture), effective population size (e.g., constant, exponential growth), and gene flow (e.g., admixture proportion, migration rate). Extending the three-population out-of-Africa model with asymmetric migrations, we observed significantly more migrations from East Asians to Europeans than from Europeans to East Asians. Notably, mrpast can reliably recover all parameters in an American admixture model, when treating non-admixed Native Americans as an unsampled ("ghost") population. Applying this model to Mexican, Puerto Rican, and Colombian populations, we found that the reconstructed histories of Native and admixed Americans align closely with both historical records and genetic evidence. Lastly, mrpast provides a comprehensive pipeline to facilitate easier, more appropriate, and robust demographic inference, in which users can easily simulate, infer, and manipulate ARGs, and illustrate and test a demographic model.

genetics↗

bioRxiv2024

Ancient Borrelia genomes document the evolutionary history of louse-borne relapsing fever

Several disease-causing bacteria have transitioned from tick-borne to louse-borne transmission, a process associated with increased virulence and genome reduction. However, the historical time frame and speed of such evolutionary transitions have not been documented with ancient genomes. Here, we discover four ancient cases of Borrelia recurrentis, the causative agent of louse-borne relapsing fever, in Britain between [~]600 and 2,300 years ago, and sequence whole genomes up to 29-fold coverage. We estimate a recent divergence from the closest tick-borne ancestor, likely within the last [~]8,000 years. We reconstruct a chronology of gene losses and acquisitions using the pan-genome of related species, and show that almost all of the reductive evolution observed in B. recurrentis had occurred by [~]2,000 years ago, and was thus a rapid process after divergence. Our observations provide a new understanding of the origins of B. recurrentis and document complex reductive evolution in a specialist vector-borne pathogen.

evolutionary biology↗

bioRxiv2024

High-resolution genomic ancestry reveals mobility in early medieval Europe

Ancient DNA has unlocked new genetic histories and shed light on archaeological and historical questions, but many known and unknown historical events have remained below detection thresholds because subtle ancestry changes are challenging to reconstruct. Methods based on sharing of haplotypes1,2 and rare variants3,4 can improve power, but are not explicitly temporal and have not been adopted in unbiased ancestry models. Here, we develop Twigstats, a new approach of time-stratified ancestry analysis that can improve statistical power by an order of magnitude by focusing on coalescences in recent times, while remaining unbiased by population-specific drift. We apply this framework to 1,151 available ancient genomes, focussing on northern and central Europe in the historical period, and show that it allows modelling of individual-level ancestry using preceding genomes and provides previously unavailable resolution to detect broader ancestry transformations. In the first half of the first millennium [~]1-500 CE (Common Era), we observe an expansion of Scandinavian-related ancestry across western, central, and southern Europe. However, in the second half of the millennium [~]500-1000 CE, ancestry patterns suggest the regional disappearance or substantial admixture of these ancestries in multiple regions. Within Scandinavia itself, we document a major ancestry influx by [~]800 CE, when a large proportion of Viking Age individuals carried ancestry from groups related to continental Europe. This primarily affected southern Scandinavia, and was differentially represented in the western and eastern directions of the wider Viking world. We infer detailed ancestry portraits integrated with historical, archaeological, and stable isotope evidence, documenting mobility at an individual level. Overall, our results are consistent with substantial mobility in Europe in the early historical period, and suggest that time-stratified ancestry analysis can provide a new lens for genetic history.

evolutionary biology↗

bioRxiv2023

A disease-associated gene desert orchestrates macrophage inflammatory responses via ETS2

Increasing global rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2 - underscoring an urgent need to better understand disease mechanisms. Here we show how genetics could address this challenge. By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasus arteritis3-6, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Genes regulated by ETS2 were prominently expressed in affected tissues from chr21q22-associated diseases and more enriched for IBD GWAS hits than almost all previously described pathways. Overexpressing ETS2 in resting macrophages produced an activated effector state that phenocopied intestinal macrophages from IBD7, with upregulation of multiple drug targets including TNF and IL-23. Using a database of cellular signatures8, we identify drugs that could modulate this pathway and validate the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this highlights the potential for common genetic associations to improve both the understanding and treatment of human disease.

immunology↗

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↗

bioRxiv2022

Balancing selection on genomic deletion polymorphisms in humans

A key question in biology is why genomic variation persists in a population for extended periods. Recent studies have identified examples of genomic deletions that have remained polymorphic in the human lineage for hundreds of millennia, ostensibly owing to balancing selection. Nevertheless, genome-wide investigations of ancient and possibly adaptive deletions remain an imperative exercise. Here, we used simulations to show an excess of ancient allele sharing between modern and archaic human genomes that cannot be explained solely by introgression or ancient structure under neutrality. We identified 63 deletion polymorphisms that emerged before the divergence of humans and Neanderthals and are associated with GWAS traits. We used empirical and simulation-based analyses to show that the haplotypes that harbor these functional ancient deletions have likely been evolving under time- and geography-dependent balancing selection. Collectively, our results suggest that balancing selection may have maintained at least 27% of the functional deletion polymorphisms in humans for hundreds of thousands of years.

evolutionary biology↗

bioRxiv2021

Inferring population histories for ancient genomes using genome-wide genealogies

Ancient genomes anchor genealogies in directly observed historical genetic variation, and contextualise ancestral lineages with archaeological insights into their geography and lifestyles. We introduce an extension of the Relate algorithm to incorporate ancient genomes and reconstruct the joint genealogies of 14 previously published high-coverage ancients and 278 present-day individuals of the Simons Genome Diversity Project. As the majority of ancient genomes are of lower coverage and cannot be directly built into genealogies, we additionally present a fast and scalable method, Colate, for inferring coalescence rates between low-coverage genomes without requiring phasing or imputation. Our method leverages sharing patterns of mutations dated using a genealogy to construct a likelihood, which is maximised using an expectation-maximisation algorithm. We apply Colate to 430 ancient human shotgun genomes of >0.5x mean coverage. Using Relate and Colate, we characterise dynamic population structure, such as repeated partial population replacements in Ireland, and gene-flow between early farmer and European hunter-gatherer groups. We further show that the previously reported increase in the TCC/TTC mutation rate, which is strongest in West Eurasians among present-day people, was already widespread across West Eurasia in the Late Glacial Period ~10k - 15k years ago, is strongest in Neolithic and Anatolian farmers, and is remarkably well predicted by the coalescence rates between other genomes and a 10,000-year-old Anatolian individual. This suggests that the driver of this signal originated in ancestors of ancient Anatolia >14k years ago, but was already absent by the Mesolithic and may indicate a genetic link between the Near East and European hunter-gatherer groups in the Late Paleolithic.

genomics↗

bioRxiv2020

Disentangling selection on genetically correlated polygenic traits using whole-genome genealogies

We present a full-likelihood method to estimate and quantify polygenic adaptation from contemporary DNA sequence data. The method combines population genetic DNA sequence data and GWAS summary statistics from up to thousands of nucleotide sites in a joint likelihood function to estimate the strength of transient directional selection acting on a polygenic trait. Through population genetic simulations of polygenic trait architectures and GWAS, we show that the method substantially improves power over current methods. We examine the robustness of the method under uncorrected GWAS stratification, uncertainty and ascertainment bias in the GWAS estimates of SNP effects, uncertainty in the identification of causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, fully controlling for pleiotropy even among traits with strong genetic correlation (|rg| = 80%; c.f. schizophrenia and bipolar disorder) while retaining high power to attribute selection to the causal trait. We apply the method to study 56 human polygenic traits for signs of recent adaptation. We find signals of directional selection on pigmentation (tanning, sunburn, hair, P=5.5e-15, 1.1e-11, 2.2e-6, respectively), life history traits (age at first birth, EduYears, P=2.5e-4, 2.6e-4, respectively), glycated hemoglobin (HbA1c, P=1.2e-3), bone mineral density (P=1.1e-3), and neuroticism (P=5.5e-3). We also conduct joint testing of 137 pairs of genetically correlated traits. We find evidence of widespread correlated response acting on these traits (2.6-fold enrichment over the null expectation, P=1.5e-7). We find that for several traits previously reported as adaptive, such as educational attainment and hair color, a significant proportion of the signal of selection on these traits can be attributed to correlated response, vs direct selection (P=2.9e-6, 1.7e-4, respectively). Lastly, our joint test uncovers antagonistic selection that has acted to increase type 2 diabetes (T2D) risk and decrease HbA1c (P=1.5e-5).

genetics↗

bioRxiv2019

A method for genome-wide genealogy estimation for thousands of samples

Knowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We developed a method, Relate, scaling to > 10,000 sequences while simultaneously estimating branch lengths, mutational ages, and variable historical population sizes, as well as allowing for data errors. Application to 1000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations. Highly diverged lineages are present in all groups, but most frequent in Africa. Outside Africa, these mainly reflect ancient introgression from groups related to Neanderthals and Denisovans, while African signals instead reflect unknown events, unique to that continent. Our approach allows more powerful inferences of natural selection than previously possible. We identify multiple novel regions under strong positive selection, and multi-allelic traits including hair colour, BMI, and blood pressure, showing strong evidence of directional selection, varying among human groups.

genetics↗