Biology subjects

Racimo, F.

Publications and source records attributed to Racimo, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Cultural affiliation accounts for most of the spatiotemporal variation in burial rite practices

Describing and interpreting spatiotemporal patterns in human culture has been a central focus of anthropology and archaeology for over a century. Recent ethnographic studies have highlighted the complexity of the processes generating these patterns, including isolation-by-distance, homophily, and common descent. However, investigating these processes in prehistoric archaeology remains challenging. Here we make use of a new interdisciplinary database and a combined dataset of ancient DNA (aDNA) genomic sequences to analyse the relationship between spatiotemporal patterns in cultural and genomic variation, by testing whether broadly defined clusters of genomic affinities correspond to spatiotemporal changes in burial rites, while controlling for other factors, using a Gaussian process model. We use data from the Big Interdisciplinary Archaeological Database (BIAD), linking mortuary information from [~]4,200 individuals with genetic ancestry and mobility data inferred from over 1,300 human genomes, from Western Eurasia [~]10,000-2000 BP. By integrating and modelling these diverse datasets, we aim to provide a detailed understanding of how genomic history intersects with cultural evolution, offering new insights into the dynamics behind these complex processes, and the extent to which genes and culture are transmitted in parallel. In the case of burial orientation, we found that cultural affiliation was the main factor accounting for variation with little to no role for ancestry, while for body position the picture was more mixed but cultural affiliation also played an important role.

genetics↗

bioRxiv2026

Promises and limitations of local ancestry inference in imputed ancient genomes

Recent advances in genome imputation have enabled the application of state-of-the-art statistical methods--originally developed for present-day genomes--to ancient genomes. One class of such methods, known as local ancestry inference (LAI), can model an individuals genome as a mosaic of tracts assigned to different putative ancestral sources, revealing patterns of genetic ancestry across the genome. However, most LAI methods have been designed to study recent admixture events in human history, and they generally assume large panels of present-day genomes. Despite the recent availability of high-quality imputed ancient genomes, it remains unknown to what degree LAI inference is reliable for such datasets. Ancient DNA is often characterized by heterogeneous geographic and temporal sampling, varying degrees of divergence between ancient source proxies and admixing populations, and complex demographic histories. Here, we performed an extensive set of population genetic simulations to evaluate the accuracy of four popular LAI methods-RFMix, FLARE, MOSAIC and simpLAI-under different demographic scenarios, various temporal sampling schemes, sample sizes, and admixture dates. We quantify the accuracy of these methods as a function of different parameters in practically relevant scenarios, and provide general guidelines for future studies utilizing LAI in ancient DNA research.

evolutionary biology↗

bioRxiv2026

Fine-scale population structure within and among Malagasy societies

The population of Madagascar exhibits a globally unique combination of African and Asian genetic ancestries. Previous studies have described the admixture history of Madagascar at island-wide scales [1,2], but less focus has been paid to fine-scale population structure across the island. We present new genome-wide genetic data from 192 individuals sampled across five regions of Madagascar. We identify population structure at extremely fine spatial scales ([~]10 km) among the Merina of the central highlands. By analysing subpopulations separately, we found one Merina group exhibited similarity to coastal populations in f4 ratios, estimated admixture dates, and pairwise FST distances, while another group was similar to other highland individuals in the same measures. This fine-scale substructure is likely associated with historical coastal-to-highland migration during the 18th and 19th centuries. In contrast, we also observe macro-scale structure in estimated timing of admixture across the island, with southeastern coastal groups exhibiting the earliest estimated admixture timings, and northern groups exhibiting the latest. This pattern corroborates previous results [1,2], and may suggest differing histories of admixture timing among Malagasy populations. Our results emphasise the importance of deep micro-geographic sampling to complement macro-scale analysis when characterising demographic history.

genetics↗

bioRxiv2025

demografr: A toolkit for simulation-based inference in population genetics

Simulation-based inference methods such as Approximate Bayesian Computation (ABC) are a popular class of techniques in evolutionary biology and population genetics. These methods are particularly useful for fitting complex models, as they can bypass the need to compute an exact likelihood function, instead relying on comparisons between observed and simulated summary statistics. However, numerous technical and practical hurdles often hinder the application of these methods to new modeling problems. They require the integration of disparate scripts and software for simulation, computing summary statistics, and inference into pipelines which have to be tailor-made for each specific research project. Moreover, computational costs of population genetic simulations can make inference laborious due to costly file format conversions throughout the entire procedure. Here we present a new R package called demografr (github.com/bodkan/demografr), which aims to alleviate most issues with traditional simulation-based inference workflows while facilitating their application to novel and complex modeling problems. First, demografr leverages the R simulation toolkit slendr for interactive, user-friendly encoding of complex demographic models. Second, demografr allows the user to set up parameter distributions and run simulations from them automatically, with built-in support for parallelization. For this purpose, automated inference routines for ABC or grid-based parameter exploration are provided, with individual components available for developing other simulation-based workflows in the future. Third, demografr allows a wide range of summary statistics to be efficiently computed directly in R, without any need for file conversion. In addition to the default slendr simulation engine, demografr also supports user-defined msprime and SLiM simulation scripts as well as entirely customizable summary statistic functions. We illustrate the features of demografr on examples which would traditionally require complex workflows with hundreds of lines of code: estimating parameters of a demographic model via coalescent simulations using ABC, exploring the influence of a set of parameters on summary statistics of interest using parameter grid search, and showcasing the ability to integrate fully customized simulation code written in pure Python or SLiM.

evolutionary biology↗

bioRxiv2025

Improving archaeological metadata reporting in human paleogenomicstudies

Paleogenomic research has dramatically increased our understanding of past demographic and adaptive processes, but has also been criticized for a perceived disconnect between geneticists and other parties involved in the study of the past. For interdisciplinary research to be productive, contextual metadata associated with paleogenomic samples should be accessible in the same publication. Here, we conduct a pilot study examining the extent of archaeological metadata reporting in 30 peer-reviewed human paleogenomic studies, based on genetic sequences from 3911 ancient humans predominately from Western Eurasia, published between 2013 and 2024. We show inconsistent reporting of archaeological data across studies, and have sought to identify the driving factors. Overall, we found no strong explanatory variables, though some metadata fields - like Geolocation - have improved in completeness over time. These inconsistencies mean that metadata reporting is often insufficient to directly investigate the relationship between patterns of cultural and genetic change on the basis of published data alone. We propose a minimum information checklist as a best-practice guideline for collecting and reporting archaeological data in the future.

genomics↗

bioRxiv2025

Faroese Whole Genomes Provide Insight into Ancestry and Recent Selection

The Faroe Islands are home to descendants of a North Atlantic founder population with a unique history shaped by both migration and periods of relative isolation. Here, we investigate the genetic diversity, population structure, and demographic history of the islands by analyzing whole genome sequencing data from 40 participants in the Faroe Genome Project. This represents the first whole genome sequencing panel of this size from the Faroe Islands. We observed numerous putatively functional private alleles, including stop gain variants and high impact missense variants in the cohort. Faroese individuals had a higher proportion of their genomes contained in long runs of homozygosity than other European groups, including Finnish, suggesting a more recent or stronger bottleneck in the Faroese population. Signals of positive selection were identified at loci containing genes that play roles in vitamin D and dietary fat absorption and DNA repair, while increased diversity on lactase persistence haplotypes was observed. Fine-scale analysis of haplotype structure in present-day and ancient European genomes revealed genetic affinities with ancient Iron Age individuals from the North and West of Europe, providing evidence for potential contributions to the Faroese gene pool from Celtic and Viking populations as well as information about the temporal order in which these events happened. This study highlights the impact of evolutionary processes, such as ancient admixture, founder events, and positive selection, on the present-day genetic architecture of North Atlantic founder populations like the Faroe Islands.

genetics↗

bioRxiv2025

Assessing the potential of ancient protein sequences in the study of hominid evolution

Palaeoproteomic data can provide invaluable insights into hominid evolution over long timescales. Yet, the potential and limitations of ancient protein sequences to resolve evolutionary relations between species remains largely unexplored. In this study, we aim to quantify how much information about these relations can be obtained from limited ancient protein data, at the scale that is currently available or will be available in the near future. We harness sequence alignments of 12 enamel and collagen proteins that have been previously reported in fossil material that is at least 1 million years old. We utilise in silico translations of hominid DNA sequences of these proteins and highlight their differential sequence conservation, indicating some of them contain much larger amounts of information than others. We also evaluate the extent to which inferred topologies from protein data differ from inferred topologies from the more informationally-dense DNA data. We show that the former may sometimes lead to inferences of the wrong tree topology due to the informational loss that comes when working with peptide data. Additionally, we determine the number of concatenated proteins necessary to confidently reconstruct the population / species tree summarizing the relations between humans, chimpanzees and gorillas, as well as those between modern humans, Neanderthals and Denisovans. As expected, increasing the number of proteins in a concatenation enhances resolution, but we note that trees inferred from the full set of collagen and enamel proteins do not necessarily correspond to population trees inferred from genome-wide data. We show this is especially the case in the closely related groups of our recent ancestors. We further demonstrate that while a number of proteins fall within archaic introgressed haplotypes of present day humans, ancient admixture is not the main source of the observed tree incongruence. Our study underscores the potential and limitations of utilising palaeoproteomic data in deep time phylogenetic reconstructions, indicating that these will be aided not only by increased recovery of proteins in the future, but also by more careful modeling of evolutionary relations across the genome, beyond simply building single phylogenetic trees.

evolutionary biology↗

bioRxiv2024

A 20+ Ma old enamel proteome from Canada's High Arctic reveals diversification of Rhinocerotidae in the middle Eocene-Oligocene

In the past decade, ancient protein sequences have emerged as a valuable source of data for deep-time phylogenetic inference. Still, the recovery of protein sequences providing novel phylogenetic insights does not exceed 3.7 Ma (Pliocene). Here, we push this boundary back to 21-24 Ma (early Miocene), by retrieving enamel protein sequences of an early-diverging rhinocerotid (Epiaceratherium sp. - CMNF-59632) from the Canadian High Arctic. We recover partial sequences of seven enamel proteins (AHSG, ALB, AMBN, AMELX, AMTN, ENAM, MMP20) and over 1000 peptide-spectrum matches, spanning over at least 251 amino acids. Authentic endogeneity of these sequences is supported by indicators of protein damage, including several spontaneous and irreversible post-translational modifications accumulated during prolonged diagenesis and reaching near-complete occupancy at many sites. Bayesian tip-dating, across 15 extant and extinct perissodactyl taxa, places the divergence time of CMNF-59632 in the middle Eocene-Oligocene, and identifies a later divergence time for Elasmotheriinae in the Oligocene. The finding weakens alternative models suggesting a deep basal split between Elasmotheriinae and Rhinocerotinae. This divergence time of CMNF-59632 coincides with a phase of high diversification of rhinocerotids, and supports a Eurasian origin of this clade in the late Eocene or Oligocene. The findings are consistent with previous hypotheses on the origin of the enigmatic fauna of the Haughton crater, which, in spite of their considerable degree of endemism, also display similarity to distant Eurasian faunas. Our findings demonstrate the potential of palaeoproteomics in obtaining phylogenetic information from a specimen that is ten times older than any sample from which endogenous DNA has been obtained.

paleontology↗

bioRxiv2024

Four centuries of commercial whaling eroded 11,000 years of population stability in bowhead whales

The bowhead whale, an Arctic endemic, was heavily overexploited during commercial whaling between the 16th-20th centuries1. Current climate warming, with Arctic amplification of average global temperatures, poses a new threat to the species2. Assessing the vulnerability of bowhead whales to near-future predictions of climate change remains challenging, due to lacking data on population dynamics prior to commercial whaling and responses to past climatic change. Here, we integrate palaeogenomics and stable isotope ({delta}13C and{delta} 15N) analysis of 201 bowhead whale fossils from the Atlantic Arctic with palaeoclimate and ecological modelling based on 823 radiocarbon dated fossils, 151 of which are new to this study. We find long-term resilience of bowhead whales to Holocene environmental perturbations, with no obvious changes in genetic diversity or population structure, despite large environmental shifts and centuries of whaling by Indigenous peoples prior to commercial harvests. Leveraging our empirical data, we simulated a time-series model to quantify population losses associated with commercial whaling. Our results indicate that commercial exploitation induced population subdivision and losses of genetic diversity that are yet to be fully realised; declines in genetic diversity will continue, even without future population size reductions, compromising the species resilience to near-future predictions of Arctic warming.

evolutionary biology↗

bioRxiv2024

Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years

The multi-millenia long history between dogs and humans has placed them at the forefront of archeological and genomic research. Despite ongoing efforts including the analysis of ancient dog and wolf genomes, many questions remain regarding their geographic and temporal origins, and the microevolutionary processes that led to the diversity of breeds today. Although ancient genomes provide valuable information, their use is hindered by low depth of coverage and post-mortem damage, which inhibits confident genotype calling. In the present study, we assess how genotype imputation of ancient dog and wolf genomes, utilising a large reference panel, can improve the resolution provided by ancient datasets. Imputation accuracy was evaluated by down-sampling high coverage dog and wolf genomes to 0.05-2x coverage and comparing concordance between imputed and high coverage genotypes. We measured the impact of imputation on principal component analyses and runs of homozygosity. Our findings show high (R2>0.9) imputation accuracy for dogs with coverage as low as 0.5x and for wolves as low as 1.0x. We then imputed a dataset of 90 ancient dog and wolf genomes, to assess changes in inbreeding during the last 10,000 years of dog evolution. Ancient dog and wolf populations generally exhibited lower inbreeding levels than present-day individuals. Interestingly, regions with low ROH density maintained across ancient and present-day samples were significantly associated with genes related to olfaction and immune response. Our study indicates that imputing ancient canine genomes is a viable strategy that allows for the use of analytical methods previously limited to high-quality genetic data.

evolutionary biology↗

bioRxiv2023

The landscape of ancient human pathogens in Eurasia from the Stone Age to historical times

Infectious diseases have had devastating impacts on human populations throughout history, but important questions about their origins and past dynamics remain1. To create the first archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which were detected for the first time in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Intriguingly, zoonotic pathogens are only detected [~]6,500 years ago, peaking [~]5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide the first direct evidence that this lifestyle change resulted in an increased infectious disease burden. Importantly, they also suggest that the spread of these pathogens increased substantially during subsequent millenia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.

evolutionary biology↗

bioRxiv2023

Enamel proteins reveal biological sex and genetic variability within southern African Paranthropus

The evolutionary relationships among extinct African hominin taxa are highly debated and largely unresolved, due in part to a lack of molecular data. Even within taxa, it is not always clear, based on morphology alone, whether ranges of variation are due to sexual dimorphism versus potentially undescribed taxonomic diversity. For Paranthropus robustus, a Pleistocene hominin found only in South Africa, both phylogenetic relationships to other taxa 1,2 and the nature of intraspecific variation 3-6 are still disputed. Here we report the mass spectrometric (MS) sequencing of enamel proteomes from four ca. 2 million year (Ma) old dental specimens attributed morphologically to P. robustus, from the site of Swartkrans. The identification of AMELY-specific peptides and semi-quantitative MS data analysis enabled us to determine the biological sex of all the specimens. Our combined molecular and morphometric data also provide compelling evidence of a significant degree of variation within southern African Paranthropus, as previously suggested based on morphology alone 6. Finally, the molecular data also confirm the taxonomic placement of Paranthropus within the hominin clade. This study demonstrates the feasibility of recovering informative Early Pleistocene hominin enamel proteins from Africa. Crucially, it also shows how the analysis of these proteins can contribute to understanding whether hominin morphological variation is due to sexual dimorphism or to taxonomic differences. We anticipate that this approach can be widely applied to geologically-comparable sites within South Africa, and possibly more broadly across the continent.

evolutionary biology↗

bioRxiv2023

Inference of population genetics parameters using discriminator neural networks: an adversarial Monte Carlo approach

Accurately estimating biological variables of interest, such as parameters of demographic models, is a key problem in evolutionary genetics. Likelihood-based and likelihood-free methods both typically use only limited genetic information, such as carefully chosen summary statistics. Deep convolutional neural networks (CNNs) trained on genotype matrices can incorporate a great deal more information, and have been shown to have high accuracy for inferring parameters such as recombination rates and population sizes, when evaluated using simulations. However these methods are typically framed as regression or classification problems, and it is not straightforward to ensure that the training data adequately model the empirical data on which they are subsequently applied. It has recently been shown that generative adversarial networks (GANs) can be used to iteratively tune parameter values until simulations match a given target dataset. Here, we investigate an adversarial architecture for discriminator-based inference, which iteratively improves the sampling distribution for training the discriminator CNN via Monte Carlo density estimation. We show that this method produces parameter estimates with excellent agreement to simulated data. We developed dinf, a modular Python package for discriminator-based inference that incorporates this method, and is available from https://github.com/RacimoLab/dinf/.

evolutionary biology↗

bioRxiv2023

Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences

1Geographic space is a fundamental dimension of evolutionary change, determining how individuals disperse and interact with each other. Consequently, space has an important influence on the structure of genealogies and the distribution of genetic variants over time. Recently, the development of highly flexible simulation tools and computational methods for genealogical inference has greatly increased the potential for incorporating space into models of population genetic variation. It is now possible to explore how spatial ecological parameters can influence the distribution of genetic variation among individuals in unprecedented detail. In this study, we explore the effects of three specific parameters (the dispersal distance, competition distance and mate choice distance) on the spatial structure of genealogies. We carry out a series of in silico experiments using forwards-in-time simulations to determine how these parameters influence the distance between closely- and distantly-related individuals. We also assess the accuracy of the maximum likelihood estimation of the dispersal distance in a Gaussian model of dispersal from tree-sequence data, and highlight how it is affected by realistic factors such as finite habitat size and limited data. We find overall that the scale of mate choice in particular has marked patterns on short and long terms patterns of dispersal, as well as on the positions of individuals within a habitat. Our results showcase the potential for linking phylogeography, population genetics and ecology, in order to answer fundamental questions about the nature of spatial interactions across a landscape.

evolutionary biology↗

bioRxiv2022

PaleoProPhyler: a reproducible pipeline for phylogenetic inference using ancient proteins

Ancient proteins from fossilized or semi-fossilized remains can yield phylogenetic information at broad temporal horizons, in some cases even millions of years into the past. In recent years, peptides extracted from archaic hominins and long-extinct mega-fauna have enabled unprecedented insights into their evolutionary history. In contrast to the field of ancient DNA - where several computational methods exist to process and analyze sequencing data - few tools exist for handling ancient protein sequence data. Instead, most studies rely on loosely combined custom scripts, which makes it difficult to reproduce results or share methodologies across research groups. Here, we present PaleoProPhyler: a new fully reproducible pipeline for aligning ancient peptide data and subsequently performing phylogenetic analyses. The pipeline can not only process various forms of proteomic data, but also easily harness genetic data in different formats (CRAM, BAM, VCF) and translate it, allowing the user to create reference panels for phyloproteomic analyses. We describe the various steps of the pipeline and its many functionalities, and provide some examples of how to use it. PaleoProPhyler allows researchers with little bioinformatics experience to efficiently analyze palaeoproteomic sequences, so as to derive insights from this valuable source of evolutionary data.

bioinformatics↗

bioRxiv2022

Ancient dolphin genomes reveal rapid repeated adaptation to coastal waters

Parallel evolution provides among the strongest evidence of the role of natural selection in shaping adaptation to the local environment. Yet, the chronology, mode and tempo of the process of parallel evolution remains broadly debated and discussed in the field of evolutionary biology. In this study, we harness the temporal resolution of paleogenomics to understand the tempo and independence of parallel coastal ecotype adaptation in common bottlenose dolphins (Tursiops truncatus). For this, we generated whole genome resequencing data from subfossil dolphins (8,610-5,626 years BP) originating from around the formation time of new coastal habitat and compared them with data from contemporary populations. Genomic data revealed a shift in genetic affinity, with the oldest ancient sample being closer to the pelagic populations, while the younger samples had intermediate ancestry that showed greater affinity with the local contemporary coastal populations. We found coastal-associated genotypes in the genome of our highest coverage ancient sample, SP1060, providing rare evidence of rapid adaptation from standing genetic variation. Lastly, using admixture graph analyses, we found a reticulate evolutionary history between pelagic and coastal populations. Ancestral gene flow from coastal populations was the probable source of standing genetic variation present in the pelagic populations that enabled rapid adaptation to newly emerged coastal habitat. The genetic response to past climatic warming provides an understanding of how bottlenose dolphins will respond to ongoing directional climate change and shifting coastlines.

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↗

bioRxiv2022

Population genomics of the island thrush elucidates one of earth's great archipelagic radiations

Tropical islands are renowned as natural laboratories for evolutionary study. Lineage radiations across tropical archipelagos are ideal systems for investigating how colonization, speciation, and extinction processes shape biodiversity patterns. The expansion of the island thrush across the Indo-Pacific represents one of the largest yet most perplexing island radiations of any songbird species. The island thrush exhibits a complex mosaic of pronounced plumage variation across its range, and is arguably the worlds most polytypic bird. It is a sedentary species largely restricted to mountain forests, yet it has colonized a vast island region spanning a quarter of the globe. We conducted comprehensive sampling of island thrush populations and obtained genome-wide SNP data, which we used to reconstruct its phylogeny, population structure, gene flow, and demographic history. The island thrush evolved from migratory Palearctic ancestors and radiated explosively across the Indo-Pacific during the Pleistocene, with numerous instances of gene flow between populations. Its bewildering plumage variation masks a biogeographically intuitive stepping stone colonization path from the Philippines through the Greater Sundas, Wallacea and New Guinea to Polynesia. The island thrushs success in colonizing Indo-Pacific mountains can be understood in light of its ancestral mobility and adaptation to cool climates; however, shifts in elevational range, degree of plumage variation and apparent dispersal rates in the eastern part of its range raise further intriguing questions about its biology.

evolutionary biology↗