Biology subjects

Tobler, R.

Publications and source records attributed to Tobler, R..

15 recordsLinked to original sources

bioRxiv2026

Palaeogenomics-informed inferences of European dog admixture enables scalable dingo conservation

Dingoes, mainland Australias sole terrestrial apex mammal for over 3,000 years, are important components of many ecosystems and Indigenous cultural heritage. Yet conflicts with farmers over livestock predation following European colonisation led to widespread lethal control. These measures are further reinforced by perceptions of hybrid ancestry with European dogs. Accurate estimation of European dog ancestry is therefore essential for effective conservation, but existing tests yield highly conflicting results. Leveraging pre-colonial dingo palaeogenomes and a robust ancestry modelling framework, we reassess the genetic ancestry of contemporary populations. Our approach corrects limitations and biases in existing methods, producing consistent estimates even with as few as 10,000 genome-wide transversion genetic markers. Accounting for admixture uncovers population structure that has persisted for over two millennia and reveals patterns of genetic admixture coinciding with human activity during the colonial era. This study underscores the value of palaeogenomes as a vital conservation tool, offering insights unattainable from modern DNA alone. By clarifying ancestry and population structure, our study offers a robust foundation for effective regionally informed dingo management across Australia.

genomics↗

bioRxiv2026

Seasonal fluctuations in fitness result in severe reductions in effective population size

Genetic evidence for fluctuating selection has begun to accumulate for different species over the past few decades, especially for the Drosophila genus where studies have reported hundreds of loci undergoing putatively adaptive oscillations across successive seasons. However, most theoretical and simulation studies of fluctuating selection have relied on abstract or weakly parameterized models, making it difficult to assess their relevance for natural populations. In this study, we simulate multilocus seasonally fluctuating selection under a recently developed model and examine its effect on the variance effective population size (Ne) at a genome-wide scale. By recapitulating genomic, demographic, and evolutionary parameters from natural Drosophila populations in our simulations, we were able to reproduce allele frequency oscillations reported in recent studies and show that these lead to [~]50% genome-wide reductions in Ne. We also demonstrate that Ne reductions are well predicted by the maximum frequency amplitude among all adaptively fluctuating loci, and that the frequency amplitudes are largely determined by the number of adaptively fluctuating loci and the strength of their epistatic interactions. Our results demonstrate that fluctuating selection can substantially reduce effective population size and underscore the importance of temporally variable selection in shaping genome-wide patterns of variation beyond classical models. Article SummaryGenetic studies of fluctuating selection in natural populations have grown steadily over the past decade, with reports suggesting that hundreds of loci undergo adaptive oscillations over seasonal timescales in cosmopolitan Drosophila populations. By simulating seasonally fluctuating selection under a recently developed model and ecological scenarios informed by published studies, the authors show that this mode of selection can reduce effective population size by [~]50%, with the magnitude of the reduction correlated with the locus exhibiting the largest allele frequency fluctuations. These findings highlight fluctuating selection as an important factor shaping genome-wide patterns of genetic variation and effective population size.

evolutionary biology↗

bioRxiv2024

The genetic history of Portugal over the past 5,000 years

BackgroundRecent ancient DNA studies uncovering large-scale demographic events in Iberia have focused primarily on Spain, with limited reports for Portugal, a country located at the westernmost edge of continental Eurasia. Here, we introduce the largest collection of ancient Portuguese genomic datasets (n = 68) to date, spanning 5,000 years, from the Neolithic to the 19th century. ResultsWe found evidence of patrilocality in Neolithic Portugal, with admixture from local hunter-gatherers and Anatolian farmers, and persistence of Upper Paleolithic Magdalenian ancestry. This genetic profile persists into the Chalcolithic, reflecting diverse local hunter- gatherer contributions. During the Bronze Age, local genetic ancestry persisted, particularly in southern Iberia, despite influences from the North Pontic Steppe and early Mediterranean contacts. The Roman period highlights Idanha-a-Velha as a hub of migration and interaction, with a notably diverse genetic profile. The Early Medieval period is marked by Central European ancestry linked to Suebi/Visigoth migrations, adding to coeval local, African, and Mediterranean influences. The Islamic and Christian Conquest periods show strong genetic continuity in northern Portugal and significant African admixture in the south, with persistent Jewish and Islamic ancestries suggesting enduring influences in the post-Islamic period. ConclusionsThis study represents the first attempt to reconstruct the genetic history of Portugal from the analysis of ancient individuals. We reveal dynamic patterns of migration and cultural exchange across millennia, but also the persistence of local ancestries. Our findings integrate genetic information with historical and archaeological data, enhancing our understanding of Iberias ancient heritage.

genomics↗

bioRxiv2024

The genetic origins and impacts of historical Papuan migrations into Wallacea

The tropical archipelago of Wallacea was first settled by anatomically modern humans (AMH) by 50 thousand years ago (kya), with descendent populations thought to have remained genetically isolated prior to the arrival of Austronesian seafarers around 3.5 kya. Modern Wallaceans exhibit a longitudinal countergradient of Papuan- and Asian-related ancestries widely considered as evidence for mixing between local populations and Austronesian seafarers, though converging multidisciplinary evidence suggests that the Papuan-related component instead comes primarily from back-migrations from New Guinea. Here, we reconstruct Wallacean population genetic history using more than 250 newly reported genomes from 12 Wallacean and three West Papuan populations and confirm that the vast majority of Papuan-related ancestry in Wallacea ([~]75-100%) comes from prehistoric migrations originating in New Guinea and only a minor fraction is attributable to the founding AMH settlers. Mixing between Papuan and local Wallacean lineages appear to have been confined to the western and central parts of the archipelago and likely occurred contemporaneously with the widespread introduction of genes from Austronesian seafarers--which now comprise between [~]40-85% of modern Wallacean ancestry--though dating historical admixture events remains challenging due to mixing continuing into the Historical Period. In conjunction with archaeological and linguistic records, our findings point to a dynamic Wallacean population history that was profoundly reshaped by the spread of Papuan genes, languages, and culture in the past 3,500 years.

evolutionary biology↗

bioRxiv2024

Benchmarking Imputed Low Coverage Genomes in a Human Population Genetics Context

Ongoing advances in population genomic methodologies have recently made it possible to study millions of loci across hundreds of genomes at a relatively low cost, by leveraging a combination of low-coverage shotgun sequencing and innovative genotype imputation methods. This approach has the potential to provide economical access to genotype information that is similar to most widely used low-cost genotyping approach - i.e. SNP panels - while avoiding potential issues related to loci being ascertained in distantly related populations. Nonetheless, adoption of imputation methods has been constrained by the lack of suitable reference panels of phased genomes, as performance degrades when panel individuals are distantly related to the target populations. Recent advances in imputation algorithms now allow genetic information from the target population to be used in the imputation process, however, potentially mitigating the lack of a suitable reference panel. Here we assess the performance of the recently released GLIMPSE imputation software on a set of 250 low coverage genomes ([~]3x) from populations from Island Southeast Asia and Near Oceania that are poorly represented in publicly available datasets, comparing the use of imputed genotypes against other common genotype calling methods for a range of standard population genomic analyses. We find that imputation performance and inference both greatly improved when genetic information from the 250 target individuals was leveraged, with comparable results to pseudo-haploid calls that trade off improved precision with reduced accuracy. Our study shows that imputed genotypes are a cost effective and robust basis for population genomic studies of groups, especially those that are poorly represented in publicly available data.

evolutionary biology↗

bioRxiv2024

Optimised in-solution enrichment of over a million ancient human SNPs

In-solution hybridisation enrichment of genetic markers is a method of choice in paleogenomic studies, where the DNA of interest is generally heavily fragmented and contaminated with environmental DNA, and where the retrieval of genetic data comparable between individuals is challenging. Here, we benchmarked the commercial "Twist Ancient DNA" reagent from Twist Biosciences using sequencing libraries from ancestrally diverse ancient human samples with low to high endogenous DNA content (0.1-44%). For each library, we tested one and two rounds of enrichment, and assessed performance compared to deep shotgun sequencing. We find that the "Twist Ancient DNA" assay provides robust enrichment of [~]1.2M target SNPs without introducing allelic bias that may interfere with downstream population genetics analyses. Additionally, we show that pooling up to 4 sequencing libraries and performing two rounds of enrichment is both reliable and cost-effective for libraries with less than 27% endogenous DNA content. Above 38% endogenous content, a maximum of one round of enrichment is recommended for cost-effectiveness and to preserve library complexity. In conclusion, we provide researchers in the field of human paleogenomics with a comprehensive understanding of the strengths and limitations of different sequencing and enrichment strategies, and our results offer practical guidance for optimising experimental protocols.

genomics↗

bioRxiv2023

Allelic bias when performing in-solution enrichment of ancient human DNA

In-solution hybridisation enrichment of genetic variation is a valuable methodology in human paleogenomics. It allows enrichment of endogenous DNA by targeting genetic markers that are comparable between sequencing libraries. Many studies have used the 1240k reagent--which enriches 1,237,207 genome-wide SNPs--since 2015, though access was restricted. In 2021, Twist Biosciences and Daicel Arbor Biosciences independently released commercial kits that enabled all researchers to perform enrichments for the same 1240k SNPs. We used the Daicel Arbor Biosciences Prime Plus kit to enrich 132 ancient samples from three continents. We identified a systematic assay bias that increases genetic similarity between enriched samples and that cannot be explained by batch effects. We present the impact of the bias on population genetics inferences (e.g., Principal Components Analysis, [f]-statistics) and genetic relatedness (READ). We compare the Prime Plus bias to that previously reported of the legacy 1240k enrichment assay. In [f]-statistics, we find that all Prime-Plus-generated data exhibit artefactual excess shared drift, such that within-continent relationships cannot be correctly determined. The bias is more subtle in READ, though interpretation of the results can still be misleading in specific contexts. We expect the bias may affect analyses we have not yet tested. Our observations support previously reported concerns for the integration of different data types in paleogenomics. We also caution that technological solutions to generate 1240k data necessitate a thorough validation process before their adoption in the paleogenomic community.

genomics↗

bioRxiv2022

Genozip Dual-Coordinate VCF format enables efficient genomic analyses and alleviates liftover limitations

We introduce Dual Coordinate VCF (DVCF), a file format that records genomic variants against two different reference genomes simultaneously and is fully compliant with the current VCF specification. As implemented in the Genozip platform, DVCF enables bioinformatics pipelines to seamlessly operate across two coordinate systems by leveraging the system most advantageous to each pipeline step, simplifying bioinformatics workflows and reducing file generation and associated data storage burden. Moreover, our benchmarking of Genozip DVCF shows that it produces more complete, less erroneous, and less biased translations across coordinate systems than two widely used alternative tools (i.e., LiftoverVcf and CrossMap). Availability and ImplementationAn open source (GPL) version of Genozip containing DVCF functionality but not compression functionality, and which includes scripts for reproducing the benchmarks presented here, is available at https://github.com/divonlan/dvcf. Documentation is available at https://genozip.com/dvcf.

bioinformatics↗

bioRxiv2021

BWA-mem is not the best aligner for ancient DNA short reads.

Xu and colleagues (Xu et al., 2021) recently suggested a new parameterisation of BWA-mem (Li, 2013) as an alternative to the current standard BWA-aln (Li and Durbin, 2009) to process ancient DNA sequencing data. The authors tested several combinations of the -k and -r parameters to optimise BWA-mems performance with degraded and contaminated ancient DNA samples. They report that using BWA-mem with -k 19 -r 2.5 parameters results in a mapping efficiency comparable to BWA-aln with -I 1024 -n 0.03 (i.e. a derivation of the standard parameters used in ancient DNA studies; (Schubert et al., 2012)), while achieving significantly faster run times. We recently performed a systematic benchmark of four mapping software (i.e. BWA-aln, BWA-mem, NovoAlign (http://www.novocraft.com/products/novoalign), and Bowtie2 (Langmead and Salzberg, 2012) for ancient DNA sequencing data and quantified their precision, accuracy, specificity, and impact on reference bias (Oliva et al., 2021). Notably, while multiple parameterisations were tested for BWA-aln, NovoAlign, and Bowtie2, we only tested BWA-mem with default parameters. Here, we use the alignment performance metrics from Oliva et al. to directly compare the recommended BWA-mem parameterisation reported in Xu et al. with the best performing alignment methods determined in the Oliva et al. benchmarks, and we make recommendations based on the results.

bioinformatics↗

bioRxiv2020

An ancient coronavirus-like epidemic drove adaptation in East Asians from 25,000 to 5,000 years ago

The current SARS-CoV-2 pandemic has emphasized the vulnerability of human populations to novel viral pressures, despite the vast array of epidemiological and biomedical tools now available. Notably, modern human genomes contain evolutionary information tracing back tens of thousands of years, which may help identify the viruses that have impacted our ancestors - pointing to which viruses have future pandemic potential. Here, we apply evolutionary analyses to human genomic datasets to recover selection events involving tens of human genes that interact with coronaviruses, including SARS-CoV-2, that likely started more than 20,000 years ago. These adaptive events were limited to the population ancestral to East Asian populations. Multiple lines of functional evidence support an ancient viral selective pressure, and East Asia is the geographical origin of several modern coronavirus epidemics. An arms race with an ancient coronavirus, or with a different virus that happened to use similar interactions as coronaviruses with human hosts, may thus have taken place in ancestral East Asian populations. By learning more about our ancient viral foes, our study highlights the promise of evolutionary information to better predict the pandemics of the future. Importantly, adaptation to ancient viral epidemics in specific human populations does not necessarily imply any difference in genetic susceptibility between different human populations, and the current evidence points toward an overwhelming impact of socioeconomic factors in the case of COVID-19.

evolutionary biology↗

bioRxiv2020

Introgression, hominin dispersal and megafaunal survival in Late Pleistocene Island Southeast Asia

The hominin fossil record of Island Southeast Asia (ISEA) indicates that at least two endemic super-archaic species - Homo luzonensis and H. floresiensis - were present around the time anatomically modern humans (AMH) arrived in the region >50,000 years ago. Contemporary human populations carry signals consistent with interbreeding events with Denisovans in ISEA - a species that is thought to be more closely related to AMH than the super-archaic endemic ISEA hominins. To query this disparity between fossil and genetic evidence, we performed a comprehensive search for super-archaic introgression in >400 modern human genomes. Our results corroborate widespread Denisovan ancestry in ISEA populations but fail to detect any super-archaic admixture signals. By highlighting local megafaunal survival east of the Wallace Line as a potential signature of deep, pre-H. sapiens hominin-faunal interaction, we propose that this understudied region may hold the key to unlocking significant chapters in Denisovan prehistory.

evolutionary biology↗

bioRxiv2020

Ancient human genomes reveal a hidden history of strong selection in Eurasia

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied upon genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has likely been underappreciated in the evolutionary history of humans and suggests that our current understanding of the tempo and mode of selection in natural populations may be quite inaccurate.

genomics↗

bioRxiv2018

Dimension Reduction and Visualization for Single-copy Alignments via Generalized PCA

Single-copy sequence alignments have been a valuable source of information for genetic studies; their lack of recombination makes phylogenetic analyses tractable [1]. Specifically, mitochondrial DNA will continue to play an important role in genetic studies due to its high mutation rate and high copy per cell count of the molecule [2]. In this paper we develop a new method for the analysis of single-copy sequence data that simultaneously considers the relationships between sequenced individuals and positions of interest in the genome. We then show that tests for relationships between genetic information and qualitative and quantitative characteristics can be calculated. We motivate the use of our method with examples from empirical data.

bioinformatics↗

bioRxiv2018

Polygenic adaptation fuels genetic redundancy in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic - i.e. result from selection on a large number of genetic loci - but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes across many contributing loci. To resolve this, we use laboratory natural selection, a framework that is powerful enough to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among adaptive alleles. We observed convergent phenotypic responses, e.g. fitness, metabolic rate and fat content, and a strong polygenic response (99 selected alleles; mean s=0.061). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses. The observed genetic redundancy potentiates this genotypic variation through multiple genetic pathways leading to phenotypic convergence. This key property of adaptive alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

evolutionary biology↗

bioRxiv2017

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation. To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements revealed extensive metabolic rewiring after only [~]60 generations in a hot environment. Analysis of genome-wide polymorphisms identified two interacting selection targets, Sestrin and SNF4A{gamma}, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation. Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4A{gamma} also exhibits clinal variation in various Drosophila species, we suggest that this large effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

evolutionary biology↗