Biology subjects

Setter, D.

Publications and source records attributed to Setter, D..

10 recordsLinked to original sources

bioRxiv2026

Tuning the SMC: efficient simulation and the structure of ARGs

Sequentially Markovian Coalescent (SMC) models are a central element of contemporary population genetics, underlying many inferential methods. While the SMC has been shown to closely approximate the canonical Coalescent with Recombination (CwR) in terms of low-dimensional, two-locus summaries, its effects on the deeper structural properties of Ancestral Recombination Graphs (ARGs) are less well understood. Here, we define a general SMC approximation, SMC(k), in which a single parameter k controls the physical scale over which common-ancestor events between non-overlapping ancestral segments are permitted. The model encompasses the standard SMC and SMC' as special cases and converges to the CwR as k increases, providing a tunable trade-off between computational efficiency and fidelity to the full recombination process. Using recently developed summaries of ARG structure, we show that SMC approximations systematically truncate the persistence of ancestral haplotypes across the genome, despite preserving marginal coalescent properties, and that increasing k progressively recovers this long-range ancestral structure. We implement the SMC(k) in msprime and show that, for small samples, it makes whole-chromosome simulation in species with large population-scaled recombination rates several orders of magnitude faster than the CwR. Finally, we use SMC simulations for chromosome-scale parametric bootstrapping of demographic inference and find that the SMC' captures uncertainty in SFS-based estimates remarkably well, with only modest changes as k increases despite substantial differences in long-range ARG structure. Thus, the importance of SMC approximation error depends strongly on which properties of ancestry are relevant to the downstream analysis.

genomics↗

bioRxiv2026

diempy: fast and reference-free genome polarisation

Most ancestry-assignment methods rely on putatively pure reference panels, which are often unrealistic and bias inference. The genome polarisation algorithm diem, introduced previously, avoids reference panels by jointly inferring the polarity of common allelic states and quantifying variant diagnosticity via an expectation-maximisation procedure. Here we present diempy, an efficient python implementation of diem coupled with tools that turn polarised calls into analysis-ready outputs. diempy offers lossless VCF-to-diem BED conversion; ploidy-aware handling of individuals and chromosomes; flexible masking of sites, regions and individuals; and interactive visualisation of polarised genomes, hybrid indices, clines and ternary plots. Post-processing functions include DI thresholding, kernel smoothing, and automatic detection and run-length encoding of contiguous ancestry tracts. BED-based I/O facilitates integration with population-genomic workflows (e.g. filtering by annotation or ploidy). These features make reference-free genome polarisation with diempy practical and reproducible for studies of population structure, admixture and species barriers.

evolutionary biology↗

bioRxiv2024

Genealogical asymmetry under the IM model and a two-taxon test for gene flow

Methods for detecting gene flow between populations often rely on asymmetry in the average length of particular genealogical branches, with the ABBA-BABA test being a well known example. Currently, asymmetry-based methods cannot be applied to a pair of populations and such analyses are instead performed using model-based methods. Here we investigate genealogical asymmetry under a two-population isolation-migration model. We focus on genealogies where the first coalescence event is between lineages sampled from different populations, as the external branches of these genealogies have equal expected length as long as there is no post-divergence gene flow. We show that unidirectional gene flow breaks this symmetry and results in the recipient population having longer external branches. We derive expectations for the probability of this genealogical asymmetry under the isolation-migration model and propose a simple statistic (Am) to detect it from genome sequence data. Am provides a two-taxon test for gene flow that only requires a single unphased diploid genome from each population, with no outgroup information. We use analytic expectations and coalescent simulations to explore how recombination, unequal effective population sizes and bidirectional gene flow influence Am and find that the statistic provides unambiguous evidence for gene flow under a continent-island history. We estimate Am for genome sequence data from Heliconius butterflies and Odocoileus deer, generating results consistent with previous model-based analyses. Our work highlights a signal of gene flow overlooked to date and provides a method that complements existing approaches for investigating the demographic history of recently diverged populations.

evolutionary biology↗

bioRxiv2023

Breakups and Hookups: a Markov model for karyotype evolution

Chromosome rearrangements represent a prominent form of genetic variation that plays a key role in creating genetic isolation between emergent species. Despite their significance, the mechanisms and constraints governing chromosome evolution remain poorly understood. Relatively few species have karyotypes with very high chromosome counts, and the chromosome sizes of most species tend to be narrowly distributed around the mean length. Here, we develop and analyze a Markov model for the evolution of chromosome number and relative sizes through fission and fusion events, exploring several alternative models for the dynamics of each as well as the effect of enforcing limits on chromosome length. We compare the distribution of chromosome lengths predicted by the Markov model to karyotype data for a range of Eukaryote species to identify the best-fitting fission/fusion dynamics. We find broad support for a model which (i) favours the breaking of long chromosomes, (ii) favours the fusion of pairs of small chromosomes, and (iii) does not require size limitations to provide a good fit to the data. However, there are exceptions. On the one hand, species with micro chromosomes fit best to models with more uniform rates of fission and/or fusion. On the other hand, many species have chromosome sizes that are much more narrowly distributed than our models predict, suggesting the need to explore alternative dynamics and/or limitations to chromosome lengths.

evolutionary biology↗

bioRxiv2023

Do chromosome rearrangements fix by genetic drift or natural selection? A test in Brenthis butterflies

Large-scale chromosome rearrangements, such as fissions and fusions, are a common feature of eukaryote evolution. They can have considerable influence on the evolution of populations, yet it remains unclear exactly how rearrangements become established and eventually fix. Rearrangements could fix by genetic drift if they are weakly deleterious or neutral, or they may instead be favoured by positive natural selection. Here we compare genome assemblies of three closely related Brenthis butterfly species and characterise a complex history of fission and fusion rearrangements. An inferred demographic history of these species suggests that rearrangements became fixed in populations with large long-term effective size (Ne). However, we also find large runs of homozygosity within individual genomes and show that a model of population structure with smaller local Ne can reconcile these observations. Using a recently developed analytic framework for characterising hard selective sweeps, we find that chromosome fusions are not enriched for evidence of past sweeps compared to other regions of the genome. Nonetheless, one chromosome fusion in the B. daphne genome is associated with a valley of diversity where genealogical branch lengths are distorted, consistent with a selective sweep. Our results suggest that drift is a stronger force in these populations than suggested by overall genetic diversity, but that the fixation of strongly underdominant rearrangements remains unlikely. Additionally, although chromosome fusions do not typically exhibit signatures of selective sweeps, a single example raises the possibility that natural selection may sometimes play a role in their fixation.

evolutionary biology↗

bioRxiv2022

Demographically explicit scans for barriers to gene flow using gIMble

Identifying regions of the genome that act as barriers to gene flow between recently diverged taxa has remained challenging given the many evolutionary forces that generate variation in genetic diversity and divergence along the genome, and the stochastic nature of this variation. Progress has been impeded by a conceptual and methodological divide between analyses that infer the demographic history of speciation and genome scans aimed at identifying locally maladaptive alleles i.e. genomic barriers to gene flow. Here we implement genomewide IM blockwise likelihood estimation (gIMble), a composite likelihood approach for the quantification of barriers, that bridges this divide. This analytic framework captures background selection and selection against barriers in a model of isolation with migration (IM) as heterogeneity in effective population size (Ne) and effective migration rate (me), respectively. Variation in both effective demographic parameters is estimated in sliding windows via pre-computed likelihood grids. gIMble includes modules for pre-processing/filtering of genomic data and performing parametric bootstraps using coalescent simulations. To demonstrate the new approach, we analyse data from a well-studied pair of sister species of tropical butterflies with a known history of post-divergence gene flow: Heliconius melpomene and H. cydno. Our analyses uncover both large-effect barrier loci (including well-known wing-pattern genes) and a genome-wide signal of a polygenic barrier architecture. Author summaryAs a fundamental process generating biological diversity, speciation involves the evolution of reproductive isolation and thus the build-up of barriers to genetic exchange among organismal groups. While population genomic data are arguably the only source of information we have about most recent speciation events, the way such data are analysed remains depressingly superficial: population genomic studies of speciation are phrased either as scans for outliers of genetic differentiation, or are based on models of neutral evolution under the constraint of a single genome-wide demography. Here we introduce a new statistical framework called gIMble to estimate the effective rate of gene flow and the effective population sizes along the genome from population genomic data. By capturing genome-wide variation in these two effective demographic parameters, gIMble disentangles the genomic footprints of different modes of selection and provides a direct quantification of the species barrier. To illustrate this framework, we analyse a classic speciation genomic dataset from Heliconius butterflies. We show that barriers to gene flow in this system include both large effect loci - most, but not all, of which were known from functional work - as well as a genome-wide signature of weak-effect polygenic barriers.

evolutionary biology↗

bioRxiv2021

Estimating the rates of crossover and gene conversion from individual genomes

Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the two processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for co-estimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at two loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well studied model. Our analyses show i) that the rates of crossover and gene conversion can be accurately co-estimated at the level of individual chromosomes and ii) that previous estimates of the population scaled rate of recombination [Formula] under a pure crossover model are likely biased.

evolutionary biology↗

bioRxiv2021

Sweeps in time: leveraging the joint distribution of branch lengths

Current methods of identifying positively selected regions of the genome are limited by their underlying model in two key ways: the model cannot account for the timing of the adaptive event and the analytic predictions are limited to single nucleotide polymorphisms. Here we develop a tractable method of describing the effect of positive selection on the genealogical histories in the surrounding genome, explicitly modeling both the timing and context of the adaptive event. In addition, our framework allows us to go beyond simple polymorphism data. We are able to leverage information contained in patterns of linked variants, and even with very small sample sizes, our analytic framework has high power to identify historically adaptive regions of the genome and to correctly infer both the time and strength of selection. Finally, we derived the marginal distribution of genealogical branch lengths at a locus affected by selection acting at a linked site. This provides a much-needed link between current theoretical models to recent advances in simulation procedures that have allowed researchers both to examine the evolution of genealogical histories at the level of full chromosomes and build methods that attempt to reconstruct full ancestries from genome sequence data.

evolutionary biology↗

bioRxiv2019

The impact of global selection on local adaptation and reproductive isolation.

Despite the homogenising effect of strong gene flow between two populations, adaptation under symmetric divergent selection pressures results in partial reproductive isolation: adaptive substitutions act as local barriers to gene flow, and if divergent selection continues unimpeded, this will result in complete reproductive isolation of the two populations, i.e. speciation. However, a key issue in framing the process of speciation as a tension between local adaptation and the homogenising force of gene flow is that the mutation process is blind to changes in the environment and therefore tends to limit adaptation. Here we investigate how globally beneficial mutations (GBMs) affect divergent local adaptation and reproductive isolation. When phenotypic divergence is finite, we show that the presence of GBMs limits local adaptation, generating a persistent genetic load at the loci which contribute to the trait under divergent selection and reducing genome-wide divergence. Furthermore, we show that while GBMs cannot prohibit the process of continuous differentiation, they induce a substantial delay in the genome-wide shutdown of gene flow.

evolutionary biology↗

bioRxiv2019

VolcanoFinder: genomic scans for adaptive introgression

Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method--VolcanoFinder--to detect recent events of adaptive introgression using polymorphism data from the recipient species only.\n\nVolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity.\n\nUsing coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.\n\nAuthor summaryThe process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source method VolcanoFinder to detect this signal in genomic data. Importantly, VolcanoFinder is a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even from a priori unknown and possibly extinct donor species.

evolutionary biology↗