Biology subjects

Gronau, I.

Publications and source records attributed to Gronau, I..

5 recordsLinked to original sources

bioRxiv2026

Targeted Chromosomal Sequencing of Wild Bonobos Identifies a Genetically Distinct Subpopulation East of the Lomami River

Bonobos (Pan paniscus), an endangered species, have for decades been genetically understudied, partly due to difficulties in obtaining high-quality samples. The study of their genome is important not only for understanding their evolution, but also for improving conservation efforts, including population management, diversity and inbreeding assessment, and tracking rescued individuals to combat illegal wildlife trafficking. Here, we use chromosome 21 target capture data from 156 non-invasively collected faecal samples from wild bonobos to perform a comprehensive analysis of their population structure. We confirm the existence of three previously suggested subpopulations identified here as Western, Central and Eastern bonobos which are defined by natural barriers of gene flow such as the Lomami River. By estimating levels of inbreeding, diversity and differentiation, we find support for isolation of mainly Western and Eastern populations and add information on the dispersal routes of their ancestors. We infer split times and separation of these populations and apply a genetic framework to geolocalize samples of unknown origin, showing that locations of their potential origin can be estimated with a precision of up to a median of [~]50 km. Our study provides valuable insight into the evolution and population structure of bonobos and reveals how rivers act as strong barriers between populations. It also offers resources for conservation efforts and highlights the need to monitor bonobo populations more closely, in particular isolated ones. ImpactBonobos have been difficult to study genetically due to their remote forest habitat and endangered status. Here we used non-invasive sampling and chromosome 21 target capture sequencing to perform the most detailed analysis to date of their population structure. We find three main subpopulations and genetic differentiation influenced by river barriers, especially with populations found on the Eastern side of the Lomami river. This data will be useful for identifying the geographic origin of confiscated samples and thus aid bonobo conservation efforts.

bioinformatics↗

bioRxiv2025

Accessible, realistic genome simulation with selection using stdpopsim

Selection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsims core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.

evolutionary biology↗

bioRxiv2024

Deep genetic substructure within bonobos

Establishing the genetic and geographic structure of populations is fundamental both to understand their evolutionary past and preserve their future, especially for endangered species. Nevertheless, the patterns of genetic population structure are unknown for most endangered species, including some of our closest living relatives. This is the case of bonobos (Pan paniscus) which together with chimpanzees (Pan troglodytes) are humans closest living relatives. Chimpanzees live across equatorial Africa and are classified into four subspecies (Groves, 2001), with some genetic population substructure even within subspecies. Conversely, bonobos live exclusively in the Democratic Republic of Congo and are considered a homogeneous group with low genetic diversity (Fischer et al. 2011) despite some population structure inferred from mtDNA. Nevertheless, mtDNA aside, their genetic structure remains unknown, hampering our understanding of the species and conservation efforts. Placing bonobos genetics in space is however challenging because, being endangered, only non-invasive sampling is possible for wild individuals. Here, we jointly analyse the exomes and mtDNA from 20 wild-born bonobos, the whole-genomes of 10 captive bonobos and the mtDNA of 61 wild individuals. We identify three genetically distinct bonobo groups of inferred Central, Western and Far-Western geographic origin within the bonobo range. We estimate the split time between the central and western populations to [~]145,000 years ago, and genetic differentiation to be in the order of that of the closest chimpanzee subspecies. We identify putative signatures of differential genetic adaptation among populations for genes associated with homeostasis, metabolism and the nervous system. Furthermore, our estimated long-term Ne for Far-West ([~]3,000) is among the lowest estimated for any great ape lineage. Our results highlight the need of attention to bonobo substructure, both in terms of research and conservation. Highlights- We identified three genetically distinct populations of bonobos, inferred as having Central, Western and Far-Western geographic origin within the species range. The estimated split time is [~]145,000 years ago for the Central and Western populations, and [~]60,000 years ago for the two Western populations. - The genetic differentiation between the Central and Far-Western bonobo populations is in the order of that between Central and Eastern chimpanzee subspecies, while the genetic differentiation among Western bonobo populations is similar to that among human groups. - Once substructure is accounted for, we infer a long-term effective population size (Ne) of only [~]3,000 for Far-Western bonobos, genetic isolation and inbreeding.

evolutionary biology↗

bioRxiv2024

Genome-AC-GAN: Enhancing Synthetic Genotype Generationthrough Auxiliary Classification

In recent years, there have been increasing attempts to develop computational methods for generating synthetic genomic data that aim to mimic real genomic datasets. Artificial genomes (AGs) generated by these methods have emerged as a promising potential solution for privacy concerns raised by public genomic datasets and as means to provide adequate representation of under-sampled populations. However, existing methods for generating AGs provide a very limited capability for faithfully capturing features of different sub-populations within a larger cohort. In this study, we propose a novel method called the Genome Auxiliary Classifier Generative Adversarial Network (Genome-AC-GAN), which generates AGs tailored to specific sub-populations. We conducted experiments to evaluate the performance of the Genome-AC-GAN and compare the AGs it generates with real genomic data as well as with AGs generated by previously published methods. The Genome-AC-GAN outperforms other methods and faithfully models population structure, which is not adequately captured by existing methods. We also demonstrate the use of AGs generated by the Genome-AC-GAN in augmentation of datasets used as training sets for classifying genomes into populations. These experiments demonstrate the benefits of AGs in enhancing classification accuracy, especially when dealing with under-sampled and closely related populations.

genomics↗

bioRxiv2020

Genomic islands of differentiation in a rapid avian radiation have been driven by recent selective sweeps

Numerous studies of emerging species have identified genomic "islands" of elevated differentiation against a background of relative homogeneity. The causes of these islands remain unclear, however, with some signs pointing toward "speciation genes" that locally restrict gene flow and others suggesting selective sweeps that have occurred within nascent species after speciation. Here, we examine this question through the lens of genome sequence data for five species of southern capuchino seedeaters, finch-like birds from South America that have undergone a species radiation during the last [~]50,000 generations. By applying newly developed statistical methods for ancestral recombination graph inference and machine-learning methods for the prediction of selective sweeps, we show that previously identified islands of differentiation in these birds appear to be generally associated with relatively recent, species-specific selective sweeps, most of which are predicted to be "soft" sweeps acting on standing genetic variation. Many of these sweeps coincide with genes associated with melanin-based variation in plumage, suggesting a prominent role for sexual selection. At the same time, a few loci also exhibit indications of possible selection against gene flow. These observations shed new light on the complex manner in which natural selection shapes genome sequences during speciation. Significance StatementGenome-wide scans can identify differentiated loci between species that may have promoted speciation. So-called "islands of differentiation" have generally been identified and characterized using standard population genetic summary statistics (e.g., FST and dxy), which are limited in distinguishing among possible causes of differentiation, such as selection against gene flow and selective sweeps. We introduce a powerful strategy for analyzing such islands, combining new methods for inferring the full Ancestral Recombination Graph and machine learning methods for identifying selective sweeps. We applied our methods to genomic sequences from closely related southern capuchino seedeaters (Neotropical tanagers) and found signatures of recent selective sweeps around pigmentation genes, including many "soft" sweeps that acted on standing variation.

evolutionary biology↗