Biology subjects

Ishigohoka, J.

Publications and source records attributed to Ishigohoka, J..

3 recordsLinked to original sources

bioRxiv2025

Shifting balancing selection on a chromosomal inversion in island populations

Chromosomal inversions often underlie local adaptation and differentiation between populations. However, little is known about how selection acting on a balanced inversion shifts in different environments in the context of demographic events. Here, we combine population genomic approaches with extensive simulations to show that split events of island populations shifted a parameter of balancing selection on a polymorphic inversion. In Eurasian blackcaps (Sylvia atricapilla), an 8 Mb-long inversion has been maintained polymorphic in most populations across the species distribution range by long-term balancing selection. The frequency of this inversion is consistently lower in island resident and continental resident populations compared to behaviourally ancestral continental migrant populations. Inference of population history shows that at least four groups of residents, specifically one continental population and three sets of populations on different island systems, originate from independent and simultaneous split events from one ancestral population. Such a demographic history indicates that the consistent reduction in the inversion frequency among these independent resident populations is unlikely due to shared stochastic events. Approximate Bayesian computation (ABC) applied to simulations of balancing selection under the blackcap demography indicates that the optimal frequency of the inversion in the regime of negative frequency-dependent selection, a type of balancing selection, became lower in island populations. These results highlight how parallel shifts in selection parameters in similar environments can contribute to genetic differentiation among populations at inversion loci.

evolutionary biology↗

bioRxiv2024

High-recombining genomic regions affect demography inference

Inference of population history of non-model species is important in evolutionary and conser- vation biology. Multiple methods of population genomics, including those to infer population history, are based on the ancestral recombination graph (ARG). These methods use observed mutations to model local genealogies changing along chromosomes. Breakpoints at which genealogies change effectively represent the positions of historical recombination events. How- ever, inference of underlying genealogies is difficult in regions with high recombination rate relative to mutation rate. This is because genealogies cover genomic intervals that are too short to accommodate sufficiently many mutations informative of the structure of the un- derlying genealogies. Despite the prevalence of high-recombining genomic regions in some non-model organisms, such as birds, its effect on ARG-based demography inference has not been well studied. Here, we use population genomics simulations to investigate the impact of high-recombining regions on ARG-based demography inference. We demonstrate that inference of effective population size and the time of population split events is systematically affected when high-recombining regions cover wide breadths of the chromosomes. We also show that excluding high-recombining genomic regions can practically mitigate this effect. Finally, we confirm the relevance of our findings in empirical analysis by contrasting demography inferences applied for a bird species, the Eurasian blackcap (Sylvia atricapilla), using different parts of the genome with high and low recombination rates. Our results suggest that demography inference using ARG-based methods should be carried out with caution when applied in species whose reference genomes contain long stretches of high-recombining regions.

evolutionary biology↗

bioRxiv2021

Recombination suppression and selection affect local ancestries in genomes of a migratory songbird

Genetic variation of the entire genome represents population structure, yet individual loci can show distinct patterns. Such deviations identified through genome scans have often been attributed to effects of selection instead of randomness. This interpretation assumes that long enough genomic intervals average out randomness in underlying genealogies, which represent local genetic ancestries. However, an alternative explanation to distinct patterns has not been fully addressed: too few genealogies to average out the effect of randomness. Specifically, distinct patterns of genetic variation may be due to reduced local recombination rate, which reduces the number of genealogies in a genomic window. Here, we associate distinct patterns of local genetic variation with reduced recombination rates in a songbird, the Eurasian blackcap (Sylvia atricapilla), using genome sequences and recombination maps. We find that distinct patterns of local genetic variation reflect haplotype structure at low-recombining regions either shared in most populations or found only in a few populations. At the former species-wide low-recombining regions, genetic variation depicts conspicuous haplotypes segregating in multiple populations. At the latter population-specific low-recombining regions, genetic variation represents variance among cryptic haplotypes within the low-recombining populations. With simulations, we confirm that these distinct patterns of haplotype structure evolve due to reduced recombination rate, on which the effects of selection can be overlaid. Our results highlight that distinct patterns of genetic variation can emerge through evolution of reduced local recombination rate. Recombination landscape as an evolvable trait therefore plays an important role determining the heterogeneous distribution of genetic variation along the genome.

evolutionary biology↗