Biology subjects

Bossu, C. M.

Publications and source records attributed to Bossu, C. M..

5 recordsLinked to original sources

bioRxiv2026

Loss of Adaptive Capacity Drives Climate Vulnerability Across Taxonomic Scales in an Alpine Specialist Species Complex

Accelerated warming at high elevations is having a disproportionate impact on alpine species. While assessments of climate vulnerability require quantifying the ecological and evolutionary components of adaptive capacity, such assessments are rare, especially in alpine systems. We leverage recent advances in population and landscape genomics to assess how variation in spatial heterogeneity and population connectivity across alpine systems influences adaptive capacity, using the North American Rosy-Finch species complex as a model system. In doing so, we clarify taxonomic relationships across the complex and identify one new ESU, the Sierra Nevada Rosy-Finch, based on its combined ecological and evolutionary distinctiveness. We then illustrate how combining genomic analyses with ecological data can improve estimates of adaptive capacity, sensitivity, and exposure and ultimately clarify climate vulnerability. Overall, our integrative analyses revealed that more isolated lineages, such as the Sierra Nevada Rosy-Finch, have lower adaptive capacity and face disproportionately high risks from climate change. This work highlights how conservation strategies that account for the multidimensional aspects of adaptive capacity can improve estimates of climate vulnerability.

evolutionary biology↗

bioRxiv2026

Identifying adaptive variation in spatially structured populations using low-coverage whole-genome sequencing data

Successful implementation of evolutionary programs to rescue climatically threatened species requires identification of adaptive variation. Although many genotype-environment association methods have been successful in identifying adaptive variation, current approaches can be improved in two important aspects. First, most existing methods do not account for genotype uncertainty in widely available low-coverage whole-genome sequencing data. Researchers often restrict analysis to loci for which genotypes can be inferred reliably or call the most probable genotype, allowing the use of genotype-based methods. However, discarding data and false genotype calls increase the uncertainty in estimates of genetic variation and can introduce systematic biases. Second, most methods use phenomenological approaches, such as logistic regression, to partition estimated variation into adaptive and non-adaptive components. Consequently, current approaches may fail to account for evolutionary processes, such as migration-selection balance. Structured migration between climatically disparate locations can produce deviations from a smooth S-shape response curve, which can be difficult to accommodate using generalized linear models. To overcome these challenges, we developed a method that accounts for genotype uncertainty in sequencing data and propagates this uncertainty to inform the parameters of an evolutionary model. A key feature of this model is that it describes mechanistically how genetic variation arises from joint interactions between local adaptation, structured migration, mutation, and drift. Our synthetic simulation tests reveal that accounting for genotype uncertainty and structured migration substantially reduces false negatives. We also applied our approach to analyze data on North American rosy-finches (3.7 million SNPs), a high-alpine, climatically threatened clade of bird species.

genomics↗

bioRxiv2025

Summer rainfall drives adaptation with gene flow in a widespread butterfly

Understanding how environmental variation interacts with gene flow to shape population genomic patterns is a central goal in evolutionary biology. We investigated how geographic and environmental differences impact genomic variation in the clouded sulfur butterfly (Colias philodice eriphyle) by conducting whole-genome resequencing across replicated transects consisting of paired high- and low-elevation sites on both sides of a major mountain range. Despite sampling across steep environmental gradients, we found no evidence of discrete population structure, indicating high connectivity across the region. Nonetheless, significant isolation by distance - strongest in eastern populations - revealed that geographic distance still imposes limits on gene flow, and genetic diversity was also elevated in the east. Genotype-environment association analyses identified more than 16,000 loci associated with elevation, precipitation, and solar radiation. Our redundancy analysis identified precipitation as the strongest predictor of adaptive genomic differentiation, and candidate genes included those linked to melanization and thermoregulation (e.g., TH and yellow). These results demonstrate that even in a largely panmictic population, environmental variation can maintain regional-scale signals of local adaptation. Because insects are declining globally and remain underrepresented in genomic monitoring, conducting whole-genome analyses in a widespread species provides valuable context for assessing how insects today persist across such diverse landscapes and their potential for withstanding future environmental change.

evolutionary biology↗

bioRxiv2025

Migration patterns and hybridization within the Asian stonechat complex in response to a major geographical barrier

Long-distance avian migration is thought to be under strong natural selection. Facing geographical barriers, migrants display various patterns considered to be adaptive. For example, they may detour along either side around the barrier or cross it, requiring specialized behavioral adaptations. Variations within closely related taxa are excellent sources for understanding the evolutionary background of migration and how barriers are shaping migration routes. In Asia, some species are assumed to have a migratory divide in response to the major geographical barrier, the Qinghai-Tibet Plateau (QTP), including the stonechat taxa (Siberian Stonechat Saxicola maurus maurus and Amur Stonechat S. stejnegeri). As they detour along either side of the QTP, these taxa are believed to disfavor a crossing over the highland. However, the more southernly distributed Tibetan Stonechat (S. m. przewalskii) breeds on the QTP, suggesting adaptation to high elevation. To investigate migration patterns and the potentially associated genetic differences, we studied migration routes and population genetics of four populations around the assumed migratory divide in Russia and Mongolia, and of one from the QTP in China. Our results confirmed the existence of a migratory divide between maurus and stejnegeri, albeit with extensive hybridization. We observed both the hypothesized western and eastern routes, but also found individuals employing intermediate routes crossing the QTP, of which two-thirds were clear hybrids. Meanwhile, przewalskii followed a highland-crossing route and was genetically differentiated from maurus and stejnegeri. The diverse migration routes among Asian stonechats show differential responses towards the geographical barrier. The intermediate route may be associated with hybridization, and its conditional viability may facilitate gene flow between maurus and stejnegeri. The Asian stonechat complex thus offers great opportunities for novel research of the genetics and evolution of migration. The specific evolutionary background associated with inhabiting and crossing the QTP can offer new perspectives in this field. Teaser textMigratory divides can arise in birds because alternative routes around migratory barriers would select for behaviors to restrict hybridization. Hybrids of parental types that employ alternative routes are hypothesized to embark on intermediate routes that would expose them to suboptimal conditions, resulting in post-zygotic reproductive isolation. However, this hypothesis is challenged when a sister taxon actually breeds on the geographical barrier. This is the case in the Asian stonechat complex that breeds near or on the Qinghai-Tibet Plateau (QTP), the roof of the world. We demonstrated a migratory divide in central Siberia to Mongolia for race maurus and stejnegeri, yet showed also evidence for extensive hybridization. Hybrids migrated along a newly discovered intermediate route, seemingly viable and overlaps with the migration trajectory of race przewalskii over the eastern part of the QTP. The Asian migratory divide relative to the QTP thus provided new insights to the evolution of landbird migration.

evolutionary biology↗

bioRxiv2024

Identifying genomic adaptation to local climate using a mechanistic evolutionary model

O_LIIdentifying genomic adaptation is key to understanding species evolutionary responses to environmental changes. However, current methods to identify adaptive variation have two major limitations. First, when estimating genetic variation, most methods do not account for observational uncertainty in genetic data because of finite sampling and missing genotypes. Second, many current methods use phenomenological models to partition genetic variation into adaptive and non-adaptive components. C_LIO_LIWe address these limitations by developing a hierarchical Bayesian model that explicitly accounts for observational uncertainty and underlying evolutionary processes. The first layer of the hierarchy is the data model that captures observational uncertainty by probabilistically linking RAD-sequence data to genetic variation. The second layer is a process model that represents how evolutionary forces, such as local adaptation, mutation, migration, and drift, maintain genetic variation. The third layer is the parameter model, which incorporates our knowledge about biological processes. For example, because most loci in the genome are expected to be neutral, the environmental sensitivity coefficients are assigned a regularized prior centered at zero. Together, the three models provide a rigorous probabilistic framework to identify local adaptation in wild organisms. C_LIO_LIAnalysis of simulated RAD-seq data shows that our statistical model can reliably infer adaptive genetic variation. To show the real-world applicability of our method, we re-analyzed RAD-seq data ([~]105k SNPs) from Willow Flycatchers (Empidonax traillii) in the USA. We found 30 genes close to loci that showed a statistically significant association with temperature seasonality. Gene ontology suggests that several of these genes play a crucial role in egg mineralization, feather development, and the ability to withstand extreme temperatures. C_LIO_LIMoreover, the data and process models can be modified to accommodate a wide range of genetic datasets (e.g., pool and low coverage genome sequencing) and demographic histories (e.g., range shifts) to study climatic adaptation in a wide range of natural systems. C_LI

genomics↗