Morales-Guerrero, A. | bioRxiv Science

bioRxiv2026

Drivers of immune-related genetic variation across human populations

Pathogen-mediated disease burden imposes some of the strongest selective pressures on human populations, shaping genetic variation in immune-related genomic regions. Because historical, cultural, ecological, and environmental factors can influence disease burden, associations between these factors and immune-related genomic signatures can provide insight into how pathogen-mediated selection varied among populations. To investigate these associations and identify factors potentially contributing to historical disease burden, we analyzed worldwide variation in the Major Histocompatibility Complex (MHC). We evaluated the relationships between global patterns of genetic variation and a comprehensive set of historical-cultural, ecological, and climatic variables compiled in DisECCO (Disease, Ecological, Cultural, and Climatic Origins dataset). This dataset includes factors potentially associated with historical disease burden, including the timing of major cultural transitions, historical climatic conditions, exposure to domesticated animals, and pre-industrial pathogen stress. Contrary to genome-wide expectations, MHC diversity and variation were not well explained by geographic distance from Africa, suggesting that neutral demographic processes play a limited role in shaping MHC variation. Instead, MHC genetic variation was significantly associated with climatic variables, domestication exposure, and the time lag between the onset of the Neolithic and urbanization, with the strongest explanatory models identified for MHC Class II. These results indicate that cultural transitions and environmental conditions have played a central role in shaping immune-related genetic variation, and may have contributed substantially to changes in disease burden. Overall, our findings show that integrating ecological and cultural-historical variables with genomic data can help explain global patterns of genetic variation in humans.

evolutionary biology↗

bioRxiv2026

Contrasting effects of forest fragmentation on the genetics and microbiomes of an endangered arboreal primate

Landscape fragmentation, one of the leading drivers of biodiversity loss, can reshape both the genetics and microbiomes of wild populations. Although fragmentation is generally expected to limit gene flow and erode genetic diversity, and to disrupt host-associated microbial communities, these responses arise via different pathways and may therefore diverge within the same population. To understand how fragmentation simultaneously shapes population genetics and gut microbiomes, we analyzed fecal-derived host genomic and microbiome data from endangered, arboreal black howler monkeys (Alouatta pigra) across a fragmentation gradient. We then integrated these data with measures of ecological connectivity, habitat quality, and demography to identify the drivers of genetic and microbiome variation and structure. Multivariate analyses indicated that genetic patterns were shaped by both connectivity and habitat quality, whereas microbiome variation was driven mainly by habitat quality. Contrary to expectations under reduced realized connectivity with increasing isolation, monkeys showed the strongest gene flow signal in the most fragmented region, and higher genetic diversity and lower inbreeding than monkeys in continuous forest. Relatedness and isolation-by-distance patterns suggested that fragmentation has sex-specific effects on movement, disrupting the usual pattern of short-range male dispersal in the most fragmented region. Gut microbiomes, however, showed predicted negative responses to fragmentation: individuals in highly fragmented habitat had lower microbial diversity and compositional shifts consistent with lower-quality diets and increased exposure to disturbed environments. These results show contrasting biological responses to fragmentation within a single population, with genetic patterns likely resulting from compensatory behavioral flexibility and microbiome patterns reflecting local habitat degradation. Our findings underscore the need for conservation assessments that integrate multiple dimensions of population health rather than relying on any single indicator of fragmentation impact.

ecology↗