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Using the Mus musculus hybrid zone to assess covariation and genetic architecture of limb bone lengths
Authors:Neva Škrabar  Leslie M. Turner  Luisa F. Pallares  Bettina Harr  Diethard Tautz
Affiliation:1. Max‐Planck Institute for Evolutionary Biology, Pl?n, Germany;2. Department of Biology and Biochemistry, Milner Centre for Evolution, University of Bath, Bath, UK;3. Lewis‐Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
Abstract:Two subspecies of the house mouse, Mus musculus domesticus and Mus musculus musculus, meet in a narrow contact zone across Europe. Mice in the hybrid zone are highly admixed, representing the full range of mixed ancestry from the two subspecies. Given the distinct morphologies of these subspecies, these natural hybrids can be used for genomewide association mapping at sufficiently high resolution to directly infer candidate genes. We focus here on limb bone length differences, which is of special interest for understanding the evolution of developmentally correlated traits. We used 172 first‐generation descendants of wild‐caught mice from the hybrid zone to measure the length of stylopod (humerus/femur), zeugopod (ulna/tibia) and autopod (metacarpal/metatarsal) elements in skeletal CT scans. We find phenotypic covariation between limb elements in the hybrids similar to patterns previously described in Mus musculus domesticus inbred strains, suggesting that the hybrid genotypes do not influence the covariation pattern in a major way. Mapping was performed using 143,592 SNPs and identified several genomic regions associated with length differences in each bone. Bone length was found to be highly polygenic. None of the candidate regions include the canonical genes known to control embryonic limb development. Instead, we are able to identify candidate genes with known roles in osteoblast differentiation and bone structure determination, as well as recently evolved genes of, as yet, unknown function.
Keywords:ecological genetics  hybrid zone  limbs  mapping  quantitative genetics
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