bioRxivEvolutionary Biology
Genomic signatures of desert adaptation at gene-rich regions in zebu cattle from the African drylands
A. Tijjani, B. Salim, M. V. Barbosa da Silva, H. A. Eltahir, T. H. Musa, K. Marshall, O. Hanotte, H. H. Musa
Abstract
Sudan, the largest country in Africa, acts as a corridor between North and sub-Saharan Africa along the river Niles. It comprises warm arid and semi-arid grazing lands, and it is home to the second-largest African population of indigenous livestock. Indigenous Sudanese cattle are mainly indicine/zebu (humped) type. They thrive in the harshest dryland environments characterised by high temperatures, long seasonal dry periods, nutritional shortages, and vector diseases challenges. We investigated genome diversity in six indigenous African zebu breeds sampled in Sudan (Aryashai, Baggara, Butana, Fulani, Gash, and Kenana). We adopted three genomic scan approaches to identify candidate selective sweeps regions (ZHp, FST, XP-EHH). We identified a set of gene-rich selective sweep regions shared across African and Asian zebu or unique to Sudanese zebu. In particular, African and Asian zebu candidate gene-rich regions are detected on chromosomes 2, 5 and 7. They include genes involved in immune response, body size and conformation, and stress response to heat. In addition, a 250 kb selective sweep on chromosome 16 was detected exclusively in five Sudanese zebu populations. This region spans seven genes, including PLCH2, PEX10, PRKCZ and SKI, which are involved in alternative adaptive metabolic strategies of insulin signalling, glucose homeostasis, and fat metabolism. Together, these genes may contribute to the zebu cattle resilience to heat, nutritional and water shortages. Our results highlight the putative importance of selection at gene-rich genome regions, which might be under a common regulatory genetic control, as an evolutionary mechanism for rapid adaptation to the complexity of environmental challenges.
- organism: zebrafish
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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