Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens

Fasil Getachew Kebede*, Martijn F.L. Derks, Tadelle Dessie, Olivier Hanotte, Carolina Pita Barros, Richard P.M.A. Crooijmans, Hans Komen, John W.M. Bastiaansen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6–7 populations per gradient). We performed signatures of selection analyses (and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified byand XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.

Original languageEnglish
Article number284
JournalBMC Genomics
Issue number1
Publication statusPublished - 18 Mar 2024


  • Environmental predictors
  • Genetic improvement
  • Local adaptation
  • Poultry production
  • Quantitative traits
  • Redundancy analysis
  • Signatures of selection


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