4.7 Article Data Paper

Whole genome sequences of 234 indigenous African chickens from Ethiopia

Journal

SCIENTIFIC DATA
Volume 9, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41597-022-01129-4

Keywords

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Funding

  1. Bill and Melinda Gates Foundation (BMGF)
  2. UK aid from the UK Government's Department for International Development of the Centre for Tropical Livestock Genetics and Health (CTLGH) [OPP1127286]
  3. University of Edinburgh
  4. SRUC (Scotland's Rural College)
  5. International Livestock Research Institute
  6. Administrative Department of Science, Technology and Innovation (Colciencias) - Colombian Government [728]
  7. CGIAR livestock program (CRP)
  8. University of Nottingham

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Indigenous chickens are dominant in poultry production in Africa, but their productivity is relatively low. Whole-genome sequences of 234 indigenous chickens from 24 Ethiopian populations have been obtained, providing valuable resources for investigating genetic diversity and environmental adaptations.
Indigenous chickens predominate poultry production in Africa. Although preferred for backyard farming because of their adaptability to harsh tropical environments, these populations suffer from relatively low productivity compared to commercial lines. Genome analyses can unravel the genetic potential of improvement of these birds for both production and resilience traits for the benefit of African poultry farming systems. Here we report whole-genome sequences of 234 indigenous chickens from 24 Ethiopian populations distributed under diverse agro-climatic conditions. The data represents over eight terabytes of paired-end sequences from the Ilumina HiSeqX platform with an average coverage of about 57X. Almost 99% of the sequence reads could be mapped against the chicken reference genome (GRCg6a), confirming the high quality of the data. Variant calling detected around 15 million SNPs, of which about 86% are known variants (i.e., present in public databases), providing further confidence on the data quality. The dataset provides an excellent resource for investigating genetic diversity and local environmental adaptations with important implications for breed improvement and conservation purposes.

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