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Whole-genome sequences of 240 indigenous African cattle from Egypt, Uganda, and South Africa
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  • Published: 19 May 2026

Whole-genome sequences of 240 indigenous African cattle from Egypt, Uganda, and South Africa

  • Njabulo Dlamini1 na1,
  • Junxin Gao  ORCID: orcid.org/0009-0003-9308-16462 na1,
  • Catarina Ginja3,4,
  • Juha Kantanen  ORCID: orcid.org/0000-0001-6350-63735,
  • Nasser Ghanem6,
  • Donald R. Kugonza7,
  • Mahlako Makgahlela  ORCID: orcid.org/0000-0003-1275-45581,8,
  • Ahmed Elnahas9,
  • Avhashoni Zwane10,
  • Barbara Mugwanya Zawedde11,
  • Christine Nakkazi11,
  • Generous Behabura8,
  • Khaniysani Nxumalo12,
  • Maano Malima1,
  • Mohamed Ali Radwan7,
  • Mohamed Hamada Elsawy13,
  • Morris Agaba8,
  • Nadia Hamdy Fahim7,
  • Rana Atef Khfagy14,
  • Rania Agamy7,
  • Rodney Okwasiimire15,
  • Sarah Waibi15,
  • Simon Lashmar1 &
  • …
  • Richard P. M. A. Crooijmans  ORCID: orcid.org/0000-0001-8108-99723 

Scientific Data (2026) Cite this article

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Subjects

  • Agricultural genetics
  • DNA sequencing
  • Next-generation sequencing

Abstract

Indigenous cattle are central to livestock production in Africa, valued for their adaptability to harsh tropical environments despite lower productivity than commercial breeds. Genome analyses offer critical insights into the genetic potential for enhancing both resilience and productive traits, supporting the advancement of worldwide cattle farming systems. Here, we generated whole-genome sequence data for 240 indigenous cattle representing breeds from distinct agro-climatic regions in Egypt, Uganda, and South Africa. The dataset comprises over ten terabytes of paired-end reads generated using the Illumina NovaSeq. 6000 platform, with an average genome coverage of approximately 10×. Post-filtering reads were mapped to the ARS-UCD1.2 reference genome with a mean mapping rate of 99.2% (range: 64.5–99.9%). Variant calling identified ~43 million SNPs and 6 million indels (≤50 bp) unevenly distributed across the genome. Functional annotation indicated that many variants were located within or near known genes. This comprehensive genomic resource provides a foundation for future studies of genetic diversity, breed identity, population structure, local adaptation, breed-specific traits, or strategies for global cattle conservation.

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Acknowledgements

We thank all members of the OPTIBOV consortium for their invaluable contributions to sample collection, sequencing, and expert input. This study was funded by the Long-term EU-Africa Research and Innovation Partnership on Food and Nutrition Security and Sustainable Agriculture (LEAP-Agri) as part of the OPTIBOV project (LEAP-Agri-326), and by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 727715. The founders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We gratefully acknowledge the collaboration of the breeders and breed associations in Africa for maintaining these local genetic resources and providing access to the animals. For Uganda, we thank Damian Munirwa (College of Veterinary Medicine, Makerere University) for sampling and laboratory work with Nkedi and Karamojong breeds; Emmanuel Tayebwa (Ankole Cattle Conservation Trust), Kasoro Charles (Butuku Cattle Marketing Cooperative Society), and Birungi Edward (Butungama Cattle Marketing Cooperative Society) for their assistance with Ankole and Ntuuku cattle. For South Africa, we appreciate the support of the Agricultural Research Council (ARC) and breed associations for facilitating sampling of indigenous and commercial breeds. We thank Marina Botes and Mokgadi Seshoka (Afrikaner), Julius Sebei and Lucas Msiza (Bonsmara and Nguni), Jim Bredenkamp, Ben Raath, Christo Rothmann, and Kevin Cook (Tuli), Sandra Erasmus (Holstein-Friesian, ARC), and Simphiwe Nini (Nguni, ARC). Additional funding for Junxin Gao was provided by the China Scholarship Council (CSC), China (grant number 202208610017).

Author information

Author notes
  1. These authors contributed equally: Njabulo Dlamini, Junxin Gao.

Authors and Affiliations

  1. Agricultural Research Council, Animal Production, Irene, South Africa

    Njabulo Dlamini, Mahlako Makgahlela, Maano Malima & Simon Lashmar

  2. Animal Breeding and Genomics, Wageningen University & Research, Wageningen, The Netherlands

    Junxin Gao

  3. CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal

    Catarina Ginja & Richard P. M. A. Crooijmans

  4. BIOPOLIS, Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal

    Catarina Ginja

  5. Natural Resources Institute Finland, Jokioinen, Finland

    Juha Kantanen

  6. Animal Production Department, Faculty of Agriculture, Cairo University, Giza, Egypt

    Nasser Ghanem

  7. College of Agricultural and Environmental Sciences, Makerere University, Kampala, Uganda

    Donald R. Kugonza, Mohamed Ali Radwan, Nadia Hamdy Fahim & Rania Agamy

  8. Department of Animal, Science, University of the Free State, Bloemfontein, South Africa

    Mahlako Makgahlela, Generous Behabura & Morris Agaba

  9. Animal Production Department, Faculty of Agriculture, Sohag University, Sohag, Egypt

    Ahmed Elnahas

  10. Department of Genetics, University of Pretoria, Hatfield, Pretoria, South Africa

    Avhashoni Zwane

  11. National Agricultural Research Organization, Mukono Zonal Agricultural Research and Development Institute, Mukono, Uganda

    Barbara Mugwanya Zawedde & Christine Nakkazi

  12. Mpumalanga Department of Agricultural Rural Development, Land Reform and Environmental Affairs, Animal Research Directorate, Nooitgedacht Research Development Centre, Mpumalanga, South Africa

    Khaniysani Nxumalo

  13. Department of Cattle, Animal Production Research Institute, Agriculture Research Center, Dokki, Giza, Egypt

    Mohamed Hamada Elsawy

  14. Department of Genetics, Faculty of Agriculture, Cairo University, Giza, Egypt

    Rana Atef Khfagy

  15. College of Veterinary Medicine, Animal Resources and Biosecurity, Makerere University, Kampala, Uganda

    Rodney Okwasiimire & Sarah Waibi

Authors
  1. Njabulo Dlamini
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  2. Junxin Gao
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  3. Catarina Ginja
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  4. Juha Kantanen
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  5. Nasser Ghanem
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  6. Donald R. Kugonza
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  7. Mahlako Makgahlela
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  8. Ahmed Elnahas
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  9. Avhashoni Zwane
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  10. Barbara Mugwanya Zawedde
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  11. Christine Nakkazi
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  12. Generous Behabura
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  13. Khaniysani Nxumalo
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  14. Maano Malima
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  15. Mohamed Ali Radwan
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  16. Mohamed Hamada Elsawy
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  17. Morris Agaba
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  18. Nadia Hamdy Fahim
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  19. Rana Atef Khfagy
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  20. Rania Agamy
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  21. Rodney Okwasiimire
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  22. Sarah Waibi
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  23. Simon Lashmar
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  24. Richard P. M. A. Crooijmans
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Corresponding authors

Correspondence to Junxin Gao or Richard P. M. A. Crooijmans.

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Competing interests

The authors declare no competing interests.

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Supplementary information

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article

Dlamini, N., Gao, J., Ginja, C. et al. Whole-genome sequences of 240 indigenous African cattle from Egypt, Uganda, and South Africa. Sci Data (2026). https://doi.org/10.1038/s41597-026-07458-y

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  • Received: 29 August 2025

  • Accepted: 12 May 2026

  • Published: 19 May 2026

  • DOI: https://doi.org/10.1038/s41597-026-07458-y

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