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The mosaic genome of indigenous African cattle as a unique genetic resource for African pastoralism


Cattle pastoralism plays a central role in human livelihood in Africa. However, the genetic history of its success remains unknown. Here, through whole-genome sequence analysis of 172 indigenous African cattle from 16 breeds representative of the main cattle groups, we identify a major taurine × indicine cattle admixture event dated to circa 750–1,050 yr ago, which has shaped the genome of today’s cattle in the Horn of Africa. We identify 16 loci linked to African environmental adaptations across crossbred animals showing an excess of taurine or indicine ancestry. These include immune-, heat-tolerance- and reproduction-related genes. Moreover, we identify one highly divergent locus in African taurine cattle, which is putatively linked to trypanotolerance and present in crossbred cattle living in trypanosomosis-infested areas. Our findings indicate that a combination of past taurine and recent indicine admixture-derived genetic resources is at the root of the present success of African pastoralism.

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Fig. 1: Historical and geographical origin of African cattle breeds in this study.
Fig. 2: Population structure of indigenous African cattle.
Fig. 3: Admixture signatures in African cattle genomes.
Fig. 4: Example of candidate selective loci on BTA7 with an excess of indicine ancestry.
Fig. 5: Example of candidate selective loci on BTA11 with an excess of taurine ancestry.
Fig. 6: Unique selection signatures in African taurine cattle following their separation from the common ancestor with Eurasian taurine cattle.

Data availability

The newly generated sequences for 114 African cattle and two African buffalo samples are available from the Sequence Read Archive (SRA) with the Bioproject accession number PRJNA574857. The publicly available sequences were downloaded from the SRA and China National GeneBank (CNGB) with the following project accession numbers; CNP0000189 (Achai, Bhagnari, Cholistani, Dajal, Dhanni, Gabrali, Hariana, Lohani, Red Sindhi, Sahiwal and Tharparkar), PRJNA318087 (Angus, Ankole, Jersey, Kenya Boran, Kenana, N’Dama and Ogaden), PRJNA514237 (Boskarin, Limia, Maremmana, Maronesa, Pajuna, Podolica and Sayaguesa), PRJNA324822 (Brahman), PRJNA343262 (Brahman, Gir, Hereford, Nelore and Simmental), PRJNA432125 (Brahman), PRJEB28185 (Eastern Finn and Western Finn), PRJNA210523 (Hanwoo), PRJNA379859 (Hariana, Sahiwal and Thaparkar), PRJNA210521 (Holstein), PRJNA386202 (Muturu) and PRJNA507259 (Nelore). The known variants file (ARS1.2PlusY_BQSR_v3.vcf.gz) for base quality score recalibration was provided by the 1000 Bull Genomes Project ( The annotation of the candidate regions was based on the ARS-UCD1.2 Gene Transfer Format file (.gtf) from Ensembl release 99 ( The PANTHER database ( was used for functional enrichment analysis of a candidate gene set.


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This work was supported by a grant from the Next-Generation BioGreen 21 Program and Post-Genome Project (Project Nos. PJ01323701 and PJ01040601), Rural Development Administration, Republic of Korea. Sampling of cattle populations was supported by the CGIAR Livestock and Fish CRP (Uganda and Ethiopia), the University of Khartoum (Sudan) and the National Biotechnology Development Agency (NABDA) (Nigeria). The following institutions and their personnel provided help for the sampling of the African cattle: the ILRI Kapiti Ranch; the Ministry of Animal Resources, Fisheries and Range (Sudan); the Ol Pejeta Conservancy (Kenya); the Institute of Biodiversity (Ethiopia); and the Directors of Veterinary Services and the cattle keepers from Ethiopia, Kenya, Uganda and Sudan. The ILRI livestock genomics program is supported by the CGIAR Research Program on Livestock (CRP Livestock), which is supported by contributors to the CGIAR Trust Fund ( This research was funded in part by the Bill & Melinda Gates Foundation and with UK aid from the UK Foreign, Commonwealth and Development Office (Grant Agreement OPP1127286) under the auspices of the Centre for Tropical Livestock Genetics and Health (CTLGH), established jointly by the University of Edinburgh, SRUC (Scotland’s Rural College) and the International Livestock Research Institute. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation or the UK Government. We thank the reviewers for their critical and constructive comments on the manuscript, and D. Gifford-Gonzalez (University of California, Santa Cruz, CA, USA) for a critical reading of the manuscript in light of the current knowledge on the archeology and history of African pastoralism.

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K.K. and O.H. devised the main conceptual ideas. O.H. and H.K. managed the project. D.L., S.C., S.J.O., H.-K.L., O.A.M., T.D., S.K., O.H. and H.K. conceived of and designed all of the described experiments. O.A.M., T.D., B.S., G.M.T. and A.T. contributed to sample collection and laboratory work. K.K., T.K., D.Y., J. Jang, S.S., S.L., J. Jung and H.J. analyzed the data. K.K., C.J., J.K. and O.H. drafted the manuscript. All authors read and approved the final manuscript.

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Correspondence to Olivier Hanotte or Heebal Kim.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Improvement in genotype concordance after genotype refinement using BEAGLE as a function of depth coverage.

The y-axis shows the concordance between genotypes called from sequencing data compared to genotypes obtained using the BovineSNP50 Genotyping BeadChip.

Extended Data Fig. 2 Delta K of cluster number K in genetic clustering analysis using ADMIXTURE.

A subset of ~1.6 million SNPs (linkage disequilibrium (LD)-based pruning using PLINK v1.9 with ‘-indep-pairwise 50 10 0.1’ option) was used for K from 1 to 10. The delta K analysis suggests K = 2 as the most likely number of distinct genetic ancestries among the 10 Ks (delta K = 31.02).

Extended Data Fig. 3 Mean pairwise Fst values between cattle breeds represented by more than one animal.

Sheko is indicated as yellow.

Extended Data Fig. 4 Estimated heterozygosity of cattle breeds.

The lower and upper bounds of box correspond to the first and third quartiles (the 25th and 75th percentiles), respectively. The horizontal line in the box represents the median value. The upper and lower whisker extend from the bounds to the largest and lowest value no further than 1.5 * interquartile range (IQR), respectively. The number of biologically independent animals used in this analysis for each breed is as follows: Achai (2), Afar (9), Angus (10), Ankole (10), Arsi (10), Barka (9), Bhagnari (3), Boskarin (1), Brahman (20), Butana (20), Cholistani (2), Dajal (1), Dhanni (2), Eastern Finn (5), Ethiopian Boran (10), Fogera (9), Gabrali (2), Gir (4), Goffa (10), Hanwoo (23), Hariana (3), Hereford (18), Holstein (10), Horro (11), Jersey (10), Kenya Boran (10), Kenana (13), Limia (1), Lohani (1), Maremmana (3), Maronesa (1), Mursi (10), Muturu (10), N’Dama (13), Nelore (10), Ogaden (9), Pajuna (2), Poldolica (1), Red Sindhi (1), Sahiwal (2), Sayaguesa (2), Sheko (9), Simmental (11), Tharparkar(3) and Wetern Finn (5). Sheko is indicated as yellow.

Extended Data Fig. 5 Runs of homozygosity patterns of cattle breeds.

Sheko is indicated as yellow.

Extended Data Fig. 6 Weighted LD decay in the Kenya Boran breed before and after fitted with a double-pulse admixture model.

The red curve shows the exponential fit to the data. a, Weighted LD fitted by a single-pulse admixture model, when using EAT and Muturu as a reference population separately. b, Weighted LD fitted by a double-pulse admixture model, when using EAT and Muturu as a reference population separately.

Extended Data Fig. 7 Distribution of proportions of SNPs with |iHS | ≥ 2 and taurine ancestry in each 50-kb window.

a, Distribution of proportions of SNPs with |iHS | ≥ 2. b, Distribution of taurine ancestry. The windows with SNPs less than 10 were removed. Dashed lines indicate the highest 1% for a, and highest or lowest 0.5% in b.

Extended Data Fig. 8 Distribution of taurine ancestry in the candidate regions (the highest 1% for proportion of SNPs with |iHS | ≥ 2), and whole genome windows.

Dashed lines indicate mean (top 1% in iHS analysis: 26.14%, and whole genome: 32.49%).

Extended Data Fig. 9 Distribution of taurine ancestry according to quantiles of proportions of SNPs with |iHS | ≥ 2 in each 50-kb window.

The lower and upper bounds of box correspond to the first and third quartiles (the 25th and 75th percentiles), respectively. The horizontal line in the box represents the median value. The upper and lower whisker extend from the bounds to the largest and lowest value no further than 1.5 * interquartile range (IQR), respectively. Asterisk indicates the highest 1% with proportions of SNPs with |iHS | ≥ 2. n = 149 (African humped cattle) biologically independent animals were used in this analysis.

Extended Data Fig. 10 Distribution of average taurine ancestry generated by resampling random windows (same number of windows as the candidate) for 0.1 million times.

Asterisk indicates average taurine ancestry of the candidate windows from iHS analysis.

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Supplementary Note, Tables 1–13 and Figs. 1–3

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Kim, K., Kwon, T., Dessie, T. et al. The mosaic genome of indigenous African cattle as a unique genetic resource for African pastoralism. Nat Genet 52, 1099–1110 (2020).

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