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Cited by 112Genetic and phenotypic traits in livestockGenetic diversity and population structureForensic and Genetic Research

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Species composition and environmental adaptation of indigenous Chinese cattle

Open access
Gao, Yahui, Gautier, Mathieu, Ding, Xiangdong, Zhang, Hao, Wang, Yachun, Wang, Xi, Faruque, MD Omar, Li, Junya, Ye, Shaohui, Gou, Xiao, Han, Jianlin, Lenstra, Johannes A., Zhang, Yi·2017·Scientific Reports
DOI 10.1038/s41598-017-16438-7PMC PMC5700937

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Abstract

Indigenous Chinese cattle combine taurine and indicine origins and occupy a broad range of different environments. By 50 K SNP genotyping we found a discontinuous distribution of taurine and indicine cattle ancestries with extremes of less than 10% indicine cattle in the north and more than 90% in the far south and southwest China. Model-based clustering and f4-statistics indicate introgression of both banteng and gayal into southern Chinese cattle while the sporadic yak influence in cattle in or near Tibetan area validate earlier findings of mitochondrial DNA analysis. Geographic patterns of taurine and indicine mitochondrial and Y-chromosomal DNA diversity largely agree with the autosomal cline. The geographic distribution of the genomic admixture of different bovine species is proposed to be the combined effect of prehistoric immigrations, gene flow, major rivers acting as genetic barriers, local breeding objectives and environmental adaptation. Whole-genome scan for genetic differentiation and association analyses with both environmental and morphological covariables are remarkably consistent with previous studies and identify a number of genes implicated in adaptation, which include TNFRSF19, RFX4, SP4 and several coat color genes. We propose indigenous Chinese cattle as a unique and informative resource for gene-level studies of climate adaptation in mammals.

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Crossref · 10.1038/s41598-017-16438-7

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Figure 1 Geographical distribution of cattle populations. Detailed information is showed in Table 1. Map was created using R Project for Statistical Computing v. 3.3.1 (https://www.R-project.org) and packages rworldmap v. 1.3–6 (https://cran.r-project.org/web/packages/rworldmap/index.html), maps v. 3.2.0 (https://cran.r-project.org/web/packages/maps/) and mapproj v. 1.2–5 (https://cran.r-project.org/web/packages/mapproj/index.html). Package rworldmap v. 1.3–6 was used to generate outline and colorful dots while packages maps v. 3.2.0 and mapproj v. 1.2–5 were used to add texts. Different color indicates different geographical regions of population origins.
Figure 1 Geographical distribution of cattle populations. Detailed information is showed in Table 1. Map was created using R Project for Statistical Computing v. 3.3.1 (https://www.R-project.org) and packages rworldmap v. 1.3–6 (https://cran.r-project.org/web/packages/rworldmap/index.html), maps v. 3.2.0 (https://cran.r-project.org/web/packages/maps/) and mapproj v. 1.2–5 (https://cran.r-project.org/web/packages/mapproj/index.html). Package rworldmap v. 1.3–6 was used to generate outline and colorful dots while packages maps v. 3.2.0 and mapproj v. 1.2–5 were used to add texts. Different color indicates different geographical regions of population origins.CC BY · PubMed Central
Figure 2 PCA plots describing the relationships among populations. (a) Whole data set of all the 45 sampled populations. (b) A subset of data including only Asian cattle. Different colors were used to indicate different regions as Fig. 1.
Figure 2 PCA plots describing the relationships among populations. (a) Whole data set of all the 45 sampled populations. (b) A subset of data including only Asian cattle. Different colors were used to indicate different regions as Fig. 1.CC BY · PubMed Central
Figure 3 Ancestries and population structuring of Chinese cattle revealed by (a) unsupervised Admixture analysis (K = 2, 3, 4, 5, 17) and (b) supervised Admixture analysis (K = 5). For supervised admixture analysis, five European cattle breeds (SH, HOL, LMS, SIM) were set to represent taurine ancestry whereas GIR and SAHW represented indicine ancestry. BAL, GAY and YAK were three outgroup bovine species. The putative hybrid animals in Bali and Gayal detected by unsupervised admixture analysis were excluded from the pure ancestry.
Figure 3 Ancestries and population structuring of Chinese cattle revealed by (a) unsupervised Admixture analysis (K = 2, 3, 4, 5, 17) and (b) supervised Admixture analysis (K = 5). For supervised admixture analysis, five European cattle breeds (SH, HOL, LMS, SIM) were set to represent taurine ancestry whereas GIR and SAHW represented indicine ancestry. BAL, GAY and YAK were three outgroup bovine species. The putative hybrid animals in Bali and Gayal detected by unsupervised admixture analysis were excluded from the pure ancestry.CC BY · PubMed Central
Figure 4 NeighborNet graph of 44 cattle populations. An allele frequency-dependent distance metric (Reynolds) was used to construct the NeighborNet. Different colors were used to indicate different regions as Fig. 1.
Figure 4 NeighborNet graph of 44 cattle populations. An allele frequency-dependent distance metric (Reynolds) was used to construct the NeighborNet. Different colors were used to indicate different regions as Fig. 1.CC BY · PubMed Central
Figure 5 Visualization of f4-statistics. (a) f4-statistics of the form D (GIR, X; BAL, YAK) identified gene flow from Bali to other breeds. (b) f4-statistics of the form D (GIR, X; GAU, YAK) identified gene flow from Gaur to other breeds. The whiskers represent the standard error. Different colors were used to indicate different regions as Fig. 1.
Figure 5 Visualization of f4-statistics. (a) f4-statistics of the form D (GIR, X; BAL, YAK) identified gene flow from Bali to other breeds. (b) f4-statistics of the form D (GIR, X; GAU, YAK) identified gene flow from Gaur to other breeds. The whiskers represent the standard error. Different colors were used to indicate different regions as Fig. 1.CC BY · PubMed Central
Figure 6 Percentages of indicine mtDNA and Y-chromosomes per breed plotted against the breed average of the autosomal indicine component as derived from the Admixture analysis.
Figure 6 Percentages of indicine mtDNA and Y-chromosomes per breed plotted against the breed average of the autosomal indicine component as derived from the Admixture analysis.CC BY · PubMed Central
Figure 7 Whole genome scan for adaptive divergence and association analyses in 20 Chinese cattle breeds. (a) Manhattan plot of the XtX statistics. (b) Manhattan plot of the BFmc (association with environmental PC1). (c) Manhattan plot based on the BFmc (association with morphological PC1).
Figure 7 Whole genome scan for adaptive divergence and association analyses in 20 Chinese cattle breeds. (a) Manhattan plot of the XtX statistics. (b) Manhattan plot of the BFmc (association with environmental PC1). (c) Manhattan plot based on the BFmc (association with morphological PC1).CC BY · PubMed Central

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Research works printed but not linked: 1

  1. China National Commission of Animal Genetics Resources. Animal genetic resources in China – Bovine. (China Agriculture Press, 2011).

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Metadata

Authors
Gao, Y., Gautier, M., Ding, X., Zhang, H., Wang, Y., Wang, X., Faruque, M. O., Li, J., Ye, S., Gou, X., Han, J., Lenstra, J. A., & Zhang, Y.
Affiliations
  • China Agricultural University (CN)
  • Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR)
  • Shanxi Academy of Agricultural Sciences (CN)
  • Bangladesh Agricultural University (BD)
  • Chinese Academy of Agricultural Sciences (CN)
  • Yunnan Agricultural University (CN)
  • Utrecht University (NL)
Corresponding author
Zhang, Yi
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2017-11-23
Volume
7
Issue
1
Pages
16196-16196
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-017-16438-7
PMC
PMC5700937
OpenAlex
W2952597679
Cited by
112
References
80
Citations by year
2026: 8 · 2025: 16 · 2024: 9 · 2023: 6 · 2022: 16 · 2021: 25 · 2020: 11 · 2019: 10 · 2018: 11
FWCI
5.79
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Funders
  • Universidade do Porto
  • China Agricultural Research System (CARS‐37)
  • Badan Penelitian dan Pengembangan Pertanian
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Keywords
mitochondrial DNA diversity, genetic admixture, climate change adaptation, whole genome scan, genetic differentiation, environmental adaptation, coat color genes, TNFRSF19, Sp4
MeSH terms
Alleles, Animals, Cattle, China, DNA, Mitochondrial, Gene Frequency, Haplotypes, Genetic Variation, Y Chromosome, Microsatellite Repeats, Polymorphism, Single Nucleotide

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