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Whole genome sequencing of Guzerá cattle reveals genetic variants in candidate genes for production, disease resistance, and heat tolerance

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Abstract

In bovines, artificial selection has produced a large number of breeds which differ in production, environmental adaptation, and health characteristics. To investigate the genetic basis of these phenotypical differences, several bovine breeds have been sequenced. Millions of new SNVs were described at every new breed sequenced, suggesting that every breed should be sequenced. Guzerat or Guzerá is an indicine breed resistant to drought and parasites that has been the base for some important breeds such as Brahman. Here, we describe the sequence of the Guzerá genome and the in silico functional analyses of intragenic breed-specific variations. Mate-paired libraries were generated using the ABI SOLiD system. Sequences were mapped to the Bos taurus reference genome (UMD 3.1) and 87% of the reference genome was covered at a 26X. Among the variants identified, 2,676,067 SNVs and 463,158 INDELs were homozygous, not found in any database searched, and may represent true differences between Guzerá and B. taurus. Functional analyses investigated with the NGS-SNP package focused on 1069 new, non-synonymous SNVs, splice-site variants (including acceptor and donor sites, and the conserved regions at both intron borders, referred to here as splice regions) and coding INDELs (NS/SS/I). These NS/SS/I map to 935 genes belonging to cell communication, environmental adaptation, signal transduction, sensory, and immune systems pathways. These pathways have been involved in phenotypes related to health, adaptation to the environment and behavior, and particularly, disease resistance and heat tolerance. Indeed, 105 of these genes are known QTLs for milk, meat and carcass, production, reproduction, and health traits. Therefore, in addition to describing new genetic variants, our approach provided groundwork for unraveling key candidate genes and mutations.

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Acknowledgements

The authors acknowledge the use of the computing resources of Genomics and Computational Biology (CEBio/Fiocruz-Minas, Brazil), and thank Prof. Vânia Maldini Penna for her advice and commitment throughout the study. Thw authors are grateful also to the Centro Brasileiro de Criadores do Guzerá (CBMG2), particularly to Paulo Menicucci and Ariane Menicucci for helping in the obtention of financial support for this project. The authors thank Mr. Peter Laspina for revising the English and also for many valuable comments. MRSC was a fellow of the Conselho Nacional de Pesquisa CNPq – 307975/2010-0 and 312068/2015-8 and was supported by CNPq – 505338/2008-A and 481018/2008-5 projects and PRPq/UFMG (PIBITI/CNPq – 4/2010). MAM, MFM, and RSV received financial support provided by CNPq. ICR was a fellow from the Fundação de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) and, subsequently, from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). JAG has a fellowship from CAPES. FSO, LRL, and AJD were fellows of a project funded by VALE. This research was funded by the following agencies and projects: Empresa Brasileira de Pesquisa Agropecuária (Embrapa), CAPES, CNPq, FAPEMIG (CBB-1181/0 and TCT 12.093/10 (MVBS)), 17003/2011 (MFM). GO was awarded with grants from FAPEMIG (RED-00014-14, REDE-56/11 and 485/2009), CNPq (309312/2012-4), NIH-USA (TW007012), VALE (17940), CAPES/CDTS-FIOCRUZ, FIOCRUZ-MG. The authors wish to thank the PDTIS-FIOCRUZ technology Platform RPT04B and Bioinformatics, BH.

Accesion IDs

All sequencing data are available at NCBI (NCBI Bioproject Accesion number: PRJNA350205).

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Authors and Affiliations

  1. Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais - UFMG, Av. Antônio Carlos, 6627, Pampulha, Belo Horizonte, MG, 31901-207, Brazil

    Izinara C. Rosse, Juliana G. Assis, Francislon S. Oliveira, Laura R. Leite & Maria Raquel S. Carvalho

  2. Grupo de Genômica e Biologia Computacional, Centro de Pesquisas René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil

    Juliana G. Assis, Francislon S. Oliveira, Laura R. Leite, Flávio Araujo, Angela Volpini, Anderson J. Dominitini & Guilherme Oliveira

  3. Embrapa Informática Agropecuária, Campinas, SP, Brazil

    Adhemar Zerlotini

  4. EPAMIG, Belo Horizonte, MG, Brazil

    Beatriz C. Lopes

  5. Embrapa Gado de Leite, Juiz de Fora, MG, Brazil

    Wagner A. Arbex, Marco A. Machado, Maria G. C. D. Peixoto, Rui S. Verneque, Marta F. Martins & Marcos V. G. B. Silva

  6. Neurogenômica, Centro de Pesquisa René Rachou - FIOCRUZ-Minas, Belo Horizonte, MG, Brazil

    Roney S. Coimbra

  7. Vale Technology Institute, Belém, PA, Brazil

    Guilherme Oliveira

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  1. Izinara C. Rosse
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Correspondence to Maria Raquel S. Carvalho.

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Rosse, I.C., Assis, J.G., Oliveira, F.S. et al. Whole genome sequencing of Guzerá cattle reveals genetic variants in candidate genes for production, disease resistance, and heat tolerance. Mamm Genome 28, 66–80 (2017). https://doi.org/10.1007/s00335-016-9670-7

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  • DOI: https://doi.org/10.1007/s00335-016-9670-7

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