Register      Login
Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

SNP included in candidate genes involved in muscle, lipid and energy metabolism behave like neutral markers

Natalia Sevane A , Javier Cañon A , John L. Williams B , Hubert Levéziel C D , Alessio Valentini E , Susana Dunner A F and the GemQual Consortium
+ Author Affiliations
- Author Affiliations

A Dpto. de Producción Animal, Facultad de Veterinaria, Universidad Complutense, 28040 Madrid, Spain.

B Parco Tecnologico Padano, Via Einstein, Polo Universitario, 26900 Lodi, Italy.

C INRA, UMR 1061, F-87000 Limoges, France.

D Université de Limoges, UMR 1061, F-87000 Limoges, France.

E Department for Innovation in Biological, Agro-Food and Forest Systems, Università della Tuscia, via De Lellis, 01100 Viterbo, Italy.

F Corresponding author. Email: dunner@ucm.es

Animal Production Science 55(9) 1164-1171 https://doi.org/10.1071/AN14605
Submitted: 21 November 2013  Accepted: 16 July 2014   Published: 30 September 2014

Abstract

Studies of population structure and diversity in cattle have provided insights into the origins of breeds, their history and evolution, and allow the identification of global livestock diversity hotspots, which is important for conservation of diversity. Genetic diversity, genetic relationship, population structure, and the presence of hotspots of genetic diversity among 15 European bovine breeds from five countries were assessed using 435 single nucleotide polymorphisms (SNP) markers identified in candidate genes for muscle, lipid and energy metabolism, thus providing the opportunity to compare the breed relationships obtained using putatively functional markers with previous data using neutral loci. Individuals belonging to 11 breeds tended to be clearly assigned to a single cluster when the number of pre-defined populations reached a maximum in the likelihood of the data at K = 12, whereas Asturiana de los Valles, Danish Red, Simmental, and Avileña-Negra Ibérica displayed a greater degree of admixture, which may be explained by their diverse ancestry. Although overall results were in agreement with those reported by studies based on neutral genetic variations, some additional breed relationship information emerged using markers in candidate functional loci, including the relationship between the Asturiana de los Valles and Piedmontese, and Danish Red and Charolais breeds. This study indicates that the analysed loci have not been main targets for selection or for adaptation processes, but also that SNP within candidate genes related with beef characteristics and performance may provide a slightly new perspective on past breeding and may also help in the development of strategies for the rational conservation of livestock diversity.

Additional keywords: adaptive variance, admixture, Bos taurus, genetic diversity, hotspots.


References

Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F (2004) ‘GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations.’ (Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université de Montpellier II: Montpellier, France)

Cañón J, García D, Delgado JV, Dunner S, Gama LT, Landi V, Martín-Burriel I, Martínez A, Penedo C, Rodellar C, Zaragoza P, Ginja C (2011) Relative breed contributions to neutral genetic diversity of a comprehensive representation of Iberian native cattle. Animal 5, 1323–1334.
Relative breed contributions to neutral genetic diversity of a comprehensive representation of Iberian native cattle.Crossref | GoogleScholarGoogle Scholar | 22440277PubMed |

Cortés O, Tupac-Yupanqui I, Dunner S, García-Atance MA, García D, Fernández J, Cañón J (2008) Ancestral matrilineages and mitochondrial DNA diversity of the Lidia cattle breed. Animal Genetics 39, 649–654.
Ancestral matrilineages and mitochondrial DNA diversity of the Lidia cattle breed.Crossref | GoogleScholarGoogle Scholar | 18822101PubMed |

Cortés O, Tupac-Yupanqui I, Dunner S, Fernández J, Cañón J (2011) Y chromosome genetic diversity in the Lidia bovine breed: a highly fragmented population. Journal of Animal Breeding and Genetics 128, 491–496.
Y chromosome genetic diversity in the Lidia bovine breed: a highly fragmented population.Crossref | GoogleScholarGoogle Scholar | 22059583PubMed |

Decker JE, Pires JC, Conant GC, McKay SD, Heaton MP, Chen K, Cooper A, Vilkki J, Seabury CM, Caetano AR, Johnson GS, Brenneman RA, Hanotte O, Eggert LS, Wiener P, Kim JJ, Kim KS, Sonstegard TS, Van Tassell CP, Neibergs HL, McEwan JC, Brauning R, Coutinho LL, Babar ME, Wilson GA, McClure MC, Rolf MM, Kim J, Schnabel RD, Taylor JF (2009) Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics. Proceedings of the National Academy of Sciences of the United States of America 106, 18 644–18 649.
Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsVKiu7zN&md5=d8e155d58e9ae33446c9b1002b06cb54CAS |

Dunner S, Sevane N, García D, Valentini A, Williams JL, Mangin B, Cañón J, Levéziel H, GeMQual Consortium (2013a) Association of genes involved in carcass and meat quality traits in fifteen European bovine breeds. Livestock Science 154, 34–44.
Association of genes involved in carcass and meat quality traits in fifteen European bovine breeds.Crossref | GoogleScholarGoogle Scholar |

Dunner S, Sevane N, García D, Levéziel H, Williams JL, Mangin B, Valentini A, GeMQual Consortium (2013b) Genes involved in muscle lipid composition in 15 European Bos taurus breeds. Animal Genetics 44, 493–501.
Genes involved in muscle lipid composition in 15 European Bos taurus breeds.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtl2lt7rJ&md5=06c5c147afbb2b05c1f8e9aa89ae2b49CAS | 23611291PubMed |

Esmailizadeh AK, Bottema CD, Sellick GS, Verbyla AP, Morris CA, Cullen NG, Pitchford WS (2008) Effects of the myostatin F94L substitution on beef traits. Journal of Animal Science 86, 1038–1046.
Effects of the myostatin F94L substitution on beef traits.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXltlWrtLo%3D&md5=7bcab3643547da732574466abd9862ceCAS | 18245504PubMed |

Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14, 2611–2620.
Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXmvF2qtrg%3D&md5=32af34a7157585a4d86a7ac5ef5d4c4eCAS | 15969739PubMed |

Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1, 47–50.

Felius M, Koolmees PA, Theunissen B, European Cattle Genetic Diversity Consortium Lenstra JA (2011) On the breeds of cattle-historic and current classifications. Diversity 3, 660–692.
On the breeds of cattle-historic and current classifications.Crossref | GoogleScholarGoogle Scholar |

Felsenstein J (1989) phylip – phylogeny inference package (version 3.2). Cladistics 5, 164–166.

Gautier M, Laloë D, Moazami-Goudarzi K (2010) Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PLoS ONE 5, e13038
Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds.Crossref | GoogleScholarGoogle Scholar | 20927341PubMed |

Lin BZ, Sasazaki S, Mannen H (2010) Genetic diversity and structure in Bos taurus and Bos indicus populations analyzed by SNP markers. Animal Science Journal 81, 281–289.
Genetic diversity and structure in Bos taurus and Bos indicus populations analyzed by SNP markers.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXptlWltb4%3D&md5=0b90a51cfd9493cc923cfbad2cbf0d82CAS | 20597883PubMed |

Liron JP, Peral-Garcia P, Giovambattista G (2006) Genetic characterization of Argentine and Bolivian Creole cattle breeds assessed through microsatellites. The Journal of Heredity 97, 331–339.
Genetic characterization of Argentine and Bolivian Creole cattle breeds assessed through microsatellites.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xotl2ksbo%3D&md5=0171bd7c58149e483aa6c349c4739433CAS | 16793865PubMed |

Martín-Burriel I, Rodellar C, Cañón J, Cortés O, Dunner S, Landi V, Martínez-Martínez A, Gama LT, Ginja C, Penedo MC, Sanz A, Zaragoza P, Delgado JV (2011) Genetic diversity, structure, and breed relationships in Iberian cattle. Journal of Animal Science 89, 893–906.
Genetic diversity, structure, and breed relationships in Iberian cattle.Crossref | GoogleScholarGoogle Scholar | 21415418PubMed |

McKay SD, Schnabel RD, Murdoch BM, Matukumalli LK, Aerts J, Coppieters W, Crews D, Dias Neto E, Gill CA, Gao C, Mannen H, Wang Z, Van Tassell CP, Williams JL, Taylor JF, Moore SS (2008) An assessment of population structure in eight breeds of cattle using a whole genome SNP panel. BMC Genetics 20, 9–37.

Nei M (1972) Genetic distance between populations. American Naturalist 106, 283–292.
Genetic distance between populations.Crossref | GoogleScholarGoogle Scholar |

Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure from multilocus genotype data. Genetics 155, 945–959.

Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. The Journal of Heredity 86, 248–249.

Rosenberg NA (2004) DISTRUCT: a program for the graphical display of population structure. Molecular Ecology Notes 4, 137–138.
DISTRUCT: a program for the graphical display of population structure.Crossref | GoogleScholarGoogle Scholar |

Sevane N, Crespo I, Cañón J, Dunner S (2011) A Primer-Extension Assay for simultaneous use in cattle Genotype Assisted Selection, parentage and traceability analysis. Livestock Science 137, 141–150.
A Primer-Extension Assay for simultaneous use in cattle Genotype Assisted Selection, parentage and traceability analysis.Crossref | GoogleScholarGoogle Scholar |

Sevane N, Armstrong E, Wiener P, Pong Wong R, Dunner S, GeMQual Consortium (2013) Association of bovine meat quality traits with genes included in the PPARG and PPARGC1A networks. Meat Science 94, 328–335.
Association of bovine meat quality traits with genes included in the PPARG and PPARGC1A networks.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXmtV2ksLg%3D&md5=d36db958aea474321a537f98a65898d3CAS | 23567132PubMed |

Simm G, Lambe N, Bünger L, Navajas E, Roehe R (2009) Use of meat quality information in breeding programmes. In ‘Improving the sensory and nutritional quality of fresh meat’. (Eds JP Kerry, D Ledward) pp. 264–291. (Woodhead Publishing Ltd: Cambridge, UK)

Tapio M, Ozerov M, Tapio I, Toro MA, Marzanov N, Cinkulov M, Goncharenko G, Kiselyova T, Murawski M, Kantanen J (2010) Microsatellite-based genetic diversity and population structure of domestic sheep in northern Eurasia. BMC Genetics 10, 11–76.

Toro MA (2006) Assessing genetic diversity between breeds for conservation. Journal of Animal Breeding and Genetics 123, 289
Assessing genetic diversity between breeds for conservation.Crossref | GoogleScholarGoogle Scholar | 16965400PubMed |

Wiener P, Burton D, Williams JL (2004) Breed relationships and definition in British cattle: a genetic analysis. Heredity 93, 597–602.
Breed relationships and definition in British cattle: a genetic analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhtVWgtb7P&md5=47d805c1a4930420b911e796d0859020CAS | 15329667PubMed |

Williams JL, Dunner S, Valentini A, Mazza R, Amarger V, Checa ML, Crisa A, Razzaq N, Delourme D, Grandjean F, Marchitelli C, García D, Pérez Gómez R, Negrini R, Ajmone Marsan P, Levéziel H (2009) Discovery, characterization and validation of single nucleotide polymorphisms within 206 bovine genes that may be considered as candidate genes for beef production and quality. Animal Genetics 40, 486–491.
Discovery, characterization and validation of single nucleotide polymorphisms within 206 bovine genes that may be considered as candidate genes for beef production and quality.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtVaiurfF&md5=a819bc47aa209480b822e7f5e19cf7a2CAS | 19397516PubMed |