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

What does the ‘closed herd’ really mean for Australian breeding companies and their customers?

K. L. Bunter A B and S. Hermesch A
+ Author Affiliations
- Author Affiliations

A Animal Genetics and Breeding Unit, University of New England, Armidale, NSW 2351, Australia.

B Corresponding author. Email: kbunter2@une.edu.au

Animal Production Science 57(12) 2353-2359 https://doi.org/10.1071/AN17321
Submitted: 15 May 2017  Accepted: 16 August 2017   Published: 20 November 2017

Abstract

The perception that the genetic background of the Australian pig population is limiting for genetic improvement of commercial pigs in Australia is considered in the context of well established theory combined with practical evidence. The diversity of pig breeds used in modern commercial pig-breeding programs is diminished worldwide relative to all the pig breeds available. Australia is no different in this respect. The use of predominantly three main breeds (Large White, Landrace, Duroc) and synthetic lines, with contributions from other minor breeds to form the basis of a cross-breeding system for commercial pig production is well established internationally. The Australian concern of relatively small founder populations is potentially of relevance, from a theoretical perspective, for (1) the prevalence of defects or the presence of desirable alleles, and (2) the loss of genetic variation or increase in inbreeding depression resulting from increased inbreeding in closed nucleus lines, potentially reducing response to selection. However, rates of response achieved in Australian herds are generally commensurate with the performance recording and selection emphasis applied, and do not appear to be unduly restricted. Moreover, favourable alleles present in unrepresented breeds are frequently present in the three major breeds elsewhere, and therefore would be expected to be present within the Australian populations. Wider testing would provide confirmation of this. Comparison of estimates of effective population size of Australian populations with experimental selection lines overseas (e.g. INRA) or other intensely selected species (e.g. Holstein cattle) suggest adequate genetic diversity to achieve ongoing genetic improvement in the Australian pig industry. However, fitness traits should be included in breeding goals. What remains to be seen is whether novel phenotypes or genotypes are required to meet future challenges, which might be imposed by changes in the environment (e.g. climate change, disease) or market needs. Given probable overlap in genetic merit across Australian and foreign populations for unselected attributes, we suggest that sufficient genetic resources are already present in Australian herds to continue commercial progress within existing Australian populations that have adapted to Australian conditions.

Additional keywords: genetic improvement, genetic variation, inbreeding.


References

Belonsky GM, Kennedy BW (1988) Selection on individual phenotype and best linear unbiased predictor of breeding value in a closed swine herd. Journal of Animal Science 66, 1124–1131.
Selection on individual phenotype and best linear unbiased predictor of breeding value in a closed swine herd.CrossRef | 1:STN:280:DyaL1c3osFaiuw%3D%3D&md5=397cea48d4a00d9ede5591830318f123CAS |

Boerner V (2017) On breed composition estimation of cross-bred animals using non-linear optimisation. In ‘Proceedings of the 22nd Association for the Advancement of Animal Breeding and Genetics conference’, 2–5 July 2017, Townsville, Queensland. (Association for the Advancement of Animal Breeding and Genetics)

Bunter KL (1996) Mate Selection for Joint Control of Response and Inbreeding in Closed Pig Breeding Herds. University of New England.

Bunter KL, Hermesch S, Luxford BG, Graser H-U, Crump RE (2005) Insulin-like growth factor-I measured in juvenile pigs is genetically correlated with economically important performance traits. Australian Journal of Experimental Agriculture 45, 783–792.
Insulin-like growth factor-I measured in juvenile pigs is genetically correlated with economically important performance traits.CrossRef | 1:CAS:528:DC%2BD2MXpt1entL4%3D&md5=46e6f0583da1d8b346c41a3fb6bd1bb0CAS |

Bunter KL, Bennett C, Luxford BG, Graser H-U (2008) Sire breed comparisons for meat and eating quality traits in Australian pig populations. Animal 2, 1168–1177.
Sire breed comparisons for meat and eating quality traits in Australian pig populations.CrossRef | 1:STN:280:DC%2BC38vptFSiug%3D%3D&md5=e44dbf65ac63fa5526ea2db073540b1cCAS |

Bunter KL, Lewis CRG, Newman S (2015) Social genetic effects influence reproductive performance of group-housed sows. Journal of Animal Science 93, 3783–3793.
Social genetic effects influence reproductive performance of group-housed sows.CrossRef | 1:CAS:528:DC%2BC2MXhsVCmt7jL&md5=4be0253d0ef02510ac2ebd115b16af82CAS |

CSIS (2015) ‘Canadian Centre for Swine Improvement 2015 annual report.’ Available at https://www.ccsi.ca/meetings/annual/Annualreport%202015_FINAL.pdf [Verified 27 September 2017]

Culbertson MS, Herring WO, Holl JW, Casey D (2017) Genetic improvement and dissemination for the global commercial swine industry. Animal Production Science 57, 2366–2369.
Genetic improvement and dissemination for the global commercial swine industry.CrossRef |

Department of Sustainability, Water, Population and Communities (2011) The feral pig (Sus scrofa). (Australian Government: Canberra)

DanBred International (2015) ‘Rapid improvement.’ Available at http://www.danbredinternational.dk/rapid-improvement [Verified 9 May 2017]

D’Augustin OD, Boerner V, Hermesch S (2017) Estimates of effective population size and inbreeding level for three Australian pig breeds. In ‘Proceedings of the 22nd Association for the Advancement of Animal Breeding and Genetics conference’, 2–5 July 2017, Townsville, Queensland. (Association for the Advancement of Animal Breeding and Genetics)

FAO (2007) ‘The state of the world’s animal genetic resources for food and agriculture.’ (Eds B Rischkowsky, D Pilling) (Food and Agricultural Organisation of the United Nations: Rome)

Garrick DJ (2017) The role of genomics in pig improvement. Animal Production Science 57, 2360–2365.
The role of genomics in pig improvement.CrossRef |

Gilbert H, Billon Y, Brossard L, Faure J, Gatellier P, Gondret F, Labussière E, Lebret B, Lefaucheur L, Le Floch N, Louveau I, Merlot E, Meunier-Salaün M-C, Montagne L, Mormede P, Renaudeau D, Riquet J, Rogel-Gaillard C, van Milgen J, Vincent A, Noblet J (2017) Review: divergent selection for residual feed intake in the growing pig. Animal 11, 1427–1439.

Gore KP, Banks R, Boerner V, Hermesch S (2017) A genetic exploration of Australian Large White pigs. In ‘Proceedings of the 22nd Association for the Advancement of Animal Breeding and Genetics conference’, 2–5 July 2017, Townsville, Queensland. (Association for the Advancement of Animal Breeding and Genetics)

Groeneveld E, van der Westhuizen B, Maiwashe A, Voordewind F, Ferraz JBS (2009) POPREP: a generic report for population management. Genetics and Molecular Research 8, 1158–1178.
POPREP: a generic report for population management.CrossRef | 1:STN:280:DC%2BD1MjitlGqsQ%3D%3D&md5=60659fd246ea96ce6b0f44cfd437e253CAS |

Gutiérrez JP, Cervantes I, Goyache F (2009) Improving the estimation of realized effective population size in farm animals. Journal of Animal Breeding and Genetics 126, 327–332.
Improving the estimation of realized effective population size in farm animals.CrossRef |

Hammond K (1982) The significance for genetic improvement of the number of individuals available for breeding. In ‘Future developments in the genetic improvement of animals’. pp. 197–207. (Academic Press: Sydney)

Hammond K (1992) The modern breeding approach. In ‘Animal breeding. The modern approach’. (Eds K Hammond, H-U Graser, CA McDonald) pp. 13–25. (University of Sydney: Sydney)

Harris DL, Newman S (1994) Breeding for profit: synergism between genetic improvement and livestock production. Journal of Animal Science 72, 2178–2200.
Breeding for profit: synergism between genetic improvement and livestock production.CrossRef | 1:STN:280:DyaK2M%2Fntl2hsQ%3D%3D&md5=f20f66455ecaeaa700fc832ab8a44789CAS |

Hazel LN (1943) The genetic basis for constructing selection indexes. Genetics 28, 476–490.

Henderson CR (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics 31, 423–447.
Best linear unbiased estimation and prediction under a selection model.CrossRef | 1:STN:280:DyaE28%2FhvFegsA%3D%3D&md5=486acb44391f19ca62c8f2ee155d5309CAS |

Henryon M, Ostersen T, Ask B, Sorensen AC, Berg P (2014) Most of the long-term genetic gains from optimum-contribution selection can be realised with restrictions imposed. In ‘10th world congress on genetics applied to livestock production’, 17–22 August 2014, Vancouver, British Columbia, Canada.

Hermesch S (2004) Genetic improvement of lean meat growth and feed efficiency in pigs. Australian Journal of Experimental Agriculture 44, 383–391.
Genetic improvement of lean meat growth and feed efficiency in pigs.CrossRef |

Hermesch S (2006) From genetic to phenotypic trends. In ‘2006 AGBU pig genetics workshop notes’. (Ed. S Hermesch) pp. 59–65. (AGBU: Armidale, NSW)

Hermesch S, Jones RM (2012) Genetic parameters for haemoglobin levels in pigs and iron content in pork. Animal 6, 1904–1912.
Genetic parameters for haemoglobin levels in pigs and iron content in pork.CrossRef | 1:CAS:528:DC%2BC38Xhs1GitLvF&md5=acf6a08b784b6c7a14abf3a185baf00eCAS |

Hill WG (1977) Selection with overlapping generations. In ‘Proceedings of the international conference on quantitative genetics’. (Eds E Pollack, O Kempthorne, TB Bailey Jr) pp. 367–378. (Iowa State University: Ames, IA)

Hill WG, Zhang X-S (2009) Maintaining genetic variation in fitness. In ‘Adaptation and fitness in animal populations’. (Eds J van der Werf, H-U Graser, R Frankham, C Gondro) pp. 59–81. (Springer Science+Business Media)

Johnson RK, Goodwin R (1995) National genetic evaluation program. In ‘National hog farmer’. (Intertec Publishing Corporation: Overland Park, KS)

Jones R, Hermesch S (2009) ‘Comparing AI boar selection strategies.’ (Animal Genetics and Breeding Unit: Armidale, NSW)

Kinghorn BP (2011) An algorithm for efficient constrained mate selection. Genetics, Selection, Evolution 43, 4
An algorithm for efficient constrained mate selection.CrossRef |

Krupa E, Zakova E, Krupova Z (2015) Evaluation of inbreeding and genetic variability of five pig breeds in Czech Republic. Asian-Australasian Journal of Animal Sciences 28, 25–36.
Evaluation of inbreeding and genetic variability of five pig breeds in Czech Republic.CrossRef | 1:STN:280:DC%2BC2MvjsFCqsQ%3D%3D&md5=484b2a2d97930682efdac7a16d1980bfCAS |

Lewis CRG, Bunter KL (2011a) Body development in sows, feed intake and maternal capacity. Part 1: performance, pre-breeding and lactation feed intake traits of primiparous sows. Animal 5, 1843–1854.
Body development in sows, feed intake and maternal capacity. Part 1: performance, pre-breeding and lactation feed intake traits of primiparous sows.CrossRef | 1:STN:280:DC%2BC38vovFWjtA%3D%3D&md5=b935fd697f9f7c8b2b8c1aaf04e93b35CAS |

Lewis CRG, Bunter KL (2011b) Effects of seasonality and ambient temperature on genetic parameters for production and reproductive traits in pigs. Animal Production Science 51, 615–626.
Effects of seasonality and ambient temperature on genetic parameters for production and reproductive traits in pigs.CrossRef |

Li L, Hermesch S (2016) Evaluation of sire by environment interactions for growth rate and backfat depth using reaction norm models in pigs. Journal of Animal Breeding and Genetics 133, 429–440.
Evaluation of sire by environment interactions for growth rate and backfat depth using reaction norm models in pigs.CrossRef | 1:STN:280:DC%2BC28fhsVWqsA%3D%3D&md5=51ad3e96aa73a0287f4131727bef63b6CAS |

McPhee CP (1965) Growth of the pedigree Large White pig population in Australia. Queensland Journal of Agricultural and Animal Sciences 22, 137–147.

Peters KJ, Meyn K (2005) Herausforderungen des internationalen Marktes fur Tiergenetik. Züchtungskunde 77, 436–456.

Rodriguez-Ramilo ST, Fernandez J, Toro MA, Hernandiz D, Villanueva B (2015) Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population. PLoS One 10, e0124157
Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population.CrossRef |

Rothschild MF, Hu Zl, Jiang Z (2007) Advances in QTL mapping in pigs. International Journal of Biological Sciences 3, 192–197.
Advances in QTL mapping in pigs.CrossRef | 1:CAS:528:DC%2BD2sXjsl2qt7k%3D&md5=4a392c0c28914cd0683df9bdc3ac755eCAS |

Taylor G, Roese G, Hermesch S (2005a) ‘PrimeFact 62. Breeds of pigs: Large White.’ (NSW DPI: Canberra)

Taylor G, Roese G, Hermesch S (2005b) ‘PrimeFact 63. Breeds of pigs: Landrace.’ (NSW DPI: Canberra)

Taylor G, Roese G, Hermesch S (2005c) ‘PrimeFact 64. Breeds of pigs: Duroc.’ (NSW DPI: Canberra)

Tholen E, Bunter KL, Hermesch S, Graser HU (1996) The genetic foundation of fitness and reproduction traits in Australian pig populations. 1. Genetic parameters for weaning to conception interval, farrowing interval, and stayability. Australian Journal of Agricultural Research 47, 1261–1274.
The genetic foundation of fitness and reproduction traits in Australian pig populations. 1. Genetic parameters for weaning to conception interval, farrowing interval, and stayability.CrossRef |

Treacy DA (1976) A genetic analysis of the pedigree Landrace pig breed in Australia. Australian Journal of Experimental Agriculture and Animal Husbandry 16, 76–81.
A genetic analysis of the pedigree Landrace pig breed in Australia.CrossRef |

Wall E, Visscher PM, Hospital F, Woolliams JA (2005) Genomic contributions in livestock gene introgression programmes. Genetics, Selection, Evolution 37, 291–313.
Genomic contributions in livestock gene introgression programmes.CrossRef |

Webb AJ (1991) Genetic programmes to improve litter size in pigs. In ‘Manipulating pig production’. (Ed. ES Batterham) pp. 229–244. (Australasian Pig Science Association, Albury, NSW)

Webb AJ, Bampton PR (1988) Impact of the new statistical technology on pig improvement. In ‘Animal breeding opportunities’. pp. 111–128. (British Society of Animal Production: Midlothian, Scotland)

Welsh CS, Stewart TS, Schwab C, Blackburn HD (2010) Pedigree analysis of 5 swine breeds in the United States and the implications for genetic conservation. Journal of Animal Science 88, 1610–1618.
Pedigree analysis of 5 swine breeds in the United States and the implications for genetic conservation.CrossRef | 1:CAS:528:DC%2BC3cXlsVWkurk%3D&md5=cf44ba333981152ba813a7893a037b3aCAS |

Wright S (1921) Systems of mating. I. The biometrical relations between parent and offspring. Genetics 6, 111–123.

Wright S (1922) Coefficients of inbreeding and relationship. American Naturalist 56, 330–338.
Coefficients of inbreeding and relationship.CrossRef |

Zhang C, Plastow G (2011) Genomic diversity in pig (Sus scrofa) and its comparison with human and other livestock. Current Genomics 12, 138–148.



Rent Article (via Deepdyve) Export Citation