Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-13T09:22:40.948Z Has data issue: false hasContentIssue false
  • English
  • Français

Genome-wide association study for calving traits in Holstein–Friesian dairy cattle

Published online by Cambridge University Press:  20 November 2013

D. C. Purfield ,
D. G. Bradley ,
J. F. Kearney  and
D. P. Berry
D. C. Purfield
Affiliation:
Smurfit Institute of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
D. G. Bradley
Affiliation:
Smurfit Institute of Genetics, University of Dublin, Trinity College, Dublin 2, Ireland
J. F. Kearney
Affiliation:
Irish Cattle Breeding Federation, Highfield House, Shinagh, Co. Cork, Ireland
D. P. Berry*
Affiliation:
Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
*
†E-mail: [email protected]
Get access

Abstract

Dystocia and perinatal mortality are quantitative traits that significantly impact animal productivity and welfare. Their economic importance is reflected by their inclusion in the national breeding goals of many cattle populations. The genetic architecture that influences these traits, however, has still yet to be thoroughly defined. Regions of the bovine genome associated with calving difficulty (direct and maternal) and perinatal mortality were detected in this study using a Bayesian approach with 43 204 single nucleotide polymorphisms (SNPs) on up to 1970 Holstein–Friesian bulls. Several SNPs on chromosomes 5, 6, 11, 12, 17,18 and 28 were detected to be strongly associated with these calving performance traits. Novel genomic regions with previously reported associations with growth, stature, birth weight and bone morphology were identified in the present study as being associated with the three calving performance traits. Morphological abnormalities are a known contributor to perinatal mortality and the most significantly associated SNP for perinatal mortality in the present study was located in a region in linkage disequilibrium with the gene SLC26A7. This gene, SLC26A7, has similarities and colocalises with SLC4A2, which has previously been associated with osteoporosis and mortality in cattle populations. The HHIP gene that is known to be associated with stature in humans was strongly associated with direct calving difficulty in the present study; large calves are known to, on average, have a greater likelihood of dystocia. A stemloop microRNA, bta-mir-1256, on chromosome 12, involved in post-transcriptional regulation of gene expression was associated with maternal calving difficulty. Previously reported quantitative trait loci associated with calving performance traits in other populations were again identified in this study; with one genomic region on chromosome 18 supporting very strong evidence of an underlying causative mutation and accounting for 2.1% of the genetic variation in direct calving difficulty. Overlapping genomic regions associated with one or more of the calving traits were also detected substantiating the known genetic covariances existing between these traits. Moreover, some genomic regions were only associated with one of the calving traits implying the selective genomic breeding programs exploiting these regions could help resolve genetic antagonisms.

Keywords

dystociamortalitycalving difficultygenomicquantitative trait loci
Type
Full Paper
Information
animal , Volume 8 , Issue 2 , February 2014 , pp. 224 - 235
Copyright
Copyright © The Animal Consortium 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Barrett, JC, Fry, B, Maller, J and Daly, MJ 2005. Haploview: an analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265.CrossRefGoogle ScholarPubMed
Bennett, GL and Gregory, KE 2001. Genetic (co)variances for calving difficulty score in composite and parental populations of beef cattle: II. Reproductive, skeletal, and carcass traits. Journal of Animal Science 79, 52–59.Google Scholar
Berger, PJ, Cubas, AC, Koehler, KJ and Healey, MH 1992. Factors affecting dystocia and early calf mortality in Angus cows and heifers. Journal of Animal Science 70, 1775–1786.CrossRefGoogle ScholarPubMed
Berry, DP and Cromie, AR 2009. Associations between age at first calving and subsequent performance in Irish spring calving Holstein–Friesian dairy cows. Livestock Science 123, 44–54.CrossRefGoogle Scholar
Bicalho, RC, Galvão, KN, Warnick, LD and Guard, CL 2008. Stillbirth parturition reduces milk production in Holstein cows. Preventative Veterinary Medicine 84, 112–120.CrossRefGoogle ScholarPubMed
Bicalho, RC, Galvão, KN, Cheong, SH, Gilbert, RO, Warnick, LD and Guard, CL 2007. Effect of stillbirths on dam survival and reproduction performance in Holstein dairy cows. Journal of Dairy Science 90, 2797–2803.CrossRefGoogle ScholarPubMed
Brinkman-Van der Linden, EC, Hurtado-Ziola, N, Hayakawa, T, Wiggleton, L, Benirschke, K, Varki, A and Varki, N 2007. Human-specific expression of Siglec-6 in the placenta. Glycobiology 17, 922–931.CrossRefGoogle ScholarPubMed
Browning, SR and Browning, BL 2007. Rapid and accurate haplotype phasing and missing data inference for whole genome association studies using localized haplotype clustering. American Journal of Human Genetics 81, 1084–1097.CrossRefGoogle ScholarPubMed
Chan, J, Deng, LY, Mikael, LG, Yan, J, Pickell, L, Wu, Q, Caudill, MA and Rozen, R 2010. Low dietary choline and low dietary riboflavin during pregnancy influence reproductive outcomes and heart development in mice. American Journal of Clinical Nutrition 91, 1035–1043.CrossRefGoogle ScholarPubMed
Clowse, MEB, Magder, LS, Witter, F and Petri, M 2005. The impact of increased lupus activity on obstetric outcomes. Arthritis and Rheumatism 52, 514–521.CrossRefGoogle ScholarPubMed
Cole, JB, VanRaden, PM, O'Connell, JR, Van Tassell, CP, Sonstegard, TS, Schnabel, RD, Taylor, JF and Wiggans, GR 2009. Distribution and location of genetic effects for dairy traits. Journal of Dairy Science 92, 2931–2946.CrossRefGoogle ScholarPubMed
Fan, B, Onteru, SK, Du, ZQ, Garrick, DJ, Stalder, KJ and Rothschild, MF 2011. Genome-wide association study identifies loci for body composition and structural soundness traits in pigs. PLoS One 6, e14726.CrossRefGoogle ScholarPubMed
Fernando, R and Garrick, DJ 2011. GenSel: user manual for a portfolio of genomic selection related analyses. In Animal breeding and genetics. Iowa State University, Ames, IA. http://www.biomedcentral.com/content/supplementary/1471-2105-12-186-s1.pdf Google Scholar
Fowden, AL 2003. The insulin-like growth factors and feto-placental growth. Placenta 24, 803–812.CrossRefGoogle ScholarPubMed
Ganss, B and Jheon, A 2004. Zinc finger transcription factors in skeletal development. Critical Reviews in Oral Biology and Medicine 15, 282–297.CrossRefGoogle ScholarPubMed
Grosz, MD and MacNeil, MD 2001. Putative quantitative trait locus affecting birth weight on bovine chromosome 2. Journal of Animal Science 79, 68–72.CrossRefGoogle ScholarPubMed
Habier, D, Fernando, RL, Kizilkaya, K and Garrick, DJ 2011. Extension of the Bayesian alphabet for genomic selection. BMC Bioinformatics 12, 186.CrossRefGoogle ScholarPubMed
Harris, B and Johnson, D 1998. Approximate reliability of genetic evaluations under an animal model. Journal of Dairy Science 81, 2723–2728.CrossRefGoogle ScholarPubMed
Hickey, JM, Keane, MG, Kenny, DA, Cromie, AR, Amer, PR and Veerkamp, RF 2007. Heterogeneity of genetic parameters for calving difficulty in Holstein heifers in Ireland. Journal of Dairy Science 90, 3900–3908.CrossRefGoogle ScholarPubMed
Höglund, JK, Guldbrandtsen, B, Lund, MS and Sahana, G 2012. Analyzes of genome-wide association follow-up study for calving traits in dairy cattle. BMC Genetics 13, 71.CrossRefGoogle ScholarPubMed
Jeffreys, H 1961. The theory of probability, 3rd edition Oxford University Press, UK.Google Scholar
Johanson, JM, Berger, PJ, Tsuruta, S and Misztal, I 2011. A Bayesian threshold-linear model evaluation of perinatal mortality, dystocia, birth weight, and gestation length in a Holstein herd. Journal of Dairy Science 94, 450–460.CrossRefGoogle Scholar
Kass, R and Raftery, A 1995. Bayes factors. Jounral of American Statistics 90, 773–795.CrossRefGoogle Scholar
Kim, H, Kim, T, Jeong, BC, Cho, IT, Han, D, Takegahara, N, Negishi-Koga, T, Takayanagi, H, Lee, JH, Sul, JY, Prasad, V, Lee, SH and Choi, Y 2013. Tmem64 modulates calcium signaling during RANKL-mediated osteoclast differentiation. Cell Metabolism 17, 249–260.CrossRefGoogle ScholarPubMed
Kirkbride, CA 1993. Bacterial agents detected in a 10-year study of bovine abortions and stillbirths. Journal of Veterinary Diagnostic Investigation 5, 64–68.CrossRefGoogle Scholar
Kühn, C, Bennewitz, J, Reinsch, N, Xu, N, Thomsen, H, Looft, C, Brockmann, GA, Schwerin, M, Weimann, C, Hiendleder, S, Erhardt, G, Medjugorac, I, Förster, M, Brenig, B, Reinhardt, F, Reents, R, Russ, I, Averdunk, G, Blümel, J and Kalm, E 2003. Quantitative trait loci mapping of functional traits in the German Holstein cattle population. Journal of Dairy Science 86, 360–368.CrossRefGoogle ScholarPubMed
Liu, JZ, Medland, SE, Wright, MJ, Henders, AK, Heath, AC, Madden, PA, Duncan, A, Montgomery, GW, Martin, NG and McRae, AF 2010. Genome-wide association study of height and body mass index in Australian twin families. Twin Research and Human Genetics: The Official Journal of the International Society for Twin Studies 13, 179–193.CrossRefGoogle ScholarPubMed
Lohi, H, Kujala, M, Makela, S, Lehtonen, E, Kestila, M, Saarialho-Kere, U, Markovich, D and Kere, J 2002. Functional characterization of three novel tissue-specific anion exchangers SLC26A7, -A8, and -A9. Journal of Biological Chemistry 277, 14246–14254.CrossRefGoogle ScholarPubMed
Luo, MF, Boettcher, PJ, Dekkers, JCM and Schaeffer, LR 1999. Bayesian analysis for estimation of genetic parameters of calving ease and stillbirth for Canadian Holsteins. Journal of Dairy Science 82, 1848.CrossRefGoogle Scholar
McClure, MC, Morsci, S, Schnabel, RD, Kim, JW, Yao, P, Rolf, MM, McKay, SD, Gregg, SJ, Chapple, RH, Northcutt, SL and Taylor, JF 2010. A genome scan for quantitative trait loci influencing carcass, post‐natal growth and reproductive traits in commercial Angus cattle. Animal genetics 41, 597–607.CrossRefGoogle ScholarPubMed
McGuirk, B, Going, I and Gilmour, A 1999. The genetic evaluation of UK Holstein Friesian sires for calving ease and related traits. Animal Science 68, 413–422.CrossRefGoogle Scholar
McKay, SD, Schnabel, RD, Murdoch, BM, Matukumalli, LK, Aerts, J, Coppieters, W, Crews, D, Dias Neto, E, Gill, CA, Gao, C, Mannen, H, Stothard, P, Wang, Z, Van Tassell, CP, Williams, JL, Taylor, JF and Moore, SS 2007. Whole genome linkage disequilibrium maps in cattle. BMC Genetics 8, 74.CrossRefGoogle ScholarPubMed
Mee, JF, Berry, DP and Cromie, AR 2011. Risk factors for calving assistance and dystocia in pasture-based Holstein–Friesian heifers and cows in Ireland. Veterinary Journal 187, 189–194.CrossRefGoogle ScholarPubMed
Meuwissen, TH, Hayes, BJ and Goddard, ME 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829.CrossRefGoogle ScholarPubMed
Meyers, SN, McDaneld, TG, Swist, SL, Marron, BM, Steffen, DJ, O'Toole, D, O'Connell, JR, Beever, JE, Sonstegard, TS and Smith, TP 2010. A deletion mutation in bovine SLC4A2 is associated with osteopetrosis in Red Angus cattle. BMC Genomics 11, 337.CrossRefGoogle ScholarPubMed
Olsen, HG, Hayes, BJ, Kent, MP, Nome, T, Svendsen, M and Lien, S 2010. A genome wide association study for QTL affecting direct and maternal effects of stillbirth and dystocia in cattle. Animal Genetics 41, 273–280.CrossRefGoogle ScholarPubMed
Onteru, SK, Fan, B, Nikkilä, MT, Garrick, DJ, Stalder, KJ and Rothschild, MF 2011. Whole-genome association analyses for lifetime reproductive traits in the pig. Journal of Animal Science 89, 988–995.CrossRefGoogle ScholarPubMed
Osmers, R, Rath, W, Pflanz, MA, Kuhn, W, Stuhlastz, HW and Szeverényi, M 1993. Glycosaminoglycans in cervical connective tissue during pregnancy and parturition. Obstetrics and gynaecology 81, 88–92.Google ScholarPubMed
Pryce, JE, Hayes, BJ, Bolormaa, S and Goddard, ME 2011. Polymorphic regions affecting human height also control stature in cattle. Genetics 187, 981–984.CrossRefGoogle ScholarPubMed
Qanbari, S, Gianola, D, Hayes, B, Schenkel, F, Miller, S, Moore, S, Thaller, G and Simianer, H 2011. Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle. BMC Genomics 12.Google ScholarPubMed
Sahana, G, Guldbrandtsen, B and Lund, MS 2011. Genome-wide association study for calving traits in Danish and Swedish Holstein cattle. Journal of Dairy Science 94, 479–486.CrossRefGoogle ScholarPubMed
Schnabel, RD, Sonstegard, TS, Taylor, JF and Ashwell, MS 2005. Whole-genome scan to detect QTL for milk production, conformation, fertility and functional traits in two US Holstein families. Animal Genetics 36, 408–416.CrossRefGoogle ScholarPubMed
Schrooten, C, Bovenhuis, H, Coppieters, W and Van Arendonk, JA 2000. Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle. Journal of Dairy Science 83, 795–806.CrossRefGoogle ScholarPubMed
Seidenspinner, T, Bennewitz, J, Reinhardt, F and Thaller, G 2009. Need for sharp phenotypes in QTL detection for calving traits in dairy cattle. Journal of Animal Breed Genetics 126, 455–462.CrossRefGoogle ScholarPubMed
Seidenspinner, T, Tetens, J, Habier, D, Bennewitz, J and Thaller, G 2011. The placental growth factor (PGF) – a positional and functional candidate gene influencing calving ease and stillbirth in German dairy cattle. Animal Genetics 42, 22–27.CrossRefGoogle ScholarPubMed
Steinbock, L, Näsholm, A, Berglund, B, Johansson, K and Philipsson, J 2003. Genetic effects on stillbirth and calving difficulty in Swedish Holsteins at first and second calving. Journal of Dairy Science 86, 2228–2235.CrossRefGoogle ScholarPubMed
Stephens, M and Balding, DJ 2009. Bayesian statistical methods for genetic association studies. Nature Review Genetics 10, 681–690.CrossRefGoogle ScholarPubMed
Ullrich, O, Reinsch, S, Urbé, S, Zerial, M and Parton, RG 1996. Rab11 regulates recycling through the pericentriolar recycling endosome. Journal of Cell Biology 135, 913–924.CrossRefGoogle ScholarPubMed
Supplementary material: File

Purfield et al. Supplementary Material

Figure

Download Purfield et al. Supplementary Material(File)
File 697.5 KB
Supplementary material: File

Purfield et al. Supplementary Material

Figure

Download Purfield et al. Supplementary Material(File)
File 636.5 KB
Supplementary material: File

Purfield et al. Supplementary Material

Figure

Download Purfield et al. Supplementary Material(File)
File 544.9 KB
Supplementary material: File

Purfield et al. Supplementary Material

Table

Download Purfield et al. Supplementary Material(File)
File 17.4 KB
Supplementary material: File

Purfield et al. Supplementary Material

Table

Download Purfield et al. Supplementary Material(File)
File 13.5 KB
Supplementary material: File

Purfield et al. Supplementary Material

Table

Download Purfield et al. Supplementary Material(File)
File 18.1 KB