SEARCH

SEARCH BY CITATION

References

  • Aslam ML, Bastiaansen JWM, Elferink MG, Megens H-J, Crooijmans RPMA, Blomberg LA, Fleischer RC, van Tassell CP, Sonstegard TS, Schroeder SG, Groenen MAM, Long JA, 2012: Whole genome SNP discovery and analysis of genetic diversity in Turkey (Meleagris gallopavo). BMC Genomics 13, 391.
  • Boysen T-J, Heuer C, Tetens J, Reinhardt F, Thaller G, 2013: Novel use of derived genotype probabilities to discover significant dominance effects for milk production traits in dairy cattle. Genetics 193, 431442.
  • Brookes AJ, 1999: The essence of SNPs. Gene 234, 177186.
  • Brown DJ, Huisman AE, Swan AA, Graser H-U, Woolaston RR, Ball AJ, Atkins KD, Banks RG, 2007: Genetic evaluation for the Australian sheep industry. Proc Assoc Advmt Anim Breed Genet 17, 187194.
  • Cervantes I, Meuwissen THE, 2011: Maximization of total genetic variance in breed conservation programmes. J Anim Breed Genet 128, 465472.
  • Chesnais JP, 2010: How is the AI industry using genomic tools in practice? In: Proc Interbull Int Workshop, Paris, France; Interbull Bull 41; Interbull Centre, Uppsala, Sweden; pp. 5962.
  • De Cara MAR, Fernández J, Toro MA, Villanueva B, 2011: Using genome-wide information to minimize the loss of diversity in conservation programmes. J Anim Breed Genet 128, 456464.
  • De Haas Y, Calus MPL, Veerkamp RF, Wall E, Coffey MP, Daetwyler HD, Hayes BJ, Pryce JE, 2012: Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets. J Dairy Sci 95, 61036112.
  • Dekkers JC, 2004: Commercial application of marker- and gene-assisted selection in livestock: Strategies and lessons. J Anim Sci 82(E-Suppl), E313E328.
  • De Rochambeau H, Licois D, Gidenne T, Verdelhan S, Coudert P, Elsen JM, 2006: Genetic variability of the resistance for three types of enteropathy in the growing rabbit. Livest Sci 101, 110115.
  • De Roos APW, Schrooten C, Veerkamp RF, Van Arendonk JAM, 2011: Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls. J Dairy Sci 94, 15591567.
  • Ducrocq V, Santus E, 2011: Moving away from progeny test schemes: Consequences on conventional (inter)national evaluations. In: Proc Interbull Int Workshop, 27-28 February 2011, Guelph, Canada; Interbull Bull 43. Available: http://www.interbull.org/images/stories/Ducrocq_copy.pdf (accessed 1 February 2013).
  • Dürr J, Philipsson J, 2012: International cooperation: the pathway for cattle genomics. Anim Front 2, 1621.
  • Eggen A, 2012: The development and application of genomic selection as a new breeding paradigm. Anim Front 2, 1015.
  • Engelsma KA, Veerkamp RF, Calus MPL, Windig JJ, 2011: Consequences for diversity when prioritizing animals for conservation with pedigree or genomic information. J Anim Breed Genet 128, 473481.
  • Falconer DS, 1989: Introduction to Quantitative Genetics, 3rd edn. Longman Scientific and Technical, New York.
  • Fan B, Du ZQ, Gorbach DM, Rothschild MF, 2010: Development and application of high-density SNP arrays in genomic studies of domestic animals. Asian-Aust J Anim Sci 23, 833847.
  • Fogarty NM, Banks RG, van der Werf JHJ, Ball AJ, Gibson JP, 2007: The Information Nucleus – a new concept to enhance sheep industry genetic improvement. Proc Assoc Advmt Anim Breed Genet 17, 2932.
  • Fulton JE, 2012: Genomic selection for poultry breeding. Anim Front 2, 3036.
  • Goddard M, 2009: Genomic selection: prediction of accuracy and maximization of long term response. Genetica 136, 245257.
  • González-Recio O, Gianola D, Rosa GJM, Weigel KA, Kranis A, 2009: Genome-assisted prediction of a quantitative trait measured in parents and progeny: application to food conversion rate in chickens. Genet Sel Evol 41, 3.
  • Guo G, Zhou Z, Wang Y, Zhao K, Zhu L, Lust G, Hunter L, Friedenberg S, Li J, Zhang Y, Harris S, Jones P, Sandler J, Krotscheck U, Todhunter R, Zhang Z, 2011: Canine hip dysplasia is predictable by genotyping. Osteoarthr Cartil 19, 420429.
  • Gyovai P, Nagy I, Gerencsér Z, Matics Z, Radnai I, Donkó T, Bokor Á, Farkas J, Szendrő Z, 2012: Genetic parameters for litter weight, average daily gain and thigh muscle volume measured by in vivo Computer Tomography technique in Pannon White rabbits. Livest Sci 144, 119123.
  • Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME, 2009: Genomic selection in dairy cattle: progress and challenges. J Dairy Sci 92, 433443.
  • Hypor, 2012: Hypor moves into a new era of genomic selection. Available: http://www.hypor.com/News/Hypor%20Moves%20Into%20A%20New%20Era%20 Of%20Genomic%20Selection.aspx (assessed 1 February 2013).
  • Ibañez-Escriche N, Gonzalez-Recio O, 2011: Review. Promises, pitfalls and challenges of genomic selection in breeding programs. Span J Agric Res 9, 404413.
  • Ke X, Kennedy LJ, Short AD, Seppälä EH, Barnes A, Clements DN, Wood SH, Carter SD, Happ GM, Lohi H, Ollier WER, 2011: Assessment of the functionality of genome-wide canine SNP arrays and implications for canine disease association studies. Anim Genet 42, 181190.
  • Kemper KE, Bowman PJ, Pryce JE, Hayes BJ, Goddard ME, 2012: Long-term selection strategies for complex traits using high-density genetic markers. J Dairy Sci 95, 46464656.
  • Koenen EPC, Aldridge LI, 2002: Testing and genetic evaluation of sport horses in an international perspective. 7th WCGALP, 19-23 August 2002, Montpellier, France.
  • Kwok P-Y, Gu Z, 1999: Single nucleotide polymorphism libraries: why and how are we building them? Mol Med Today 5, 538543.
  • Liu Z, 2011: Use of MACE results as input for genomic models. In: Proc Interbull Int Workshop, 27-28 February 2011, Guelph, Canada; Interbull Bull 43. Available: http://www.interbull.org/images/stories/Liu.pdf (accessed 1 February 2013).
  • Liu Z, Seefried FR, Reinhardt F, Rensing S, Thaller G, Reents R, 2010: Dairy cattle genetic evaluation enhanced with genomic information. 9th WCGALP, 1-6 August 2010, Leipzig, Germany.
  • Meuwissen THE, Hayes BJ, Goddard ME, 2001: Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 18191829.
  • Meuwissen THE, Hayes BJ, Goddard ME, 2013: Accelerating improvement of livestock with genomic selection. Annu Rev Anim Biosci 1, 221237.
  • Miglior F, Chesnais J, van Doormaal B, 2012: Genetic improvement: a major component of increased dairy farm profitability. 38th Ann Meet ICAR, 28 May to 1 June 2012, Cork, Ireland.
  • Montaldo HH, Casas E, Ferraz JBS, Vega-Murillo VE, Romá-Ponce SI, 2012: Opportunities and challenges from the use of genomic selection for beef cattle breeding in Latin America. Anim Front 2, 2329.
  • Muir WM, 2007: Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters. J Anim Breed Genet 124, 342355.
  • Oliete JQ, 2012: Application of Genome-Wide Single Nucleotide Polymorphism Arrays to Understanding Dog Disease and Evolution. PhD thesis. University of Barcelona, Barcelona.
  • Parker HG, Ostrander EA, 2005: Canine genomics and genetics: running with the pack. PLoS Genet 1, e58.
  • Patry C, Ducrocq V, 2011: Evidence of biases in genetic evaluations due to genomic preselection in dairy cattle. J Dairy Sci 94, 10111020.
  • Petersen JL, Mickelson JR, Rendahl AK, Valberg SJ, Andersson LS, Axelsson J, Bailey E, Bannasch D, Binns MM, Borges AS, Brama P, da Câmara Machado A, Capomaccio S, Cappelli K, Cothran EG, Distl O, Fox-Clipsham L, Graves KT, Guérin G, Haase B, Hasegawa T, Hemmann K, Hill EW, Leeb T, Lindgren G, Lohi H, Lopes MS, McGivney BA, Mikko S, Orr N, Penedo MCT, Piercy RJ, Raekallio M, Rieder S, Røed KH, Swinburne J, Tozaki T, Vaudin M, Wade CM, McCue ME, 2013: Genome-wide analysis reveals selection for important traits in domestic horse breeds. PLoS Genet 9, e1003211. doi:10.1371/journal.pgen.1003211.
  • Pryce JE, Daetwyler HD, 2012: Designing dairy cattle breeding schemes under genomic selection: a review of international research. Anim Prod Sci 52, 107114.
  • Pryce JE, Hayes B, 2012: A review of how dairy farmers can use and profit from genomic technologies. Anim Prod Sci 52, 180184.
  • Pryce JE, Gredler B, Bolormaa S, Bowman PJ, Egger-Danner C, Fuerst C, Emmerling R, Sölkner J, Goddard ME, Hayes BJ, 2011: Genomic selection using a multiple-breed, across-country reference population. J Dairy Sci 94, 26252630.
  • Pryce JE, Hayes B, Goddard ME, 2012: Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information. J Dairy Sci 95, 377388.
  • Ralph J, 2012: Future uses of genomics in the poultry industry. Available: http://www.aviagenturkeys.com/media/204651/future_uses_of_genomics_in_the_poultry_industry.pdf (assessed 8 February 2013).
  • Schaeffer L, 2006: Strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet 123, 218223.
  • Schefers JM, Weigel KA, 2012: Genomic selection in dairy cattle: integration of DNA testing into breeding programs. Anim Front 2, 49.
  • Schröder W, Klostermann A, Stock KF, Distl O, 2012: A genome-wide association study for quantitative trait loci of show-jumping in Hanoverian warmblood horses. Anim Genet 43, 392400.
  • Sellner EM, Kim JW, McClure MC, Taylor KH, Schnabel RD, Taylor JF, 2007: Applications of genomic information in livestock. J Anim Sci 85, 31483158.
  • Simianer H, Chen J, Erbe M, 2011: Animal breeding in the genomics era: Challenges and opportunities for the maintenance of genetic diversity. In: Proc 62nd Ann Meet EAAP, Stavanger, Norway; EAAP, Rome, Italy; p. 76 (abstract).
  • Smith C, 1967: Improvement of metric traits through specific genetic loci. Anim Prod 9, 349358.
  • Sonesson AK, Meuwissen THE, 2009: Testing strategies for genomic selection in aquaculture breeding programs. Genet Sel Evol 41, 37.
  • Toosi A, Fernando RL, Dekkers JCM, 2010: Genomic selection in admixed and crossbred populations. J Anim Sci 88, 3246.
  • Van der Werf JHJ, 2009: Potential benefit of genomic selection in sheep. Proc Assoc Advmt Anim Breed Genet 18, 3841.
  • Van Grevenhof EM, Van Arendonk JAM, Bijma P, 2012: Response to genomic selection: The Bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting. Genet Sel Evol 44, 26.
  • Weigel KA, Van Tassell CP, O'Connell JR, Van Raden PM, Wiggans GR, 2010: Prediction of unobserved single nucleotide polymorphism genotypes of Jersey cattle using reference panels and population based imputation algorithms. J Dairy Sci 93, 22292238.
  • Weigel KA, Hoffmann PC, Herring W, Lawlor TJ, 2012: Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves on commercial dairy farms. J Dairy Sci 95, 22152225.