Advertisement

Current Status of Genomic Maps: Genomic Selection/GBV in Livestock

  • Agustin Blasco
  • R. N. Pena
Chapter

Abstract

Our understanding on how the genome is structured has improved substantially since the human genome was first sequenced in 2001. The sequencing of livestock and other model animals, in addition to other organisms, has also helped to identify common genomic patterns and features, which can now be summarised in genome maps. The annotation of sequence variation in the livestock genomes has opened up the possibility of using its genomic information for improving the prediction accuracy of its genetic merit. This chapter will give a general view on the main features annotated to the livestock genomes and outline the application of molecular information in the prediction of the genetic breeding value of the animals. The advantages and limitations of implementing this methodology in distinct production systems are also discussed.

Keywords

Genetic maps Genomic selection Livestock genomics Gene annotation Animal breeding 

References

  1. Andersson R (2015) Promoter or enhancer, what’s the difference? Deconstruction of established distinctions and presentation of a unifying model. BioEssays 37:314–323.  https://doi.org/10.1002/bies.201400162 CrossRefPubMedGoogle Scholar
  2. Archibald AL et al (1995) The PiGMaP consortium linkage map of the pig (Sus scrofa). Mamm Genome 6:157–175CrossRefPubMedGoogle Scholar
  3. Berry DP, Kearney JF (2011) Imputation of genotypes from low- to high-density genotyping platforms and implications for genomic selection. Animal 5:1162–1169CrossRefPubMedGoogle Scholar
  4. Blasco A (2008) The role of genetic engineering in livestock production. Livestock Sci 113:191–201CrossRefGoogle Scholar
  5. Blasco A (2017) Bayesian statitics for animal scientists. Springer, New YorkGoogle Scholar
  6. Blasco A, Toro MA (2014) A short critical history of the application of genomics to animal breeding. Livstock Sci 166:4–9CrossRefGoogle Scholar
  7. Chen CY, Misztal I, Aguilar I, Tsuruta S, Meuwissen THE, Aggrey SE, Wing T, Muir WM (2011) Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: an example using broiler chickens. J Anim Sci 89:23–28CrossRefPubMedGoogle Scholar
  8. Clark SA, van der Werf J (2013) Genomic best linear unbiased prediction (gBLUP) for the estimation of genomic breeding values. In: Gondro C, van der Werf J, Hayes B (eds) Genome-wide association studies and genomic prediction. Springer, New YorkGoogle Scholar
  9. Cleveland MA, Hickey JM (2013) Practical implementation of cost-effective genomic selection in commercial pig breeding using imputation. J Anim Sci 91:3583–3592CrossRefPubMedGoogle Scholar
  10. ENCODE Project Consortium (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489:57–74.  https://doi.org/10.1038/nature11247 CrossRefGoogle Scholar
  11. Falconer D, Mackay TFC (1996) Introduction to quantitative genetics. Longman, EdinburghGoogle Scholar
  12. Fernando RL, Garrick D (2013) Bayesian methods applied to GWAS. In: Gondro C, van der Werf J, Hayes B (eds) Genome-wide association studies and genomic prediction. Springer, New YorkGoogle Scholar
  13. Groenen MAM, Schook LB, Archibald AL (2011) Pig genomics. In: Rothschild MF, Ruvinsky A (eds) The genetics of the pig, 2nd edn. CAB International, Wallingford, UK, p 496.  https://doi.org/10.1079/9781845937560.0000 CrossRefGoogle Scholar
  14. Habier D, Fernando RL, Dekkers JCM (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389–2397PubMedPubMedCentralGoogle Scholar
  15. Hangauer MJ, Vaughn IW, McManus MT (2013) Pervasive transcription of the human genome produces thousands of previously unidentified long intergenic noncoding RNAs. PLoS Genet 9:e1003569.  https://doi.org/10.1371/journal.pgen.1003569 CrossRefPubMedPubMedCentralGoogle Scholar
  16. Hausser J, Zavolan M (2014) Identification and consequences of miRNA-target interactions--beyond repression of gene expression. Nat Rev Genet 15:599–612.  https://doi.org/10.1038/nrg3765 CrossRefPubMedGoogle Scholar
  17. Horton BH, Banks R, Van der Werf JHJ (2015) Industry benefits from using genomic information in two- and three-tier sheep breeding systems. Anim Prod Sci 55:437–446CrossRefGoogle Scholar
  18. Huang Y, Hickey JM, Cleveland MA, Maltecca C (2012) Assessment of alternative genotyping strategies to maximize imputation accuracy at minimal cost. Genet Sel Evol 44:25CrossRefPubMedPubMedCentralGoogle Scholar
  19. Ibañez N, Blasco A (2011) Modifying growth curve parameters by multitrait genomic selection. J Anim Sci 89:661–668CrossRefGoogle Scholar
  20. Ibáñez-Escriche N, Forni S, Noguera JL, Varona L (2014) Genomic information in pig breeding: science meets industry needs. Livestock Sci 166:94–100CrossRefGoogle Scholar
  21. Jonas E, de Koning DJ (2015) Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs. Anim Front 6:1–8Google Scholar
  22. Knap PW, Wang L (2012) Pig breeding for improved feed efficiency. In: Patience JF (ed) Feed efficiency in swine. Wageningen Academic Publishers, WageningenGoogle Scholar
  23. Knol EF, Nielsen B, Knap PW (2016) Genomic selection in commercial pig breeding. Anim Front 6:15–22CrossRefGoogle Scholar
  24. Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756PubMedPubMedCentralGoogle Scholar
  25. Legarra A, Aguilar I, Misztal I (2009) A relationship matrix including full pedigree and genomic information. J Dairy Sci 92:4656–4663CrossRefPubMedGoogle Scholar
  26. Libri D (2015) Sleeping beauty and the beast (of pervasive transcription). RNA 21:678–679.  https://doi.org/10.1261/rna.050948.115 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Lillehammer M, Meuwissen THE, Sonesson AK (2013) Genomic selection for two traits in a maternal pig breeding scheme. J Anim Sci 91:3079–3087CrossRefPubMedGoogle Scholar
  28. Lund MS, Su G, Janss L, Guldbrandtsen B, Brøndum RF (2014) Genomic evaluation of cattle in a multi-breed context. Livestock Sci 166:101–110CrossRefGoogle Scholar
  29. Mattick JS (2011) The central role of RNA in human development and cognition. FEBS Lett 585:1600–1616CrossRefPubMedGoogle Scholar
  30. Meuwissen TH, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829PubMedPubMedCentralGoogle Scholar
  31. Misztal I, Legarra A, Aguilar I (2009) Computing procedures for genetic evaluation including phenotypic, full pedigree and genomic information. J Dairy Sci 92:4648–4655CrossRefPubMedGoogle Scholar
  32. Neale DB et al (2014) Decoding the massive genome of loblolly pine using haploid DNA and novel assembly strategies. Genome Biol 15:R59.  https://doi.org/10.1186/gb-2014-15-3-r59 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Nicholas FW, Smith C (1983) Increased rates of genetic change in dairy cattle by embryo transfer and splitting. Anim Prod Sci 36:341–353CrossRefGoogle Scholar
  34. Rolf MM, Decker JE, Mckay SD, Tizioto PC, Branham KA, Whitacre LK, Hoff JL, Regitano LCA, Taylor JF (2014) Genomics in the United States beef industry. Livestock Sci 166:84–93CrossRefGoogle Scholar
  35. Rupp R, Mucha S, Larroque H, McEwan J, Conington J (2016) Genomic application in sheep and goat breeding. Anim Front 6:39–44CrossRefGoogle Scholar
  36. Schaeffer LR (2006) Strategy for applying genome-wide selectionin strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet 123:218–223CrossRefPubMedGoogle Scholar
  37. Shumbusho F, Raoul J, Astruc JM, Palhiere I, Lemarié S, Fugeray-Scarbel A, Elsen JM (2016) Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program. Animal 6:1033–1041Google Scholar
  38. Silver LM (1995) Mouse genetics. Oxford University Press, Bar Harbor, MaineGoogle Scholar
  39. Simianier H (2016) Genomic and other revolutions why some technologies are quickly adopted and others are not. Anim Front 6:53–58CrossRefGoogle Scholar
  40. Smith C, Smith DJ (1993) The need for close linkages in markers-assisted selection for economic meritin livestock. Anim Breed Abst 61:197–204Google Scholar
  41. Soller M (1978) The use of loci associated with quantitative traits in dairy cattle improvement. Anim Prod 27:133–139CrossRefGoogle Scholar
  42. Van Eenennaam AL, Weigel KA, Young AE, Matthew AC, Dekkers JCM (2013) Applied animal genomics: results from the field. Annu Rev Anim Biosci 2:9.1–9.35Google Scholar
  43. Van Raden PM, O’Connell JR, Wiggans GR, Weigel KA (2011) Genomic evaluations with many more genotypes. Genet Sel Evol 43:10CrossRefGoogle Scholar
  44. Vitezica ZG, Varona L, Elsen JM, Misztal I, Herring W, Legarra A (2016) Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs. Genet Sel Evol 48:6CrossRefPubMedPubMedCentralGoogle Scholar
  45. Warren WC et al (2017) A new chicken genome assembly provides insight into avian genome structure. G3 7:109–117.  https://doi.org/10.1534/g3.116.035923 CrossRefPubMedGoogle Scholar
  46. Wiggans GR, Cole JB, Hubbard SM, Sonstegard TS (2017) Genomic selection in dairy cattle: the USDA experience. Annu Rev Anim Biosci 5:309–327CrossRefPubMedGoogle Scholar
  47. Wolc A, Zhao HH, Arango J, Settar P, Fulton JE, O’Sullivan NP, Preisinger R, Stricker C, Habier D, Fernando RL, Garrick DJ, Lamont SJ, Dekkers JCM (2015) Response and inbreeding from a genomic selection experiment in layer chickens. Genet Sel Evol 47:59CrossRefPubMedPubMedCentralGoogle Scholar
  48. Wolc A, Kranis A, Arango J, Settar P, Fulton JE, O’Sullivan NP, Avendano A, Watson KA, Hickey JM, De los Campos G, Fernando RL, Garrick DJ, Dekkers JCM (2016) Implementation of genomic selection in the poultry industry. Anim Front 6:23–31CrossRefGoogle Scholar
  49. Won KJ et al (2013) Comparative annotation of functional regions in the human genome using epigenomic data. Nucleic Acids Res 41:4423–4432.  https://doi.org/10.1093/nar/gkt143 CrossRefPubMedPubMedCentralGoogle Scholar
  50. Wright MW (2014) A short guide to long non-coding RNA gene nomenclature. Hum Genomics 8:7.  https://doi.org/10.1186/1479-7364-8-7 CrossRefPubMedPubMedCentralGoogle Scholar
  51. Xu J, Zhang J (2016) Are human translated pseudogenes functional? Mol Biol Evol 33:755–760.  https://doi.org/10.1093/molbev/msv268 CrossRefPubMedGoogle Scholar
  52. Yerle M et al (1995) The PiGMaP consortium cytogenetic map of the domestic pig (Sus scrofa domestica). Mamm Genome 6:176–186CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute for Animal Science and TechnologyUniversitat Politècnica de ValènciaValenciaSpain
  2. 2.Department of Animal ScienceUniversity of Lleida – Agrotecnio CentreLleidaSpain

Personalised recommendations