Use of SNP for Whole Genome Selection in Cattle, Page 6

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SNP Evaluation Systems (continued)

Refinements of SNP Selection and Future Aspects

SNP technology will not replace current methods of selecting breeding cattle but will be used in addition to them. We will use all the pedigree information (including the new SNP information on parents) in decision making, as well as the individual’s phenotype (e.g., birth weight). The term “genomic enhanced EPDs” already has been introduced to beef cattle breeders. Also, specific allelic information will be used, such as sex (embryos), coat color, freedom from recessive alleles for genetic diseases, desirable alleles such as for meat tenderness or milk composition, etc.

The SNP marker information also will be used by researchers to identify the alleles that are being marked; gene chips eventually will discriminate among those alleles, making the whole process of using SNP markers obsolete. This also gets around having to work within populations or families because problems due to crossing over between markers and alleles will disappear. This will take years to accomplish for a substantive number of genes, and because genes/alleles interact, SNP-type systems, including thousands of simultaneous equations, will likely be used for some time; sophisticated mathematics will be needed to find optimal combinations of alleles.

Implicit in this discussion is that the objective has been selecting the optimal animals for breeding purposes. This is somewhat different from choosing the best animals from a phenotypic standpoint. For example, for breeding purposes, homozygosity of alleles (resulting in breeding “true”) will be aimed for, whereas for production purposes, heterozygosity will likely be more desirable for some genes. This gets further complicated in the context of optimal maternal versus terminal cross lines.

Intense selection for homozygous desirable alleles directly results in increased inbreeding but also increases inbreeding indirectly, as adjacent lengths of DNA are selected to homogeneity. However, SNP systems can be directed to minimize inbreeding, and they automatically select against allelic combinations that cause inbreeding depression, at least for the trait(s) being selected. As genomic-enhanced selection procedures can be used either to ameliorate or exacerbate problems such as decreased fertility of high milk-producing dairy cows, thoughtful application is essential. One other obvious approach just alluded to is to have parental lines for breeding purposes that are crossed for production purposes, as is routine for poultry, pigs, sheep, and hybrid plants. SNPs can be used to mark alleles causing inbreeding depression and then ensure that those alleles result in a heterozygous configuration for particular matings.

It is only a small step to incorporate transgenic technology into such systems; for example, polled alleles might be added to genotypes for high-producing dairy cows without compromising the allelic profile for profitable milk production. This particular example might not be considered transgenic because it would simply be changing a bovine allele to result in the exact endpoint that would occur by introgression through repeated back-crossing.

The value of this technology for basic research has only been alluded to briefly. As one example, this technology can be used for pinpointing the meiotic crossing-over events that occur in each chromosome in every gamete produced. The next few decades will be truly exciting as assisted reproduction technologies, such as sexed semen and embryo transfer, are combined with genetic technologies such as genomic-enhanced selection using SNPs. While I have emphasized cattle, SNP technology already is being used on a large scale for plant breeding and will also find use with most domestic animals including companion animals. There also will be applications for endangered species, and as mentioned earlier, related technology will be of great value applied to our own species, particularly for treating diseases and possibly even for retarding aging, especially for conditions such as Parkinson’s or Alzheimer’s diseases.

Acknowledgments

A number of persons provided useful comments during preparation of this manuscript. The references cited are excellent sources for those wanting additional information. This paper is nearly identical to a version first published in Reproduction, Fertility and Development in January 2010, 22:138-144.

Author Information

G.E. Seidel, Jr.
Animal Reproduction and Biotechnology Laboratory
Colorado State University

References

The Bovine HapMap Consortium. (2009). Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 324, 528-532.

Bromfield J., Messare, W., and Albertini. D. F. (2008). Epigenetic regulation during oogenesis. Reprod. Fertil. Dev. 20, 74-80.

Edelson D. L. (2008). Insights and applications from sequencing the bovine genome. Reprod. Fertil Dev. 20, 54-60.

Elsik, C. G., Tellam, R. L., Worley, K. C., and The Bovine Genome Sequencing and Analysis Consortium. (2009). The genome sequence of taurine cattle: A window to ruminant biology and evolution. Science 324, 522-528.

Hayes, B. J., Bowman, P. J., Chamberlain, A. J., and Goddard, M. E. (2009). Genomic selection in dairy cattle: Progress and challenges. J. Dairy Sci. 92, 433-443.

Le Bourhis, D., Amigues, Y., Charreaux, F., Lacaze, S., Tissier, M., Guyader-Joly, C., Mervant, G., Moulin, B., Vignon, X., Gonzalez, C., and Humblot, P. (2009). Embryo genotyping from in vivo biopsied bovine embryos after whole genome amplification. Reprod. Fertil. Develop. 22, 192 (Abstr. 187).

Lee, S. H., van der Werf, J. H. J., Hayes, B. J., Goddard, M. E., and Visscher, P. M. (2008). Predicting unobserved phenotypes for complex traits from whole-genome SNP data. PLoS Genet. 4, e1000231, doi:10.1371/journal.pgen.1000231.

Sonstegard, T. S., and iBMC Consortium. (2008). Applied genomics in cattle SNPs to chips: Changing the paradigm of selection of cattle. Acta Sci. Vet. 36 (Suppl. 2), s287-s298.

VanRaden, P. M., Van Tassell, C. P., Wiggans, G. R., Sonstegard, T. S., Schnabel, R. D., Taylor, J. F., and Schenkel, F. S. (2009). Reliability of genomic predictions for North American Holstein bulls. J. Dairy Sci. 92, 16-24.

 


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This work is supported by the USDA National Institute of Food and Agriculture, New Technologies for Ag Extension project.