Measuring changes in diversity

Utilisation and conservation of farm animal genetic resources 73 Chapter 3. What is genetic diversity? interpretation of this measure in terms of evolutionary forces is diicult in livestock because selection plays a major role in breed development and neutrality of easily measured quantitative traits conformation, production, reproduction is perhaps more questionable than anonymous DNA markers. Q ST can be expressed as σ B 2 σ B 2 +2σ W 2 , so high values of Q ST indicate a high degree of diferentiation between breeds, and consequently the importance of breed variation. It is closely related to the direct measure g 1 =σ B 2 σ B 2 +σ W 2 based upon extant genetic variation since Q ST = g 1 2-g 1 . For example, using the values of g 1 in Box 3.2, estimates of Q ST for feed conversion and relative growth rate were 0.14 and 0.20. 4. Probabilities of ixation and loss of individual alleles from a population and hence the number of alleles we observe will depend on migration, drit and also selection if the allele is not neutral. he extent of drit, and consequently how these probabilities will change over time, will depend on ΔF. his is covered in more detail by Crow and Kimura 1972, and results have also been developed for selection e.g. Caballero et al., 1996.

8. Conclusion

In ‘he Name of the Rose’ by Umberto Eco 1992, as translated by William Weaver, Father William of Baskerville delights in the diversity of nature by declaring ‘the beauty of the cosmos derives not only from unity in variety, but also from variety in unity’. He summarises in just 18 words − and only 13 distinct words − that when examining the population of a species we should expect variety, and will invariably ind it, and as we look closer at what appears at irst sight to be a more uniform sub-population of individuals, so variety remains. However, quantifying diversity, understanding its scientiic nature and importance, and providing guidance on how to use and conserve it, requires many more words References Caballero, A., M. Wei and W.G. Hill, 1996 Survival rates of mutant genes under artiicial selection using individual and family information. Journal of Genetics 75: 63-80. Crow, J.F. and M. Kimura,1972. Introduction to Population Genetics heory. Harper Row. Carlborg, O., L. Jacobsson, P. Ahgren, P. Siegel and L. Andersson., 2006. Epistasis and the release of genetic variation during long-term selection. Nature Genetics 38: 418-420. Cundif, L.V., M.D. MacNeil, K.E. Gregory and R.M. Koch, 1986. Between- and within-breed genetic analysis of calving traits, and survival to weaning in beef cattle. Journal of Animal Science 63: 27-33. Daetwyler, H.D., F.S. Schenkel and J.A.B. Robinson, 2006. Relationship of multilocus homozygosity and inbreeding in Canadian Holstein sires. Proceedings of the Canadian Society of Animal Scientists Halifax Joint Colloquium, Halifax, NS, Canada. 74 Utilisation and conservation of farm animal genetic resources John Woolliams and Miguel Toro Eco, U. and W. Weaver, 1992. he Name of the Rose. Vintage. Falconer, D.S. and T.F.C Mackay, 1996. Introduction to Quantitative Traits. 4th edition, Longman, Harlow, Essex, UK. Fedorova L. and A. Fedorov, 2005. Puzzles of the human genome: Why do we need our introns? Current Genomics 6: 589-595. Fernandez, J., Villanueva, R. Pong-Wong and M.A. Toro, 2005. Eiciency of the use of pedigree and molecular marker information in conservation programs. Genetics 170: 1313-1321. Jenkins, T.G., M. Kaps. L.V. Cundif and C.L. Ferrell, 1991. Evaluation of between- and within- breed variation in measures of weight to age-relationships. Journal of Animal Science 69: 3118-3128. Lush, J.L., 1994. he Genetics of Populations. Special Report 94. Iowa State University. Lynch, M. and B. Walsh, 1998. Genetics and Analysis of Quantitative Traits. Sinauer Associates. McKay, J.K. and R.G. Latta, 2002. Adaptive population divergence: markers, QTL and traits. Trends in Ecology and Evolution 17: 285-291. Maynard Smith, J. and J. Haigh, 1974.he hitch-hiking efect of a favourable gene. Genetical Research 23: 23–35. Reed D.H. and R. Frankham, 2001. How closely correlated are molecular and quantitative measures of genetic variation? A meta-analysis. Evolution 55: 1095-1103. Slate, J., P. David, K.G. Dodds, B.A. Veenvliet, B.C. Glass, T.E. Broad and J.C. McEwan, 2004. Understanding the relationship between the inbreeding coeicient and multilocus heterozygosity: theoretical expectations and empirical data. Heredity 93: 255-265. hiessen, R.B., E. Hnizdo, D.A.G. Maxwell, D. Gibson and St.C.S. Taylor, 1984. Multibreed comparisons of British cattle: variation in body-weight, growth-rate and food-intake. Animal Production 38: 323-340. hiessen, R.B., St.C.S. Taylor and J. Murray, 1985. Multibreed comparisons of British cattle: variation in relative growth-rate, relative food-intake and food conversion eiciency. Animal Production 41: 193-199. Toro, M., C. Barragan, C. Ovilo, J. Rodriganez, C. Rodriguez and L. Silió, 2002. Estimation of coancestry in Iberian pigs using molecular markers. Conservation Genetics 3: 309-320. Toro, M., J. Fernandez and A. Caballero, 2006. Scientiic basis for policies in conservation of farm animal genetic resources. Proceedings 8 th World Congress on Genetics Applied to Livestock Production, CD- ROM Communication No. 33-05. Wheeler, T.L., L.V. Cundif, R.M. Koch and J.D. Crouse, 1996. Characterisation of biological types of cattle cycle IV: carcass traits and longissimus palatability. Journal of Animal Science 74: 1023-1035. Wiener, P., D. Burton, P. Ajmone-Marsan, S. Dunner, G. Mommens, I.J. Nijman, C. Rodellar, A. Valentini and J.L. Williams., 2003. Signatures of selection? Patterns of microsatellite diversity on a chromosome containing a selected locus. Heredity 90: 350-358. Woolliams, J.A., R. Pong-Wong and B. Villanueva, 2002. Strategic optimisation of short and long-term gain and inbreeding in MAS and non-MAS schemes. Proceedings of the 7 th World Congress on Genetics Applied to Livestock Production 33: 155-162. Wright, S., 1969. Evolution and the genetics of populations. Vol. 2. he heory of Gene Frequencies. University of Chicago, Chicago.