Hostname: page-component-77c89778f8-gq7q9 Total loading time: 0 Render date: 2024-07-21T05:57:07.607Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimation of heritabilities and correlations between repeated faecal egg count measurements in lambs facing natural nematode parasite challenge, using a random regression model

Published online by Cambridge University Press:  26 April 2007

D. VAGENAS ,
I. M. S. WHITE ,
M. J. STEAR  and
S. C. BISHOP
D. VAGENAS
Affiliation:
Roslin Institute (Edinburgh), Midlothian EH25 9PS, UK
I. M. S. WHITE
Affiliation:
Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK
M. J. STEAR
Affiliation:
Department of Veterinary Clinical Studies, Glasgow University Veterinary School, Bearsden Road, Glasgow G61 1QH, Scotland, UK
S. C. BISHOP*
Affiliation:
Roslin Institute (Edinburgh), Midlothian EH25 9PS, UK
*
*To whom all correspondence should be addressed. Email: Stephen.Bishop@bbsrc.ac.uk
Get access Rights & Permissions [Opens in a new window]

Summary

The development of the genetic control of nematode resistance in growing lambs is of biological interest, as well as being important in terms of designing practical strategies to breed for increased nematode resistance. The current paper demonstrates the use of random regression techniques for quantifying the development of the heritability of faecal egg count (Fec), the indicator of nematode resistance, in growing lambs and predicted inter-age genetic and phenotypic correlations for Fec. Fec data from 732 lambs, collected at 4-week intervals from c. 8–24 weeks of age, were analysed using random regression techniques. Random effects fitted in the model included genetic, individual animal environmental, litter and residual random effects. Output (co)variance components were interpolated to weekly time points. Individual variance components showed complex patterns of change over time; however, the estimated heritability increased smoothly with age, from 0·10 to 0·38, and showed more stable time trends than were obtained from univariate analyses of Fec at individual time points. Inter-age correlations decreased as the time interval between measurements increased. Genetic correlations were always positive, with 0·6 of all possible inter-age correlations being greater than 0·80. Phenotypic correlations were lower, and decreased more quickly as the time interval between measurements increased. The results presented confirm biological understanding of the development of immunity to nematode infections in growing lambs. Additionally, they provide a tool to determine optimal sampling ages when assessing lambs' relative resistance to nematode infections.

Type
Animals
Information
The Journal of Agricultural Science , Volume 145 , Issue 5 , October 2007 , pp. 501 - 508
Copyright
Copyright © Cambridge University Press 2007

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

REFERENCES

Albuquerque, L. G. & Meyer, K. (2001). Estimates of covariance functions for growth from birth to 630 days of age in Nelore cattle. Journal of Animal Science 79, 2776–2789.CrossRefGoogle ScholarPubMed
Bairden, K. (1991). Ruminant parasitic gastroenteritis: some observations on epidemiology and control. Ph.D. Thesis, University of Glasgow.Google Scholar
Bishop, S. C., Bairden, K., McKellar, Q. A., Park, M. & Stear, M. J. (1996). Genetic parameters for faecal egg count following mixed, natural predominately O. circumcincta infection and relationships with liveweight in young lambs. Animal Science 63, 423–428.CrossRefGoogle Scholar
Bouix, J., Krupinski, J., Rzepecki, R., Nowosad, B., Skrzyzala, I., Roborzynski, M., Fudalewicz-Niemczyk, W., Skalska, M., Malczewski, A. & Gruner, L. (1998). Genetic resistance to gastrointestinal nematode parasites in Polish long-wool sheep. International Journal for Parasitology 28, 1797–1804.CrossRefGoogle ScholarPubMed
Coop, R. L., Graham, R. B., Jackson, F., Wright, S. E. & Angus, K. W. (1985). Effect of experimental Ostertagia circumcincta infection on the performance of grazing lambs. Research in Veterinary Science 38, 282–287.CrossRefGoogle ScholarPubMed
Eady, S. J., Woolaston, R. R., Mortimer, S. I., Lewer, R. P., Raadsma, H. W., Swan, A. A. & Ponzoni, R. W. (1996). Resistance to nematode parasites in merino sheep: sources of genetic variation. Australian Journal of Agricultural Research 47, 895–915.CrossRefGoogle Scholar
Gilmour, A. R., Thompson, R., Cullis, B. R. & Welham, S. (1999). ASREML Reference Manual. Biometrics Bulletin No. 3. Orange, NSW, Australia: New South Wales Agriculture.Google Scholar
Gordon, H. M. & Whitlock, H. V. (1939). A new technique for counting nematode eggs in sheep faeces. Journal of the Council for Scientific and Industrial Research, Australia 12, 50–52.Google Scholar
Jackson, F & Coop, R. L. (2000). The development of anthelmintic resistance in sheep nematodes. Parasitology, 120, 95–107.CrossRefGoogle ScholarPubMed
Jensen, J. (2001). Genetic evaluation of cattle using test-day models. Journal of Dairy Science 84, 2803–2812.CrossRefGoogle ScholarPubMed
Kettunen, A., Mantysaari, E. A. & Poso, J. (2000). Estimation of genetic parameters for daily milk yield of primiparous Ayrshire cows by random regression test-day models. Livestock Production Science 66, 251–261.CrossRefGoogle Scholar
Kirkpatrick, M., Lofsvold, D. & Bulmer, M. (1990). Analysis of the inheritance, selection and evolution of growth trajectories. Genetics 124, 979–993.CrossRefGoogle ScholarPubMed
Lawes Agricultural Trust (1993). Genstat 5. Release 3.2. Harpenden: Rothamsted Experimental Station.Google Scholar
McEwan, J. C., Dodds, K. G., Greer, G. J., Bain, W. E., Duncan, S. J., Wheeler, R., Knowler, K. J., Reid, P. J., Green, R. S. & Douch, P. G. C. (1995). Genetic estimates for parasite resistance traits in sheep and their correlations with production traits. New Zealand Journal of Zoology 22, 177.Google Scholar
McEwan, J. C., Mason, P., Baker, R. L., Clarke, J. N., Hickey, S. M. & Turner, K. (1992). Effect of selection for productive traits on internal parasite resistance in sheep. Proceedings of the New Zealand Society of Animal Production 52, 53–56.Google Scholar
Meyer, K. (1999). Estimates of genetic and phenotypic covariance functions for postweaning growth and mature weight of beef cows. Journal of Animal Breeding and Genetics 116, 181–205.CrossRefGoogle Scholar
Meyer, K. (2005). Random regression analyses using B-splines to model growth of Australian Angus cattle. Genetics Selection Evolution 37, 473–500.CrossRefGoogle ScholarPubMed
Meyer, K. & Hill, W. G. (1997). Estimation of genetic and phenotypic covariance functions for longitudinal or ‘repeated’ records by restricted maximum likelihood. Livestock Production Science 47, 185–200.CrossRefGoogle Scholar
Morris, C. A., Vlassoff, A., Bisset, S. A., Baker, R. L., West, C. J. & Hurford, A. P. (1997). Responses of Romney sheep to selection for resistance or susceptibility to nematode infection. Animal Science 64, 319–329.CrossRefGoogle Scholar
Morris, C. A., Vlassoff, A., Bissett, A., Baker, R. L., Watson, T. G., West, C. J. & Wheeler, M. (2000). Continued selection of Romney sheep for resistance or susceptibility to nematode infection: estimates of direct and correlated responses. Animal Science 70, 17–27.CrossRefGoogle Scholar
Perry, B. D., McDermott, J. J., Randolph, T. F., Sones, K. R. & Thornton, P. K. (2002). Investing in Animal Health Research to Alleviate Poverty. Nairobi, Kenya: International Livestock Research Institute (ILRI). Available online at www.ilri.org/InfoServ/Webpub/fulldocs/investinginanimal/index.htm (verified 13/03/2007).Google Scholar
Raadsma, H. W., Gray, G. D. & Woolaston, R. R. (1997). Genetics of disease resistance and vaccine response. In The Genetics of Sheep (Eds Piper, L. & Ruvinsky, A.), pp. 199–224. Wallingford, Oxfordshire, UK: CAB International.Google Scholar
Stear, M. J. & Bishop, S. C. (1999). The curvilinear relationship between worm length and fecundity of Teladorsagia circumcincta. International Journal for Parasitology 29, 777–780.CrossRefGoogle ScholarPubMed
Stear, M. J., Bairden, K., Duncan, J. L., Holmes, P. H., McKellar, Q. A., Park, M., Strain, S., Murray, M., Bishop, S. C. & Gettinby, G. (1997). How hosts control worms. Nature 389, 27.CrossRefGoogle ScholarPubMed
Stear, M. J., Strain, S. & Bishop, S. C. (1999). Mechanisms underlying resistance to nematode infection. International Journal for Parasitology 29, 51–56.CrossRefGoogle ScholarPubMed
Strabel, T. & Jamrozik, J. (2006). Genetic analysis of milk production traits of Polish black and white cattle using large-scale random regression test-day models. Journal of Dairy Science 89, 3152–3163.CrossRefGoogle ScholarPubMed
Waller, P. J. (1997). Anthelmintic resistance. Veterinary Parasitology 72, 391–405.CrossRefGoogle ScholarPubMed
Woolaston, R. R. & Piper, L. R. (1996). Selection of merino sheep for resistance to Haemochus contortus: genetic variation. Animal Science 62, 451–460.CrossRefGoogle Scholar
Woolaston, R. R. & Windon, R. G. (2001). Selection of sheep for response to Trichostrongylus colubriformis larvae: genetic parameters. Animal Science 73, 41–48.CrossRefGoogle Scholar