4.4 Article

Analysis of the influence of the PrP genotype on the litter size in Polish sheep using classification trees and logistic regression

Journal

LIVESTOCK SCIENCE
Volume 159, Issue -, Pages 11-17

Publisher

ELSEVIER
DOI: 10.1016/j.livsci.2013.11.008

Keywords

PRNP; Sheep; Litter size; Classification trees; Logistic regression

Funding

  1. European Social Fund
  2. Polish National Budget
  3. Kuyavian-Pomeranian Voivodeship Budget in terms of Human Capital Operational Programme, Priority VIII, activity 8.2, subactivity 8.2.2 Regional Innovation Strategies

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The relation between prion protein (PrP) genotype class and litter size was analysed in Polish Merino, Black-headed, Ile de France and Berrichon du Cher sheep in Poland. Litter size was analysed with the classification tree technique and multiple logistic regression for effects of breed, age of ewe, PrP genotype, litter size of ewe at her birth, and at her rearing and year of ewe's birth. The resulting classification tree was 6-level deep and contained 21 leaves. Age, breed and year of birth were more important determinants of litter size than PrP genotype. Importance of PrP genotype in the tree development was 0.560 relative to age of ewe. While the logistic regression analysis showed that the overall effect of the PrP genotype on the number of born lambs was not significant, the classification trees technique demonstrated that the PrP genotype differentiated ewes within some breeds and ages in terms of the litter size. Black-headed ewes homozygous for ARR gave birth to twins less often compared to heterozygous or non ARR ewes. However, in Polish Merino and Berrichon du Cher ewes aged 2-4 years and born after 2001, litter size was larger for homozygous ARR ewes. Consequently, a direct effect of the PrP genotype itself on litter size is unlikely, since the direction of the effect differed between sheep breeds. The classification trees technique proved to be effective in detailing effects of the PrP genotype on litter size and may be used as an additional approach in exploring data. (C) 2013 Elsevier B.V. All rights reserved.

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