4.5 Article

Predictive potential of microsatellite markers on heterosis of fecundity in crossbred sheep

Journal

MOLECULAR BIOLOGY REPORTS
Volume 39, Issue 3, Pages 2761-2766

Publisher

SPRINGER
DOI: 10.1007/s11033-011-1032-7

Keywords

Sheep; Microsatellite; Heterosis; Litter size

Funding

  1. National Key Technology Research and Development (R&D) Program of China [2008BADB2B04]
  2. earmarked fund for China Agriculture Research System [CARS-39]
  3. National Key Basic R&D Program of China [2006CB102105]
  4. Beijing Science and Technology Program of China [Y0705003041131, BJNY2006-03]

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Small Tail Han (STH) sheep is a famous Chinese local breed and has perfect prolificacy performance, but it is inferior to imported mutton sheep breeds on meat production. In this study, six imported male sheep populations (White Suffolk, Black Suffolk, Texel, Dorper, South African Mutton Merino and East Friesian) were crossbred with STH female sheep respectively. The heterosis values of litter size, average daily gain (ADG) and feed conversion ratio (FCR) of crossbred sheep were analyzed for seeking the optimal cross. Meanwhile 28 microsatellite markers were used to measure the genetic distance between imported populations and STH population. Regression between the genetic distance and heterosis was analyzed for evaluating potential of microsatellite on predicting heterosis. Results showed a significant positive linear correlation (r = 0.892, P < 0.05) between heterosis of litter size and genetic distance D-A of six crosses. This implied that these microsatellite markers had moderate potential to forecast heterosis of litter size in sheep. Results of this study also indicated that South African Mutton Merino and East Friesian sheep would be the optimal sire breeds for the litter size and might bring the greatest economic benefit in six imported populations; Suffolk sheep could be prior consideration as sire breeds when breeding objective focused on ADG. Finally these results provided valuable information for Chinese sheep industry.

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