Quantitative trait loci analysis of swine meat quality traits

Quantitative trait loci analysis of swine meat quality traits
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DOI:
10.2527/jas.2009-2590
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发表时间:
2010-09-01
影响因子:
3.3
通讯作者:
Bendixen, C.
Bendixen, C.
中科院分区:
农林科学2区
文献类型:
--
作者:
Li, H. D.;Lund, M. S.;Bendixen, C.

文献摘要

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在半同胞家系中进行了QTL研究,以表征猪肉品质性状变异的遗传背景,并研究在标记辅助选择方案中包括QTL的可能性。品质性状包括LM和半膜肌中的最终pH、滴水损失以及分别代表肉的亮度、红色和黄色的美能达颜色测量值L*、a* 和B*。这些家系由12头杜洛克公猪的3,883个后代组成,这些后代被评估以鉴定QTL。该连锁图由18个猪常染色体上的462个SNP标记组成。数量性状基因座的定位使用线性混合模型与固定因素(公畜,性别,畜群,月份,母猪年龄)和随机因素(多基因效应,QTL效应,和窝)。全染色体和全基因组的显着性阈值确定Peipho的方法,和95%贝叶斯可信区间估计从QTL位置的后验分布。在5%染色体水平上共检测到31个与6个肉质性状相关的QTL,其中11个QTL在5%基因组水平上达到显著水平,5个QTL在0.1%基因组水平上达到显著水平。还调查了所鉴定的QTL在不同家系中的分离。大多数QTL在1 ~ 2个家系中分离。对于影响LM和半膜肌最终pH值的QTL以及影响SSC 6上L* 和B* 值的QTL,其位置和似然曲线的形状基本相同。此外,这些QTL的估计效应在4个性状之间存在很强的相关性,表明控制这些性状的基因是相同的。对于影响2种肌肉中的最终pH和滴水损失的QTL,在SSC 15上观察到类似的模式。本研究的结果将有助于精细定位和鉴定影响肉质性状的基因,紧密连锁的标记可能被纳入标记辅助选择程序。
A QTL study was performed in large half-sib families to characterize the genetic background of variation in pork quality traits as well as to examine the possibilities of including QTL in a marker-assisted selection scheme. The quality traits included ultimate pH in LM and the semimembranosus, drip loss, and the Minolta color measurements L*, a*, and b* representing meat lightness, redness, and yellowness, respectively. The families consist of 3,883 progenies of 12 Duroc boars that were evaluated to identify the QTL. The linkage map consists of 462 SNP markers on 18 porcine autosomes. Quantitative trait loci were mapped using a linear mixed model with fixed factors (sire, sex, herd, month, sow age) and random factors (polygenic effect, QTL effects, and litter). Chromosome-wide and genome-wide significance thresholds were determined by Peipho's approach, and 95% Bayes credibility intervals were estimated from a posterior distribution of the QTL position. In total, 31 QTL for the 6 meat quality traits were found to be significant at the 5% chromosome-wide level, among which 11 QTL were significant at the 5% genome-wide level and 5 of these were significant at the 0.1% genome-wide level. Segregation of the identified QTL in different families was also investigated. Most of the identified QTL segregated in 1 or 2 families. For the QTL affecting ultimate pH in LM and semimembranosus and L* and b* value on SSC6, the positions of the QTL and the shapes of the likelihood curves were almost the same. In addition, a strong correlation of the estimated effects of these QTL was found between the 4 traits, indicating that the same genes control these traits. A similar pattern was seen on SSC15 for the QTL affecting ultimate pH in the 2 muscles and drip loss. The results from this study will be helpful for fine mapping and identifying genes affecting meat quality traits, and tightly linked markers may be incorporated into marker-assisted selection programs.