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奶牛性状遗传效应的分布与定位

Distribution and location of genetic effects for dairy traits.

作者信息

Cole J B, VanRaden P M, O'Connell J R, Van Tassell C P, Sonstegard T S, Schnabel R D, Taylor J F, Wiggans G R

机构信息

Animal Improvement Programs Laboratory, ARS, USDA, Beltsville, MD 20705-2350, USA.

出版信息

J Dairy Sci. 2009 Jun;92(6):2931-46. doi: 10.3168/jds.2008-1762.

Abstract

Genetic effects for many dairy traits and for total economic merit are evenly distributed across all chromosomes. A high-density scan using 38,416 single nucleotide polymorphism markers for 5,285 bulls confirmed 2 previously known major genes on Bos taurus autosomes (BTA) 6 and 14 but revealed few other large effects. Markers on BTA18 had the largest effects on calving ease, several conformation traits, longevity, and total merit. Prediction accuracy was highest using a heavy-tailed prior assuming that each marker had an effect on each trait, rather than assuming a normal distribution of effects as in a linear model, or that only some loci have nonzero effects. A prior model combining heavy tails with finite alleles produced results that were intermediate compared with the individual models. Differences between models were small (1 to 2%) for traits with no major genes and larger for heavy tails with traits having known quantitative trait loci (QTL; 6 to 8%). Analysis of bull recessive codes suggested that marker effects from genomic selection may be used to identify regions of chromosomes to search in detail for candidate genes, but individual single nucleotide polymorphisms were not tracking causative mutations with the exception of diacylglycerol O-acyltransferase 1. Additive genetic merits were constructed for each chromosome, and the distribution of BTA14-specific estimated breeding value (EBV) showed that selection primarily for milk yield has not changed the distribution of EBV for fat percentage even in the presence of a known QTL. Such chromosomal EBV also may be useful for identifying complementary mates in breeding programs. The QTL affecting dystocia, conformation, and economic merit on BTA18 appear to be related to calf size or birth weight and may be the result of longer gestation lengths. Results validate quantitative genetic assumptions that most traits are due to the contributions of a large number of genes of small additive effect, rather than support the finite locus model.

摘要

许多奶牛性状和总经济价值的遗传效应在所有染色体上均匀分布。对5285头公牛使用38416个单核苷酸多态性标记进行的高密度扫描证实了牛常染色体(BTA)6和14上2个先前已知的主要基因,但几乎没有发现其他大的效应。BTA18上的标记对产犊难易度、几个体型性状、寿命和总价值影响最大。使用重尾先验假设每个标记对每个性状都有影响时预测准确性最高,而不是像线性模型那样假设效应呈正态分布,或者仅假设一些位点有非零效应。将重尾与有限等位基因相结合的先验模型产生的结果介于各个模型之间。对于没有主要基因的性状,模型之间的差异较小(1%至2%),而对于有已知数量性状位点(QTL)的性状,重尾模型之间的差异较大(6%至8%)。对公牛隐性编码的分析表明,基因组选择的标记效应可用于识别染色体区域,以便详细搜索候选基因,但除二酰基甘油O-酰基转移酶1外,单个单核苷酸多态性并未追踪到致病突变。为每条染色体构建了加性遗传价值,BTA14特异性估计育种值(EBV)的分布表明,即使存在已知的QTL,主要选择产奶量也并未改变脂肪百分比的EBV分布。这种染色体EBV也可能有助于在育种计划中识别互补的配偶。BTA18上影响难产、体型和经济价值的QTL似乎与犊牛大小或出生体重有关,可能是妊娠期较长的结果。结果验证了数量遗传学假设,即大多数性状是由大量具有小加性效应的基因贡献所致,而不支持有限位点模型。

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