摘要
【目的】通过Meta分析,利用数学模型整合与优化猪后腿腿臀质量、腿臀肉质量和腿臀比性状的QTL,提高QTL定位的准确度和有效性,为猪后腿性状QTL的精细定位和分子辅助育种奠定基础。【方法】收集猪后腿腿臀质量,腿臀肉质量和腿臀比性状的QTL及其相关信息,利用BioMercator2.1,将原始QTL映射到美国肉畜研究中心(USDA-MARC 2.0)公布的猪遗传连锁图谱,构建新的整合图谱,分析得到QTL簇。进一步对各QTL簇进行Meta分析,定位"真实"QTL(MQTL),缩短95%置信区间,减少定位误差。【结果】收集了93个猪后腿性状的QTL及其相关信息,经比对、映射,构建了新的整合图谱,发现19个QTL簇。通过Meta分析,得到19个MQTL,其图距比原平均图距缩短16.19%～78.96%,其中,MQTL1、MQTL5、MQTL6、MQTL8、MQTL9、MQTL10、MQTL11、MQTL12和MQTL17等9个MQTL图距的缩短比例均超过50%。【结论】Meta分析得到的MQTL图距均有不同程度缩短,最小的仅1.75cM,缩短比例最大可达78.96%,提高了QTL定位的准确度和有效性。
【Objective】 A meta-analysis was conducted for the Quantitative Trait Loci（QTL） related to ham traits to estimate the number and refine the positions of QTL.【Method】 An integrated map of ham weight QTL in swine was established with the swine linkage map of USDA-MARC 2.0 as a reference map.With the software BioMercator2.1,information of QTL was collected and projected to the reference map.Meta-QTL were obtained by meta-analysis which reduced the QTL confidence intervals compared to individual QTL estimates.【Result】 93 ham traits QTL were collected from 36 published papers.19 meta-QTL as well as their corresponding markers were obtained.The confidence intervals and the number of QTL were reduced compared to the QTL before the meta-analysis.The reduction in the confidence interval ranged from 16.19% to 78.96%.For instance,the confidence interval of MQTL1,MQTL6,MQTL9,MQTL12 was only 5.81 cM,1.75 cM,2.88 cM,8.94 cM,respectively.【Conclusion】 The confidence interval of meta-QTL was narrowed down by as much as 78.96% compared to that before the meta-analysis.The minimum confidence interval shrank to 1.75 cM in SSC4,with the marker SW714 on the left and the marker SW1996 on the right.These results could lead to more precise QTL position estimates,and offered a basis for gene mining and molecular breeding in swine.
出处
《西北农林科技大学学报（自然科学版）》
CSCD
北大核心
2012年第4期31-37,共7页
Journal of Northwest A&F University(Natural Science Edition)
基金
辽宁省科技厅科学计划项目(2011408004)
辽宁医学院青年科技启动基金项目(Y2011Z024)
