麦类作物学报
麥類作物學報
맥류작물학보
JOURNAL OF TRITICEAE CROPS
2009年
4期
553-558
,共6页
敖雁%胡治球%汤在祥%王学枫%徐辰武
敖雁%鬍治毬%湯在祥%王學楓%徐辰武
오안%호치구%탕재상%왕학풍%서신무
双亲本杂交%相关群体%QTL作图%极大似然方法
雙親本雜交%相關群體%QTL作圖%極大似然方法
쌍친본잡교%상관군체%QTL작도%겁대사연방법
The cross of two inbred lines%Related population%QTL mapping%Maximum likelihood estimation
为了研究双亲杂交衍生的多个群体QTL作图分析的方法,对两个亲本通过任意杂交设计衍生的任意多个相关群体联合分析的方法进行了探讨.其要点是:首先利用染色体上所有标记基因型联合计算该染色体上任一假定位置QTL的条件概率,然后根据混合分布理论建立基于EM算法实现的QTL作图的极大似然估计方法.以双亲杂交衍生的F2和BC群体联合分析为例,用计算机模拟数据研究了QTL遗传力和样本容量两个因素对方法的影响.结果表明,在染色体水平模拟时,相同的遗传力下,F2和BC群体联合分析的统计功效明显高于这两个群体单独分析的统计功效.此外,即使两个群体联合分析时的样本容量与两个群体单独分析时的样本容量相等,联合分析的统计功效亦明显高于单独分析的统计功效.且随着遗传力和样本容量的提高,本方法的统计功效逐步提高.在参数估计的准确度和精确度上,相同的遗传力下,F2和BC群体联合分析普遍高于这2个群体的单独分析,尤其是在低遗传力(5%)和较少样本容量下(50),这种优势更为明显.且随着遗传力和样本容量的提高,各参数估计的准确度和精确度亦逐步提高.为了验证本方法的效用,在全基因组水平进行了模拟分析,同样得到了预期的结果.
為瞭研究雙親雜交衍生的多箇群體QTL作圖分析的方法,對兩箇親本通過任意雜交設計衍生的任意多箇相關群體聯閤分析的方法進行瞭探討.其要點是:首先利用染色體上所有標記基因型聯閤計算該染色體上任一假定位置QTL的條件概率,然後根據混閤分佈理論建立基于EM算法實現的QTL作圖的極大似然估計方法.以雙親雜交衍生的F2和BC群體聯閤分析為例,用計算機模擬數據研究瞭QTL遺傳力和樣本容量兩箇因素對方法的影響.結果錶明,在染色體水平模擬時,相同的遺傳力下,F2和BC群體聯閤分析的統計功效明顯高于這兩箇群體單獨分析的統計功效.此外,即使兩箇群體聯閤分析時的樣本容量與兩箇群體單獨分析時的樣本容量相等,聯閤分析的統計功效亦明顯高于單獨分析的統計功效.且隨著遺傳力和樣本容量的提高,本方法的統計功效逐步提高.在參數估計的準確度和精確度上,相同的遺傳力下,F2和BC群體聯閤分析普遍高于這2箇群體的單獨分析,尤其是在低遺傳力(5%)和較少樣本容量下(50),這種優勢更為明顯.且隨著遺傳力和樣本容量的提高,各參數估計的準確度和精確度亦逐步提高.為瞭驗證本方法的效用,在全基因組水平進行瞭模擬分析,同樣得到瞭預期的結果.
위료연구쌍친잡교연생적다개군체QTL작도분석적방법,대량개친본통과임의잡교설계연생적임의다개상관군체연합분석적방법진행료탐토.기요점시:수선이용염색체상소유표기기인형연합계산해염색체상임일가정위치QTL적조건개솔,연후근거혼합분포이론건립기우EM산법실현적QTL작도적겁대사연고계방법.이쌍친잡교연생적F2화BC군체연합분석위례,용계산궤모의수거연구료QTL유전력화양본용량량개인소대방법적영향.결과표명,재염색체수평모의시,상동적유전력하,F2화BC군체연합분석적통계공효명현고우저량개군체단독분석적통계공효.차외,즉사량개군체연합분석시적양본용량여량개군체단독분석시적양본용량상등,연합분석적통계공효역명현고우단독분석적통계공효.차수착유전력화양본용량적제고,본방법적통계공효축보제고.재삼수고계적준학도화정학도상,상동적유전력하,F2화BC군체연합분석보편고우저2개군체적단독분석,우기시재저유전력(5%)화교소양본용량하(50),저충우세경위명현.차수착유전력화양본용량적제고,각삼수고계적준학도화정학도역축보제고.위료험증본방법적효용,재전기인조수평진행료모의분석,동양득도료예기적결과.
Most of the current methods for QTL mapping are designed for the single segregation population derived from the cross of two inbred lines. Incorporating the existing populations derived from two parents may improve QTL mapping and QTL-based breeding programs. However, no general maximum likelihood method has been available for this strategy. In this paper, the general mapping method that can combine multiple related populations derived from two parents was proposed. Computer simulations were performed to validate the proposed method. Taking the joint analysis of F2 and BC populations for example, the results showed that: (1) under the same heritability, the method jointing two populations obtained higher power than the one treating the two populations respectively. Moreover, when the sample size of jointing analysis amounted to that of single population analysis, the statistical power of joint analysis was also higher than that of single population analysis. The same conclusion was observed in parameter estimation. Under the same heritability, the accuracy and precision of method jointing two populations were higher than that of method analyzing the population respectively, especially for those treatments with lower heritabilities and smaller sample sizes. Moreover, higher QTL heritability and larger sample sizes can lead to not only higher statistical power, but also more accurate and precise estimates. (2) A whole genome was simulated to further verify the utility of this method. Satisfactory results were also observed.