Paterson A H, Damon S, Hewitt J D, Zamir D, Rabinowitch H D, Lincoln S E, Lander E S, Tanksley S D
Department of Plant Breeding and Biometry, Cornell University, Ithaca, New York 14853.
Genetics. 1991 Jan;127(1):181-97. doi: 10.1093/genetics/127.1.181.
As part of ongoing studies regarding the genetic basis of quantitative variation in phenotype, we have determined the chromosomal locations of quantitative trait loci (QTLs) affecting fruit size, soluble solids concentration, and pH, in a cross between the domestic tomato (Lycopersicon esculentum Mill.) and a closely-related wild species, L. cheesmanii. Using a RFLP map of the tomato genome, we compared the inheritance patterns of polymorphisms in 350 F2 individuals with phenotypes scored in three different ways: (1) from the F2 progeny themselves, grown near Davis, California; (2) from F3 families obtained by selfing each F2 individual, grown near Gilroy, California (F3-CA); and (3) from equivalent F3 families grown near Rehovot, Israel (F3-IS). Maximum likelihood methods were used to estimate the approximate chromosomal locations, phenotypic effects (both additive effects and dominance deviations), and gene action of QTLs underlying phenotypic variation in each of these three environments. A total of 29 putative QTLs were detected in the three environments. These QTLs were distributed over 11 of the 12 chromosomes, accounted for 4.7-42.0% of the phenotypic variance in a trait, and showed different types of gene action. Among these 29 QTLs, 4 were detected in all three environments, 10 in two environments, and 15 in only a single environment. The two California environments were most similar, sharing 11/25 (44%) QTLs, while the Israel environment was quite different, sharing 7/20 (35%) and 5/26 (19%) QTLs with the respective California environments. One major goal of QTL mapping is to predict, with maximum accuracy, which individuals will produce progeny showing particular phenotypes. Traditionally, the phenotype of an individual alone has been used to predict the phenotype of its progeny. Our results suggested that, for a trait with low heritability (soluble solids), the phenotype of F3 progeny could be predicted more accurately from the genotype of the F2 parent at QTLs than from the phenotype of the F2 individual. For a trait with intermediate heritability (fruit pH), QTL genotype and observed phenotype were about equally effective at predicting progeny phenotype. For a trait with high heritability (mass per fruit), knowing the QTL genotype of an individual added little if any predictive value, to simply knowing the phenotype. The QTLs mapped in the L. esculentum X L. cheesmanii F2 appear to be at similar locations to many of those mapped in a previous cross with a different wild tomato (L. chmielewskii).(ABSTRACT TRUNCATED AT 400 WORDS)
作为正在进行的关于表型数量变异遗传基础研究的一部分,我们确定了影响果实大小、可溶性固形物浓度和pH值的数量性状基因座(QTL)在栽培番茄(Lycopersicon esculentum Mill.)与近缘野生种L. cheesmanii杂交后代中的染色体位置。利用番茄基因组的RFLP图谱,我们比较了350个F2个体中多态性的遗传模式与以三种不同方式评分的表型:(1)来自在加利福尼亚州戴维斯附近种植的F2后代本身;(2)来自通过使每个F2个体自交获得的F3家系,在加利福尼亚州吉尔罗伊附近种植(F3-CA);(3)来自在以色列雷霍沃特附近种植的等效F3家系(F3-IS)。采用最大似然法估计了这三种环境中每个环境下表型变异潜在的QTL的大致染色体位置、表型效应(加性效应和显性偏差)以及基因作用。在这三种环境中总共检测到29个假定的QTL。这些QTL分布在12条染色体中的11条上,占某一性状表型变异的4.7 - 42.0%,并表现出不同类型的基因作用。在这29个QTL中,4个在所有三种环境中都被检测到,10个在两种环境中被检测到,15个仅在单一环境中被检测到。加利福尼亚的两种环境最为相似,共享11/25(44%)的QTL,而以色列环境差异较大,与相应的加利福尼亚环境分别共享7/20(35%)和5/26(19%)的QTL。QTL定位的一个主要目标是以最大的准确性预测哪些个体将产生表现出特定表型的后代。传统上,仅使用个体的表型来预测其后代的表型。我们的结果表明,对于遗传力低的性状(可溶性固形物),从F2亲本在QTL处的基因型预测F3后代的表型比从F2个体的表型更准确。对于遗传力中等的性状(果实pH值),QTL基因型和观察到的表型在预测后代表型方面效果大致相同。对于遗传力高的性状(单果质量),了解个体的QTL基因型对于简单地了解表型几乎没有增加预测价值。在L. esculentum×L. cheesmanii F2中定位的QTL似乎与之前与另一种野生番茄(L. chmielewskii)杂交中定位的许多QTL位于相似位置。(摘要截断于400字)