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醋栗番茄耐低磷胁迫的遗传规律分析

Genetic Analysis of Solanum pimpinellifolium Resistance to Low Phosphorus Stress
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摘要 为了研究野生醋栗番茄耐低磷胁迫的遗传规律,以耐低磷胁迫野生醋栗番茄和低磷胁迫敏感栽培番茄003为材料,通过杂交自交构建6世代(P1,P2,F1,B1,B2和F2)群体,采用植物数量性状主基因+多基因混合遗传模型方法,分析番茄缺磷症状叶遗传规律。结果表明:野生醋栗番茄LA722耐低磷胁迫遗传符合MX2-ADI-AD模型,即2对加性-显性-上位性主基因+加性-显性多基因控制。2对主基因加性效应相等且为负,显性效应均为正,且第2对主基因的显性效应大于第1对主基因,2对主基因的遗传以负向的加性效应为主,多基因的遗传以显性效应为主。B1、B2和F2群体中主基因的遗传率分别为31.44%、81.47%和78.35%,多基因遗传率均为0,环境因素为18.53%~68.56%。利用本研究结果不仅为耐低磷胁迫的育种设计奠定理论基础,同时也为耐低磷胁迫资源的挖掘和筛选提供理论依据。 In order to study the genetic regularity of resistance to low-phosphorus stress in Solanum pimpinellifolium, six generations(P1, P2, F1, B1, B2 and F2) populations were used to analyze the genetic regularity of leaves deficiency in Solanum pimpinellifolium using the main gene and polygene mixed genetic model of plant quantitative traits. The results showed that the genetic resistance of Solanum pimpinellifolium LA722 was similar to that of MX2-ADI-AD model, that is, two pairs of additive-dominance-epistatic major gene plus additivedominant polygene control. 2 had the same additive effect on the main gene, and the dominant effect was positive,and the dominant effect of the second pair of main genes was greater than that of the first pair of major genes. The inheritance of the two main genes was negative. The inheritance of main and polygene was dominant. The heritability of the main genes in the B1, B2 and F2 populations was 31.44%, 81.47% and 78.35% respectively, and the genetic rates of the polygene were 0 and the environmental factors were 18.53%~68.56%. The results of this study not only provided the theoretical basis for the breeding design of low phosphorus stress, but also provided the theoretical basis for the mining and screening of low phosphorus stress resources.
出处 《分子植物育种》 CAS CSCD 北大核心 2017年第12期5121-5127,共7页 Molecular Plant Breeding
基金 江苏省自然科学基金青年基金项目(BK20140277) 苏州市科技发展计划项目应用基础研究(SYN201418) 内蒙古自治区自然科学基金(2017MS0374)共同资助
关键词 野生醋栗番茄 耐低磷 主基因+多基因 遗传规律 Solarium pimpinellifolium, Tolerance to phosphorous, Major gene plus polygene, Genetic analysis
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