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麦芽大麦收获前发芽的QTL与环境建模

QTL x environment modeling of malting barley preharvest sprouting.

作者信息

Sweeney Daniel W, Kunze Karl H, Sorrells Mark E

机构信息

Plant Breeding and Genetics Section, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, 14853, USA.

出版信息

Theor Appl Genet. 2022 Jan;135(1):217-232. doi: 10.1007/s00122-021-03961-5. Epub 2021 Oct 11.

Abstract

HvMKK3 alleles are temperature sensitive and are major contributors to environmental stability of preharvest sprouting in barley. Preharvest sprouting (PHS) can severely damage barley (Hordeum vulgare L.) malting quality, but PHS resistance is often negatively correlated with malting quality. Seed dormancy is closely related to PHS. Increased temperature during grain fill can decrease seed dormancy in barley, but genetic components of seed dormancy temperature sensitivity are poorly understood. Six years of PHS data were used to fit quantitative trait locus (QTL) x environment mixed models incorporating marker data from seed dormancy genes HvAlaAT1, HvGA20ox1, and HvMKK3 and weather covariates in spring and winter two-row malting barley. Variation in winter barley PHS was best modeled by average temperature range during grain fill and spring barley PHS by total precipitation during grain fill. Average high temperature during grain fill also accurately modeled PHS for both datasets. A highly non-dormant HvMKK3 allele determined baseline PHS susceptibility and HvAlaAT1 interactions with multiple HvMKK3 alleles conferred environmental sensitivity. Polygenic variation for PHS within haplotype was detected. Residual genotype and QTL by environment interaction variance indicated additional environmental and genetic factors involved in PHS. These models provide insight into genotype and environmental regulation of barley seed dormancy, a method for PHS forecasting, and a tool for breeders to improve PHS resistance.

摘要

HvMKK3等位基因对温度敏感,是影响大麦收获前发芽环境稳定性的主要因素。收获前发芽(PHS)会严重损害大麦(Hordeum vulgare L.)的制麦品质,但抗PHS能力通常与制麦品质呈负相关。种子休眠与PHS密切相关。灌浆期温度升高会降低大麦种子休眠,但对种子休眠温度敏感性的遗传成分了解甚少。利用六年的PHS数据拟合数量性状位点(QTL)×环境混合模型,该模型纳入了来自种子休眠基因HvAlaAT1、HvGA20ox1和HvMKK3的标记数据以及春、冬二棱制麦大麦的气象协变量。冬大麦PHS的变化最好用灌浆期平均温度范围来模拟,春大麦PHS用灌浆期总降水量来模拟。灌浆期平均高温也能准确模拟两个数据集的PHS。一个高度非休眠的HvMKK3等位基因决定了PHS的基线敏感性,HvAlaAT1与多个HvMKK3等位基因的相互作用赋予了环境敏感性。检测到单倍型内PHS的多基因变异。残差基因型和QTL与环境的互作方差表明,PHS还涉及其他环境和遗传因素。这些模型为大麦种子休眠的基因型和环境调控提供了见解,为PHS预测提供了一种方法,也为育种者提高PHS抗性提供了一个工具。

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