Regions of the genome that affect grain and malt quality in a North American two-row barley cross
Regions of the genome that affect grain and malt quality in a North American two-row barley cross
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DOI：
10.2135/cropsci1997.0011183x003700020039x
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发表时间：
1997-03-01
期刊：
影响因子：
2.3
通讯作者：
Kasha, KJ
中科院分区：
文献类型：
--
作者：
Mather, DE;Tinker, NA;Kasha, KJ
制麦芽是大麦的重要最终用途。大麦是否适合制麦芽取决于许多质量特性，所有这些特性都受到遗传和环境变异的影响，其中许多特性是相互关联的。在这里，我们的目标是使用基因组定位，以提高知识的遗传基础上的变化和协变的谷物和麦芽品质特征。对两行大麦杂交“Harrington”/“TR 306”的亲本和双单倍体后代在6个田间环境中产生的籽粒进行了籽粒灌浆、籽粒重量、籽粒蛋白质、细磨提取物、细粗差、可溶性蛋白质、提取物β-葡聚糖、提取物粘度、糖化力和α-淀粉酶活性测定。利用127个作图标记和两种QTL分析方法（简单区间作图（SIM）和简化复合区间作图（SIM））检测了数量性状位点和QTL与环境的互作。每个性状受2 ~ 4个主要QTL（同时使用SIM和sCIM检测的QTL）和相似数量的次要QTL（仅使用SIM或sCIM中的一个检测的QTL）影响。总的来说，这些QTL解释了每个性状21%至67%的表型方差。这些QTL的数量、效应和相对位置与数量性状的分布和性状间的相关性一致。除第2号染色体外，所有染色体都含有至少一个重要QTL的区域。几个基因组区域影响多个性状。大多数QTL与环境互作，但许多QTL表现出足够的一致性，它们可能作为标记辅助选择的目标。这里检测到的QTL位置与之前在代表其他种质群的杂交中针对相同性状检测到的QTL位置几乎没有相似性。
Malting is an important end use of barley (Hordeum vulgare L.). The suitability of barley for malting depends on numerous quality characteristics, all of which are affected by genetic and environmental variation and many of which are inter-related. Here, our objective was to use genome mapping to improve knowledge about the genetic basis for variation and covariation in grain and malt quality characteristics. Kernel plumpness, kernel weight, grain protein, fine-grind extract, fine-coarse difference, soluble protein, extract beta P-glucan, extract viscosity, diastatic power, and alpha-amylase activity were measured on grain produced in six field environments, from parents and doubled-haploid progeny of a two-row barley cross, 'Harrington'/'TR306'. Quantitative trait loci and QTL x environment interactions were detected by means of 127 mapped markers and two methods of QTL analysis: simple interval mapping (SIM) and simplified composite interval mapping (SIM). Each trait was affected by two to four primary QTL (those detected using both SIM and sCIM) and similar numbers of secondary QTL (those detected by only one of SIM or sCIM). Together, these QTL explained 21 to 67% of the phenotypic variance per trait. The numbers, effects, and relative positions of these QTL were in concordance with the quantitative trait distributions and with correlations among traits. All chromosomes, except chromosome 2, contained regions with at least one important QTL. Several genomic regions affected multiple traits. Most QTL interacted with environment, but many showed effects consistent enough that they might serve as targets for marker-assisted selection. There was little similarity in the QTL positions detected here and those detected previously for the same traits in crosses representing other germplasm groups.