Plant improvement requires a response to selection, which can be complicated when the biochemical bases of a trait are poorly understood, difficult to measure, genetically complex, or some combination of these common obstacles. We applied nontargeted metabolomic profiling to generate a deep (but largely anonymous) dataset of potato (Solanum tuberosum L.) tubers to increase our understanding of the genetic bases for compositional traits. We examined water–methanol extracts of cooked potato tuber cores from 185 clones that had previously been single nucleotide polymorphism (SNP) genotyped by the Solanaceae Coordinated Agricultural Project (SolCAP) and detected 981 features that represent a mixture of primary metabolites, specialized metabolites, and hydrolyzed fragments of abundant proteins. Using GWASpoly, an R package that considers gene dosage through a series of genetic models, 472 features could be associated with at least one SNP marker, markedly increasing the number of marker–trait associations that have been made in potato to date. An additive genetic model detected the most associations, where 301 compositional features were associated with SNPs; in contrast, a duplex‐dominant model detected the least (160 features). Unexpectedly, SNPs associated with features were not uniformly distributed throughout the genome but were instead clustered on chromosomes 3, 7, and 8, with dozens of features associated with several small (∼2 Mbp) regions. Also interesting was that the most significant SNPs for several glycoalkaloids (α‐chaconine, β‐chaconine, and α‐solamarine)—detected on chromosomes 2, 7, and 8—are unlinked to any known glycoalkaloid biosynthetic genes.

中文翻译：

---

马铃薯块茎代谢产物组成的遗传分析：全基因组关联研究应用于非目标代谢组

植物改良需要对选择的反应，当对一个特征的生化基础了解不足，难以测量，遗传复杂或这些常见障碍的某种结合时，这可能会很复杂。我们应用了非目标代谢组学分析来生成马铃薯的深层（但主要是匿名的）数据集（马铃薯）L.）块茎，以增加我们对组成性状遗传基础的了解。我们检查了185个克隆的煮熟的马铃薯块茎核心的水-甲醇提取物，这些克隆先前由茄科农业协调计划（SolCAP）进行了单核苷酸多态性（SNP）基因分型，并检测到981种特征，这些特征代表了主要代谢物，专门代谢物和丰富蛋白质的水解片段。使用GWASpoly（一种通过一系列遗传模型考虑基因剂量的R包），可以将472个特征与至少一个SNP标记相关联，从而显着增加迄今为止在马铃薯中建立的标记与性状关联的数量。加性遗传模型检测到最多的关联，其中301个组成特征与SNP相关。相反，双工主导模型检测最少（160个特征）。出乎意料的是，与特征相关的SNP在整个基因组中分布不均匀，而是聚集在3、7和8号染色体上，数十个特征与几个小（〜2 Mbp）区域相关。同样有趣的是，在2号，7号和8号染色体上检测到的几种糖生物碱（α-查茄碱，β-查茄碱和α-茄香碱）的最显着SNP与任何已知的糖生物碱生物合成基因均无关联。