Esposito Salvatore, D'Agostino Nunzio, Taranto Francesca, Sonnante Gabriella, Sestili Francesco, Lafiandra Domenico, De Vita Pasquale
Research Centre for Cereal and Industrial Crops (CREA-CI), CREA-Council for Agricultural Research and Economics, Foggia, Italy.
Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy.
Front Genet. 2022 Nov 22;13:1058471. doi: 10.3389/fgene.2022.1058471. eCollection 2022.
Although wheat ( L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.
虽然普通小麦(Triticum aestivum L.)是世界主要的主食作物,也是碳水化合物和蛋白质的主要来源,但功能基因组学和等位基因挖掘仍然面临巨大挑战。鉴于下一代测序(NGS)技术的进步,鉴定与目标表型相关的因果变异已变得可行。基于这些原因,在此,我们通过将序列捕获和目标富集方法与高通量NGS重测序相结合,能够在全外显子水平上扫描来自重组自交系群体的46个随机选择的面包小麦个体,并鉴定和分类大量单核苷酸多态性(SNP)。为了对结果进行技术验证,将八个随机选择的SNP转化为竞争性等位基因特异性PCR(KASP)标记。该资源被建立为一个可访问且可重复使用的用于等位基因数据挖掘的分子工具包。我们提供的数据集可用于面包小麦遗传学的新研究,并作为启动旨在改善不同关键农艺性状的育种计划的基础。