Institute for Sustainable Agriculture, CSIC, Córdoba, Spain.
Proteomics Facility, SCAI, University of Córdoba, Córdoba, Spain.
J Proteome Res. 2020 Mar 6;19(3):1000-1012. doi: 10.1021/acs.jproteome.9b00365. Epub 2020 Feb 10.
causes blight, one of the major diseases in pea worldwide. Cultivated pea plants have a low resistance to this disease. Although quantitative trait loci (QTLs) involved in the resistance to blight have been identified, the specific genes associated with these QTLs remain unknown, which makes marker-assisted selection difficult. Complex traits alter proteins and their abundance. Quantitative estimation of proteins in pea might therefore be useful in selecting potential markers for breeding. In this work, we developed a strategy using a combination of shotgun proteomics (viz., high performance liquid chromatography-mass spectrometry data-dependent acquisition) and data-independent acquisition (DIA) analysis, to identify putative protein markers associated with resistance to blight and explored its use for breeding selection. For this purpose, an initial list of target peptides based on proteins closely related to resistance to was compiled by using two genotypes with contrasting responses to the disease. Then, targeted data analysis (viz., shotgun proteomics-DIA) was used for constitutive quantification of the target peptides in a representative number of the recombinant inbred line population segregated for resistance as derived from a cross between the two genotypes. Finally, a peptide panel of potential markers for resistance to was built. The results thus obtained are discussed and compared with those of previous gene expression studies using the same parental pea genotypes responding to the pathogen. Also, a molecular defense mechanism against blight in pea is proposed. To the authors' knowledge, this is the first time a targeted proteomics approach based on data analysis has been used to identify peptides associated with resistance to this disease.
引起疫病，这是豌豆在世界范围内的主要疾病之一。栽培豌豆对这种疾病的抵抗力很低。尽管已经确定了与疫病抗性相关的数量性状位点（QTL），但与这些 QTL 相关的特定基因仍然未知，这使得标记辅助选择变得困难。复杂性状会改变蛋白质及其丰度。因此，对豌豆中蛋白质进行定量估计可能有助于选择潜在的标记用于育种。在这项工作中，我们开发了一种使用组合的 shotgun 蛋白质组学（即高效液相色谱-质谱数据依赖性采集）和数据独立采集（DIA）分析的策略，以鉴定与疫病抗性相关的潜在蛋白质标记，并探索其在育种选择中的应用。为此，我们使用两种对疾病反应不同的基因型，根据与疫病抗性密切相关的蛋白质，编制了一份初始目标肽列表。然后，使用靶向数据分析（即 shotgun 蛋白质组学-DIA）对来自两种基因型杂交产生的、对疫病呈分离的重组自交系群体中的代表性数量进行目标肽的组成型定量。最后，构建了一个潜在疫病抗性标记肽的面板。讨论并比较了与使用相同亲本豌豆基因型对病原体反应的先前基因表达研究的结果。此外，还提出了豌豆对疫病的分子防御机制。据作者所知，这是首次使用基于数据分析的靶向蛋白质组学方法来鉴定与这种疾病抗性相关的肽。
