Chilean Forest Institute (INFOR), Chile.
Universidad de Córdoba, Spain.
J Proteomics. 2018 Mar 20;175:95-104. doi: 10.1016/j.jprot.2018.01.005. Epub 2018 Jan 11.
Stone pine (Pinus pinea) is characterized by low differentiation of growth parameters, high phenotypic plasticity and low genetic variability; detecting its diversity in introduced Chilean populations is therefore relevant for conservation and breeding programs. Here, variability among allochthonous Stone pine populations in Chile was explored using electrophoresis-based proteomic analysis of pine nuts. Cones from 30 populations distributed along a climatic gradient in Chile were surveyed and sampled, and proteins were extracted from seed flour using the TCA-acetone precipitation protocol. Extracts were subjected to SDS-PAGE and 2-DE for protein resolution, gel images captured, and spot or bands intensity quantified and subjected to statistical analysis (ANOVA, unsupervised Hierarchical Analysis Clustering and PLS regression). Protein yield ranged among populations from 161.7 (North populations) to 298.7 (South populations) mg/g dry weight. A total of 50 bands were resolved by SDS-PAGE in the 6.5-200 kDa Mr. range, of which 17 showed quantitative or qualitative differences, with 12 proteins identified. Pine nut extracts from the most distant populations were analyzed by 2-DE and a total of 129 differential spots were observed, out of which 13 were proposed as putative protein markers of variability. Out of the 129 spots, 118 proteins were identified after MALDI-TOF/TOF analysis. Identified proteins were classified into two principal categories: reserve and stress related. We provide the first protein map of P. pinea nuts. The use of a proteomic approach was useful to detect variability of Stone pine across three Chilean macrozones, with correlations between protein profiles and geoclimatic parameters, suggesting a new approach to study the variability of this species.
This study presents the first protein map of Stone pine nuts, relevant for the advancement of protein characterization in pine nuts. Putative protein markers are proposed, evidencing that a proteomic approach may be useful to detect variability of Stone pine across Chilean macrozones, suggesting a new approach to study the variability of this species, which may also be extrapolated to other forest fruit species.
石松(Pinus pinea)的生长参数分化程度低,表型可塑性高,遗传变异性低;因此,检测其在引入智利的种群中的多样性对于保护和繁殖计划具有重要意义。在这里,通过松仁的基于电泳的蛋白质组分析探索了智利异源石松种群的变异性。对分布在智利气候梯度上的 30 个种群的锥体进行了调查和采样,并使用 TCA-丙酮沉淀法从种子粉中提取蛋白质。提取物进行 SDS-PAGE 和 2-DE 以进行蛋白质分辨率,捕获凝胶图像,并对斑点或带强度进行定量,并进行统计分析(ANOVA、无监督层次分析聚类和 PLS 回归)。种群间的蛋白质产量范围从 161.7(北部种群)到 298.7(南部种群)mg/g 干重。在 6.5-200 kDa Mr 范围内通过 SDS-PAGE 解析了 50 个条带,其中 17 个表现出定量或定性差异,鉴定出 12 种蛋白质。对来自最遥远种群的松子提取物进行 2-DE 分析,观察到总共 129 个差异斑点,其中 13 个被提议作为变异性的潜在蛋白质标记。在 MALDI-TOF/TOF 分析后,共鉴定出 129 个斑点中的 118 种蛋白质。鉴定出的蛋白质分为两类:储备和应激相关。我们提供了 P. pinea 松子的第一张蛋白质图谱。蛋白质组学方法的使用有助于检测智利三个宏观区域内石松的变异性,蛋白质图谱与地理气候参数之间存在相关性,这表明了研究该物种变异性的新方法。
本研究提供了石松子的第一张蛋白质图谱,这对于推进松子中的蛋白质特性研究具有重要意义。提出了潜在的蛋白质标记,证明蛋白质组学方法可用于检测智利宏观区域内石松的变异性,这表明了研究该物种变异性的新方法,也可推广到其他森林水果物种。