ABSTRACT
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 6.5-200â¯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. BIOLOGICAL SIGNIFICANCE: 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.
