The aim of the project is to estimate the adaptive potential of forest tree species, in order to enable the development of strategies to improve adaptability and resilience of declining forest genetic resources.
Our approach aims at studying local adaptation in species belonging to the genus Fagus, Sorbus and Juniperus along altitudinal gradients, thus mirroring, with the space-for-time substitution, possible climate change scenarios at regional scale. It aims not only at elucidating the genetic structure and population dynamics along altitude, but also to estimate the function and behavior of genes linked to environmental selection among three related species growing in Japan (F. crenata, S. commixta and J. communis var. nipponica) and Italy (F. sylvatica, S. aucuparia and J. communis), which have different biogeography and demographic history.
For each species, three mountain ranges will be identified, comprising the distribution areas in both countries and each site will be divided into three altitudinal zones (high, medium and low). At each altitude a population will be identified and the leaves of 24 individuals will be collected.
The DNA extracted from each sample will be genotyped with Single Nucleotide Polymorphisms (SNP) markers by means of Single Primer Enrichment Technology (SPET) to search for gene variants related to local adaptation, taking advantage of the most recent high-throughput genotyping platforms.
The species of the genus Fagus and Sorbus will be genotyped with SNP markers developed within the framework of the latest European projects (H2020-GenTree, H2020-Forgenius), in which the Italian research group is involved. Regarding the genus Juniperus, for which very few genomic resources are available, one of the objectives of the project is to obtain the whole transcriptome sequence, thus developing a new database of SNP markers.
Population genomics analysis on the selected forest tree species will result in:
1. studying genetic diversity and genetic structure distributed along horizontal and vertical axes;
2. studying the history of population dynamics, such as estimating the time of population main demographic events in each elevation range;
3. discovering of altitude-related adaptive genetic variation.