Development and utilization of a SNP panel for identification of the geographic origin of <i>Cryptomeria japonica</i>

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  • UCHIYAMA Kentaro
    Department of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute
  • MATSUMOTO Asako
    Department of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute

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  • スギの遺伝的地域性識別のためのSNPパネルの開発と利用
  • スギ ノ イデンテキ チイキセイ シキベツ ノ タメ ノ SNP パネル ノ カイハツ ト リヨウ

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Abstract

Sugi, C. japonica D. Don, is the most important commercial forestry species in Japan; it has been widely planted across the whole of the country and constitutes 44% of all plantation forests. Previous large-scale genome wide analysis have detected four phylogeographic groups in this species. These genetic groups have considerable relevance to C. japonica silviculture, for example, in ensuring the use of local seed sources, that are considered to be best adapted to local environments, in afforestation and to reduce the risk of any deleterious gene flow from planted forests into remnant natural stands. In C. japonica, however, thousands of DNA markers are required to reliably detect these phylogeographic genetic groups because of its low range-wide genetic differentiation. The aim of this study was to develop a small set of SNPs, more evenly spread across the genome, which could more efficiently distinguish between the four phylogeographic groups of C. japonica. From the 2500 mapped markers of C. japonica, we selected 288SNP, which were roughly evenly spaced across the C. japonica genetic map. Conversion of these SNPs to a cost-effective and flexible throughput SNP typing system generated successful assays for 257SNPs. In order to test the utility of the resulting SNP set, genotyping was performed to determine levels of polymorphism within 234 trees representing 18 natural populations of C. japonica. The results indicate samples were clustered into the four genetic groups consistent with their geographic origin, and that SNP set developed in this study can successfully identify population structure. Furthermore, we successfully identified the origin of samples of unknown geographic origin from artificial forests in Yakushima islands. We anticipate that the genomewide SNP set reported here will be useful for evaluating the species range-wide genetic structure and identification of the geographic origin of unknown samples.

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