Dataset Information

DNA databases of an important tropical timber tree species Shorea leprosula (Dipterocarpaceae) for forensic timber identification.

ABSTRACT: International timber trade communities are increasingly demanding that timber in the wood supply chain be sourced from sustainably harvested forests and certified plantations. This is to combat illegal logging activities to prevent further depletion of our precious forests worldwide. Hence, timber tracking tools are important to support law enforcement officials in ensuring only sustainably harvested timbers are traded in the market. In this study, we developed chloroplast DNA (cpDNA) and simple sequence repeat (SSR) databases as tracking tools for an important tropical timber tree species, Shorea leprosula from Peninsular Malaysia. A total of 1410 individual trees were sampled from 44 natural populations throughout Peninsular Malaysia. Four cpDNA regions were used to generate a cpDNA haplotype database, resulting in a haplotype map comprising 22 unique haplotypes derived from 28 informative intraspecific variable sites. This cpDNA database can be used to trace the origin of an unknown log at the regional level. Ten SSR loci were used to develop the SSR allele frequency database. Bayesian cluster analysis divided the 44 populations into two genetic clusters corresponding to Region A and Region B. Based on conservativeness evaluation of the SSR databases for individual identification, the coancestry coefficients (θ) were adjusted to 0.1900 and 0.1500 for Region A and B, respectively. These databases are useful tools to complement existing timber tracking systems in ensuring only legally sourced timbers are allowed to enter the wood supply chain.

SUBMITTER: Ng CH

PROVIDER: S-EPMC9184630 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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DNA databases of an important tropical timber tree species Shorea leprosula (Dipterocarpaceae) for forensic timber identification.

Ng Chin Hong CH Ng Kevin Kit Siong KKS Lee Soon Leong SL Zakaria Nurul-Farhanah NF Lee Chai Ting CT Tnah Lee Hong LH

Scientific reports 20220609 1

International timber trade communities are increasingly demanding that timber in the wood supply chain be sourced from sustainably harvested forests and certified plantations. This is to combat illegal logging activities to prevent further depletion of our precious forests worldwide. Hence, timber tracking tools are important to support law enforcement officials in ensuring only sustainably harvested timbers are traded in the market. In this study, we developed chloroplast DNA (cpDNA) and simple ...[more]

PMID: 35680966

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Project description:IntroductionShorea macrophylla is a commercially important tropical tree species grown for timber and oil. It is amenable to plantation forestry due to its fast initial growth. Genomic selection (GS) has been used in tree breeding studies to shorten long breeding cycles but has not previously been applied to S. macrophylla.MethodsTo build genomic prediction models for GS, leaves and growth trait data were collected from a half-sib progeny population of S. macrophylla in Sari Bumi Kusuma forest concession, central Kalimantan, Indonesia. 18037 SNP markers were identified in two ddRAD-seq libraries. Genomic prediction models based on these SNPs were then generated for diameter at breast height and total height in the 7th year from planting (D7 and H7).Results and discussionThese traits were chosen because of their relatively high narrow-sense genomic heritability and because seven years was considered long enough to assess initial growth. Genomic prediction models were built using 6 methods and their derivatives with the full set of identified SNPs and subsets of 48, 96, and 192 SNPs selected based on the results of a genome-wide association study (GWAS). The GBLUP and RKHS methods gave the highest predictive ability for D7 and H7 with the sets of selected SNPs and showed that D7 has an additive genetic architecture while H7 has an epistatic genetic architecture. LightGBM and CNN1D also achieved high predictive abilities for D7 with 48 and 96 selected SNPs, and for H7 with 96 and 192 selected SNPs, showing that gradient boosting decision trees and deep learning can be useful in genomic prediction. Predictive abilities were higher in H7 when smaller number of SNP subsets selected by GWAS p-value was used, However, D7 showed the contrary tendency, which might have originated from the difference in genetic architecture between primary and secondary growth of the species. This study suggests that GS with GWAS-based SNP selection can be used in breeding for non-cultivated tree species to improve initial growth and reduce genotyping costs for next-generation seedlings.

Dataset Information

DNA databases of an important tropical timber tree species Shorea leprosula (Dipterocarpaceae) for forensic timber identification.

Publications

DNA databases of an important tropical timber tree species Shorea leprosula (Dipterocarpaceae) for forensic timber identification.

Similar Datasets

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