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Dev SA, Unnikrishnan R, Prathibha PS, Sijimol K, Sreekumar VB, AzharAli A, Anoop EV, Viswanath S. Artificial intelligence in timber forensics employing DNA barcode database. 3 Biotech 2023; 13:183. [PMID: 37193334 PMCID: PMC10182240 DOI: 10.1007/s13205-023-03604-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 05/03/2023] [Indexed: 05/18/2023] Open
Abstract
Extreme difficulties in species identification of illegally sourced wood with conventional tools have accelerated illicit logging activities, leading to the destruction of natural resources in India. In this regard, the study primarily focused on developing a DNA barcode database for 41 commercial timber tree species which are highly vulnerable to adulteration in south India. The developed DNA barcode database was validated using an integrated approach involving wood anatomical features of traded wood samples collected from south India. Traded wood samples were primarily identified using wood anatomical features using IAWA list of microscopic features for hardwood identification. Consortium of Barcode of Life (CBOL) recommended barcode gene regions (rbcL, matK & psbA-trnH) were employed for developing DNA barcode database. Secondly, we employed artificial intelligence (AI) analytical platform, Waikato Environment for Knowledge Analysis (WEKA) for analyzing DNA barcode sequence database which could append precision, speed, and accuracy for the entire identification process. Among the four classification algorithms implemented in the machine learning algorithm (WEKA), best performance was shown by SMO, which could clearly allocate individual samples to their respective sequence database of biological reference materials (BRM) with 100 % accuracy, indicating its efficiency in authenticating the traded timber species. Major advantage of AI is the ability to analyze huge data sets with more precision and also provides a large platform for rapid authentication of species, which subsequently reduces human labor and time. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03604-0.
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Affiliation(s)
- Suma Arun Dev
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
| | - Remya Unnikrishnan
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
- Cochin University of Science & Technology, Kochi, Kerala India
| | - P. S. Prathibha
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
| | - K. Sijimol
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
| | - V. B. Sreekumar
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
| | - A. AzharAli
- Department of Forest Products and Utilization, College of Forestry, Kerala Agricultural University, Vellanikara, Thrissur, Kerala 680654 India
| | - E. V. Anoop
- Department of Forest Products and Utilization, College of Forestry, Kerala Agricultural University, Vellanikara, Thrissur, Kerala 680654 India
| | - Syam Viswanath
- Forest Genetic & Biotechnology Division, Kerala Forest Research Institute, Peechi, Thrissur, Kerala 680653 India
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Dong S, Zhou M, Zhu J, Wang Q, Ge Y, Cheng R. The complete chloroplast genomes of Tetrastigma hemsleyanum (Vitaceae) from different regions of China: molecular structure, comparative analysis and development of DNA barcodes for its geographical origin discrimination. BMC Genomics 2022; 23:620. [PMID: 36028808 PMCID: PMC9412808 DOI: 10.1186/s12864-022-08755-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/07/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Tetrastigma hemsleyanum is a valuable traditional Chinese medicinal plant widely distributed in the subtropical areas of China. It belongs to the Cayratieae tribe, family Vitaceae, and exhibited significant anti-tumor and anti-inflammatory activities. However, obvious differences were observed on the quality of T. hemsleyanum root from different regions, requiring the discrimination strategy for the geographical origins. RESULT This study characterized five complete chloroplast (cp) genomes of T. hemsleynum samples from different regions, and conducted a comparative analysis with other representing species from family Vitaceae to reveal the structural variations, informative markers and phylogenetic relationships. The sequenced cp genomes of T. hemsleyanum exhibited a conserved quadripartite structure with full length ranging from 160,124 bp of Jiangxi Province to 160,618 bp of Zhejiang Province. We identified 112 unique genes (80 protein-coding, 28 tRNA and 4 rRNA genes) in the cp genomes of T. hemsleyanum with highly similar gene order, content and structure. The IR contraction/expansion events occurred on the junctions of ycf1, rps19 and rpl2 genes with different degrees, causing the differences of genome sizes in T. hemsleyanum and Vitaceae plants. The number of SSR markers discovered in T. hemsleyanum was 56-57, exhibiting multiple differences among the five geographic groups. Phylogenetic analysis based on conserved cp genome proteins strongly grouped the five T. hemsleyanum species into one clade, showing a sister relationship with T. planicaule. Comparative analysis of the cp genomes from T. hemsleyanum and Vitaceae revealed five highly variable spacers, including 4 intergenic regions and one protein-coding gene (ycf1). Furthermore, five mutational hotspots were observed among T. hemsleyanum cp genomes from different regions, providing data for designing DNA barcodes trnL and trnN. The combination of molecular markers of trnL and trnN clustered the T. hemsleyanum samples from different regions into four groups, thus successfully separating specimens of Sichuan and Zhejiang from other areas. CONCLUSION Our study obtained the chloroplast genomes of T. hemsleyanum from different regions, and provided a potential molecular tracing tool for determining the geographical origins of T. hemsleyanum, as well as important insights into the molecular identification approach and and phylogeny in Tetrastigma genus and Vitaceae family.
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Affiliation(s)
- Shujie Dong
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.,School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Manjia Zhou
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jinxing Zhu
- Bureau of Agricultural and Rural Affairs of Suichang, Suichang, China
| | - Qirui Wang
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yuqing Ge
- The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
| | - Rubin Cheng
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China. .,Academy of Chinese Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.
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Tracing the geographic origin of planted tropical timber Neobalanocarpus heimii (chengal) with DNA approach. CONSERV GENET RESOUR 2022. [DOI: 10.1007/s12686-022-01288-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Ng CH, Ng KKS, Lee SL, Zakaria NF, Lee CT, Tnah LH. DNA databases of an important tropical timber tree species Shorea leprosula (Dipterocarpaceae) for forensic timber identification. Sci Rep 2022; 12:9546. [PMID: 35680966 PMCID: PMC9184630 DOI: 10.1038/s41598-022-13697-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
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, Shorealeprosula 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.
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Affiliation(s)
- Chin Hong Ng
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia.
| | - Kevin Kit Siong Ng
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia
| | - Soon Leong Lee
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia
| | - Nurul-Farhanah Zakaria
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia
| | - Chai Ting Lee
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia
| | - Lee Hong Tnah
- Genetics Laboratory, Forest Research Institute Malaysia, 52109, Kepong, Selangor, Malaysia
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Lee SL, Zakaria NF, Tnah LH, Ng CH, Ng KKS, Lee CT, Lau KH, Chua LSL. DNA databases of a CITES listed species Aquilaria malaccensis (Thymelaeaceae) as the tracking tools for forensic identification and chain of custody certification. Forensic Sci Int Genet 2021; 57:102658. [PMID: 34998185 DOI: 10.1016/j.fsigen.2021.102658] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 12/20/2021] [Accepted: 12/23/2021] [Indexed: 11/04/2022]
Abstract
Aquilaria malaccensis (Thymelaeaceae) is the main source of high-grade agarwood in Southeast Asia. Aggressive collections and trade activities over the past decades have put great pressure on the natural stands and raised concerns over the long-term survival potential of A. malaccensis. Tracking and authentication of agarwood require method with a high degree of accuracy. Therefore, this study aimed to develop DNA databases of A. malaccensis as the tracking tools at species, population and individual levels for forensic identification and chain of custody certification. Using two cpDNA (rbcL and matK) and an rDNA (ITS2) markers, species identification database of Aquilaria was developed to distinguish A. malaccensis from A. hirta, A. microcarpa, A. beccariana, A. crassna, A. sinensis and A. rostrata. In addition, based on 35 populations of A. malaccensis throughout Peninsular Malaysia, cpDNA haplotype and STR allele frequency databases were developed for population and individual identification. A haplotype distribution map based on 29 haplotypes derived from seven cpDNA showed that the A. malaccensis in Peninsular Malaysia can be associated to Kedah-Perak and Kelantan-Johor regions. Similarly, genetic relatedness and Bayesian clustering analyses based on 10 STR markers also divided the 35 populations into two main genetic clusters, corresponding to Kedah-Perak and Kelantan-Johor regions. The STR allele frequency databases were established and characterized according to these two regions. To determine the performance of the STR allele frequency databases for population identification, independent self-assignment tests showed that the percentage of individuals correctly assigned into the origin population was 93.88% in Kedah-Perak and 90.29% in Kelantan-Johor. For the STR allele frequency databases to be used for individual identification, conservativeness tests showed that the θ should be adjusted to 0.250 and 0.200 in the Kedah-Perak and Kelantan-Johor databases, respectively. To ensure consistency in allele calling for the dinucleotide repeat loci across different electrophoretic platforms or laboratories, allelic ladders have been developed for the 10 STR loci. Two case studies are presented of how these databases were used to track A. malaccensis to the origin population and stump. These databases are ready to be used to provide admissible forensic evidence for legal proceedings against the illegal harvesters of agarwood and for agarwood certification to meet the consumer country regulations.
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Affiliation(s)
- Soon Leong Lee
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Nurul-Farhanah Zakaria
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Lee Hong Tnah
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Chin Hong Ng
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Kevin Kit Siong Ng
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Chai Ting Lee
- Genetics Laboratory, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Kah Hoo Lau
- Forest Health and Conservation Programme, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
| | - Lillian Swee Lian Chua
- Forest Health and Conservation Programme, Forest Research Institute Malaysia, 52109 Kepong, Selangor Darul Ehsan, Malaysia.
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