Using alignment-based methods in the phylogenetic inferencing of genus Andrographis Wall. ex Nees

Family Acanthaceae is widely known for its medicinal and economic values – one of which is genus Andrographis Wall. ex Nees. Andrographis paniculata (Burm.f.) Nees is considered most significant, given its broad range of pharmacological activities. However, the circumscription of genus Andrographis...

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Bibliographic Details
Main Author: Juaban, Ma. Loren Elena C.
Format: text
Language:English
Published: Animo Repository 2022
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Online Access:https://animorepository.dlsu.edu.ph/etdb_bio/15
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1014&context=etdb_bio
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Institution: De La Salle University
Language: English
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Summary:Family Acanthaceae is widely known for its medicinal and economic values – one of which is genus Andrographis Wall. ex Nees. Andrographis paniculata (Burm.f.) Nees is considered most significant, given its broad range of pharmacological activities. However, the circumscription of genus Andrographis is still unclear, recording different numbers of species across global databases. This study aims to analyze chloroplast gene variability within A. paniculata and between Andrographis spp. to determine a candidate gene barcode for species discrimination, and to conduct phylogenetic tree comparisons based on alignment-based methods. Among rbcL, matK, trnL-F, and trnH-psbA markers, non-coding loci, trnL-F, and psbA-trnH, exhibited higher variability. The candidate marker for genus Andrographis was the trnL-F region. Out of 18 sample Andrographis species, six were successfully discriminated across trnL-F gene trees. The Maximum Likelihood method with bootstrap support performed best, localizing 4 Andrographis spp. into separate clades. However, a single gene locus was insufficient to achieve discriminatory power for the remaining Andrographis spp. Tree topologies were also inaccurate when compared with the reference Andrographis tree and existing taxonomic keys. Utilizing multigene barcodes can further improve species-level discrimination and phylogenetic tree accuracy.