DNA BARCODING OF Adansonia digitata USING MULTI-LOCI GENE REGIONS (ITS, rbcL, rpoC1 and psbA-trnH)
DOI:
https://doi.org/10.25271/sjuoz.2025.13.3.1511Keywords:
Adansonia Digitata, BLAST, DNA Barcoding, Phylogeny, PSBA-TRNH, RBCL, Chalcones and its derivatives, NCBI, Multinomial logistic regression model; Odds ratio; categorical data analysis; maximum likelihood method; Binary variable; generalized linear models; classification., Sanger SequencingAbstract
Adansonia digitata, also known as Baobab, is a tree species endemic to Africa. It belongs to the family Malvaceae. The species holds immense economic, cultural, and scientific value worldwide. As a result, it has been introduced to other parts of the world such as India, Sri Lanka, and Australia. Despite its immense value, information on its DNA barcodes for effective identification and conservation efforts of the species is inadequate in the literature. This study aimed to molecularly characterize A. digitata found in Nigerian flora using DNA barcodes from ITS, rbcL, rpoC1, and psbA-trnH primers. DNA was isolated from young leaves, and Sanger sequencing reactions were subsequently performed. Sequences obtained from each primer were subjected to Basic Local Alignment Search Tool (BLAST) analyses conducted on the National Center for Biotechnology Information (NCBI) website. A high percentage similarity range of 98-100% was recorded. Phylogeny was inferred using the Maximum likelihood method with a bootstrap test of 1000 replications. Results revealed a successful species-level identification of A. digitata by rbcL, ITS, and PsbA-trnH primers, as the consensus clustered with identical species with 39%, 88%, and 57% bootstrap support values, respectively. The DNA barcode of A. digitata obtained from the rpoC1 primer submitted to the NCBI nucleotide database with accession number OR251003.1 is the first to be submitted to the database. The accession numbers for the rbcL, ITS, and PsbA-trnH primers are OQ694034, OP709538, and OR135362 respectively. This study provides DNA barcodes for the identification of A. digitata relevant for research, economic, and conservation endeavours.
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Copyright (c) 2025 Khadijat Abdulkareem Abdulhamid, Yakub Adebare Ajibade, Rashidat Alaba Yusuff , ABDULTOYYIB BELLO, Khalilrahman Olatunji Sidiq, Bolaji Umar Olayinka, Azeez Adebola Lateef , Isiaka Kareem, Mohammed Muazu Danzaki
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