Identifying microsatellite molecular markers using transcriptome data mining in medicinal plant Citrullus colocynthis L.

Mutashar Jabrt Allh Alzubaidi, Zaman; Soltani Howyzeh, Mehdi

doi:10.22092/ijrfpbgr.2025.367090.1467

Identifying microsatellite molecular markers using transcriptome data mining in medicinal plant Citrullus colocynthis L.

Document Type : Research Paper

Authors

¹ M.Sc. Student, Department of Genetics, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

² Department of Genetics and Plant Breeding, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

10.22092/ijrfpbgr.2025.367090.1467

Abstract

Background and objective: Next-generation sequencing (NGS) technology offers an opportunity to analyze microsatellite molecular markers linked to terpenoid pathway genes. Microsatellite molecular markers are a powerful way to understand genetic diversity. In this study, the transcriptome sequencing of the Citrullus colocynthis medicinal plant was used for the first time to identify microsatellite markers.
Methodology: In this research, the data of the transcriptome sequencing study of the fruit of the C. colocynthis medicinal plant were used in which 83,807 de novo assembly sequences were prepared. The assembled transcripts of C. colocynthis plant were analyzed to determine the frequency and distribution of microsatellites. We searched for microsatellite markers using Krait v1.5.1, a robust and ultra-fast identification tool with a user-friendly graphical interface for genome-wide screening of microsatellites. Also, specific primers for microsatellite markers identified by Krait software were designed and saved as Fasta files. For the functional annotation and gene similarity comparison, the microsatellites of the C. colocynthis transcriptome against the microsatellites of the nucleotide sequences of the five reference genomes include Uniprot, Arabidopsis thaliana (Atha), Citrullus lanatus subsp. 97103 (Clan), Momordica charantia (Mcha) and Citrullus lanatus subsp. Charleston Gray (WCG) were blasted with E-Value less than 10e-5. In other functional interpretation, the sequences of unigenes containing microsatellites were uploaded to the KEGG automatic interpretation server (http://www.Genome.Jp/kegg/kaas) and interpreted using specific KO (KEGG Orthology) identifiers. The execution method of KO specific identifiers was based on the Single-directional Best Hit method. According to KO assignment, the information of the metabolic pathways related

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