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Plant Science Today (PST)

Review Articles

Early Access

Bioinformatics and computational tools for post-sequencing data analysis in DNA barcoding studies - A review

DOI
https://doi.org/10.14719/pst.6418
Submitted
30 November 2024
Published
25-06-2025
Versions

Abstract

DNA barcoding is a significant and valuable method for identifying species and it is one of the key fields of biodiversity and evolutionary research. It changed biodiversity studies with computational techniques and next-generation sequencing. Post-sequencing data analysis is an essential stage encompassing many critical procedures to ensure precise identification of organisms and their classification. Processing generated mass-sequenced information is a significant problem in any barcoding studies. Various analysis methods are employed for inferring organismal taxonomy, such as tree-based, similarity-based, composition-based and hybrid methods. This study will review the diversity of these computational methods for post-sequence data analysis in DNA barcoding studies. Tree-based techniques (e.g.: MrBayes and RAxML) illustrate evolutionary relationships among species, similarity-based techniques (e.g.: SOrt-ITEMS and BLAST) assist in identifying species by sequence similarities and composition-based techniques (e.g.: Phymm and NBC) categorize species according to their nucleotide composition. These methods are combined in hybrid approaches (e.g.: PhyScimm and RITA) to provide an in-depth investigation. Computational tools for post-sequence analysis use graphical user, command line or web-based interfaces with supervised, unsupervised, or semi-supervised machine learning approaches. Operating systems such as Linux, UNIX, Windows and macOS are used to analyze DNA barcoding data, while Java, R, Python, C/C++ and Perl are the most widely used programming languages. This review emphasizes how crucial it is to incorporate such bioinformatics and computational techniques to improve the robustness and consistency of DNA barcoding studies and provide an adequate set of tools for advanced biodiversity research.

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