Analisis Mutasi dan Pohon Filogenetik pada Varian SARS-CoV-2 Menggunakan Metode UPGMA, Neighbor-Joining, dan Maksimum Parsimony

Rahmawati, Rizka Ayu (2025) Analisis Mutasi dan Pohon Filogenetik pada Varian SARS-CoV-2 Menggunakan Metode UPGMA, Neighbor-Joining, dan Maksimum Parsimony. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

SARS-CoV-2 merupakan virus penyebab pandemi COVID-19 yang dimulai pada akhir 2019 telah mengalami mutasi yang menghasilkan lebih dari 4000 varian. Varian-varian ini diklasifikasikan berdasarkan potensi transmisinya menjadi Variants of Concern (VOC), Variants of Interest (VOI), dan Variants Under Monitoring (VUM). Penelitian ini bertujuan untuk menganalisis pohon filogenetik varian SARS-CoV-2 guna memahami kemiripan dan perbedaan genetik antar varian berdasarkan sekuens genomnya. Metode berbasis jarak seperti UPGMA dan Neighbor-Joining (NJ), serta metode berbasis karakter Maksimum Parsimony, digunakan untuk membangun pohon filogenetik. Penelitian ini memanfaatkan data sekuens genom SARS-CoV-2 dari berbagai varian yang tersedia di GenBank. Pensejajaran sekuens dilakukan menggunakan Clustal Omega, yang memungkinkan analisis cepat dan akurat terhadap data sekuens panjang. Hasil penelitian menunjukkan bahwa analisis filogenetik mampu mengidentifikasi mutasi dari genom refensi Wuhan-Hu-1 hingga varian terbaru seperti Omicron, memberikan wawasan penting tentang dinamika evolusi SARS-CoV-2.
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SARS-CoV-2 is the virus that causes the COVID-19 pandemic which started at the end of 2019 and has undergone mutations that have produced more than 4000 variants. These variants are classified based on their transmission potential into Variants of Concern (VOC), Variants of Interest (VOI), and Variants Under Monitoring (VUM). This research aims to analyze the phylogenetic tree of SARS-CoV-2 variants to understand the genetic similarities and differences between variants based on their genome sequences. Distance-based methods such as UPGMA and Neighbor-Joining (NJ), as well as the character-based method Maximum Parsimony, are used to construct phylogenetic trees. This research utilizes SARS-CoV-2 genome sequence data from various variants available in GenBank. Sequence alignment was performed using Clustal Omega, which allows fast and accurate analysis of long sequence data. The results showed that phylogenetic analysis could identify mutations from the Wuhan-Hu-1 reference genome to newer variants such as Omicron, providing important insights into the evolutionary dynamics of SARS-CoV-2.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	SARS-CoV-2, Mutasi, Pohon Filogenetik, UPGMA, Neighbor-Joining, Maksimum Parsimony, SARS-CoV-2, Mutation, Phylogenetic Tree, UPGMA, Neighbor-Joining, Maximum Parsimony
Subjects:	Q Science > QA Mathematics > QA76.9 Computer algorithms. Virtual Reality. Computer simulation. Q Science > QH Biology > QH426 Genetics R Medicine > RA Public aspects of medicine
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44101-(S2) Master Thesis
Depositing User:	Rizka Ayu Rahmawati
Date Deposited:	03 Feb 2025 02:34
Last Modified:	03 Feb 2025 02:34
URI:	http://repository.its.ac.id/id/eprint/117671

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