Population connectivity and genetic diversity population connectivity of Rabbitfish (Siganus canaliculatus) among Bangladesh, China and Indonesia

Abstract

Population genetics studies genetic variation involving gene and allele frequencies in spatial and temporal space. Genetic information can be used in conservation management through identification of phylogenetic tree reconstructions, genetic distance, genetic structure, and haplotype connectivity to maintain population existence. The samples used were primary genetic data of Siganus canaliculatus taken from Indonesian waters and secondary data accessed from the BOLD SYSTEM database from several locations, namely Indonesia, China, and Bangladesh. This research was conducted to determine the kinship of Siganus canaliculatus in Indonesia, China, and Bangladesh through genetic analysis. The results of genetic distance analysis showed that the baronang fish samples from China and Bangladesh had a close relationship with a value of 0.0534 while samples from Indonesia and Bangladesh had the farthest relationship with a value of 0.8212. Reconstruction of the phylogeny tree at maximum likelihood can show convergence within the same clade. The results of the reconstruction of the phylogeny tree showed that the species from Ambon, Bali, and Lombok came from the same clade while samples from Bangladesh had different clades with the furthest distance. The results of structural analysis and genetic diversity showed that samples from Bangladesh, China, and Indonesia had different DNA characteristics. This is correlated with the form of network integration in haplotype connectivity analysis.

A Hamilton Path-Based Approach to DNA Sequence Analysis

“…In this research, we have discussed Hamiltonian pathways applications in DNA and protein sequencing. DNA sequencing determines the order of nucleotides in a DNA molecule [17]. There are multiple justifications for the importance of exploring Hamiltonian paths and their characteristics.…”

“…DNA sequencing involves a tricky issue regarding the best way to visit each DNA fragment in a particular set. When using high-throughput sequencing methods like Next-Generation Sequencing (NGS) to assemble a genome from short DNA sequences [16], arranging the complete sequence means putting together each individual fragment in the most efficient manner. In short, determining the optimal path or visit order of DNA fragments is a general challenge in this field.…”