Open AccessHierarchical Clustering on Principal Components of Microsatellite Frequency Allele Data from Indonesian Buffaloes
Author(s) -
Ferdy Saputra,
Anneke Anggraeni,
Cece Sumantri
Publication year - 2022
Publication title -
trends in sciences
Language(s) - English
Resource type - Journals
ISSN - 2774-0226
DOI - 10.48048/tis.2022.2045
Subject(s) - principal component analysis , microsatellite , genetic diversity , population , biology , allele frequency , cluster analysis , allele , indonesian , genetics , statistics , mathematics , demography , gene , linguistics , philosophy , sociology
Buffalo is a livestock that is used for meat, milk, draught animals, and religious ceremonies in Indonesia. Buffalo genetic information has not been obtained optimally for the development of buffalo breeding programs. Allele frequency is essential information to determine the genetic diversity of a population. This study investigates the use of one of the multivariate analyzes, hierarchical clustering on principal component (HCPC). The data used were microsatellite allele frequency data of 199 swamp buffaloes and 12 river buffaloes in 8 population (7 populations swamp buffalo and 1 population of river buffalo). Furthermore, the data is processed using factoextra and FactoMineR package in R 4.0.0. The results found that the ILSTS61 and ILSTS17 loci could be used as genetic markers to determine the genetic relationship of Indonesian buffalo. From the study, it is concluded that the HCPC method with allele frequency data can be used to analyze genetic relationships in Indonesian buffalo. The PC (Principle Component) value can describe which loci determines the genetic relationship.
HIGHLIGHTS
Allele frequency data can be used to determine genetic relationships among population
Principle component value can determine which the loci is influential in determining a genetic relationship
Hierarchical Clustering on Principal Components can be used to analyze genetic relationships
GRAPHICAL ABSTRACT