[HTML][HTML] Genetic diversity of Indonesian cattle breeds based on microsatellite markers
Asian-Australasian journal of animal sciences, 2019•ncbi.nlm.nih.gov
Objective This research was conducted to study the genetic diversity in several Indonesian
cattle breeds using microsatellite markers to classify the Indonesian cattle breeds. Methods
A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase
chain reaction process was conducted using 12 labeled primers. The size of allele was
generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS
programs were used to obtain the observed number of alleles, effective number of alleles …
cattle breeds using microsatellite markers to classify the Indonesian cattle breeds. Methods
A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase
chain reaction process was conducted using 12 labeled primers. The size of allele was
generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS
programs were used to obtain the observed number of alleles, effective number of alleles …
Abstract
Objective
This research was conducted to study the genetic diversity in several Indonesian cattle breeds using microsatellite markers to classify the Indonesian cattle breeds.
Methods
A total of 229 DNA samples from of 10 cattle breeds were used in this study. The polymerase chain reaction process was conducted using 12 labeled primers. The size of allele was generated using the multiplex DNA fragment analysis. The POPGEN and CERVUS programs were used to obtain the observed number of alleles, effective number of alleles, observed heterozygosity value, expected heterozygosity value, allele frequency, genetic differentiation, the global heterozygote deficit among breeds, and the heterozygote deficit within the breed, gene flow, Hardy-Weinberg equilibrium, and polymorphism information content values. The MEGA program was used to generate a dendrogram that illustrates the relationship among cattle population. Bayesian clustering assignments were analyzed using STRUCTURE program. The GENETIX program was used to perform the correspondence factorial analysis (CFA). The GENALEX program was used to perform the principal coordinates analysis (PCoA) and analysis of molecular variance. The principal component analysis (PCA) was performed using adegenet package of R program.
Results
A total of 862 alleles were detected in this study. The INRA23 allele 205 is a specific allele candidate for the Sumba Ongole cattle, while the allele 219 is a specific allele candidate for Ongole Grade. This study revealed a very close genetic relationship between the Ongole Grade and Sumba Ongole cattle and between the Madura and Pasundan cattle. The results from the CFA, PCoA, and PCA analysis in this study provide scientific evidence regarding the genetic relationship between Banteng and Bali cattle. According to the genetic relationship, the Pesisir cattle were classified as Bos indicus cattle.
Conclusion
All identified alleles in this study were able to classify the cattle population into three clusters ie Bos taurus cluster (Simmental Purebred, Simmental Crossbred, and Holstein Friesian cattle); Bos indicus cluster (Sumba Ongole, Ongole Grade, Madura, Pasundan, and Pesisir cattle); and Bos javanicus cluster (Banteng and Bali cattle).
ncbi.nlm.nih.gov
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