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      Genetic diversity of Indonesian cattle breeds based on microsatellite markers


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          This research was conducted to study the genetic diversity in several Indonesian cattle breeds using microsatellite markers to classify the Indonesian cattle breeds.


          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.


          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.


          All identified alleles in this study were able to classify the cattle population into three clusters i.e. 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).

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          Most cited references26

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          convert: A user-friendly program to reformat diploid genotypic data for commonly used population genetic software packages

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            Genetic differentiation of eastern wolves in Algonquin Park despite bridging gene flow between coyotes and grey wolves.

            Distinguishing genetically differentiated populations within hybrid zones and determining the mechanisms by which introgression occurs are crucial for setting effective conservation policy. Extensive hybridization among grey wolves (Canis lupus), eastern wolves (C. lycaon) and coyotes (C. latrans) in eastern North America has blurred species distinctions, creating a Canis hybrid swarm. Using complementary genetic markers, we tested the hypotheses that eastern wolves have acted as a conduit of sex-biased gene flow between grey wolves and coyotes, and that eastern wolves in Algonquin Provincial Park (APP) have differentiated following a history of introgression. Mitochondrial, Y chromosome and autosomal microsatellite genetic data provided genotypes for 217 canids from three geographic regions in Ontario, Canada: northeastern Ontario, APP and southern Ontario. Coyote mitochondrial DNA (mtDNA) haplotypes were common across regions but coyote-specific Y chromosome haplotypes were absent; grey wolf mtDNA was absent from southern regions, whereas grey wolf Y chromosome haplotypes were present in all three regions. Genetic structuring analyses revealed three distinct clusters within a genetic cline, suggesting some gene flow among species. In APP, however, 78.4% of all breeders and 11 of 15 known breeding pairs had assignment probability of Q0.8 to the Algonquin cluster, and the proportion of eastern wolf Y chromosome haplotypes in APP breeding males was higher than expected from random mating within the park (P<0.02). The data indicate that Algonquin wolves remain genetically distinct despite providing a sex-biased genetic bridge between coyotes and grey wolves. We speculate that ongoing hybridization within the park is limited by pre-mating reproductive barriers.
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              Power and sample size for nested analysis of molecular variance.

              Analysis of molecular variance (AMOVA) is a widely used tool for quantifying the contribution of various levels of population structure to patterns of genetic variation. Implementations of AMOVA use permutation tests to evaluate null hypotheses of no population structure within groups and between groups. With few populations per group, between-group structure might be impossible to detect because only a few permutations of the sampled populations are possible. In fact, with fewer than six total populations, permutation tests will never result in P-values <0.05 for higher-level population structure. I present minimum numbers of replicates calculated from multinomial coefficients and an r script that can be used to evaluate the minimum P-value for any sampling scheme. While it might seem counterintuitive that a large sample of individuals is uninformative about hierarchical structure, the power to detect between-group differences depends on the number of populations per group and investigators should sample appropriately.

                Author and article information

                Asian-Australas J Anim Sci
                Asian-australas. J. Anim. Sci
                Asian-Australasian Journal of Animal Sciences
                Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST)
                April 2019
                27 August 2018
                : 32
                : 4
                : 467-476
                [1 ]Research Center for Biotechnology-Indonesian Institute of Sciences, Cibinong 16911, West Java, Indonesia
                [2 ]Laboratory of Genetics Indonesia, Cikarang Technopark, Bekasi, West Java 17550, Indonesia
                [3 ]Research Center for Biology-Indonesian Institute of Sciences, Cibinong 16911, West Java, Indonesia
                [4 ]Faculty of Animal Science, Bogor Agricultural University, Darmaga Campus, Bogor 16680, Indonesia
                Author notes
                [* ]Corresponding Author: Paskah Partogi Agung, Tel: +62-21-875-4587, Fax: +62-21-875-4588, E-mail: paskah_partogi@ 123456yahoo.com
                Copyright © 2019 by Asian-Australasian Journal of Animal Sciences

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Animal Breeding and Genetics

                genetic diversity,indonesian,cattle breed,microsatellite


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