Journal of Animal Breeding and Genomics (J Anim Breed Genom)
Ho Chan Kang1, Eun Ho Kim1, Cheol Hyun Myung1, Ji Yeong Kim1, Sang Hyun Song2, Dae Yong Yang3, Chang Wan Sun3, Hyun Tae Lim1,4,*
1Department of animal science, Gyeongsang National University, Jinju 52828, Korea
2College of Agriculture and Life Sciences, Gyeongsang national University, Jinju 52828, Korea
3Korea Institute for Animal Product Quality Evaluation, Sejong 30100, Korea
4Institutue of Agriculture and Life Science, Gyongsang National University, Jinju 52828, Korea
Correspondence to Hyun Tae Lim, E-mail: s_htim@gnu.ac.kr
Volume 7, Number 2, Pages 37-44, March 2023.
Journal of Animal Breeding and Genomics 2023, 7(2), 37-44. https://doi.org/10.12972/jabng.20230005
Received on 23 May, 2023, Revised on 23 May, 2023, Accepted on 28 June, 2023, Published on 30 June, 2023.
Copyright © 2023 Korean Society of Animal Breeding and Genetics.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0).
This research was conducted to present the possibility of utilization as basic data and future genetic resources for planning for breeding and breeding direction planning for the preservation of the Gyeongsang National University (GNU) line through genetic diversity, genetic structure and character analysis of GNU line black goats, by using Microsatellite (MS) marker. A total of 247 Korean native black goats of four lines were used (Dang-jin; DJ : 68, Jang-su; JS : 80, Tong-yeong; TY : 71, GNU : 30), and a basic statistical analysis confirmed values suitable for the study. In addition, as a result of FIS analysis, it is thought that line differentiation is occurring in the case of the GNU line because it is farther away from 0 (-0.110), which is the standard of Hardy-Weinberg equilibrium, in a negative direction than other goat lines. Also , through Factor Correspondence Anlysis (FCA ) and STRUCTURE analysis , it has been determined that the GNU line displays a different genetic structure compared to other native black goat lines, indicating that there has been no genetic exchange or admixture. Therefore, in this study, it is judged that the GNU line is valuable as a future genetic resource and can be used as basic data for maintenance and conservation through planned breeding considering inbreeding rate.
Genetic diversity, Genetic Structure, Microsatellite marker, Korean native black goat
Cooperative research program for agriculture science and technology development (Project PJ016710022023) from the Korean Rural Development Administration.
Adrana MA, Guimaraes SEF, Pereira CS, Lopes PS, Rodrigues MT and Machado TMM. 2010. Paternity in Brazilian goat with DNA microsatellites. R. Bras. Zootec. 39: 1011-1014.
[DOI]
Barbara AA. 1990. Composition of foods; Beef products. Nutrition Monitoring Division, US Department of Agriculture.
Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N. and Bonhomme, F. 2004. GENETIX ver. 4.05, logical sous Windows TM pour la genetique des POPulations. Labaratoire Genome, populations, Interactions, CNRS UMR 5000, Universite de Montpeller II. Montpellier. France.
Chung ER. 2002. Identification of Korean native goat meat using amplified fragment length polymorphism (AFLP) DNA markers. Kor. Food Sci. Anim. Resour. 22, 301-309
Dieringer D and Schltterer C. 2003. Microsatellite analyser (MSA): a platform independent analysis tool for large microsatellite data sets. Mol. Ecol. Notes. 3: 167-169.
[DOI]
Earl DA and Von-Holdt BM. 2012. Structure Harvester: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources. 4: 359-361.
[DOI]
Evanno G, Regnaut S, Goudet J. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14: 2611-2620.
[DOI][PubMed]
Falush D, Stephens M, Pritchard JK. 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics. 164: 1567-1587.
[DOI][PubMed][PMC]
Falush D, Stephens M, Pritchard JK. 2007. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol. Ecol. Notes. 7: 574-578.
[DOI][PubMed][PMC]
Frankham R. 1996. Relationship of genetic variation to population size in wild life. Conservation Biology. 10: 1500-1508.
[DOI]
Goudet J. 2001. FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3). Accessed in https://www2.unil.ch/ popgen/softwares/fstat.htm on 14 August 2005
Groenen MA, Croojimans RP, Veenendaal A, Cheng HH, Siwek M and van der Poel JJ. 1998. A comprehensive microsatellite linkage map of the chicken genome. Genomics. 49: 265-274.
[DOI][PubMed]
Hedrick PW. 2000.Genetics of population. Jones and Bartlett Publishers, Sudbury, Mass. 34-47. (Book)
Hubisz MJ, Falush D, Stephens M, Pritchard JK. 2009. Inference weak population structure with the assistance of sample group information. Mol. Ecol. Resour. 9: 1322-1332.
[DOI][PubMed][PMC]
Khan BB. 2008. Health and Husbandry of Dairy Animals. TM Pringers, Faisalabad, Pakistan. Kim YB, Jeon GH, Lee NH, Yang SY, Mon BY and Jang AR. 2005. Nutritional quality of black goat meat. Proceedings of the Korean Society for Food Science of Animal Resources Conference. 103-106.
Kranis A, Gheyas AA, Boschiero C, Turner F, Yu L, Smith S, Talbot R, Pirani A, Brew F, Kaiser P, Hocking PM, Fife M, Salmon N, Fulton J, Strom TM, Haberer G, Weigend S, Preisinger R, Gholami M, Qanbari S, Simianer H, Watson KA, Woolliams HA and Burt DW. 2013. Development of a high density 600K SNP genotyping array for chicken. BMS Genomics. 14: 59.
[DOI][PubMed][PMC]
Lee SH, Lee J, Jeon D, Lee SS, Kim S, Kim KW. 2019. Morphological characteristics and growth performance of Korean native black goats. J. Korea Acad. Industr. Coop. Soc. 20, 149-155.
Ligda C, Altarayrah J, Georgoudis A and Consortium E. 2009. Genetic analysis of Greek sheep breeds using microsatellite markers for setting conservation priorities. Small Ruminant Res. 83: 42-48.
[DOI]
Marshall TC, Slate J, Kruuk LEB, Pemberton JM. 1998. Statistical confidence for likelihood-based paternity inference in natural populations. Molecular Ecology 7:639-655.
[DOI][PubMed]
Pritchard JK, Stephens M and Donnelly P. 2000. Inference of population structure using multilocus genotype data. Genetics. 155: 945-959.
[DOI][PubMed][PMC]
Ramos AM, Croojimans RPMA, Affara NA, Amaral AJ, Archibald AL, Beever JE, Bendixen C, Churcher C, Clark R, Dehais P, Hansen MS, Hedegaard J, Hu ZL, Kerstens HH, Law AS, Megens HJ, Millan D, Nonneman DJ, Rohrer GA, Rothschild MF, Smith TPL, Schnabel RD, Van Tassell CP, Taylor JF, Wiedmann RT, Schook LB and Croenen MAM. 2009. Desing of a high density SNP genotyping assay in the pig using SNPs identified and characterized by next generation sequencing technology. Plos One. 4: e6524.
[DOI][PubMed][PMC]
Raymond M, Rousset F. 1995. GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. Journal of Heredity 86:248249.
[DOI]
Serrano M, Calvo JH, Martinez M, Marcos-Carcavilla A, Cuevas J, Gonzalez C, Jurado JJ and de Tejada PD. 2009. Microsatellite based genetic diversity and population structure of the endangered Spanish Guadarrama goat breed. BMC Gene. 10.
[DOI][PubMed][PMC]
Stothard P, Choi JW, Basu U, Sumner-Thmsom JM, Meng Y, Liao X and Moore SS. 2011. Whole genome resequencing of black Angus and Holstein cattle for SNP and CNV discovery. BMC Genomics. 12: 559.
[DOI][PubMed][PMC]
Tefiel H, Ata N, Chahbar M, Benyarou M, Fantazi K, Yilmaz O, Cemal I, Karaca O, Boudoouma D and Gaouar SBS. 2018. Genetic characterization of four Algerian goat breeds assessed by microsatellite markers. Small Ruminant Research. 160: 65-71.
[DOI]
Weir BS, Hill WG. 2002. Estimating F-statistics. Annual Review of Genetics 36:721-750
[DOI][PubMed]