Microsatellite based genetic diversity estimation in Kajali sheep and its phylogenetic relationship with other indigenous sheep breeds

S SINGH; A K MISHRA; V VOHRA; K N RAJA; Y SINGH; K M SINGH; I GANGULY; R ARORA

doi:10.56093/ijans.v87i9.74316

Authors

S SINGH ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
A K MISHRA ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
V VOHRA ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
K N RAJA ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
Y SINGH ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
K M SINGH ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
I GANGULY ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
R ARORA ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India

https://doi.org/10.56093/ijans.v87i9.74316

Keywords:

Characterization, Diversity analysis, Kajali sheep, Microsatellite markers

Abstract

Microsatellite based characterization of Kajali sheep population found in Punjab and adjoining regions was carried out and genetic diversity measures were analysed. High measures of allele (7.778±0.80) and gene diversity (0.66±0.03) were observed across this population. A significant positive FIS (0.23±0.03) value suggested a deficiency in the number of heterozygotes in Kajali sheep which may be attributed to population sub-structuring into different colour variants (White and Kali Kajali). The population revealed presence of genetic diversity and there was no significant heterozygosity excess indicating the absence of genetic bottleneck in the recent past. The phylogenetic study analysis with 18 other Indian sheep breeds revealed that Kajali sheep clustered in same node with Munjal sheep (bootstrap value of 22%). However, Kajali and Munjal sheep are phenotypically distinct from each other. The genetic characterization of Kajali sheep will help in devising suitable strategies for its genetic improvement, management and recognition at national level.

Downloads

Download data is not yet available.

References

Arora R, Bhatia S, Mishra B P, Jain A and Prakash B. 2011a. Diversity analysis of sheep breeds from Southern peninsular and Eastern regions of India. Tropical Animal Health and Production 43(2): 401–08. DOI: https://doi.org/10.1007/s11250-010-9706-z

Arora R, Bhatia S, Mishra B P and Joshi B K. 2011b. Population structure in Indian sheep ascertained using microsatellite information. Animal Genetics 42(3): 242–50. DOI: https://doi.org/10.1111/j.1365-2052.2010.02147.x

Arora R, Bhatia S, Yadav D K and Mishra B P. 2011c. Current genetic profile of sheep breeds/populations from Northwestern semi arid zone of India. Livestock Science 135: 193–98. DOI: https://doi.org/10.1016/j.livsci.2010.07.008

Bhatia S and Arora R. 2010. Lesser known ovine germplasm- An under evaluated asset of India. Indian Journal of Animal Sciences 80(9): 880–90.

Botstein D, White R L, Skolnick M and Davis R W. 1980. Construction of genetic linkage maps in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32: 314–31.

Bradley D G, Fries R, Bumstead N, Nicholas F W, Cothran E G, Ollivier L and Crawford A M. 1997. Report of an advisory group of the International Society of Animal Genetics as a contribution to assist FAO prepare for the MoDAD Project, DADIS. FAO: 1–15.

Cornuet J M and Luikart G. 1996. Analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144: 2001–14. DOI: https://doi.org/10.1093/genetics/144.4.2001

Di Stasio L. 2001. Applied genetics in sheep and goats. Panel of markers for parentage verification tested at the 2001/02 ISAG comparison test. www.isag.org.uk/pdf/2005PanelsMarkersSheepGoats.pdf.

FAO. 1996. Global Project for the Maintenance of Domestic Animal Genetic Diversity (MoDAD). http://www.fao.org/dad- is/.

Kimura M and Crow J F. 1964. The number of alleles that can be maintained in a finite population. Genetics 49: 725–38. DOI: https://doi.org/10.1093/genetics/49.4.725

Levene H. 1949. On a matching problem in genetics. Annals of Mathematical Statistics 20: 91–94. DOI: https://doi.org/10.1214/aoms/1177730093

Livestock census (Nineteenth). 2012. Department of Animal Husbandry, Dairying and Fisheries, Ministry of Agriculture, Government of India.

Luikart G, Allendorf F W, Cournuet J M and Sherwin W B. 1998. Distortion of allele frequency distributions provides a test for recent population bottlenecks. Journal of Heredity 89: 238– 47. DOI: https://doi.org/10.1093/jhered/89.3.238

Luikart G and Cornuet J M. 1997. Empirical evaluation of a test for identifying recently bottlenecked populations from allele frequency data. Conservation Biology 12: 228–37. DOI: https://doi.org/10.1046/j.1523-1739.1998.96388.x

Mishra A K, Raja K N, Vohra V, Singh S and Singh Y. 2016. Phenotypic traits and performance of Kajali Sheep: a lesser known ovine genetic resource of Punjab, India. Indian Journal of Animal Sciences 86(11): 1279–82.

Mishra A K, Raja K N, Vohra V, Singh S and Singh Y. 2017. Principal component analysis of the biometric traits to explain body conformation in Kajali sheep of Punjab, India. Indian Journal Animal Sciences 87(1): 93–98.

Peakall R and Smouse P E. 2005. GENALEX-6.5: Genetic Analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Note 6: 288–95. DOI: https://doi.org/10.1111/j.1471-8286.2005.01155.x

Piry S, Luikart G and Cornuet J M. 1999. Bottleneck: A computer programme for detecting recent reductions in the effective population size using allele frequency data. Journal of Heredity 90: 502–03. DOI: https://doi.org/10.1093/jhered/90.4.502

Sambrook J, Fritsch E F and Maniatis T. 1989. Molecular Cloning: A Laboratory Manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY.

Singh S, Raja K N, Ganguly I, Arora R and Kataria R S. 2015. Genetic characterization of Koraput sheep of Odisha. Indian Journal of Animal Sciences 85(6): 667–69.

Yeh F C, Yang R C and Boyle T. 1999. POPGENE 32 – Version 1.31. Population genetics software. http.//www.ualberta.ca/fyeh/fyeh.