Investigating genetic heterogeneity using microsatellite markers after long term selection for egg production in Rhode Island Red chicken

ANANTA KUMAR DAS; SANJEEV KUMAR; ABDUL RAHIM; JOWEL DEBNATH; LAXMIKANT SAMBHAJI KOKATE

doi:10.56093/ijans.v90i10.111323

Authors

ANANTA KUMAR DAS West Bengal University of Animal and Fishery Sciences, Nadia, West Bengal
SANJEEV KUMAR ICAR-Central Avian Research Institute, Izatnagar, Uttar Pradesh 243 122 India
ABDUL RAHIM ICAR-Central Avian Research Institute, Izatnagar, Uttar Pradesh 243 122 India
JOWEL DEBNATH ICAR-Central Avian Research Institute, Izatnagar, Uttar Pradesh 243 122 India
LAXMIKANT SAMBHAJI KOKATE ICAR-Central Avian Research Institute, Izatnagar, Uttar Pradesh 243 122 India

https://doi.org/10.56093/ijans.v90i10.111323

Keywords:

Genetic identity and distance, Hardy-Weinberg disequilibrium, Heterozygosity, Microsatellites, Phylogeny, RIR chicken

Abstract

Genetic heterogeneity was investigated using 24 microsatellite markers and genomic DNA of 24 randomly selected birds from the selected and control lines of RIR chicken maintained at ICAR-Central Avian Research Institute, Izatnagar. The microsatellite alleles were determined on urea-PAGE, recorded using GelDoc system and the samples were genotyped. The complete genotypic data set was analyzed using POPGENE software. The observed heterozygosity (H_o) means were 0.6306±0.3901 and 0.6528±0.4345 in the selected and control line, respectively. Explicitly the control line contained more Ho mean and thus the more diverse than the selected population. The expected heterozygosity (He) ranged from 0.5053 (MCW0059) to 0.8421 (MCW0004) with mean of 0.7066±0.020 in the selected line, and from 0.2899 (MCW0059) to 0.9130 (ADL0136) with mean of 0.7095±0.030 in the control line. The Ho mean was less than the He mean in each population; the Chi square and G-square tests revealed significant deviations of almost all the loci from the Hardy-Weinberg equilibrium. The selected and control line populations had the corresponding genetic identity and genetic distance of 0.5264 and 0.6418 as original measures, and 0.5528 and 0.5928 as unbiased measures. The phylogenetic analysis revealed their moderate genetic diversity reflecting 29.64 to 32.09% common inheritance. This present investigation thus estimated genetic heterogeneity using a set of microsatellite markers after long term selection for egg production in RIR chicken and could be useful in the study of population dynamics under selection pressure.

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References

Albers G A A and van Sambeek F M J P. 2002. Breeding strategies for layers in view of new technologies. Abstracts Proceedings of 11th European Poultry Conference p. 31.

Anonymous 2011. CARI Annual Report, 2010–11. ICAR-Central Avian Research Institute, Izatnagar, Bareilly, India. pp. 32–33.

Babar M E, Nadeem A, Hussain T, Wajid A, Shah S A, Iqbal A, Sarfraz Z and Akram M. 2012. Microsatellite markers based genetic diversity among four varieties of Pakistani Aseel chicken. Pakistan Veterinary Journal 32: 237–41.

Beidler J L, Hilliard P R and Rill R L. 1982. Ultrasensitive staining of nucleic acids with silver. Analytical Biochemistry 126: 374– 80. DOI: https://doi.org/10.1016/0003-2697(82)90530-9

Chatterjee R N, Niranjan M, Sharma R P, Dange M and Bhattacharya T K. 2010. Estimation of genetic heterogeneity of chicken germplasm being used for development of rural varieties utilizing DNA markers. Journal of Genetics 89: e33– e37. DOI: https://doi.org/10.1007/s12041-011-0006-9

Cheng H H, Levin R L, Vallejo H, Khatib J B, Dodgson L B, Crittenden and Hillel J. 1995. Development of a genetic map of the chicken with markers of high utility. Poultry Science 74: 1855–74. DOI: https://doi.org/10.3382/ps.0741855

Das A K, Kumar S and Rahim A. 2015a. Estimating microsatellite based genetic diversity in Rhode Island Red chicken. Iranian Journal of Veterinary Research 16: 274–77.

Das A K, Kumar S and Rahim A. 2015b. Microsatellite analysis after long term selection for egg production in Rhode Island Red chicken. Indian Journal of Animal Sciences 85: 1220–24.

Hillel J, Groenen M A M, Tixier-Boichard M, Korol A B, David L, Kirzhner V M, Burke T, Barre-Dirie A, Crooijmans R P M A, Elo K, Feldman M W, Freidlin P J, Maki-Tanila A, Oortwijn M, Thomson P, Vignal A, Wimmers K and Weigend S. 2003. Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools. Genetics Selection Evolution 35: 533–57. DOI: https://doi.org/10.1186/1297-9686-35-6-533

Jing-Ting S, Wen-Bin B, Jin-Hua C and Guo-Hong C. 2007. Study on correlation between microsatellite markers and meat quality traits in chicken, Research Journal of Animal Science 1: 107– 10.

Lawson R and Kofron C P. 1989. Alloenzyme variation in natural populations of Nile crocodile. Integrative and Comparative Biology 29: 863–71. DOI: https://doi.org/10.1093/icb/29.3.863

Nei M. 1972. Genetic distance between populations. American Naturalist 106: 283–92. DOI: https://doi.org/10.1086/282771

Nei M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89: 583– 90. DOI: https://doi.org/10.1093/genetics/89.3.583

Ojango J M, Mp Ofu N, Marshall K and Andersson-Eklund L. 2011. Module 4: Quantitative methods to improve the understanding and utilization of animal genetic resources. (Eds) Ojango J M, Malmfors B and Okeyo A M. Animal Genetics Training Resources, Version 3 (Edn.). International Livestock Research Institute, Nairobi, Kenya, and Swedish University of Agricultural Sciences, Uppsala, Sweden.

Pandey A K, Tantia M S, Kumar D, Mishra B, Chaudhary P and Vijh R K. 2002. Microsatellite analysis of three poultry breeds of India. Asian Australasian Journal of Animal Science 15: 1536–42. DOI: https://doi.org/10.5713/ajas.2002.1536

Pirany N, Romonov N M, Ganpule P S, Devegowda G and Prasad T D. 2007. Microsatellite analysis of genetic diversity in Indian chicken populations. Journal of Poultry Science 44: 19–28. DOI: https://doi.org/10.2141/jpsa.44.19

Rajkumar U, Gupta R B and Reddy R A. 2008. Genomic heterogeneity of chicken populations in India. Asian Australasian Journal of Animal Sciences 21: 1710–20. DOI: https://doi.org/10.5713/ajas.2008.80299

Ramadan G S, Moghaieb R E, El-Ghamry A A, El-Komy E M, Nassar F S, Ghaly M M and Stino F K R. 2014. Microsatellite markers assisted selection for high body weight in local broiler breeders. International Journal of Advanced Research 2: 901– 10.

Romanov M N and Weigend S. 2001. Analysis of genetic relationships between various populations of domestic and jungle fowl using microsatellite markers. Poultry Science 80: 1057–63. DOI: https://doi.org/10.1093/ps/80.8.1057

Tadano R, Nishibori M, Nagasaka N and Tsudzuki M. 2007. Assessing genetic diversity and population structure for commercial chicken lines based on forty microsatellite analyses. Poultry Science 86: 2301–08. DOI: https://doi.org/10.3382/ps.2007-00233

van Marle-Koster E and Nel L H. 2000. Genetic characterization of native southern African chicken populations: evaluation and selection of polymorphic microsatellite markers. South African Journal of Animal Science 30: 1–6. DOI: https://doi.org/10.4314/sajas.v30i1.3866

Vanhala T, Tuiskala-Haavisto M, Elo K, Vilkki J and Maki-Tanila A. 1998. Evaluation of genetic variability and genetic distances between eight chicken lines using microsatellite markers. Poultry Science 77: 783–90. DOI: https://doi.org/10.1093/ps/77.6.783

Wardecka B, Olszewski R, Jaszczak K, Zieba G and Pierzchala M. 2003. Preliminary mapping of QTLs affecting egg quality on chromosomes 1–5 in chickens. Czech Journal of Animal Science 48: 97–105.

Wardecka B, Olszewski R, Jaszczak K, Zieba G, Pierzchala M and Wicinska K. 2002. Relationship between microsatellite marker alleles on chromosomes 1–5 originating from the Rhode Island Red and Greenlegged Partrigenous breeds and egg production and quality traits in F(2) mapping population. Journal of Applied Genetics 43: 319–29.

Wimmers K, Ponsuksili S, Schmoll F, Hardge T, Sonaiya E B, Schellander K and Horst P. 1999. Application of microsatellite analysis to group chicken according to their genetic similarity. Archives Animal Breeding 42: 629–39. DOI: https://doi.org/10.5194/aab-42-629-1999

Yeh F C, Yang R and Boyle T. 1999. User manual for POPGENE Version 1.31, Microsoft Window-based Freeware for Population Genetic Analysis. A joint Project Development by Francis C Yeh and Rong-Cai Yang, University of Alberta and Tim Boyle, Centre for International Forestry Research; August 1999.