Assessing Genetic Diversity in Two Local Chicken Breeds in Egypt Using Microsatellite Markers
الموضوعات :M.I. El-Hefnawy 1 , E.A. El-Gendy 2 , A.M. El-Kaiaty 3 , M. Helal 4
1 - Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
2 - Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
3 - Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
4 - Department of Animal Production, Faculty of Agriculture, Cairo University, Giza, Egypt
الکلمات المفتاحية: Diversity, microsatellites, genomic information, local chickens,
ملخص المقالة :
Local chicken breeds play vital roles in rural development and sustainability; therefore, the preservation of local breeds’ genetic diversity is crucial, also, assessing and advancing local breeds is crucial considering the impact of climate change on chicken production. The current study evaluated the differences between a fully feathered local chicken line (CE2) and a naked-neck local chicken line (CE4) at the microsatellite loci level. For this purpose, nine microsatellite primers were used to scan the genomes of both lines. The results generated by different loci between the two lines showed that the lowest allele numbers were 0 and 4 alleles detected at loci LEI0094 and MCW217, respectively, and the highest allele number was 10 detected at MCW328 and ADL299 loci, with an overall mean of 6.69 alleles/locus. The levels of heterozygosity were relatively high and were higher for line CE4 than for line CE2. The genetic distance between males and females of line CE2 was shorter (0.018) than that between males and females of line CE4 (0.104), and the opposite was observed for genetic identity. Also, ΦPT values were 0.088 (P<0.001), and 0.080 (P<0.01) for line CE2 and line CE4, respectively. The association between alleles and body weights revealed different alleles of microsatellites MCW217, MCW328, MCW193, ADL299, and MCW064 contributed significantly to body weight variance at different ages. The study provided an outlook on the genetic diversity of two chicken lines and indicated substantial room for improvement within Egyptian native breeds.
Abasht B., Dekkers J.C.M. and Lamont S.J. (2006). Review of Quantitative Trait Loci Identified in Chicken. Poult. Sci. 85, 2079-2096.
Allentoft M.E. and O’Brien J. (2010). Global amphibian declines, loss of genetic diversity and fitness: A review. Diversity. 2, 47-71.
Atzmon G., Ronin Y.I., Korol A., Yonash N., Cheng H. and Hillel J. (2006). QTLs associated with growth traits and abdominal fat weight and their interactions with gender and hatch in commercial meat-type chickens. Anim. Genet. 37, 352-358.
Besbes B., Tixier-Boichard M., Hoffmann I. and Jain G. (2007). Future trends for poultry genetic resources. Pp. 1-25 in Proc. Int. Poult. Conf. Bangkok, Thailand.
Bhattacharya T.K., Kumar P., Joshi J.D. and Kumar S. (2003). Estimation of inbreeding in cattle using RAPD markers. J. Dairy Res. 70, 127-129.
Canales Vergara A.M., Landi V., Delgado Bermejo J.V., Martínez A.M., Cervantes Acosta P., Pons Barros A., Bigi D., Sponenberg P., Helal M., Banabazi M.H. and Camacho Vallejo M.E. (2020). Design and development of a multiplex microsatellite panel for the genetic characterisation and diversity assessment of domestic turkey (Meleagris gallopavo). Italian J. Anim. Sci. 19, 392-398.
Chatterjee R., Sharma R.P., Mishra A., Dange M. and Bhattacharya T.K. (2008). Association of microsatellites with growth and immunocompetence traits in crossbred layer chicken. J. Poult. Sci. 45, 186-191.
Chatterjee R., Sharma R.P., Bhattacharya T.K., Niranjan M. and Reddy B.L. (2010). Microsatellite variability and its relationship with growth, egg production, and immunocompetence traits in chickens. Biochem. Genet. 48, 71-82.
Das A.K., Kumar S., Rahim A. and Kokate L.S. (2016). Association study between microsatellite genotypes and layer performances in Rhode Island Red chicken. Indian J. Anim. Sci. 86, 1021-1024.
Debnath J., Kumar S., Das A.K. and Rahim A. (2019). Association of microsatellites with pre-housing body weights and age at sexual maturity of Rhode Island Red chicken. Indian J. Anim. Sci. 89, 1118-1122.
Do Rosário M.F., Ledur M.C., Moura A.S.A.M.T., Coutinho L.L. and Garcia A.A.F. (2009). Genotypic characterization of microsatellite markers in broiler and layer selected chicken lines and their reciprocal F1s. Sci. Agric. 66, 150-158.
El-Gendy E.A. (2009). A model for the genetic employment of chickens local to warm climate 1. Crossing with a fast-growing strain and growth patterns of the crossbreds. Int. J. Poult. Sci. 8, 299-306.
El-Gendy E. and Helal M.A. (2011). An approach to marker-assisted selection for increased body weights in local chickens in Egypt. Poult. Sci. 90(1), 1-8.
El-Gendy E., Abbas E., El-Tantawy S., Mohamed A., Helal M., Zaki El-Deen M. and Wageh A. (2013). A model for the genetic employment of chickens local to warm climate. 2. Genome scanning of two lines selected for growth. African J. Biol. Sci. 9, 95-100.
El-Gendy E. and Helal M. (2014). The genetic variation and polymorphism at microsatellite loci in chickens of warm regions selected for meat production. Int. J. Biotechnol. Allied Fields. 2, 100-116.
El-Gendy E.A., Higazy D.M., El-Kashef A.A.M. and Helal M.M. (2018). The growth pattern of warm-region chickens under prolonged natural severe heating conditions with a reference to association between microsatellite loci on chromosomes 3, 4 and 5 and QTL of growth. Pp. 990-995 in Proc. World Congr. Genet. Appl. Livest. Prod., New Zealand.
Ezzulddin T.A., Jwher D.M. and Dabdoub S.A. (2020). Detection of similarity and genetic distance between Iraqi chicken varieties and different standard strains. Iraqi J. Vet. Sci. 34, 333-337.
Figueira G.M., Risterucci A.M., Zucchi M.I., Cavallari M.M. and Noyer J.L. (2010). Development and characterisation of microsatellite markers for Boraginaceae (Cordia verbenacea), an important medicinal species from the Brazilian coast. Conserv. Genet. 11, 1127-1129.
Hartl D.L. and Clark G.C. (1997). Principles of Population Genetics. Sinauer Associates, Sunderland, United Kingdom.
Helal M.M. and El-Gendy E.A. (2023). Marker-assisted selection for improving body weight in local chickens in Egypt. J. Agric. Sci. 161, 135-147.
Malvika S., Ghosh P.R., Dhar B., Devi N.N., Paul R., Halder A., Mazumder A., Choudhury Y., Kumar S. and Ghosh S.K. (2019). Genetic status of indigenous poultry (red jungle fowl) from India. Gene. 705, 77-81.
Mpenda F.N., Schilling M.A., Campbell Z., Mngumi E.B. and Buza J. (2019). The genetic diversity of local african chickens: A potential for selection of chickens resistant to viral infections. J. Appl. Poult. Res. 28, 1-12.
Muñoz L.J., Carballosa-Gautam M.M., Yanowsky K., García-Atarés N. and López D.E. (2017). The genetic audiogenic seizure hamster from Salamanca: The GASH: Sal. Epilep. Behav. 71, 181-192.
Nei M. (1973). Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. 70, 3321-3323.
Okumu O.N., Ngeranwa J.J.N., Binepal Y.S., Kahi A.K., Bramwel W.W., Ateya L.O. and Wekesa F.C. (2017). Genetic diversity of indigenous chickens from selected areas in Kenya using microsatellite markers. J. Genet. Eng. Biotechnol. 15, 489-495.
Padhi M.K. (2016). Importance of indigenous breeds of chicken for rural economy and their improvements for higher production performance. Scientifica. 2016, 1-9.
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 J. Anim. Sci. 15, 1536-1542.
Peakall R. and Smouse P.E. (2006). GENALEX 6: Genetic analysis in excel. Population genetic software for teaching and research. Mol. Ecol. Notes. 6, 288-295.
Ramadan S., Kayang B.B., Inoue E., Nirasawa K., Hayakawa H., Ito S. and Inoue-Murayama M. (2012). Evaluation of genetic diversity and conservation priorities for Egyptian chickens. Open J. Anim. Sci. 2, 183-190.
Sabry A., Mohamed A.A. and Hassen M. (2021). Genetic diversity of indigenous chicken (Gallus Gallus domesticus) from ecozones of Egypt and Kingdom of Saudi Arabia. Open J. Anim. Sci. 11, 775-787.
Sambrook J., Fritsch E.F. and Maniatis T. (1989). Molecular Cloning: A Laboratory Manual. Cold Spring Harbor Press, Cold Spring Harbor, New York, USA.
SAS Institute. (1999). SAS®/STAT Software, Release 8. Institute, Inc., Cary, NC. USA.
Sheriff O. and Alemayehu K. (2018). Genetic diversity studies using microsatellite markers and their contribution in supporting sustainable sheep breeding programs: A review. Cogent Food Agric. 4, 1-9.
Verma A.K. (2021). Influence of climate change on balanced ecosystem, biodiversity and sustainable development: An overview. Int. J. Biol. Innov. 3, 331-337.
Yeh F.C., Yang R.C. and Boyle T. (1999). POPGENE Version 1.32: Microsoft Window-Based Freeware for Population Genetics Analysis. University of Alberta, Edmonton.
Yonash N., Cheng H.H., Hillel J., Heller D.E. and Cahaner A. (2001). DNA microsatellites linked to quantitative trait loci affecting antibody response and survival rate in meat-type chickens. Poult. Sci. 80, 22-28.
