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Marker-assisted selection for improving body weight in local chickens in Egypt

Published online by Cambridge University Press:  25 January 2023

M. M. Helal Open the ORCID record for M. M. Helal [Opens in a new window]  and
E. A. El-Gendy
M. M. Helal*
Affiliation:
Department of Animal Production, Faculty of Agriculture, Cairo University, 12613 Giza, Egypt
E. A. El-Gendy
Affiliation:
Department of Animal Production, Faculty of Agriculture, Cairo University, 12613 Giza, Egypt
*
Author for correspondence: M. M. Helal, E-mail: Mostafa.helal@agr.cu.edu.eg
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Abstract

There is a need for a low-cost strategy that accelerates the genetic change in local chicken breeds. Therefore, the objective of this study is to develop a strategy for marker-assisted selection for growth in local chickens in the developing countries. The studied lines were a homozygous normally feathered selected line (CE1), homozygous naked-neck selected line (CE3) and their corresponding control lines (CE2 and CE4). Lines CE1 and CE3 have been selected for high 6-week body weight (BW) for five generations. Three generations were obtained for this study. In the current study, we consider the 6th generation as the base generation for marker-assisted selection study. Two subsequent selected generations were obtained from the base generation. The selected lines were significantly heavier at 6 weeks of age than their corresponding control lines by 24.15 and 27.07% in the base generation and by 51.4 and 34.5% in the second selected generation. A total of 34 polymorphic alleles in 19 loci were flown over generations and the flow trends were different in different lines and families within lines. Principal component analysis was applied to the data of both lines and two main components were found and three canonical correlations were obtained. Four and five alleles were persistently concomitant with the highly performed families in lines CE1 and CE3, respectively. These alleles would have brought 6-week BW into higher levels of performance by 25.1 and 16.6% in the second generation if they would have been considered in the selection for 6-week BW.

Keywords

Allele frequencychickensgrowthMASmicrosatellites
Type
Animal Research Paper
Information
The Journal of Agricultural Science , Volume 161 , Issue 1 , January 2023 , pp. 135 - 147
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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References

Agossou, DJ and Koluman, N (2018) Sustainability of local goat genetic resources in the Mediterranean region. In Simões, J and Gutiérrez, C (eds), Sustainable Goat Production in Adverse Environments. Springer, pp. 15–29. https://doi.org/10.1007/978-3-319-71855-2_2.Google Scholar
Anthony, NB, Nestor, KE and Marks, HL (1996) Short-term selection for four-week body weight in Japanese quail. Poultry Science 75, 1192–1197.CrossRefGoogle ScholarPubMed
Barbato, GF (1992) Divergent selection for exponential growth rate at fourteen or forty-two days of age. 1. Early responses. Poultry Science 71, 1985–1993.CrossRefGoogle ScholarPubMed
Bijma, P and Bovenhuis, H (2009) Developments in quantitative genetics and genomics relevant for poultry breeding. In Hocking, P (ed.), Biology of Breeding Poultry, pp. 29–44. https://doi.org/10.1079/9781845933753.0029.CrossRefGoogle Scholar
Cahaner, A, Ajuh, JA, Siegmund-Schultze, M, Azoulay, Y, Druyan, S and Zárate, AV (2008) Effects of the genetically reduced feather coverage in naked neck and featherless broilers on their performance under hot conditions. Poultry Science 87, 2517–2527.CrossRefGoogle ScholarPubMed
Canales Vergara, AM, Landi, V, Delgado Bermejo, JV, Martínez, AM, Cervantes Acosta, P, Pons Barros, A, Bigi, D, Sponenberg, P, Helal, M, Banabazi, MH and Camacho Vallejo, ME (2020) Design and development of a multiplex microsatellite panel for the genetic characterisation and diversity assessment of domestic Turkey (Meleagris gallopavo gallopavo). Italian Journal of Animal Science 19, 392–398.CrossRefGoogle Scholar
Carlborg, Ö, Kerje, S, Schütz, K, Jacobsson, L, Jensen, P and Andersson, L (2003) A global search reveals epistatic interaction between QTL for early growth in the chicken. Genome Research 13, 413–421.CrossRefGoogle ScholarPubMed
Chin, V (2003) Patterns of chicken consumption in South-East China. British Poultry Science 44, 784–785.CrossRefGoogle ScholarPubMed
Cui, HX, Shen, QC, Zheng, MQ, Su, YC, Cai, RC, Yu, Y, Yang, XR, Chen, ZW, Wen, J and Zhao, GP (2019) A selection method of chickens with blue-eggshell and dwarf traits by molecular marker-assisted selection. Poultry Science 98, 3114–3118.CrossRefGoogle ScholarPubMed
Deeb, N and Cahaner, A (2002) Genotype-by-environment interaction with broiler genotypes differing in growth rate. 3. Growth rate and water consumption of broiler progeny from weight-selected versus nonselected parents under normal and high ambient temperatures. Poultry Science 81, 293–301.CrossRefGoogle ScholarPubMed
Dekkers, JC (2004) Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons. Journal of Animal Science 82(E-Suppl), E313–E328.Google ScholarPubMed
Dekkers, JCM and Hospital, F (2002) The use of molecular genetics in the improvement of agricultural populations. Nature Reviews Genetics 3, 22–32.CrossRefGoogle ScholarPubMed
Duncan, DB (1955) Multiple range and multiple F tests. Biometrics 11, 1.CrossRefGoogle Scholar
El-Gendy, EA (2009a) A genome scan inference to the genetic evaluation of selected and randombred chicken populations. Arab Journal of Biotechnology 12, 1–12.Google Scholar
El-Gendy, EA (2009b) 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. International Journal of Poultry Science 8, 299–306.CrossRefGoogle Scholar
El-Gendy, E and Helal, M (2014) The genetic variation and polymorphism at microsatellite loci in chickens of warm regions selected for meat production. International Journal of Biotechnology and Allied Fields 2, 100–116.Google Scholar
El-Gendy, E, Atallah, A, Mohamed, F and Atta, AM (1995) Strain variation in young chickens in response to chronic heat stress condition. Egyptian Journal of Animal. Production 32, 237–251.Google Scholar
El-Gendy, EA, Helal, M, Goher, N and Mostageer, A (2005) Molecular characterization of genetic biodiversity in ducks, using RAPD-PCR analysis. Arab Journal of Biotechnology 8, 253–264.Google Scholar
El-Gendy, EA, El-Komy, EM, El-Far, AA, El-Gamry, AKA and El-Mallah, GM (2011) Developmental stability in chickens local to warm climatic region 2. Variation in blood metabolites due to genetic selection and crossing. International Journal of Poultry Science 10, 358–364.Google Scholar
El-Henfnawy, M, El-Gendy, EA, El-Kaiaty, AM and Helal, M (2022) Genotype-by-sex interaction effect on growth traits at different ages in slow-growing chickens. Journal of Animal Health and Production 10, 226–231.CrossRefGoogle Scholar
Gomez-Raya, L and Klemetsdal, G (1999) Two-stage selection strategies utilizing marker-quantitative trait locus information and individual performance. Journal of Animal Science 77, 2008–2018.CrossRefGoogle ScholarPubMed
Guimaraes, EP, Ruane, J, Scherf, BD, Sonnino, A and Dargie, JD (2007) Marker-Assisted Selection: Status and Future Perspectives in crops, Livestock, Forestry and Fish E.P. Guimarães, J. Ruane, B.D. Scherf, A. Sonnino & J.D. Dargie (Eds) FAO, Viale delle Terme di Caracalla, 00153 Rome, Italy Published in 2007, pp. 471 ISBN: 978-92-5-105717-9. Animal Genetic Resources/Resources Génétiques Animales/Recursos Genéticos Animales 41, 126–126. doi:10.1017/S1014233900002406Google Scholar
Havenstein, GB, Ferket, PR and Qureshi, MA (2003) Growth, livability, and feed conversion of 1957 versus 2001 broilers when fed representative 1957 and 2001 broiler diets. Poultry Science 82, 1500–1508.CrossRefGoogle ScholarPubMed
Helal, MM (2019) Association between growth hormone receptor gene polymorphism and body weight in growing rabbits. Advances in Animal and Veterinary Sciences 7, 994–998.Google Scholar
Helal, M and El-Gendy, EA (2014) Comparison of growth curves of two selected chicken lines in Egypt. Poultry science association annual meeting. In Poultry Science Association Annual Meeting. Texas, USA: Corpus Christi. Available at https://poultryscience.org/files/galleries/2014-PSAAnnual_Meeting_Abstracts.pdfGoogle Scholar
Helal, M, Hany, N, Maged, M, Abdelaziz, M, Osama, N, Younan, YW, Ismail, Y, Abdelrahman, R and Ragab, M (2022) Candidate genes for marker-assisted selection for growth, carcass and meat quality traits in rabbits. Animal Biotechnology 33, 1691–1710.CrossRefGoogle ScholarPubMed
Hoeschele, I and VanRaden, PM (1993) Bayesian analysis of linkage between genetic markers and quantitative trait loci. II. Combining prior knowledge with experimental evidence. Theoretical and Applied Genetics 85, 946–952.CrossRefGoogle ScholarPubMed
Ikeobi, CON, Woolliams, JA, Morrice, DR, Law, A, Windsor, D, Burt, DW and Hocking, PM (2004) Quantitative trait loci for meat yield and muscle distribution in a broiler layer cross. Livestock Production Science 87, 143–151.CrossRefGoogle Scholar
Keightley, PD, Hardge, T, May, L and Bulfield, G (1996) A genetic map of quantitative trait loci for body weight in the mouse. Genetics 142, 227–235.CrossRefGoogle ScholarPubMed
Lahav, T, Atzmon, G, Blum, S, Ben-Ari, G, Weigend, S, Cahaner, A, Lavi, U and Hillel, J (2006) Marker-assisted selection based on a multi-trait economic index in chicken: experimental results and simulation. Animal Genetics 37, 482–488.CrossRefGoogle ScholarPubMed
Lamont, SJ (2003) Unique population designs used to address molecular genetics questions in poultry. Poultry Science 82, 882–884.CrossRefGoogle ScholarPubMed
Lamont, SJ, Lakshmanan, N, Plotsky, Y, Kaiser, MG, Kuhn, M, Arthur, JA, Beck, NJ and O'Sullivan, NP (1996) Genetic markers linked to quantitative traits in poultry. Animal Genetics 27, 1–8.CrossRefGoogle ScholarPubMed
Leitch, HW, Smith, C, Burnside, EB and Quinton, M (1994) Genetic response and inbreeding with different selection methods and mating designs for nucleus breeding programs of dairy cattle. Journal of Dairy Science 77, 1702–1718.CrossRefGoogle ScholarPubMed
Li, H, Deeb, N, Zhou, H, Ashwell, CM and Lamont, SJ (2005) Chicken quantitative trait loci for growth and body composition associated with the very low density apolipoprotein-II gene. Poultry Science 84, 697–703.CrossRefGoogle ScholarPubMed
Liu, G, Dunnington, EA and Siegel, PB (1994) Responses to long-term divergent selection for eight-week body weight in chickens. Poultry Science 73, 1642–1650.CrossRefGoogle ScholarPubMed
Merat, P (1990) Major genes in fowls (Gallus gallus): genes other than those affecting size. Productions Animales 3, 355–368.Google Scholar
Meuwissen, THE and Goddard, ME (1996) The use of marker haplotypes in animal breeding schemes. Genetics Selection Evolution 28, 161–176.CrossRefGoogle Scholar
Mignon-Grasteau, S, Piles, M, Varona, L, De Rochambeau, H, Poivey, JP, Blasco, A and Beaumont, C (2000) Genetic analysis of growth curve parameters for male and female chickens resulting from selection on shape of growth curve. Journal of Animal Science 78, 2515–2524.CrossRefGoogle ScholarPubMed
Mignon-Grasteau, S, Beaumont, C and Ricard, FH (2001) Genetic analysis of a selection experiment on the growth curve of chickens. Poultry Science 80, 849–854.CrossRefGoogle ScholarPubMed
Mou, C, Pitel, F, Gourichon, D, Vignoles, F, Tzika, A, Tato, P, Yu, L, Burt, DW, Bed'Hom, B and Tixier-Boichard, M (2011) Cryptic patterning of avian skin confers a developmental facility for loss of neck feathering. PLoS Biology 9, e1001028.CrossRefGoogle ScholarPubMed
Ovaska, U and Soini, K (2017) Local breeds – rural heritage or new market opportunities? Colliding views on the conservation and sustainable use of landraces. Sociologia Ruralis 57, 709–729.CrossRefGoogle Scholar
Podisi, BK, Knott, SA, Dunn, IC, Law, AS, Burt, DW and Hocking, PM (2011) Overlap of quantitative trait loci for early growth rate, and for body weight and age at onset of sexual maturity in chickens. Reproduction (Cambridge, England) 141, 381–389.CrossRefGoogle ScholarPubMed
Pongpisantham, B (1994) Applying Genotype and Marker-Assisted Selection for the Improvement of Quantitative Traits in Poultry. M.Sc. Thesis. University of New England, pp. 121.Google Scholar
SAS (1999) SAS/STAT User's Guide: Statistics. Cary, NC, USA: SAS Institute Inc. Analysis System Institute Cary.Google Scholar
Scott, T and Crawford, RD (1977) Feather number and distribution in the throat tuft of naked neck chicks. Poultry Science 56, 686–688.CrossRefGoogle Scholar
Sharifi, AR, Horst, P and Simianer, H (2010) The effect of naked neck gene and ambient temperature and their interaction on reproductive traits of heavy broiler dams. Poultry Science 89, 1360–1371.CrossRefGoogle ScholarPubMed
Siegel, PB, Haberfeld, AHA, Mukherjee, TK, Stallard, LC, Marks, HL, Anthony, NB and Dunnington, EA (1992) Jungle fowl–domestic fowl relationships: a use of DNA fingerprinting. World's Poultry Science Journal 48, 147–155.Google Scholar
Spelman, R and Bovenhuis, H (1998) Genetic response from marker assisted selection in an outbred population for differing marker bracket sizes and with two identified quantitative trait loci. Genetics 148, 1389–1396.CrossRefGoogle Scholar
Tatsuda, K (2016) Production of chickens with high body weights, low amounts of abdominal fat, and a high thigh meat yield using DNA microsatellite marker-assisted selection. Journal of Animal Science 94, 127–127.CrossRefGoogle Scholar
Uemoto, Y, Sato, S, Odawara, S, Nokata, H, Oyamada, Y, Taguchi, Y, Yanai, S, Sasaki, O, Takahashi, H, Nirasawa, K and Kobayashi, E (2009) Genetic mapping of quantitative trait loci affecting growth and carcass traits in F2 intercross chickens. Poultry Science 88, 477–482.CrossRefGoogle ScholarPubMed
Van Der Beek, S and Van Arendonk, JAM (1996) Marker-assisted selection in an outbred poultry breeding nucleus. Animal Science 62, 171–180.Google Scholar
Van Marle-Köster, E, Hefer, CA, Nel, LH and Groenen, MAM (2008) Genetic diversity and population structure of locally adapted South African chicken lines: implications for conservation. South African Journal of Animal Science 38, 271–281.Google Scholar
Vergara, AMC, Landi, V, Bermejo, JVD, Martínez, A, Acosta, PC, Barro, ÁP, Bigi, D, Sponenberg, P, Helal, M, Banabazi, MH and Vallejo, MEC (2019) Tracing worldwide Turkey genetic diversity using D-loop sequence mitochondrial DNA analysis. Animals 9, 897–908. https://doi.org/10.3390/ani9110897.Google Scholar
Wang, Y, Gu, X, Feng, C, Song, C, Hu, X and Li, N (2012) A genome-wide survey of copy number variation regions in various chicken breeds by array comparative genomic hybridization method. Animal Genetics 43, 282–289.CrossRefGoogle ScholarPubMed
Yahav, S, Straschnow, A, Plavnik, I and Hurwitz, S (1996) Effects of diurnally cycling versus constant temperatures on chicken growth and food intake. British Poultry Science 37, 43–54.CrossRefGoogle ScholarPubMed
Yunis, R and Cahaner, A (1999) The effects of the naked neck (Na) and frizzle (F) genes on growth and meat yield of broilers and their interactions with ambient temperatures and potential growth rate. Poultry Science 78, 1347–1352.CrossRefGoogle ScholarPubMed