ارزیابی برنامه های انتخاب با و بدون استفاده از داده های ژنومی در مرغ های بومی ایران

Aguilar I., Misztal I., Johnson D. L., Legarra A., Tsuruta S. and Lawlor T. J. 2010. Hot topic: A unified approach to utilize phenotypic, full pedigree and genomic information for genetic evaluation of Holstein final score1. Journal of Dairy Science, 93: 743-752.

Ajayi F. O. 2010. Nigerian indigenous chickens: a valuable genetic resource for meat and egg production. Asian Journal of Poultry Science, 4: 164-172.

Alders R. G. and Pym R. A. E. 2009. Village poultry: still important to millions eight thousand years after domestication. World's Poultry Science Journal, 65: 181-190.

Assan N. 2015. Prospects for indigenous chicken's genetic improvement and conservation in Zimbabwe. Agricultural Advances, 4: 49-56.

Baumung R. and Solkner J. 2003. Pedigree and marker information requirement to monitor genetic variability. Genetics Selection Evolution, 35: 369-383.

Bernardo R. 2010. Breeding for quantitative traits in plants (2^nd ed). Stemma Press, Woodsbury Minn. Pp. 390.

Caballero A. and Toro M. A. 2002. Interrelations between effective population size and other pedigree tools for management of conserved populations. Genetics Research, 75: 331-343.

Chen C. Y., Misztal I., Aguilar I., Tsuruta S., Meuwissen T. H. E., Aggrey S. E., Wing T. and Muir W. M. 2011. Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens. Journal of Animal Science, 89(1): 23-28.

Chen G. K., Marjoram P. and Wall J. D. 2009. Fast and flexible simulation of DNA sequence data. Genome Research, 19: 136-142.

Clark S. A., Kinghorn B. P., Hickey J. M. and Van der Werf J. H. J. 2013. The effect of genomic information on optimal contribution selection in livestock breeding programs. Genetics Selection Evolution, 45: 44-52.

Dagnachew B. S. and Meuwissen T. H. 2014. An iterative algorithm for optimal contribution selection in large scale breeding program. In: Proceedings of the 10^th WCGALP, Vancouver. Canada, Pp. 23.

deRoos A. P. W., Schrooten C., Veerkamp R. F. and Van Arendonk J. A. M. 2011. Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bull. Journal of Dairy Science, 94: 1559-1567.

Du Plessis P. H. S. and Erasmus J. 1972. The relationship between egg productions, egg weight and body weight in laying hens. World’s Poultry Science Journal, 28(2): 73-78.

El-Dlebshany A. E. 2008. The relationship between age at sexual maturity and some productive traits in local chickens strain. Egypt Poultry Science, 28: 1253-1263.

Falconer D. S. and Mackay T. F. C. 1996. Introduction to quantitative genetics (4^th ed). Addison Wesley Longman, Harlow. Pp. 480.

Forutan M., Ansari Mahyari S., Baed B., Melzer N., Schenkel F. S. and Sargolzaei M. 2018. Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle. BMC Genomics, 19: 98-110.

Gaya  L. G., Costa A. M., Ferraz J. B., Rezende F. M., Mattos E. C., Eler J. P., Michelan-Filho T., Mourao G. B. and Figueiredo L. G. 2007. Genetic trend of absolute and relative heart weight in a male broiler line. Genetics and Molecular Research, 6(4): 1091-1096.

Gaynor R. C., Gorjanc G. and Wilson D. L. AlphaSimR: An R Package for Breeding Program Simulations. Manuscript Prep. https://alphagenes.roslin.ed.ac.uk/wp/software-2/alphasimr.

Ghorbani S. H. and Kamali M. A. 2007. Genetic trend in economic traits in Iranian native fowl. Pakistan Journal of Biological Science, 10: 3215-3219.

Goger H., Yurtogullari S. and Demirtas S. 2010. Effect of applied index selection approach on egg production traits in two pure breed brown egg layers. Trends in Animal and Veterinary Science Journal, 1(2):75-78.

Gorjanc G., Gaynor R. C. and Hickey J. M. 2018. Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection. Theoretical and Applied Genetics, 131(9): 1953-1966.

Heidaritabar M., Vereijken A., Muir W. M., Meuwissen T., Cheng H., Megens H. J., Groenen M. A. M. and Bastiaansen J. W. M. 2014. Systematic differences in the response of genetic variation to pedigree and genome-based selection methods. Heredity, 113(6): 503-513.

Hickey J. M. and Gorjanc G. 2012. Simulated data for genomic selection and genome-wide association studies using a combination of coalescent and gene drop methods. G3, 2: 425-427.

Hudson R. R. 2004. ms- a program for generating samples under neutral models. Bioinformatics, 18: 337-338.

Hussain N. 2016. Evaluation and genetic analysis of production traits in Rajasri birds. MSc. thesis, Veterinary University. P. V. Narsimha Rao Telangana.

Jafarnejad A., Kamali M. A., Fatemi S. J. and Aminafshar M. 2017. Genetic evaluation of laying traits in Iranian indigenous hens using univariate and bivariate animal models.The Journal of Animal and Plant Sciences, 27(1): 20-27.

Korte A, Vilhjlmsson B. J, Segura V, Platt A., Long Q. and Nordborg M. 2012. A mixed model approach for genome-wide association studies of correlated traits in structured populations. Nature Genetics, 44: 1066-1071.

Lillehammer M., Meuwissen T. H. E. and Soneson A. K. 2011. A comparison of dairy cattle breeding designs that use genomic selection. Journal of Dairy Science, 94: 493-500.

Liu T., Qu H., Luo C., Shu D., Wang J., Lund M. and Su G. 2014. Accuracy of genomic prediction for growth and carcass traits in Chinese triple-yellow chickens. BMC Genetics, 15: 110-118.

Maier R., Moser G, Chen G. B., Ripke S., Coryell W. and Potash J. B. 2015. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder.  The American Journal of Human Genetics, 96: 283-294.

Malik S. and Singh N. P. 2010. Performance of CARI Nirbheek in agro-climatic conditions of Tripura. Indian Journal of Animal Sciences, 80 (12): 1213-1216.

Medrano J. F., Ahmadi A. and Casellas J. 2010. Dairy cattle breeding simulation program: a simulation program to teach animal breeding principles and practices. Journal of Dairy Science, 93: 2816-2826.

Misztal I., Tsuruta S., Lourenco D., Aguilar I., Legarra A. and Vitezica Z. 2015. Manual for BLUPF90 family of program. http://nce.ads.uga.edu/wiki/lib/exe/fetch.php?media=blupf90_all2.pdf.

Niknafs S., Abdi H., Fatemi S. and Baneh H. 2013. Genetic trend and inbreeding coefficients effects for growth and reproductive traits in Mazandaran indigenous chicken. Journal of Biology, 3(1): 25-31.

Niknafs S., Nejati A., Mehrabani H. and Fatemi A. 2011. Genetic and phenotypic trends for body weight and egg production in Mazandaran indigenous chicken. Journal of Animal Science, 89:31-32.

Petrus N. P., Mpofu I., Schneider M. B. and Nepembe M. 2011. The constraints and potentials of pig production among communal farmers in Etayi Constituency of Namibia. Livestock Research for Rural Development, 23(7).

R Core Team .2018. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org.

Roos A. P. W., Schrooten C., Veerkamp R. F. and Arendonk J. A. M. 2010. Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls. Journal of Dairy Science, 94: 1559-1567.

Rosa J. O., Venturini G. C., Chud T. C. S., Pires B. C., Buzanskas M. E., Stafuzza N. B., Furquim G. R., Cruz V. A. R., Schmidt G. S., Figueiredo E. A. P., Lima V. F. M. H., Ledur M. C. and Munari D. P. 2018. Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens. Czech Journal of Animal Science, 63(6): 230.236.

Sargolzaei M., Iwaisaki H. and Colleau J. 2006. CFC: A tool for monitoring genetic diversity. In: Proceedings of the 8^th World Congress on Genetic Application in Livestock Production. Belo Horizonte. Brazil, Pp. 27-28.

Shadparvar A. A. and Enayati B. 2012. Genetic parameters for body weight and laying traits in Mazandaran native breeder hens. Iranian Journal of Applied Animal Science, 2: 251-256.

Sonesson A. K., Woolliams J. A. and Meuwissen T. H. E. 2012. Genomic selection requires genomic control of inbreeding. Genetics Selection Evolution, 44: 27-37.

Sun X., Peng T. and Mumm R. H. 2011. The role and basics of computer simulation in support of critical decisions in plant breeding. Molecular Breeding, 28: 421-436.

Szwaczkowski T. 2003. Use of mixed model methodology in poultry breeding: Estimation of genetic parameters. In: W.M. Muir, S.E. Aggrey (Editors). Poultry Genetics, Breeding and Biotechnology. CAB International, 11, 165-201.

Thiruvenkadan A. K., Panneerselvam S. and Prabakaran R. 2010. Layer breeding strategies-an overview. World’s Poultry Sciences Journal, 66: 477-501.

Thiruvenkadan A. K., Prabakaran R. and Panneerselvam S. 2011. Broiler breeding strategies over the decades: an overview. World’s Poultry Sciences Journal, 67: 309-336.

Wang C. and Da Y. 2014. Quantitative genetics model as the unifying model for defining genomic relationship and inbreeding coefficient. PLoS One, 9(12): 1-23.

Weller J. I. 2016. Genomic selection in animals (1^th ed). Wiley Backwell Press. Pp. 192.

Wolc A. 2015. Genomic selection in layer and broiler breeding. LOHMANN Information, 49(1): 4-11.

Wolc A., Zhao H., Arango J., Settar P., Fulton J. and O'Sullivan N. 2015. Response and inbreeding from a genomic selection experiment in layer chickens. Genetics Selection Evolution, 47(1): 59-71.

Zander K. K., Signorello G., Salvo M. D., Gandini G. and Drucker A. G. 2013. Assessing the total economic value of threatened livestock breeds in Italy: Implications for conservation policy. Ecological Economics, 93: 219-229.

Zibei L., Cogan N. O. L., Pembleton L. W., Spangenberg G. C., Forsrer J. W., Hayes B. J. and Daetwyler H. D. 2016. Genetic gain and inbreeding from genomic selection in a simulated commercial breeding program for Penennial Ryegrass. The Plant Genome, 9: 1-12.