مطالعه پویش کل ژنومی صفات کیفی گوشت در جمعیت F2 حاصل از مرغ بومی آذربایجان غربی و سویه گوشتی آرین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری اصلاح نژاد دام دانشگاه تربیت مدرس

2 عضو هیئت علمی دانشگاه تربیت مدرس

چکیده

در این تحقیق به منظور شناسایی جایگاه‌ها و ژن‌های مرتبط با صفات کیفیت گوشت، مطالعه پویش کل ژنوم (GWAS) با استفاده از یک تراشه SNP ژنوم مرغ (SNP Beadchip (Illumnia 60k Chicken در یک جمعیت F2 حاصل از تلاقی دوطرفه مرغ بومی آذربایجان غربی و لاین B سویه گوشتی آرین انجام شد. برای هر پرنده، صفات شامل: ظرفیت نگهداری آب، رنگ گوشت (روشنایی ، قرمزی و زردی)، میزان نیروی برشی و PH نهایی گوشت اندازه‌گیری شد. با استفاده از دو مدل خطی معمول (GLM) و مدل خطی مختلط فشرده (Compressed MLM) ارتباط هر یک SNP‌ها با صفات کیفیت گوشت بررسی شد. در مجموع تعداد 36 نشانگر SNP در سطح احتمال پیشنهادی و معنی‌داری برای صفات کیفیت گوشت شناسایی شد که تعداد 3 نشانگر SNP با روش Compressed MLM برای صفت فاکتور زردی گوشت و تعداد 18 نشانگر SNP با روش GLM برای صفات فاکتور زردی گوشت، pH نهایی گوشت، ظرفیت نگهداری آب و میزان نیروی برشی معنی‌دار شدند. ژن‌های کاندیدای شناسایی‌شده، عملکرد مولکولی مرتبط با صفات کیفیت گوشت داشتند و لذا می‌توان از این ژن‌های کاندیدا در برنامه‌های اصلاحی طیور مورد استفاده قرار‌داد.

کلیدواژه‌ها


عنوان مقاله [English]

Genome-Wide Association Study for meat quality traits in an F2 intercross between Azerbaijan native chickens and Ariyan broiler line

نویسندگان [English]

  • ali javanrouh aliabad 1
  • Ali akbar masoudi 2
  • alireza ehsani 2
2 member of science Tarbiat Modares University
چکیده [English]

In order to identify loci and genes associated with meat quality traits, genome-wide association study (GWAS) were conducted in a F2 population derived from a reciprocal cross between Azerbaijan native chickens and Aryan broiler line by using Illumnia 60 K Chicken SNP Bead chip. For each bird, a total 6 traits including water holding capacity, meat color lightness (L*), redness (a*), yellowness (b*), shear force and ultimate pH were measured. The SNPs that were associated with meat quality traits were identified using both GLM and compressed mixed linear models (CMLM). A total of 36 SNPs were associated with meat quality traits in the genome–wide significance and suggestive levels, that 3 SNPs were significantly associated with meat color yellowness through CMLM model and 18 SNPs were suggestively associated with meat color yellowness, ultimate pH, water holding capacity and shear force through GLM model. The identified candidate genes have molecular functions related to meat quality traits. So, these candidate genes can be applied in the chicken breeding scheme.

کلیدواژه‌ها [English]

  • candidate genes
  • chicken
  • F2 population
  • GWAS
  • Meat quality traits
Archibald AL, Cockett NE, Dalrymple BP, Faraut T, Kijas JW, Maddox JF, McEwan JC, Hutton Oddy V, Raadsma HW, Wade C, Wang J, Wang W and Xun X (2010) The sheep genome reference sequence: a work in progress. Animal Genetics. 41: 449-453. 
Bihan-Duval EL, Debut M, Berri CM, Sellier N, Lhoutellier VS, Jégo Y and Beaumont C (2008) Chicken meat quality: genetic variability and relationship with growth and muscle characteristics. BMC Genetics. 9: 53-58.
Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y and Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics. 23(19): 2633-2635.
Burkard TR, Planyavsky M, Kaupe I, Breitwieser FP, Bürckstümmer T, Bennett KL, Superti-Furga G and Colinge J (2011) Initial characterization of the human central proteome. BMC System Biology. 5: 17.
Chaurasia SS, Haque R, Pozdeyev N, Jackson CR and Iuvone PM (2006) Temporal coupling of cyclic AMP and Ca/calmodulin-stimulated adenylyl cyclase to the circadian clock in chick retinal photoreceptor cells. Journal of Neurochemistry. 99(4): 1142-1150.
Cheadle L and Biederer T (2012) The novel synaptogenic protein Farp1 links postsynaptic cytoskeletal dynamics and transsynaptic organization.  The Journal of Cell Biology. 199: 985-1001.
Chen MH, Kabir K and Yang JH (2000) Editing activity of mouse RED2 (ADAR3) in vitro. Submitted to the EMBL/GenBank/DDBJ databases.
Chen S, An J, Lian L, Qu L, Zheng J, Xu G and Yang N (2013) Polymorphisms in AKT3, FIGF, PRKAG3, and TGF-β genes are associated with myofiber characteristics in chickens. Poultry Science. 92(2): 325-330.
Church DM, Goodstadt L, Hillier LW, Zody MC, Goldstein S, She X, Bult CJ, Agarwala R, Cherry L, DiCuccio M, Hlavina W, Kapustin Y, Meric P, Maglott D, Birtle Z, Marques AC, Graves T, Zhou S,Teague B, Potamousis K, Churas C, Place M, Herschleb J, Runnheim R, Forrest D, Amos-Landgraf J, Schwartz DC, Cheng Z, Lindblad-Toh K, Eichler EE and Ponting CP (2009) Lineage-specific biology revealed by a finished genome assembly of the mouse. PLoS Biology. 7(5): e1000112.
Harhay GP, Sonstegard TS, Keele JW, Heaton MP, Clawson ML, Snelling WM, Wiedmann RT, Van Tassell CP and Smith TP (2005) Characterization of 954 bovine full-CDS cDNA sequences. BMC Genomics. DOI: 10.1186/1471-2164-6-166.
Hillier LW, Miller W, Birney E, Warren W, Hardison RC, Ponting CP, Bork P, Burt DW, Groenen MAM, Delany ME, Dodgson JB, Chinwalla AT, Cliften PF,Clifton SW, Delehaunty KD, Fronick C, Fulton RS and Graves TA (2004) Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature.  432: 695-716.
Huttlin EL, Jedrychowski MP, Elias JE, Goswami T, Rad R, Beausoleil SA, Villén J, Haas W, Sowa ME and Gygi SP (2010) A tissue-specific atlas of mouse protein phosphorylation and expression. Cell. 143(7): 1174-89.  
Liu R, Sun Y, Zhao, G, Wang F, Wu D, Zheng M, Chen J, Zhang L, Hu Y and Wen J (2013) Genome-Wide Association Study Identifies Loci and Candidate Genes for Body Composition and Meat Quality Traits in Beijing-You Chickens. PLOS ONE. 8(4): e61172.
Nadaf J, Gilbert H, Pitel F, Berri CM, Feve K, Beaumont C, Duclos MJ and Vignal A (2007) Identification of QTL controlling meat quality traits in an F2 cross between two chicken lines selected for either low or high growth rate. BMC Genomics DOI: 10.1186/1471-2164-8-155.
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ and Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses.The American Journal of Human Genetics. 81(3): 559-75.
 Sun Y, Zhao G, Liu R, Zheng M,  Hu Y, Wu D, Zhang L, Li P and Jie Wen (2013) The identification of 14 new genes for meat quality traits in chicken using a genome-wide association study. BMC Genomics. 14: 458
Turner S (2014) Package qqman: Q-Q and manhattan plots for GWAS data.
Van Kaam JB, Groenen MA, Bovenhuis H, Veenendaal A, Vereijken AL and Van Arendonk JA (1999) Whole genome scan in chickens for quantitative trait loci affecting carcass traits. Poultry Science. 78(8): 1091-9.
VanRaden PM (2008) Efficient Methods to Compute Genomic Predictions. Journal of Dairy Science. 91: 4414–4423.
Wright  D, Kerje S, Lundström K, Babol J, Schütz K, Jensen P and Andersson L (2006) Quantitative trait loci analysis of egg and meat production traits in a red jungle fowl White Leghorn cross. Animal Genetics. 37(6): 529-534.
Zeng F, Xie L, Pang X, Liu W, Nie Q and Zhang X (2011) Complementary deoxyribonucleic acid cloning of avian G0/G1 switch gene 2, and its expression and association with production traits in chicken. Poultry Science. 90(7): 1548-54.
Zhang Z, Ersoz E, Lai CQ, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu J, Arnett DK, Ordovas JM and Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nature Genetics. 42(4): 355-60.
Zhang T, Fan QC, Wang JY, Zhang GX, Gu YP and Tang Y (2015) Genome-wide association study of meat quality in chicken. Genetics and Molecular Research. 14(3): 10452-10460.
Zimin AV, Delcher AL, Florea L, Kelley DR, Schatz MC, Puiu D, Hanrahan F, Pertea G, Van Tassell CP, Sonstegard TS, Marçais G, Roberts M, Subramanian P, Yorke JA and Salzberg SL (2009) A whole-genome assembly of the domestic cow, Bos taurus. Genome Biology. 10(4): R42.