Research Note Polymorphisms in AKT3, FIGF, PRKAG3, and TGF-β genes are associated with myofiber characteristics in chickens Sirui Chen ,1 Jianyong An ,1 Ling Lian , Lujiang Qu , Jiangxia Zheng , Guiyun Xu , and Ning Yang 2 National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China ABSTRACT Muscle characteristics such as myofiber for each bird. Six SNP with a very low minor allele fre- diameter, density, and total number are important quency (<1%) were excluded for further analysis. The traits in broiler breeding and production. In the pres- remaining 13 SNP were used for the association study ent study, 19 SNP of 13 major genes, which are located with muscle characteristics. The results showed that in the vicinity of quantitative trait loci affecting breast SNP in TGF-β1/2/3 had significant effects on myofiber muscle weight, including INS, IGF2, PIK3C2A, AKT3, diameter. A SNP in PRKAG3 had a significant effect PRKAB2, PRKAG3, VEGFA, RPS6KA2/3, FIGF, and on myofiber density (P < 0.05). A C > G mutation in TGF-β1/2/3, were chosen to be genotyped by high- FIGF was strongly associated with total fiber number throughput matrix-assisted laser desorption/ionization (P < 0.05). Additionally, birds with the GG genotype time-of-flight mass spectrometry in a broiler popula- of the C > G mutation in AKT3 had significantly larger tion. One hundred twenty birds were slaughtered at 6 myofiber numbers (P < 0.05) than birds with the CC or wk of age. Body weight, breast muscle weight, myofiber GC genotype. The SNP identified in the present study diameter, density, and total number were determined might be used as potential markers in broiler breeding. Key words: AKT3 , FIGF , PRKAG3 , TGF-β , myofiber characteristic 2013 Poultry Science 92 :325–330 http://dx.doi.org/ 10.3382/ps.2012-02766 INTRODUCTION tions in the mammalian target of rapamycin (mTOR) pathway, which have been considered as important me- Muscle is a fibrous composite material at any level diators of protein synthesis and significantly associated of its structure, and as such its macroscopic properties with muscle mass and strength (Nie et al., 2005; Park depend on characteristics at all of these levels. Myofi- et al., 2006). Transforming growth factor β (TGF-β) bers are major components of the muscle tissue. Previ- is a secreted protein that exists in at least 3 isoforms ous studies have attempted to relate the myofiber char- called TGF-β1, TGF-β2, and TGF-β3 (Kambadur acteristics to muscle mass or muscularity in different et al., 1997; Rehfeldt et al., 2000). All 3 isoforms of domestic animal species. Joubert (1956) demonstrated TGF-β are related with the mTOR pathway through that a close relationship exists between myofiber di- their effects on RPS6KB1 via the PP2A gene (Petri- ameter and total musculature in lamb. Double-muscled tsch et al., 2000; Batut et al., 2008). They are unique cattle have twice as many myofibers as normal cattle growth factors because of their multifunctional and di- (Swatland and Kiefer, 1974). In pigs, a positive rela- verse activities in affecting cellular function of a variety tionship between myofiber number and fast growth of different cells (Cordeiro, 2002). All 13 genes we se- rate has been reported (Dwyer and Stickland, 1991). In lected are in the vicinity of QTL affecting breast muscle broiler breeding, myofiber characteristics such as myo- weight (BMW; http://www.animalgenome.org/cgi- fiber diameter, density, and total number are indispens- bin/QTLdb/index). The purpose of this investigation is able indicators of meat quality. to examine the association of genetic variation in these Numerous pathways/gene families/SNP play im- genes with muscle mass and myofiber characteristics in portant roles in muscle weight and tenderness. The chickens. genes AKT3, FIGF, IGF2, INS, PIK3C2A, PRKAB2, PRKAG3, RPS6KA2/3, and VEGFA are crucial junc- MATERIALS AND METHODS Bird Management and Muscle © 2013 Poultry Science Association Inc. Received September 12, 2012. Characterization Accepted October 14, 2012. 1 These authors contributed equally to the work. Chicks from a pure line of broilers were raised on a 2 Corresponding author: [email protected] floor and managed in a conventional way. Commercial 325 326 CHEN ET AL. diets were provided ad libitum. One hundred twenty in 1 mm2 was used to represent the fiber density. The birds in equal numbers of males and females were killed total myofiber number was determined based on the at 6 wk of age. The BW and BMW of each bird were method reported by Gollnick et al. (1981). All proce- measured. The whole chicken was immerged in 10% dures in this experiment were approved by the Animal (vol/vol) buffered formalin fixative pH 7.0 at 4°C for Care Committee of the China Agricultural University. at least 2 d. After fixation, the right side of the breast muscle was removed. A proper sample was taken from Genotyping the anterior portion of the breast by dissecting along the lengthwise myofiber orientation (Figure 1). Sam- Genomic DNA was extracted from the blood sam- ples were processed as described by Scheuermann et al. ples using a traditional phenol-chloroform protocol, (2004). then quantified using a NanoDrop spectrophotometer Muscle sections were stained with hematoxylin and (GE Healthcare Life Sciences, Uppsala, Sweden), and eosin to observe the morphology of the muscle tissue. the final concentrations were 2 to 10 ng/μL. Nineteen The images of the slide were captured by the digital SNP in 13 genes, AKT3, FIGF, IGF2, INS, PIK3C2A, microscope camera linked with a biological microscope PRKAB2, PRKAG3, RPS6KA2/3, TGF-β1/2/3, and (YS100, Nikon, Tokyo, Japan). An image analyzer (Im- VEGFA, were selected from the UCSC SNP database age Pro Plus 5.0, Media Cybernetics, Silver Spring, (http://genome.ucsc.edu/cgi-bin/). Three primers, MD) was used to score all of the parameters in the sec- composed of 2 PCR primers and 1 extension primer, tions. At least 50 fibers in each picture were measured were designed for each SNP (Table 1). Genotyping of to get the mean of the fiber diameter. Number of fibers the 120 individuals was performed using matrix-assist- ed laser desorption/ionization time-of-flight mass spec- trometry on the Mass ARRAY iPLEX Platform (Se- quenom, San Diego, CA). Genotype quality control and data filtering were conducted for all SNP data across the 120 individuals before further analysis. Statistical Analysis Single nucleotide polymorphisms that deviated from the Hardy-Weinberg equilibrium were excluded. The SNP with a genotype call rate <85% and minor allele frequency <1% across all individuals were discarded. The association of the remaining SNP with chicken muscle characteristics was performed with the GLM procedure in SAS version 9.2 software (SAS Institute Inc., Cary, NC). The model was as follows: Yijk = μ + Gi + Sj + Gi × Sj + eijk, where Yijk represents the observed values of the traits, μ is the population mean, Gi is the fixed effect of SNP genotypes, Sj is the fixed effect of sex, Gi × Sj is the interaction effect between SNP genotype and sex, and eijk are the residuals. RESULTS AND DISCUSSION In the present study, genotype quality control and data filtering resulted in the removal of 6 SNP with a low minor allele frequency. The remaining 13 SNP in Hardy-Weinberg equilibrium were finally detected as polymorphic with minor allele frequency > 1% and genotype call rate > 85% (Table 2). Association analy- sis revealed that none of 13 SNP were significantly as- sociated with BW or BMW, although they are in the vicinity of quantitative trait loci affecting BMW. Six Figure 1. Schematic view of pectoralis muscle sampling: a meat sample was taken from the breast by dissecting along the lengthwise of them were significantly associated with at least one myofiber orientation. myofiber characteristic, as shown in Table 3. Table 1. Primer sequences for the selected SNP sites Location Gene SNP code in UCSC1 of SNP Forward primer Reverse primer Extension primer INS Snp.34.128.23869.S.1 Intron 1 ACGTTGGATGTTTGCTTGCTCTGCTCGTAG ACGTTGGATGAACTGTTCTGCATTTGGCCC GCTTCTTCACCCATCAC Snp.34.128.25436.S.1 Intron 1 ACGTTGGATGATAGATGGAGAAGAGTCCCC ACGTTGGATGGAGCTGTACTATAGTTAGGG TCGTACCCTGCCAAGTCCCAATCAT IGF-2 Snp.34.125.29324.S.1 3′-downstream ACGTTGGATGATTACCATTATCAGCGTGCC ACGTTGGATGCCCATCATCCTCTCTCCTAA TCCAATTATCAGCGTGCCCTTGTG region Snp.34.126.10608.S.1 5′-upstream ACGTTGGATGCTCACCAGCAAACATAGCTC ACGTTGGATGTAATGGCCTTCTTCCCATGC ATGCAATCAGCCCCTTAATT region NOTE RESEARCH PIK3C2A Snp.34.179.36113.S.1 Intron 21 ACGTTGGATGGGTGTGGGAAAGGAATTAAG ACGTTGGATGTCCAAGGTATTTGGAATCTG ATGCTCCCTGACTCA Snp.34.179.7791.S.1 5′-upstream ACGTTGGATGTCACAGGTAGGTAGAGCAAG ACGTTGGATGGTGAAGCTTGTTAGGTACCC GAGGTAGAGCAAGTACTTT region Akt3 Snp.9.219.25666.S.2 5′-upstream ACGTTGGATGCGAAACCTTAAGGAAACGCC ACGTTGGATGTGCTGCGTTGCAAAGAATGG TGAAACGCCAGAGGAG region Snp.9.216.35315.S.3 Intron 9 ACGTTGGATGTCTCACCCCCTTCAAAACTC ACGTTGGATGGACAGCTGACTTAAACTGGC TCCTTCCACATGATGTCATA PRKAB2 Snp.40.153.727.S.1 5′-upstream ACGTTGGATGTTGGATATGCCCACAGCTTG ACGTTGGATGCTTCAGACCTCAGTTTCCAC AGTCTGATCTGTTGCTATATGATA region PRKAG3 Snp.15.42.7455.S.1 3′-downstream ACGTTGGATGGGTGTGAGGAGCAAAGAGAG ACGTTGGATGACCTCCTCTTTTTCTCCCTG AAGTAGCAAAGAGAGCTACTC region TGF-β1 Snp.41.175.82522.S.1 5′-upstream ACGTTGGATGTACACAATCCTGTCTAGGAG ACGTTGGATGTCAAGCATCTGTAGGCTCTG GATCCTGTCTAGGAGCATCTC region TGF-β2 Snp.9.573.9474.S.1 Intron 6 ACGTTGGATGCCCTTCGGTGCTTTTGTAAA