Research Note

Polymorphisms in AKT3, FIGF, PRKAG3, and TGF-β 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 (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 RESEARCH NOTE 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 ACGTTGGATGTGCACTGATAGGGAAGGAAG TCCATTCTGAAATTGCAGATAAAAG TGF-β3 Snp.2.355.42866.S.1 Intron 5 ACGTTGGATGAATACGCTGCCTGGATGCTG ACGTTGGATGTCTGGTTCAGGTTTGGAAGC CCCTTGCACCATTAGCTGTGT VEGFA Snp.9.330.1297.S.1 Intron 6 ACGTTGGATGTCTGTACCTGAGCGTAGCAC ACGTTGGATGTATCACGGCACTGAGGTTAG CCACCCCATTGTTATATCCCTG RPS6KA2 Snp.44.76.15963.S.1 3′-downstream ACGTTGGATGTATGAGATGCAGGTGGGTAG ACGTTGGATGAAAGTAACAAACCTGAGCCC CCACGTTGTTGTATCATCTGCCA region Snp.44.77.51327.S.1 Intron 5 ACGTTGGATGTTTCTCATTCCCTGAGCTAC ACGTTGGATGTAAAGAAGAATCCCGGGCAG TCTTACCCAATGTGGC RPS6KA3 Snp.8.634.19641.S.1 Intron 18 ACGTTGGATGACAGATGACCTTTCCCCTTG ACGTTGGATGTCAACCTTCAGCTTGCACAG GAGTACCTTTCCCCTTGCATATCTTA FIGF Snp.8.701.28638.S.1 Intron 4 ACGTTGGATGCCATACTCTGGAGTGAGATG ACGTTGGATGCTCATCCAGTCTTGGTTTGC GGCCGGAGTGAGATGTGAAATCACTTTT Snp.8.701.33425.S.1 Exon 7 ACGTTGGATGCGATGTCCAAAGGAGAAGAG ACGTTGGATGGCAAAGCAGTGGATTTCTGG CCCCCCCTTGACTCAGCTTCT 1UCSC = The University of California, Santa Cruz Genome Browser (http://genome.ucsc.edu). 327 328 Chen et al. Table 2. Frequencies of genotypes and SNP and Hardy-Weinberg equilibrium (HWE) testing

Genotype frequency Allele frequency P-value for Gene SNP code in UCSC1 AA2 BB AB A B HWE testing INS Snp.34.128.23869.S.1 0.582 0.091 0.327 0.745 0.254 0.784 Snp.34.128.25436.S.1 0.571 0.893 0.339 0.741 0.259 0.887 IGF-2 Snp.34.125.29324.S.1 0.589 0.089 0.321 0.750 0.250 0.767 Snp.34.126.10608.S.1 0.571 0.089 0.339 0.741 0.259 0.887 PIK3C2A Snp.34.179.36113.S.1 0.949 0 0.051 0.975 0.025 0.981 Snp.34.179.7791.S.1 0.983 0 0.02 0.992 0.008 0.999 Akt3 Snp.9.219.25666.S.2 0.729 0 0.271 0.864 0.135 0.601 Snp.9.216.35315.S.3 0.491 0.051 0.458 0.720 0.280 0.744 PRKAB2 Snp.40.153.727.S.1 0.932 0 0.068 0.966 0.034 0.965 PRKAG3 Snp.15.42.7455.S.1 0.424 0.051 0.525 0.686 0.314 0.450 TGF-β1 Snp.41.175.82522.S.1 0.304 0.161 0.536 0.571 0.428 0.884 TGF-β2 Snp.9.573.9474.S.1 0.418 0.254 0.327 0.582 0.418 0.224 TGF-β3 Snp.2.355.42866.S.1 0.424 0.068 0.508 0.678 0.322 0.653 VEGFA Snp.9.330.1297.S.1 0.893 0 0.107 0.946 0.054 0.919 RPS6KA2 Snp.44.76.15963.S.1 0.446 0.143 0.411 0.652 0.348 0.883 Snp.44.77.51327.S.1 0.915 0 0.085 0.958 0.042 0.946 RPS6KA3 Snp.8.634.19641.S.1 0.559 0.085 0.356 0.737 0.263 0.911 FIGF Snp.8.701.28638.S.1 0.559 0.017 0.424 0.771 0.229 0.987 Snp.8.701.33425.S.1 0.714 0.036 0.25 0.839 0.161 0.999 1UCSC = The University of California, Santa Cruz Genome Browser (http://genome.ucsc.edu). 2AA means the dominant allele.

Polymorphisms in all 3 isoforms of TGF-β had sig- tion of AKT3 may play a major role in human vascular nificant effects on myofiber diameter, an important smooth muscle cell proliferation. determinant of myofiber hypertrophy. The AA geno- The c-fos-induced growth factor (FIGF) is a mem- type of the G > A polymorphism, located upstream of ber of the platelet-derived growth factor/vascular en- TGF-β1, had a positive effect on myofiber diameter (P dothelial growth factor family. It is a secreted factor < 0.05), whereas it had a negative effect on myofiber with mitogenic and morphogenic activity on fibroblast density (P < 0.05). The GG individuals with the G cells and is located in the downstream region of the > T mutation in TGF-β2 was significantly associated mTOR pathway (Rocchigiani et al., 1998). In this with a larger fiber diameter (P < 0.05) than that of study, a C > G polymorphism was found in the FIGF the TT genotype. The SNP in TGF-β3 also had a sig- gene, and the CC genotype was with a greater total nificant effect on muscle characteristics. Birds with the fiber number (P < 0.05) than that of the GC or GG GG genotype had smaller myofiber diameter (P < 0.05) genotype (Table 3). Orlandini et al. (1996) demon- than those with the TT genotype, whereas the myofiber strated that FIGF is a secreted dimeric protein able density of birds with the GG genotype was significantly to stimulate mitogenic activity in fibroblasts, and its larger (P < 0.01) than that of those with the TT geno- overexpression induces morphological alterations in fi- type. Kennard et al. (2008) demonstrated that TGF-β1 broblasts. promoted the expression of smooth muscle differentia- The PRKAG3 gene, which encodes AMP-activated tion genes during myofibroblast and smooth muscle dif- protein γ-subunit, was considered to be a major ferentiation. In vitro, TGF-β1 played an important role gene affecting meat quality traits (Li et al., 2006). In in vascular smooth muscle cells communication, migra- this study, a polymorphism in the chicken PRKAG3 tion, and proliferation (Qi et al., 2011). The TGF-β gene had a significant effect on myofiber density (P < gene families have been shown to be a potent chemotac- 0.05). Birds possessing the C allele had greater myofi- tic stimulant in fibroblasts (Hogg et al., 1995; Cordeiro ber density (Table 3). Studies of the pig counterpart et al., 2000). suggest that this subunit may play a key role in gly- The RAC-gamma serine/threonine-protein kinase is cogen content and the regulation of energy metabo- an that is encoded by the AKT3 gene in human lism in skeletal muscle (Cheung et al., 2000; Milan et (Borgatti et al., 1997). In current study, birds with the al., 2000; Ciobanu et al., 2001). In humans, PRKAG3 GG genotype of the C > G polymorphism in AKT3 had has increased protein levels in trained skeletal muscle significantly larger myofiber numbers (P < 0.05) than (Nielsen et al., 2003). birds with the CC or GC genotype, as shown in Table We conclude that the TGF-β genes are of particular 3. The AKT are known to be regulators of cell importance for myofiber hypertrophy, and the polymor- signaling and are involved in a wide variety of biological phisms in the AKT3, FIGF, and PRKAG3 genes were processes including cell proliferation, differentiation, as also significantly associated with myofiber characteris- well as glycogen synthesis and glucose uptake (Naka- tics in broilers, as in other animals. The SNP identified tani et al., 1999). Sandirasegarane and Kester (2001) in the present study might be used as potential markers found that phosphoinositide-3kinase-dependent activa- in broiler breeding. Table 3. Single nucleotide polymorphism with a significant effect on muscle characteristics (mean ± SE)

Myofiber Total myofiber Gene SNP code in UCSC1 Genotype BW/g BMW2/g diameter/μm Myofiber density3 number (×105)

PRKAG3 Snp.15.42.7455.S.1 CC 1,492.97 ± 37.77 182.74 ± 6.58 29.09 ± 0.57 785.21 ± 27.35a 9.97 ± 0.46 CT 1,546.66 ± 31.80 186.07 ± 5.78 29.41 ± 0.49 721.90 ± 23.35a 9.64 ± 0.39 TT 1,523.75 ± 107.90 187.50 ± 21.70 32.24 ± 1.64 528.91 ± 78.14b 7.56 ± 1.30 FIGF Snp.8.701.28638.S.1 CC 1,535.40 ± 32.25 187.76 ± 5.83 29.72 ± 0.49 746.65 ± 24.15 10.28 ± 0.38a GC 1,504.31 ± 36.48 179.36 ± 6.30 29.00 ± 0.54 729.97 ± 26.65 9.05 ± 0.42b GG 1,571.00 ± 207.45 188.60 ± 32.80 32.18 ± 2.75 517.35 ± 134.60 7.07 ± 2.08c RESEARCH NOTE Akt3 Snp.9.216.35315.S.3 CC 1,509.93 ± 34.94 185.95 ± 6.20 30.04 ± 0.52 712.50 ± 26.65 8.99 ± 0.39a GC 1,513.02 ± 35.03 179.58 ± 6.12 28.86 ± 0.53 756.14 ± 27.08 9.89 ± 0.39a GG 1,547.00 ± 109.55 184.05 ± 18.60 29.74 ± 1.62 808.67 ± 83.54 12.64 ± 1.22b TGF-β1 Snp.41.175.82522.S.1 AA 1,588.99 ± 43.04 195.36 ± 7.84 31.02 ± 0.69a 663.82 ± 33.74a 9.07 ± 0.58 AG 1,483.47 ± 31.25 180.73 ± 5.90 29.12 ± 0.49b 740.47 ± 24.07b 9.90 ± 0.41 GG 1,505.00 ± 59.98 185.50 ± 10.93 28.56 ± 0.95b 804.34 ± 46.20c 10.13 ± 0.79 TGF-β2 Snp.9.573.9474.S.1 GG 1,546.88 ± 35.95 190.17 ± 6.69 30.42 ± 0.57a 710.09 ± 29.84 9.59 ± 0.48 GT 1,522.80 ± 40.85 186.49 ± 7.59 29.79 ± 0.64b 733.22 ± 33.20 9.54 ± 0.53 TT 1,453.70 ± 50.95 173.94 ± 9.24 27.92 ± 0.79c 772.70 ± 41.40 10.02 ± 0.66 TGF-β3 Snp.2.355.42866.S.1 GG 1,537.33 ± 35.88 184.66 ± 6.19 29.70 ± 0.53a 755.87 ± 26.07A 9.67 ± 0.44 GT 1,496.80 ± 33.40 183.57 ± 6.05 28.78 ± 0.48a 752.68 ± 23.71A 10.02 ± 0.40 TT 1,668.00 ± 103.48 214.93 ± 17.85 33.22 ± 1.49b 527.25 ± 73.47B 8.38 ± 1.25 a–cMeans in same row with a trait lacking common superscripts differ significantly (P < 0.05). A,BMeans in same row with a trait lacking common superscripts differ significantly (P < 0.01). 1UCSC = The University of California, Santa Cruz Genome Browser (http://genome.ucsc.edu). 2BMW = breast muscle weight. 3Myofiber number in 1 mm2. 329 330 Chen et al. ACKNOWLEDGMENTS Li, M. Y., D. W. Chen, and K. Y. Zhang. 2006. PRKAG3 gene expression difference in tissues and organs and the relationships This work was supported in part by funds from Na- between its relative expression and carcass traits in pigs. Chinese J. Anim. Vet. Sci. 37:566–570. tional Natural Science Foundation of China (Beijing; Milan, D., J. T. Jeon, C. Looft, V. Amarger, A. Robic, M. Thel- 31201794), the Chinese Universities Scientific Fund ander, C. R. Gaillard, S. Paul, N. Iannuccelli, L. Rask, H. Ronne, (2012QJ096), and Programs for Changjiang Scholars K. Lundstrom, N. Reinsch, J. Gellin, E. Kalm, P. L. Roy, P. and Innovative Research in University (IRT0945 and Chardon, and L. Andersson. 2000. A mutation in PRKAG3 as- sociated with excess glycogen content in pig skeletal muscle. Sci- IRT1191). ence 288:1248–1251. Nakatani, K., H. Sakaue, D. A. Thompson, R. J. Weigel, and R. A. Roth. 1999. Identification of a human Akt3 ( REFERENCES gamma) which contains the regulatory serine phosphorylation site. Biochem. Biophys. Res. Commun. 257:906–910. Batut, J., B. Schmierer, J. Cao, L. A. Raftery, C. S. Hill, and M. Nie, Q., M. Lei, J. Ouyang, H. Zeng, G. Yang, and X. Zhang. 2005. Howell. 2008. Two highly related regulatory subunits of PP2A Identification and characterization of single nucleotide polymor- exert opposite effects on TGF-β/Activin/Nodal signaling. De- phisms in 12 chicken growth-correlated genes by denaturing high velopment 135:2927–2937. performance liquid chromatography. Genet. Sel. Evol. 37:339– Borgatti, P., G. Zauli, M. L. Colamussi, D. Gibellini, M. Previati, 360. L. L. Cantley, and S. Capitani. 1997. Extracellular HIV-1 Tat Nielsen, J. N., K. J. Mustard, D. A. Graham, H. Y. Yu, C. S. Mac- protein activates phosphatidylinositol 3- and Akt/PKB kinas- Donald, H. Pilegaard, L. J. Goodyear, D. G. Hardie, E. A. Rich- es in CD4+ T lymphoblastoid Jurkat cells. Eur. J. Immunol. ter, and J. F. Wojtaszewski. 2003. 5′-AMP-activated protein ki- 27:2805–2811. nase activity and subunit expression in exercise-trained human Cheung, P. C., I. P. Salt, S. P. Davies, D. G. Hardie, and D. Carling. skeletal muscle. J. Appl. Physiol. 94:631–641. 2000. Characterization of AMP-activated protein kinase gamma- Orlandini, M., L. Marconcini, R. Ferruzzi, and S. Oliviero. 1996. subunit isoforms and their role in AMP binding. Biochem. J. Identification of a c-fos-induced gene that is related to the plate- 346:659–669. let-derived growth factor/vascular endothelial growth factor fam- Ciobanu, D., J. Bastiaansen, M. Malek, J. Helm, J. Woollard, G. ily. Proc. Natl. Acad. Sci. USA 93:11675–11680. Plastow, and M. Rothschild. 2001. Evidence for new alleles in the Park, H. B., L. Jacobasson, P. Wahlberg, P. B. Siegel, and L. An- protein kinase adenosine monophosphate activated γ -subunit 3 derson. 2006. QTL analysis of body composition and metabolic gene associated with low glycogen content in pig skeletal muscle traits in an intercross between chicken lines divergently selected and improved meat quality. Genetics 159:1151–1162. for growth. Physiol. Genomics 25:216–223. Cordeiro, M. F., S. S. Bhattacharya, G. S. Schultz, and P. T. Khaw. Petritsch, C., H. Beug, A. Balmain, and M. Oft. 2000. TGF-β inhib- 2000. TGF-β1, -β2 & -β3 in vitro: Biphasic effects on tenon’s its p70 S6 kinase via protein phosphatase 2A to induce G arrest. fibroblast contraction, proliferation & migration. Invest. Oph- 1 Genes Dev. 14:3093–3101. thalmol. Vis. Sci. 41:756–763. Qi, Y. X., J. Jiang, X. H. Jiang, X. D. Wang, S. Y. Ji, Y. Han, D. Cordeiro, M. F. 2002. Beyond mitomycin: TGF-β and wound heal- K. Long, B. R. Shen, Z. Q. Yan, S. Chien, and X. L. Jiang. 2011. ing. Prog. Retin. Eye Res. 21:75–89. PDGF-BB and TGF-β1 on cross-talk between endothelial and Dwyer, C. M., and N. C. Stickland. 1991. Sources of variation in smooth muscle cells in vascular remodeling induced by low shear myofiber number with and between litters of pigs. Anim. Prod. stress. Proc. Natl. Acad. Sci. USA 108:1908–1913. 52:527–533. Rehfeldt, C., I. Fiedler, G. Dietl, and K. Ender. 2000. Myogenesis Gollnick, P. D., B. Pernow, B. Essen, E. Jansson, and B. Saltin. and postnatal skeletal muscle cell growth as influenced by selec- 1981. Availability of glycogen and plasma FFA for substrate uti- tion. Livest. Prod. Sci. 66:177–188. lization in leg muscle of man during exercise. Clin. Physiol. Rocchigiani, M., M. Lestingi, A. Luddi, M. Orlandini, B. Franco, 1:27–42. E. Rossi, A. Ballabio, O. Zuffardi, and S. Oliviero. 1998. Hu- Hogg, P., M. Calthorpe, S. Ward, and I. Grierson. 1995. Migration man FIGF: Cloning, gene structure, and mapping to chromo- of cultured bovine trabecular meshwork cells to aqueous humor some Xp22.1 between the PIGA and the GRPR genes. Genomics and constituents. Invest. Ophthalmol. Vis. Sci. 36:2449–2460. 47:207–216. Joubert, D. M. 1956. Analysis of factors influencing postnatal growth Sandirasegarane, L., and M. Kester. 2001. Enhanced stimulation of and development of the muscle fiber. J. Agric. Sci. 47:59–102. Akt-3/protein kinase B-gamma in human aortic smooth muscle Kambadur, R., M. Sharma, T. P. Smith, and J. J. Bass. 1997. Muta- cells. Biochem. Biophys. Res. Commun. 283:158–163. tions in myostatin (GDF8) in double-muscled Belgian blue and Scheuermann, G. N., S. F. Bilgili, S. Tuzun, and D. R. Mulvaney. Piedmontese cattle. Genome Res. 7:910–916. 2004. Comparison of chicken genotypes: Myofiber number in pec- Kennard, S., H. Liu, and B. Lilly. 2008. Transforming growth factor- toralis muscle and myostatin ontogeny. Poult. Sci. 83:1404–1412. beta (TGF-beta 1) down-regulates Notch 3 in fibroblasts to pro- Swatland, H. J., and N. M. Kiefer. 1974. Fetal development of dou- mote smooth muscle gene expression. J. Biol. Chem. 283:1324– ble-muscled condition in cattle. J. Anim. Sci. 38:752–757. 1333.