An Investigation into the Genetic
Controls of Pork Quality
Steven Moeller1, Keith Irvin1,
1The Ohio State University, Department of Animal Sciences, Columbus, Ohio
Consumers and many sectors of the pork industry are demanding improvements in meat quality. This provides a new challenge for the breeding industry, which is seeking advanced genetic tools that can be practically incorporated in selection schemes for trait improvement. The heightened interest in meat (muscle) quality has led to investigations into the physiological and genetic controls of these economically important traits. Often studies in livestock are modeled after known rodent or human genetic markers associated with diseases, which may also be related to body composition or changes in energy metabolism. Genetic markers characterized in other species serve as guides or “candidate” genes for investigation of the phenotypic differences found in swine.
Although several genetic markers and QTLs affecting meat quality and performance traits have been detected in the pig (for review see Rothschild and Plastow, 1999), the quest continues to identify markers that explain significant variation in these traits of economic importance. It is anticipated that the detection of new molecular genetic markers, together with advances in the area of quantitative genetics, will lead to the development of marker assisted selection (MAS) programs for meat quality improvement and practical utilization by swine producers.
As more information becomes available in swine molecular genetics, there exists a need to analyze associations between these markers and phenotypes in individual genetic lines or populations. The objective of this study was to determine the association between variation found in performance, carcass, and meat quality traits and several candidate genes of interest in different pig populations.
Materials & Methods
Candidate Gene Association Studies
The population utilized for the project consisted of both purebred and crossbred animals from the 1998 National Barrow Show Progeny Test and the 1999 Hampshire Sire Progeny Test. All animals were managed by identical protocols, and performance, carcass, meat quality, and sensory panel measurements were taken on each animal. Individuals of four major U.S. breeds were chosen for DNA extraction from frozen loin chops. Berkshire (n=180), Duroc (n=77), Hampshire (n=160), and Landrace (n=55) sire breeds were represented. Genotypes were obtained for six candidate genes using Polymerase Chain Reaction – Restriction Fragment Length Polymorphism (PCR-RFLP) procedures unique for each gene analyzed. Statistical analyses were performed within each breed separately, and across breeds for the total population. Only pigs classified as free of the Porcine Stress Syndrome mutation were utilized in these analyses. A SAS (1999) Mixed Model analysis was completed for the total population utilizing the fixed effects of breed, genotype, sex, day off-test group (depending on the trait), and Rendement Napole (RN) gene status, with a sire(breed) random effect. The within breed analysis included a random effect of sire, and fixed effects of genotype, sex, day off-test group (depending on the trait), and RN classification. A second PPARg analysis excluding the underrepresented 22-genotype animals (n=12) was performed to more clearly define the differences between the 11 and 12-animals. Allelic frequencies were calculated within breed and for the total population based upon observed genotype classifications.
Two additional genes were chosen as possible candidate genes for meat quality based on their observed physiological functions in other mammalian species. Primers for use in PCR amplification were designed based on porcine sequence available for each gene in GenBank. PCR conditions were optimized for each gene separately. Sequencing and comparisons of breed DNA pools were completed in order to search for sequence variation among the breeds. Physical mapping was achieved by use of a pig-rodent somatic cell hybrid panel (Yerle et al., 1996).
Leptin Receptor (LEPR)
Daily gain and backfat thickness are important traits for livestock producers to consider in order to produce efficient, fast growing and lean animals. The leptin receptor gene (LEPR), is a high affinity receptor (for review see Tartaglia, 1997) that mediates the regulation of the well known “obesity” gene, leptin (Zhang et al., 1997). Mutations in LEPR have been reported to be associated with obesity in humans and rodents (Reichart et al., 2000; Clement et al., 1998; Chen et al., 1996). Given the physiological role of LEPR, it is interesting as a candidate gene for backfat deposition and daily gain in the pig. Vincent et al. (1997) identified a HinfI polymorphism in porcine LEPR and mapped its location to pig chromosome 6 (SSC6). A few studies have reported on associations between leptin levels and production traits in pigs (Ramsay et al. 1998; Robert et al. 1998), but the effects of LEPR on pork quality traits of economic importance to the industry have not been investigated.
A leptin receptor (LEPR) MboI RFLP, developed by Vincent at Iowa State University (M.F. Rothschild, personal communication), was found to be polymorphic in all breeds analyzed; Berkshire (n=177), Duroc (n=76), Landrace (n=49), and Hampshire (n=149). Allele 2 was the most frequent (.91) in the total population and was found to be associated with leaner animals (Table 1).
Total population analysis revealed effects (P<.05) of LEPR on last lumbar backfat with the 11-animals having the fattest phenotype (Table 1). Although not significant (P>.05), last rib and 10th rib backfat (not shown) had similar numerical trends. Average daily gain was also different (P<.05) between the genotypes (Table 1). The results of the individual breed analyses (not shown) revealed differences (P<.05) between LEPR genotypes and off flavor score for Berkshire; average daily gain and Japanese color score for Duroc; glycolytic potential, loin glycogen and lactate concentration, intramuscular fat, and quality index (which includes Minolta, IMF, & pHu) for Hampshire; 10th rib backfat, average daily gain, loin pHu, Minolta and Hunter color values, and quality index for Landrace.
As previously reported in other mammalian species, LEPR appears to have the greatest effects on backfat and average daily gain in the pig, but may also be associated with correlated pork quality differences within genetic lines.
Melanocortin-4 Receptor (MC4R)
Melanocortin-4 receptor (MC4R) has been found to play a significant role in regulating leptin’s effects on food intake and body weight (Seeley et al., 1997; Fan et al., 1997). Kim et al. (2000) demonstrated that a missense mutation in MC4R was associated with backfat thickness, growth, and feed intake in different genetic lines of pigs. No studies to date have reported associations between meat quality characteristics and MC4R genotypes.
Results with the TaqI MC4R RFLP, developed by Kim et al. (2000), show an allelic frequency of .60 for allele 2, which was associated with much fatter animals in the total population. Genotypic frequencies varied within the breeds, however the heterozygote 12-animals were the most frequent (.45) in the total population.
The effect of MC4R on last lumbar backfat was highly significant (P<.001) (Table 1). Approximately, 0.18 cm in last lumbar backfat is added with the inclusion of each 2 allele. MC4R genotype groups were also different (P<.05) for last rib backfat. and 10th rib backfat approached significance (P=.085) with the fatter 22-animals being in line with the last lumbar result. These backfat results are also in agreement with Kim et al. (2000) who demonstrated that 11-homozygote pigs had approximately 9 % less backfat than 22-pigs. Instron force was less (P<.05) for the 22-genotype (Table 1), indicating increased tenderness in the fatter animals. Interesting trends in loin muscle area, average daily gain, and color score were also noted. The results of the individual breed analysis (not shown) revealed differences (P<.05) between MC4R genotypes and soundness score, last lumbar backfat, last rib backfat, average backfat, average daily gain, and loin lactate concentration for Berkshire; and juiciness score, intramuscular fat, Minolta, Hunter color, and quality index for Landrace.
Our results suggest that MC4R has its greatest effects on backfat and Instron tenderness for the total population. However, differences between MC4R genotypes were also reported for average daily gain and meat quality traits within the breed populations. Further analysis in larger populations will be needed with this marker to fully characterize the effects of MC4R on meat quality.
Mealnocortin-5 Receptor (MC5R)
Melanocortin-5 receptor (MC5R) has been found to be associated with thermoregulation through gland secretion (van der Kraan et al., 1998; Chen et al., 1997) and serves a possible role in lipolysis of adipocytes (Boston, 1999). Kim et al. (1999) mapped porcine MC5R to SSC 6 and detected two single nucleotide polymorphisms within the porcine sequence. Previous analyses have not investigated the association between the porcine MC5R gene and fat deposition, growth or carcass quality traits in pigs.
Results indicate that the MC5R BsaHI RFLP, developed by Kim et al. (1999) was polymorphic in Berkshire, Duroc, Landrace and Hampshire populations. The frequency of alelle 1 was .82. Genotypic frequencies varied within the breeds, however, the homozygote 11-animals were the most frequent (.75) in the total population.
Total population analysis revealed effects (P<.05) of MC5R on 10th rib backfat (Table 1), with the 11 and 12-animals being fatter. Similar numerical differences were also noted for the last rib location (P=.14). Loin muscle area also approached significance for the total population analysis (P=.10). The results of the individual breed analysis (not shown) revealed differences (P<.05) between MC5R genotypes with color and Japanese subjective scores, Minolta and Hunter color values, as well as, Instron tenderness for Berkshire; quality index for Hampshires; all backfat measures and intramuscular fat % for Landrace.
This MC5R BsaHI RFLP appears to have its greatest effects on backfat in the total population. Further analysis is needed to fully characterize the differences in meat quality characteristics such as color and intramuscular fat % within the breed populations.
Peroxisome Proliferator Activated Receptor-g (PPARg)
Peroxisome Proliferator Activated Receptor-gamma (PPARg) is a member of the nuclear receptor superfamily (for review see Green, 1995) and regulates the expression of several genes encoding proteins involved in adipocyte differentiation (Rosen et al., 2000; Spiegelman et al., 1997) and fat deposition (for review see Schoonjans et al., 1996). Genetic mutations in PPARg have been found to be associated with extreme obesity in humans (Freake, 1999). In pigs, PPARg expression levels in adipose tissue vary among different breeds and ages (Grindflek et al., 1998). An association study (Grindflek, in manuscript), reported a difference in loin fatty acid composition in Norwegian pigs for a BsrI RFLP, but no significant differences were noted for backfat or intramuscular fat measurements.
Our results show that a BsrI PPARg RFLP (Grindflek, personal communication) was polymorphic in Berkshire, Duroc, Landrace, and Hampshire populations. The frequency of allele 1 was .81. Total population analysis revealed effects (P<.05) on off flavor score (Table 1), although interesting trends in average daily gain, tenderness and juiciness approached significance. The results of the individual breed analysis (not shown) revealed differences (P<.05) between PPARg genotypes and loin muscle area and marbling for Duroc, average daily gain for Hampshire; and last rib backfat, and Instron tenderness for Landrace. This PPARg RFLP remains an interesting candidate gene for meat quality traits within specific lines of swine. These results, while promising, warrant larger scale investigation to determine the potential use of PPARg in future selection programs.
Heart Fatty Acid Binding Protein (HFABP)
Intramuscular fat percentage (IMF) has been found to be positively associated with sensory attributes of pork (Fernandez et al., 1999; Touraille et al., 1989). Hovenier et al. (1992) reported that backfat reduction is not completely related with reductions in IMF. Therefore, it may be possible to treat the two traits separately in a breeding scheme with the proper selection tools.
Heart Fatty Acid Binding Protein-1 (HFABP) is a member of the fatty acid binding protein family (FABP), which is involved in fatty acid transport from the cell membrane to the intracellular sites of fatty acid utilization (Veerkamp and Maatman, 1995). Given this physiological role, HFABP has been considered to be an interesting candidate gene for IMF and backfat in pigs. Gerbens et al. (1997) mapped HFABP to pig chromosome 6. QTL studies have also identified IMF and BF loci in this region of chromosome 6 (Ovilo et al. 2000b; de Koning et al., 1999), further implicating HFABP as a strong candidate gene for IMF and backfat in the pig.
Gerbens et al. (1997) reported three polymorphic sites in the porcine HFABP gene (HaeIII, MspI, and HinfI) and conducted an association study to determine the genotype effects on traits in pigs (Gerbens et al., 1999). This study reported IMF and backfat differences between HFABP genotype groups and thus hypothesized that HFABP, or a closely linked marker, controlled IMF differences in pigs. Two of these markers were also informative in a Norwegian pig population (E. Grindflek, personal communication), and Ovilo et al. (2000a) also reported differences in genotype groups for the HFABP HaeIII RFLP.
Results from our population show that the HaeIII HFABP RFLP (originally reported by Gerbens et al., 1997) is polymorphic in Berkshire, Duroc, Landrace and Hampshire populations. The frequency of allele 1 was .63. Total population analysis reveals effects of HFABP on ultimate loin pH (P<.05) and quality index (P<.01) (Table 2), and intramuscular fat % and pork flavor also showed interesting trends. The results of the individual breed analysis (not shown) revealed differences between HFABP genotypes and loin muscle area, loin glycogen concentration, intramuscular fat, Instron tenderness, and quality index for Berkshire. The Berkshire analysis results are similar to those of Gerbens et al. (1999), which found an advantage of the HaeIII HFABP 12-heterozygote for intramuscular fat % and backfat. Loin glycogen concentration was also significantly different (P<.05) in Duroc; last rib backfat, flavor score, and water holding capacity for Hampshire; and last rib backfat, and intramuscular fat for Landrace. HFABP remains an interesting candidate gene for meat quality traits of importance within specific breeds of swine.
Tenderness is an important quality attribute that pork consumers desire (Moeller, 1999). However, currently there are few direct selection tools that can be utilized to improve this important trait in livestock. Calpain, a calcium-dependent protease, has been reported to be a contributor to the postmortem tenderization of skeletal muscle (for review see Koohmaraie, 1996). Calpastatin (CAST) is the endogenous inhibitor of the calpains. Levels of calpastatin vary considerably between species (Koohmaraie, 1991; Ouali and Talmant, 1990), breeds (Shackelford et al., 1994) and muscles (Geesink et al., 1992). Many studies in livestock, particularly beef animals, have been completed to determine calpastatin’s physiological role in tenderness, as well as the genetic components of the CAST gene (Parr et al., 1999; Boehm et al., 1998; Huff-Lonergan et al., 1996; Lonergan et al., 1995; Killefer and Koohmaraie, 1994). Previous studies have found an inverse relationship between calpastatin levels and the development of tenderness in meat (Sensky et al., 1996; Koohmaraie et al., 1994; Koohmaraie et al., 1991). The relationship between levels of calpastatin and muscle growth has also been investigated in livestock (for review see Goll et al., 1998).
Results of the two CAST RFLPs: RsaI (CASTRsa) and MspI (CASTMsp) (developed by Ernst et al., 1999) indicate that the markers were polymorphic in all breeds analyzed: Berkshire (n=169), Duroc (n=76), Landrace (n=48), and Hampshire (n=150). The frequency of allele 1 for CASTRsa was .75. Allele 1 of CASTRsa was associated with fatter animals in the total population. Genotypic frequencies varied among the breeds, however the CASTRsa 11-animals were the most frequent (.58) in the total population. Interestingly, the allelic frequencies for the CASTMsp marker were the opposite of the CASTRsa RFLP with .29 for allele 1. Allele 2 of CASTMsp was associated with fatter animals in the total population, and the 22-animals were the most frequent (.53) in the total population.
Total population analysis reveals effects (P<.05) of CASTRsa and CASTMsp on last lumbar backfat, 10th rib backfat, and loin muscle area (Table 2). Ultimate loin pH, tenderness score, and Instron tenderness (CASTMsp only) also approached significance for the total population. The results of the individual breed analysis (not shown) revealed differences (P<.05) between CASTRsa and CASTMsp genotypes for Instron tenderness in Berkshire; loin muscle area in Duroc; and last lumbar backfat, average backfat and loin muscle area in Landrace. Hampshire genotypes differed (P<.05) for Japanese color and color scores for the CASTMsp locus and tenderness score for the CASTRsa locus. These CAST RFLPs remain interesting genetic markers for the improvement of carcass composition in pigs.
Mapping of Adipocyte Determination and Differentiation Factor-1 (ADD) to SSC 12.
Adipocyte determination and differentiation factor-1 (ADD1), also known as, sterol regulatory element binding protein-1 (SREBP1) in human and mouse studies, is a transcription factor believed to play a role in encoding enzymes of lipid biosynthesis (Wang, et al., 1994; Shimomura et al., 1998), and may also be involved in the control of plasma cholesterol levels (Yokayama et al, 1993). ADD1 has been reported to increase the activity of peroxisome proliferator activated receptor-g (PPARg), another transcription factor involved in adipocyte differentiation (Kim et al., 1998), and Boizard et al. (1998) demonstrated that ADD1 is involved in the over expression of fatty-acid synthase gene (FAS) in obese mice. Along the same lines, Ding et al. (1999) reported that the expression of ADD1 is positively associated with porcine adipocyte differentiation both in vivo and in vitro. Shimomura et al. (1998) demonstrated a decrease in fat deposits in transgenic mice that over expressed SREBP1. Given the physiological effects of this gene in other mammalian species, ADD1 may also control backfat deposition in the pig, and may correlate with variation in meat quality traits.
The ADD1 PCR fragment amplified in the pig was 95% homologous to the rat, and 83% homologous to human ADD1 sequence. Polymorphisms between the breed pools sequenced were also noted. Analysis of 27 porcine-rodent somatic cell hybrids (Yerle et al., 1996) determined regional assignment of ADD1 to porcine chromosome (SSC) 12 with 1.0 probability and to region 12p11-q15 with .95 probability (Figure 1). Results from the physical mapping in this study are in agreement with the localization of human ADD1 to HSA 17p11.2 (Hua et al., 1995), and chromosomal homologies between pig chromosome 12 and human chromosome 17 (Shi et al., 2000; Goureau et al., 1996). Other markers for meat quality have also been found on SSC 12 (Malek et al., 2000; Anderson-Eklund et al.,1996), therefore further analysis of genes on this chromosome is warranted.
A two-point linkage analysis was performed in five of the PiGMaP families (Archibald et al., 1995) using the CRI-MAP program (Green et al., 1990), and close linkage was found between ADD1 and markers previously mapped to the distal end of the q-arm of porcine chromosome 12, which confirms the physical mapping position of ADD1. Further association studies utilizing the ADD1 RFLPs detected are planned in order to determine the effects of ADD1 on backfat and meat quality characteristics in the pig.
Mapping of Pyruvate Dehydrogenase E1-alpha (PDHA1) to SSC X
The pyruvate dehydrogenase (PDH) complex contains multiple copies of three enzymes: E1, E2 and E3 (Ho et al., 1989). The E1-alpha subunit plays a key role in the function of the PDH complex since it contains the E1 active site, which may be thought of as the enzyme’s “on/off” switch. The E1-alpha subunit functions specifically to catalyze the decarboxylation of pyruvate into acetyl-CoA (Reed, 1974). A deficiency in PDH is one of the most commonly defined genetic defects of mitochondrial energy metabolism in humans (Robinson et al., 1987). The PDH complex effects energy metabolism in the cell as it is a rate-limiting enzyme connecting glycolysis with the tricarboxylic acid (TCA) cycle (Lissens et al, 2000). Thus, the PDH complex plays an essential role in carbohydrate metabolism. Ward et al. (1982) reported that activation of PDH regulates the use of glycogen and glucose during exercise in humans, while Hagg et al. (1976) found that PDH activity is increased in rats that were exercised. Peters et al. (1998) reported that carbohydrate metabolism is decreased when PDH is down-regulated.
Analysis of 27 porcine-rodent somatic cell hybrids (Yerle et al., 1996) allowed regional assignment of PDHA1 to porcine chromosome (SSC) X with 1.0 probability and to region Xp22-p23 with .81 probability (Figure 1). Results from the physical mapping in this study are in agreement with the localization of the human pyruvate dehydrogenase E1-alpha subunit to HSA Xp22.2-Xp22.1 (Borglum et al., 1997). Quantitative trait loci (QTL) for backfat and production traits (Rohrer et al.,1998ab), as well as off flavor score (Malek et al., 2000) have also been reported on SSC X. Future linkage analysis to confirm the mapping location is planned, as well as, association studies to determine the effects of PDHA1 on meat quality in breed populations.
Pork producers currently utilize expected progeny differences (EPD), production indexes, phenotypic selection, and information on “major gene” (RN & Halothane) status, in order to improve traits of economic importance in pigs. The practical implementation of MAS in commercial swine production will depend on future advances of both molecular and quantitative genetics.
This study contributes to the information available on genetic markers that have potential to be utilized in genetic improvement programs of commercial herds. The results also highlight the need for continued investigation of the effects of candidate genes within specific genetic lines. Larger populations will be needed in order to fully characterize the effects of these markers on traits of interest. It is important to note that the markers used for these association studies represent a single change in each gene of interest. There are potentially more markers within each gene, some of which may have greater effects where they have a direct effect on the trait, or they are in linkage disequilibrium with a causative mutation. The addition of two new genetic markers (ADD1 and PDHA1) increases the information available on the pig genome, as well as provides potential new gene markers for the improvement of pork quality through marker assisted selection. Continued investigations with ADD1 and PDHA1 polymorphisms are planned in order to further define their effects on pork quality. Results of this study indicate, there is great potential for the improvement of meat quality traits through the use of genetic markers in swine
Access to primer sequences was provided by Dr. Graham Plastow of the PIC International Group, UK, Dr. Max Rothschild and Kwan-Suk Kim of Iowa State University, and Ms. Eli Grindflek of the Agricultural University of Norway.
The technical assistance of Ms. Eli Grindflek, Ms. Jeannine Helm, and Dr. Stephan Marklund at Iowa State University was greatly appreciated. Thanks to Dr. Michael Davis of The Ohio State University for statistical advice.
Partial funding and access to animals were provided by: The Ohio State University Department of Animal Sciences, The National Pork Producers Council, the National Swine Registry, the Hampshire Swine Registry, and the Iowa Agriculture and Home Economics Experiment Station, as well as by Hatch Act and State of Iowa funds.
Andersson-Eklund, L., et al. 1996. Animal Genetics. 27 (Supp. 2):111.
Archibald A. et al., 1995. Mammalian Genome. 6:157-175.
Boehm, M. L., et al. 1998. Journal of Animal Science. 76:2415-2434.
Boizard, M., et al. 1998. J. Biol. Chem. 273:29164-29171.
Borglum, A. D., et al. 1997. Human Genetics. 99:80-82.
Boston, B. A. 1999. Ann. NY Acad. Sci. 885:75-84.
Chen, G., et al.1996. Proceedings of the National Academy of Science. USA. 93:14795.
Chen, W., et al. 1997. Cell. 91:789-798.
Clement, K., et al. 1998. Nature. 392:398.
de Koning, D. J., et al. 1999. Genetics 152, 1679-1690.
Ding, S. T., et al. 1999. Comp. Biochem. Physiol. B. Comp. Biochem. Mol. Biol. 122:307.
Ernst C. W., et al. 1998. Animal Genetics. 29:212-215.
Fan, W., et al. 1997. Nature. 385:165-168.
Fernandez, X., et al. 1999. Meat Science. 53:67-72.
Freake, H. C. 1999. Nutrition Reviews. 57:154-156.
Geesink, G. H., et al. 1992. In: Proceedings of the 38th International Congress of Meat
Science and Technology. Clermont Ferrand. pp 363-366.
Gerbens, F., et al. 1999. Journal of Animal Science. 77:846-852.
Gerbens, F., et al. 1997. Mammalian Genome. 8:328-332.
Goll, D. E., et al. 1998. Canadian Journal of Animal Science. 78:503-512.
Goureau, A., et al. 1996. Genomics. 36:252-262.
Green, P., et al. 1990. Documentation for CRI-MAP, version 2.4. Washington University
School of Medicine, St. Louis, MO.
Green, Stephen. 1995. Mutation Research. 333:101-109.
Grindflek, E., et al. 1998. Biochemical and Biophysical Research Communications.
Hagg, S. A., et al. 1976. Biochem. J. 158:203-210.
Ho, L., et al. 1989. Proceedings of the National Academy of Sciences. 86:5330-5334.
Hovenier, R., et al. 1992. Livestock Production Science. 32:309-321.
Hua, X., et al. 1995. Genomics. 25:667-673.
Huff-Lonergan, E., et al.1996. Journal Animal Science. 74:993-1008.
Killefer, J., and M. Koohmaraie.1994. Journal of Animal Science. 72:606-614.
Kim, K. S., et al. 2000. Mammalian Genome. 11:131-135.
Kim, K. S. 1999. Iowa State University, Masters Thesis. Ames, IA.
Kim, J. B., et al. 1998. Proceedings of the National Academy of Science. USA. 95:4333.
Koohmaraie, M. 1996. Meat Science. 43:193-201.
Koohmaraie, M., et al. 1994. In: A. Ouali, D. Deneyer, and F. Smulders (Ed.) pp 395-
412. Utrecht, The Netherlands.
Koohmaraie M., et al. 1991. Journal of Animal Science. 69:617-624.
Lissens, W., et al. 2000. Human Mutation. 15:209-219.
Lonergan, S. E., et al. 1995. Journal of Animal Science. 73:3608-3612.
Malek, M., et al. 2000. Proceedings of the 2000 ISAG meetings. Minneapolis, MN
Moeller, S. J. 1999. Pork ’99. June.
Ouali, A, and A. Talmant. 1990. Meat Science. 28:331-348.
Ovilo, C., et al. 2000a. Proceedings of the 2000 ISAG meetings. Minneapolis, MN.
Ovilo, C. M., et al. 2000b. Mammalian Genome. 11:344-346.
Parr T., et al. 1999. Journal of Animal Science. 77:661-668.
Peters, S. J., et al. 1998. American Journal of Physiology. 275:E980-986.
Ramsay, T. G., et al. 1998. Journal of Animal Science. 76:484-490.
Reed, L. J. 1974. Acc. Chem. Res. 7:40-46.
Reichart, U., et al. 2000. Biochemical and Biophysical Research Communications.
Robert, C., et al. 1998. Canadian Journal of Animal Science. 78:473-482.
Robinson, B. H., 1987. Journal of Pediatrics. 111:525-533.
Rohrer, G. A. and J. W. Keele. 1998a. Journal of Animal Science. 76:2247-2254.
Rohrer, G. A. and J. W. Keele. 1998b. Journal of Animal Science. 76:2255-2263.
Rosen, E. D., and B. M. Spiegelman. 2000. Annual Reviews Cell and Developmental
Rothschild, M.F. and G. S. Plastow. 1999. AgBiotechNet. vol. 1, February edition.
SAS. 1999. SAS system for Windows (Release 8.0) SAS Inst., Inc. Cary, NC.
Schoonjans, K., et al. 1996. Biochimica et Biophysica Acta. 1302:93-109.
Seeley, R. J., et al. 1997. Nature. 390:349.
Sensky, P. L., et al. 1996. Animal Science. 62:663-664.
Shackelford, S. D., et al. 1994. Journal of Animal Science. 72:857.
Shi. X.-W., et al. 2000. Proceedings of the 2000 ISAG meetings. Minneapolis, MN
Shimomura, I., et al. 1998. Genes and Development. 12:3182-3194.
Spiegelman, B. M., et al. 1997. Biochimie. 79:111-112.
Tartaglia, L. A. 1997. The Journal of Biological Chemistry. 272:6093-6096.
Touraille, C., et al.1989. Meat Science. 25:177-186.
van der Kraan, M. et al. 1998. Endocrinology. 139: 2348-2355.
Veerkamp, J. H., and R. G. H. J. Maatman. 1995. Progressive Lipid Research. 34:17-52.
Vincent. A. L., et al., 1997. Journal of Animal Science. 75:2287.
Ward, G. R., et al.1982. Clinical Science. 63:87-92.
Wang, X., et al. 1994. Cell. 77:53-62.
Yerle, M., et al. 1996. Cytogenetics and Cell Genetics. 73:194-202.
Yokoyama, C., et al. 1993. Cell. 75:187-197.
Zhang, Y., et al. 1997. Biochemical and Biophysical Research Communications.