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ANIMAL GENETICS |
* Livestock Research Institute, Tokushima Agriculture, Forestry and Fisheries Technology Center, Anan, Tokushima 774-0047, Japan;
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National Institute of Agrobiological Sciences, Tsukuba, Ibaraki 305-0901, Japan;
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STAFF-Institute, Tsukuba, Ibaraki 305-0854, Japan; and
and
National Institute of Livestock and Grassland Science, Tsukuba, Ibaraki 305-0901, Japan
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Abstract |
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 Top Abstract IntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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Key Words: Linkage Analysis • Meat Quality • Muscle Fiber • Pigs • Quantitative Trait Loci
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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). Japanese wild boars are genetically separate from European wild boars (Okumura et al., 2001). They are expected to contain novel genetic resources because they were not used when most commercial pig breeds were established in Europe. If QTL for meat quality, in which Japanese wild boar alleles are preferable to those of European pigs, are mapped, this information will be useful for genetic improvement of commercial pigs.
European wild boars are characterized as having a high ratio of red muscle fibers (Essén-Gustavsson and Lindholm, 1984; Solomon et al., 1985). The number of red muscle fibers was negatively associated with that of white muscle fibers, the higher proportion of which leads to increased R-values (degrees of deamination of adenosine) and lactate production, resulting in poor meat quality (Reiner et al., 2002). Existing QTL analyses using intercrosses between European wild boar and Large White populations (Andersson et al., 1994; Andersson-Eklund et al., 1998; Knott et al., 1998) have indicated no QTL affecting meat quality at the genome-wise significance level. It is more difficult to identify QTL that affect meat quality than to identify those affecting growth and carcass composition because meat quality traits, such as water-holding capacity, cooking loss, juiciness, and pH are influenced by both pre- and postmortem environmental factors.
Here we focused on muscle fiber characteristics that are key determinants of meat quality affected by few environmental factors and also on general biochemical properties. To identify QTL affecting muscle fiber traits, we produced an F2 resource population from a cross between a Japanese wild boar male and three Large White females, and performed analyses with interval mapping.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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Analyzed Traits
Phenotypes of 24 traits affecting meat quality and muscle composition of the F2 animals were recorded. These traits are listed in Table 1, which also shows the means, standard deviations, and results of analyses of variance with respect to sex and parity for each trait. Because of occasional sampling problems, measurements of some traits were not available for some animals. The 24 traits are described in the following sections.
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Water-holding capacity was measured using two different methods: a filter paper press method (WHC1; Wierbichki and Deatherage, 1958) and a filter paper centrifugation method (WHC2; Irie et al., 1992). The filter paper press method was performed by placing a meat sample, weighing 400 to 600 mg, on a filter paper, which was then sandwiched between translucent plastic plates and pressed at 35 kg/cm2 for 1 min. The meat and liquid areas on the filter paper were measured with a video image analysis system (Aspect, Mitani, Fukui, Japan). The following formula was applied: WHC1 = (1 – [area of liquid, cm2 – area of meat, cm2] x 9.47/sample [mg]) x 100%. At the same time, spreadability was assessed according to the meat sample area:meat sample weight ratio. The centrifugation method was carried out with polypropylene tubes, each equipped with a filter and beads at the bottom to separate the meat from the expelled liquid. A meat sample weighing 400 to 600 mg was centrifuged at 2,100 x g for 30 min at 4°C, after which the meat was reweighed to obtain WHC2 as the difference between weights of sample before and after centrifugation.
To measure cooking loss, a loin cube was taken from the longissimus, weighed, placed in a polyethylene bag, and incubated in water at 70°C for 1 h. The bag was then immersed in flowing water at room temperature for 30 min, and the solid portion in it was reweighed. Cooking loss was obtained as the difference between the weight of the sample before and after the treatment. After measuring cooking loss, the cooked sample was divided into two masses. One mass was formed into a 10 mm x 10 mm x 5 mm piece and pressed at 35 kg/cm2 for 1 min to assess its juiciness. The other mass was formed into 1.2-mm-diameter rolls in the direction of the muscle fiber, for use in Warner-Bratzler shear force measurements.
Hematin content was determined by acidified acetone extraction (Hornsey et al., 1956). A minced meat sample, weighed in 2-g increments, was placed in 50-mL centrifuge tube. To each tube, 8.6 mL of acid-acetone mixture was added (8.4 mL of acetone and 0.2 mL of concentrated hydrochloric acid). Each sample was homogenized for 40 s in a blender (Physcotron NS-51K, Microtec, Chiba, Japan). After the extract was centrifuged at 1,700 x g for 15 min, the supernatant fluid was filtered and the absorbance was measured with a spectrophotometer (U-2000, Hitachi, Tokyo, Japan) at 512 nm against a reagent blank. Hematin content (fresh tissue basis) was calculated as follows: hematin (mg/100 g) = absorbance (512 nm) x 0.35 x 100.
For the measurement of connective tissue, a meat sample was dried and defatted in a 2:1 solution of chloroform-methanol mixture. The dried and defatted matter (DDM) was used to analyze the i.m. connective tissue components. The amounts of total collagen (T collagen) and heat-soluble collagen (HS collagen) (DM basis) were determined using the procedure of Bergman and Loxley (1963). The ratio of HS collagen was defined as the amount of HS collagen divided by that of T collagen. The percentage of intramuscular fat (IMF) in the LM (fresh-tissue basis) was determined using the Sox-hlet apparatus. After being chopped up, samples of the longissimus were dried by heating to 100°C for 24 h in a drying oven, and water content was calculated from sample weight before and after drying. Pork color standard (PCS; Nakai et al., 1975) was assessed visually on a six-point scale (1 = pale; 6 = dark). Total sugar (fresh-tissue basis) was determined using the anthrone reagent as described by Seifert et al. (1950).
Muscle Fiber Traits.
Within 24 h after slaughter, three samples of the LM were taken, covering almost the complete cross section of the muscle, at the level of the 7th and 8th ribs. The samples were frozen in isopentane cooled with liquid N and were stored at –80°C until analysis. Transverse serial sections (8 µm thick) were cut at –20°C with a cryostat microtome (CM1850; Leica, Solms, Germany) and stained using the myosin adenosine triphosphatase method (Brooke and Kaiser, 1970), with an alkaline preincubation buffer (pH 10.55). The muscle fibers were identified as type I, IIA, or IIB according to the method of Brooke and Kaiser (1970). The proportion of the number of each fiber type was obtained by counting at least 800 fibers per LM. The proportion of the relative area (RA) was scored with (number in each type x average cross-sectional area of each type)/(total cross-sectional area) x 100%.
Genotyped Markers and Linkage Map
We selected 224 informative microsatellite markers from the USDA-Meat Animal Research Center (USDA-MARC) linkage map (Rohrer et al., 1996). We also used a DNA marker, PRKAG3I, developed in the intron of PRKAG3 (AF214520), which is polymorphic in its number of cytosine repeats. The forward sequence of its PCR primer pair was 5'-AGGAGCACACCTGCTACGAT-3', and the reverse was 5'-AGTTGCAGAGCTGGGAT-GAC-3'. The 225 markers were genotyped with the four parents, 10 F1, and 353 F2 pigs. A sex-averaged linkage map was constructed for the resource family by using CRI-MAP (Green et al., 1990) for the 18 autosomes and the sex chromosome.
QTL Analysis
A QTL analysis for each trait was performed using the method developed by Haley et al. (1994). The analysis assumed that the grandparental breeds were fixed for alternative alleles at a given QTL. The statistical model was based on a linear regression of phenotypes on probabilities of QTL genotypes at a given location and expressed as
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where y is a vector of phenotypic observations of a trait for all F2 individuals; b is a vector of nongenetic fixed effects; g is a vector of additive effect, a, and dominance effect, d, at a QTL (i.e., g = (a, d)'); X and U are incidence matrices relating y to fixed effects b and genetic effects g, respectively; and e contains residuals. The ith row of U is obtained by the probability of QTL genotype for the ith F2 individual and is written as (prob(QQ) – prob(qq), prob(Qq)), where prob(XX) is the probability of an individual being genotype XX, and Q and q indicate alleles inherited from a wild boar sire and Large White dams, respectively. As nongenetic fixed effects, general mean, sex, and parity were taken into account in the analysis of each trait. The least squares method was applied to detect QTL. We calculated F-ratios from residual sums of squares under the null model assuming no QTL (g = (0,0)'), and under the full model, including parameters for QTL effects, for every 1 cM on our linkage map as well as the information content described by Knott et al. (1998). The analysis of sex chromosome was performed following method of Knott et al. (1998). The pseudoautosomal section of the sex chromosome was analyzed using the model described above. Denoting the QTL genotypes on the sex-specific section of a wild boar sire and Large White dams as QY and qq, respectively, where Y indicates the Y-chromosome, the possible QTL genotypes are QY and qY for F2 males and QQ and Qq for F2 females. Thus, one effect corresponding to the difference between the two possible genotypes of QTL, instead of additive and dominance effects, was fitted separately for each sex in the analyses of the sex-specific section on the sex chromosome. Genome-wise significant thresholds were obtained with 5,000 repetitions of the permutation test for each trait (Table 2).
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Results |
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). However, our linkage map showed a different marker order from that of the USDA-MARC linkage map at three places: SW1311 and SW974 on SSC1 (107 cM); SW776 and S0091 on SSC2 (63 cM); and from KS158 to SW2608 on SSC15 (from 51 to 82 cM). More importantly, we could not locate a marker for the SSC5p region due to a lack of polymorphic markers in the region, where SW70 was the end marker of SSC5p in our map (0 cM), but SW70 was located at 72 cM on the USDA map.
Statistics on traits were listed in Table 1
. Effects of the parity were significant for all the traits, except for IMF, whereas effects of the sex were detected in meat color, hematin content, pH, WHC, cooking loss, juiciness, water content, and IMF. The results of QTL mapping are summarized in Table 2. We analyzed the characteristics of 24 traits and identified 24 QTL for 11 traits at the 5% genome-wise significance level. Of the 24 QTL, 13 loci for eight traits were significant at the 1% genome-wise level. The significant QTL are shown in Figure 1a through h. Most of the detected QTL were new findings and are being reported for the first time. No significant QTL were detected for Minolta L* value, pork color standard score, cooking loss, WHC1, WHC2, spreadability, shear force value, juiciness, total sugar, water content, T collagen, HS collagen, or ratio of HS collagen to T collagen.
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; Figure 1a, f, and h). Wild boar alleles of the QTL on SSC14 had positive effects, increasing number of type I muscle fibers, and the others had negative effects. Three QTL for the number of type IIA muscle fibers were located at 59.1 and 105.7 cM on SSC2 and at 5.0 cM on SSC14 (Table 2; Figure 1b and f), in which wild boar alleles had positive effects. With a negative correlation between the proportions of muscle fibers of different types, we detected QTL for number of type IIB muscle fibers at the two regions on SSC14 of QTL for number of type I and IIA muscle fibers (Table 2; Figure 1f). A QTL for the number of type IIB muscle fibers was also detected at 103.5 cM on SSC2 (Table 2; Figure 1b), and wild boar alleles had the effect of decreasing the number of type IIB muscle fibers. Relative area and the number of each type of muscle fiber were closely related to each other, so the QTL for RA of type I muscle fibers was detected on SSCX (93.1 cM; Figure 1h), that of type IIA was on SSC2 (61.1 cM; Figure 1b), and those of type IIB were on SSC14 (4.0 and 32.0 cM; Figure 1f). Also, in the SSC6pter region, QTL were detected for RA of types IIA (17.7 cM) and IIB (14.5 cM) muscle fibers (Figure 1e), in which wild boar alleles had positive and negative effects, respectively, regardless of the number of fibers. The fraction of phenotypic variances explained by these QTL for muscle fiber traits ranged from 0.04 to 0.07. The QTL for type IIA muscle fibers detected at 59.1 cM on SSC2 acted dominantly, whereas the other QTL were almost additive.
In the SSC6pter region, QTL for the Minolta a* value (redness; 18.7 cM) and for hematin content (20.9 cM) were also detected. The fractions of phenotypic variance explained by this QTL for Minolta a* and hematin content were both 0.09, which were the largest in this study. Another QTL for the Minolta a* value was also detected at 149.8 cM on SSC4 (Figure 1d). For the Minolta b* value (yellow), QTL were detected at 68.4 and 101.6 cM on SSC3 and at 52.4 cM on SSC15 (Figure 1c, g). For IMF and pH, QTL were detected in the same region on SSC15. The effects of wild boar alleles of QTL on SSC15 decreased the fat amount and the Minolta b* value, while slightly raising the pH of the samples.
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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reported QTL for marbling, meat color, pH, and glycogen potential. Ovilo et al. (2002) reported QTL for IMF, pH, hematin content, and meat color. Sato et al. (2003) reported QTL for moisture and IMF. Quintanilla et al. (2003) reported QTL for fat androstenone level. Few studies have detected significant QTL related to water-holding capacity and cooking loss, which are arguably the most important objective measures of meat quality. One reason why it is difficult to identify the QTL related to these traits is the complexity of their regulation, as they are influenced by polygenic factors, as well as environmental factors both before and after slaughter.
Meats are composite constructions of fat and skeletal muscle, so the properties of skeletal muscle are some of the key determinants of meat quality. According to the amounts of three types of muscle fiber, types I, IIA, and IIB, the properties of skeletal muscle were determined, and their proportions were found to be largely affected by genetic factors (Larzul et al., 1997). The three types of muscle fiber differ phenotypically in expressed subsets of myofibrillar isoforms with different adenosine triphosphatase activities as well as different metabolic enzyme activities. The myosin heavy-chain isoforms are coded by separate genes, some of which are preferentially expressed in myofibrils of fast muscle fibers (white; type IIB) or in slow ones (red; types I and IIA; Goldspink, 1996).
Larger fiber diameter and a higher proportion of white muscle fibers (type IIB) lead to increased R-values (degree of deamination of adenosine) and lactate production, resulting in poor meat quality (Reiner et al., 2002). To improve meat quality, it is preferable to increase the proportions of types I and IIA muscle fibers and to decrease that of type IIB. In this study, QTL affecting muscle fiber composition were mapped in seven genomic regions. In a QTL at approximately 35 cM on SSC14, wild boar alleles were suggested to increase type I and decrease type IIB muscle fibers. In QTL on the SSC14pter region, at approximately 105 cM on SSC2 and at approximately 20 cM on SSC6, wild boar alleles were suggested to decrease type IIB muscle fibers. In QTL at approximately 60 cM on SSC2, wild boar alleles increased type IIA muscle fibers. In these five QTL, wild boar alleles had favorable effects, increasing the red muscle fibers, types I and IIA. In the other two QTL mapped on SSC1 and SSCX, the effects of wild boar alleles decreased type I muscle fibers.
In mammals, the calcineurin signaling pathway plays a critical role in regulating skeletal muscle fiber type switching (Olson and Williams, 2000; Parsons et al., 2003). Transcriptional factors of the nuclear factor of activated T cells (NFAT) family are major targets of calcineurin and affect the expression level of slow and fast myosin heavy chain (McCullagh et al., 2004). Among the genes involved in the calcineurin signaling pathway, two of calcineurin’s subunits and one of the modulators of NFAT were located in regions of human chromosomes that correspond to those of swine chromosomes on which the QTL described above were mapped. Thus, PPP3CC (protein phosphatase 3 catalytic subunit 
isoform, calcineurin A gamma) was located on HSA8p21.3, PPP3CB (protein phosphatase 3 catalytic subunit ßisoform, calcineurin A beta) was located on HSA10q21, and NFAM1 (NFAT activation molecule 1) was located on HSA22q13. These three human genomic regions correspond to regions on SSC14. We selected these three genes as candidates, of which assignments to the swine genome are in progress now.
Around the two regions of SSC14, to which we mapped the QTL for muscle fiber composition, de Koning et al. (2001) had mapped the QTL for cooking loss (1 cM) and redness of meats (35 cM), and Rohrer and Keele (1998) had mapped the QTL (40 cM) for fatness. Karlsson et al. (1993) and Brocks et al. (1998) reported that muscle fiber composition was related to leanness, but we could not detect any QTL for growth or fat deposition traits in these regions (data not shown).
The region of QTL for the Minolta a* value on SSC6 overlapped those for RA of types IIA and IIB muscle fibers and that for hematin pigment content. This result suggested that increased type IIA and decreased type IIB muscle fibers increased meat redness. In addition to the QTL on SSC6, we also mapped QTL for meat color on SSC3, 4, and 15. Among them, the QTL on SSC3 and 4 were similar to parts of those in reports by de Koning et al. (2001; SSC3, 4, and 13 for meat color), by Ovilo at al. (2002; SSC4, 7, and 8 for meat color and SSC4 and 7 for hematin content), and by Sato et al. (2003; SSC3 for meat color). Furthermore, Malek et al. (2001) reported QTL for meat color on SSC5 and 17.
The QTL for the Minolta b* value on SSC15 overlapped with that for pH. In dark cutting meats (dark, firm, and dry), lower glycolytic potential was reported and it raised the pH of meats (Wulf et al., 2002). In QTL on SSC15, wild boar alleles would raise the pH and decrease the yellowness of the meat. We proposed AMP-activated protein kinase gamma subunit (PRKAG3) gene, which affected glycogen metabolism in vivo and was reported to affect meat quality (Milan et al., 2000) as a candidate for this QTL. By a linkage analysis using an intron polymorphism, PRKAG3 was located 20 cM apart from the peak of QTL (Figure 1g). The QTL for the Minolta b* value on SSC15 also overlapped with that for IMF. Thus, it is possible that wild boar alleles affect meat color by decreasing fat content.
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Implications |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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1 Correspondence: Watariagari, Shimoono (phone: +81-884-22-2938; fax: +81-884-23-4180; e-mail: nii_masahiro_1{at}pref.tokushima.lg.jp).
Received for publication July 7, 2004. Accepted for publication October 20, 2004.
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Literature Cited |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionImplicationsLiterature Cited |
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and Aß gene-targeted mice. Mol. Cell. Biol. 23:4331–4343.This article has been cited by other articles:
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  M. Lei, C. Luo, X. Peng, M. Fang, Q. Nie, D. Zhang, G. Yang, and X. Zhang Polymorphism of Growth-Correlated Genes Associated with Fatness and Muscle Fiber Traits in Chickens Poult. Sci., May 1, 2007; 86(5): 835 - 842. [Abstract] [Full Text] [PDF]
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 H. J. van Wijk, H. Buschbell, B. Dibbits, S.C. Liefers, B. Harlizius, H. C. M. Heuven, E. F. Knol, H. Bovenhuis, and M. A. M. Groenen Variance component analysis of quantitative trait loci for pork carcass composition and meat quality on SSC4 and SSC11 J Anim Sci, January 1, 2007; 85(1): 22 - 30. [Abstract] [Full Text] [PDF]
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S. Mikawa, T. Hayashi, M. Nii, S. Shimanuki, T. Morozumi, and T. Awata Two quantitative trait loci on Sus scrofa chromosomes 1 and 7 affecting the number of vertebrae J Anim Sci, October 1, 2005; 83(10): 2247 - 2254. [Abstract] [Full Text] [PDF]
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