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ANIMAL GENETICS |
Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, 330045, Nanchang, China
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Abstract |
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 Top Abstract INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Key Words: glycolytic potential • pH • pig • quantitative trait loci • temperature
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INTRODUCTION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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; Bidner et al., 2004; Lindahl et al., 2006).
The pH of meat is a multifactorial trait, and its heritability has been estimated to range from 0.07 to 0.41 (Sellier, 1994). So far, 2 major genes (RYR1 and PRKAG3) affecting pH have been identified. The R615C mutation in RYR1 is associated with less pH value and greater temperature at 45 min postmortem, resulting in PSE meat (Fujii et al., 1991). The R200Q mutation of PRKAG3 is responsible for acid meat in Hampshire and Hampshire-synthetic lines (Milan et al., 2000). However, PSE and acid meat are often observed in noncarriers of unfavorable RYR1 and PRKAG3 alleles, indicating that the genetic determinator of pH remains largely unknown. To date, QTL for pH at 45 min and 24 h postmortem have been widely studied and detected on all chromosomes except SSC 10 and 17 using different resource populations (http://www.animalgenome.org).
Muscle metabolism and pH decline processes are very complex and are influenced by many enzymes and regulation reactions (Lundberg and Vogel, 1986; Bertram et al., 2001). Bowker et al. (2000) highlighted factors responsible for metabolism in PSE meat and the biochemistry behind the transformation of muscle to meat. Many factors play a role at specific stages postmortem. However, QTL for pH development (pH decline) during the whole 24-h postmortem period remain unexplored.
The aim of this study was to perform a whole genome scan and identify QTL for pH, pH decline, and pork temperature during the whole 24-h postmortem period in LM and semimembranosus muscle (SM) and glycolytic potential in LM using a large scale White Duroc x Erhualian resource population.
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MATERIALS AND METHODS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Population Structure and Management
A 4-generation resource population was developed and managed as described in Ren et al. (2006). Briefly, 2 purebred White Duroc sires from the PIC company (Zhangjiaguang, China) and 17 Chinese Erhualian dams were used to produce F1 animals, from which 9 F1 boars and 59 F1 dams were intercrossed to generate 1,912 F2 animals in 6 batches from 2002 to 2004. Sixty-two F2 males and 149 F2 females were chosen to produce 1,530 F3 animals in 3 batches. Traits related to reproduction, meat quality, production, health, and appearance were recorded in F2 and F3 animals. All F0 pigs were noncarriers of the unfavorable RYR1 (615C) and PRKAG3 (200Q) alleles according to a DNA test (Fujii et al., 1991; Milan et al., 2000).
At the experimental farm of Jiangxi Agricultural University, all F2 piglets were weaned at 46 d of age and then moved into a nursery (males were castrated at 90 d of age), where they received an ad libitum diet containing 21% CP, 3,300 kJ of DE, and 1.25% lysine. At 120 d of age, pigs were placed in pens that allowed for an average of 2 m2 per pig. The ad libitum diet was changed to 16% CP, 3,100 kJ of DE, and 0.78% lysine until slaughter. All diets were fortified with vitamins and minerals for the age of pig. Water was provided ad libitum.
Trait Measurement
One thousand thirty F2 animals at 240 ± 3 d were transported and slaughtered at a commercial abattoir, where pigs were kept together in lairage overnight (approximate 20 h before slaughter) without food, but ad libitum access to water feeders. At that time, the average BW was 96.31 ± 16.82 kg, ranging from 50.5 to 146.2 kg of BW. The slaughter procedure was as follows: pigs were vertically suspended from a shackling chain by one hindlimb, exsanguinated from major blood vessels near the heart, scalded in hot water (about 60 to 70°C), dehaired with a dehair machine, and cooled in cold water (10 to 12°C). At approximately 30-min postmortem, LM and SM were collected from the left side of the carcass and separated into several pieces for different measurements. Before 45-min postmortem, carcass and meat samples for pH and temperature measurements were kept in a cool room at 12°C. Subsequently, they were stored in a refrigerator at 0 to 4°C during the next 24 h.
The pH values and temperatures were measured in LM (3 x 9 cm) between 11/14th ribs with a Delta 320 pH Meter (Mettler Toledo, Greifensee, Switzerland) at 45 min, and 3, 9, 15, and 24 h postmortem. The pH-control system was fitted with an insertion glass electrode and an automatic temperature compensation probe (Mettler Toledo, Greifensee, Switzerland). A glass electrode was calibrated in buffers at pH values of 7.00 and 4.01. Duplicate measurements were performed from the dorsal and ventral LM and their average values were used in the analysis. Temperature was determined at the middle of the samples. Measurements were also evaluated in SM (3 x 9 cm) at the same time and in the same way.
A subsample of LM between the 14/15th ribs was collected, bagged, labeled, and frozen in liquid nitrogen immediately at approximately 30 min postmortem. Subsequently, all samples were stored at –80°C. Glycogen, glucose, and glucose-6-phosphate (G-6-P) concentrations were measured according to procedures described in Passonneau and Lowry (1993). The lactate concentration was determined as described previously (Noll, 1970). Glycolytic potential was calculated using the following formula: glycolytic potential (µmol/g of wet muscle) = 2 x ([glycogen] + [glucose-6-phosphate] + [glucose]) + [lactate] (Monin and Sellier, 1985; Maribo et al., 1999b). The values for total glycogen (glycogen + glucose + G-6-P; µmol/g), residual glycogen (glycogen + glucose; µmol/g), G-6-P (µmol/g), and lactate (µmol/g) and glycolytic potential were used for the QTL analysis in this study.
DNA Isolation, Marker Selection, and Genotyping
The DNA was isolated from ear tissues or blood with a standard phenol/chloroform method. Microsatellite markers were initially selected from the USDA-Meat Animal Research Center reference map (http://www.animalgenome.org). A final set of 183 informative microsatellite markers covering the pig genome with a mean interval of 20 cM were genotyped across the entire White Duroc x Erhualian resource population. One primer of each primer pair was labeled with fluorescent dyes of NED (ABI, Foster City, CA), HEX, or FAM (Sangon, Shanghai, China). Amplifications were performed in a 15-µL reaction containing 40 ng of DNA, 1 x buffer, 1.5 mM MgCl2, 2 mM of each dNTP (Sangon), 200 nM of each primer, and 1 unit of Taq DNA polymerase (Takara, Dalian, China). The thermocycle conditions included 3 min at 94°C, followed by 35 cycles of 20 s at 94°C, 20 s at optimal annealing temperatures and 30 s at 72°C, and 20 min at a final extension step. Amplified fragments were detected with a 3130xl Genetic Analyzer and recorded by Genemapper software version 4.0 (ABI).
QTL Analysis
Comprehensive linkage maps were constructed with the Crimap version 2.4 software in a routine way (Green et al., 1990). The QTL analysis was performed using QTL express at http://qtl.cap.ed.ac.uk/(Seaton et al., 2002) based on a least-squares method (Haley et al., 1994). The option F2 ANALYSIS was used to detect single QTL with additive, dominance, or imprinting effects on the 18 autosomes and additive effects on the X chromosome. The least squares regression model in the QTL analysis included the fixed effects of sex and batch, and a covariate of carcass weight for all traits measured. The F-ratios of the full QTL model including additive, dominance, and imprinting effects to the reduced QTL model without the above effects were obtained at 1-cM intervals across individual chromosomes. Significance thresholds at the 5 and 1% chromosome-wise levels and 5 and 1% genome-wise levels were computed by permutation tests with 1,000 permutations (Churchill and Doerge, 1994). Empirical 95% confidence intervals for the location of QTL were determined using the bootstrap method through 1,000 iterations (Visscher et al., 1996).
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RESULTS AND DISCUSSION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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and 2, respectively. A total of 73 suggestive QTL were detected on 15 autosomes, including 49 for pH, 20 for glycolytic potential, and 4 for 45-min temperature. Ten 1% genome-wise significant QTL were detected for 24-h pH in LM and SM on SSC15, for glycolytic potential, total glycogen, and residual glycogen on SSC3, 6, and 7. Six 5% genome-wise significant QTL were mapped for 9-h pH in SM on SSC3, pH decline from 3/9-h to 24-h on SSC7, glycolytic potential on SSC1, and total glycogen on SSC1 and 6. Each QTL explained 1 to 6% of the phenotypic variance. Most favorable alleles for pH and glycogen related traits were inherited from the Erhualian breed. The statistic F-curves indicating the genome-wise significant QTL are shown in Figure 1.
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Genome scans for mapping pH in LM and SM have been carried out using different crossbred populations (http://www.animalgenome.org/QTLdb/pig.html). A total of 70 QTL for pH in LM and SM have been detected on all chromosomes except for SSC8, 10, and 17. In this study, we detected 49 QTL for pH (Table 2
), which not only confirmed previously reported effects on 18 autosomes except SSC1, 11 and 12, but also found 2 significant associations for pH and pH decline at 71 to 77 cM on SSC8 and at 127 to 128 cM on SSC10. The greater detection power could be due to a large number of experimental pigs and pH measured at several time points in this study.
A genomic region flanked by SW1562 and SW946 on SSC15 showed the most significant associations with 24-h pH in LM and SM in this study (Figure 1). This genomic region has been characterized as a locus affecting 24-h pH in a Japanese Wild Boar x Large White resource population (Nii et al., 2005). An adjacent region between SW1683 and SW936 has been previously identified as a QTL for 24-h pH in loin and ham in a Berkshire x Yorkshire F2 population (Malek et al., 2001; Kim et al., 2005). The PRKAG3 was mapped to this chromosomal region. Strong evidence has been shown for significant association between 3 substitutions of PRKAG3 (I199V, T30N, and G52S), especially I199V, and 24-h pH in the Berkshire x Yorkshire intercross and commercial breeds (Ciobanu et al., 2001). It is noteworthy that PRKAG3 is located apart from the peak of F-ratios curve for 24-h pH in this study. White Duroc founder boars were homozygous for the favorable allele 199I, and Erhualian founder sows were all homozygous for the unfavorable allele 199V (data not shown), which was in contrast to breed characteristics. Moreover, partial imprinting effect existed at this locus, which is inconsistent with the inheritance model of PRKAG3. Taken together, it is likely that PRKAG3 is not the causal gene for 24-h pH in LM and SM on SSC15 in the present population.
To date, only 2 studies have reported QTL for pH decline between different time points before 24 h after slaughter. Edwards et al. (2008) found 4 QTL for 45-min to 24-h pH decline on SSC3, 7, 11, and 17 in a Duroc x Pietrain resource population. Markljung et al. (2008) reported a 5% genome-wise significant effect and 4 suggestive effects for pH decline from 45 min to 3 h and from 3 h to 5 h on SSC6, 10, and 12. In this study, two 5% genome-wise significant QTL for pH decline from 3 h to 24 h and from 9 h to 24 h in SM were mapped to a region between SW1856 and S0066 on SSC7 (Figure 1), indicating that the corresponding causal gene could have profound effects on the development of pH. A 5% genome-wise significant QTL for pH decline from 45 min to 3 h on SSC6 (Markljung et al., 2008) is in an adjacent region for pH decline from 45 min to 24 h in this study. To our knowledge, this is the first time to identify significant QTL for pH decline at the above 5 time points.
Quantitative trait loci for pH at adjacent time points in 1 muscle were always identified in adjacent genomic regions, whereas those for pH at a specific time point in both tissues were detected in distinct regions. For instance, one 5% genome-wise significant QTL for 9-h pH and 2 suggestive QTL for 3-h and 15-h pH in SM were identified in an adjacent region on SSC3. Neither of these was detected on SSC3 affecting pH in LM at the 3 times. Quantitative trait loci for 45-min and 3-h pH on SSC2 and for 15-h and 24-h pH in LM on SSC15 were detected at the same position, whereas QTL for 3-h and 9-h pH in SM were mapped to 3 adjacent regions on SSC3, 4, and 7. Additionally, no QTL for pH measured at the same time points in both muscles were detected in adjacent regions except for 24-h pH on SSC15. These results clearly indicated that the quantitative trait genes for pH play distinct roles at specific stages, in specific muscles, or both.
Another interesting result was that some QTL for pH showed a discordant influence at different postmortem stages. For example, the White Duroc allele at chromosomal region (36 to 40 cM) on SSC15 increased pH decline from 45 min to 24 h in LM, resulting in less 24-h pH. In contrast, the White Duroc allele at the location (67 cM) on SSC2 decreased pH in LM before 3 h postmortem, but retarded pH decline from 3 to 24 h.
QTL for Glycolytic Potential
During the first 24-h postmortem, glycogen reserves in the muscle convert to lactate, and muscle metabolism stops. A great amount of glycogen in the muscle at slaughter provides the potential for glycolysis, which could result in less ultimate pH. Monin and Sellier (1985) proposed that glycolytic potential could be used as an indicator of the potential lactate formation in muscle at slaughter. Glycolytic potential levels explained roughly 35% to 50% of the variation in 24-h pH (Maribo et al., 1999b; van Laack and Kauffman, 1999). The glycolytic potential in LM was not different irrespective of sampling time (Maribo et al., 1999b). Decreasing glycolytic potential measured at 1 h postmortem also improved 24-h pH and water-holding capacity (Costa et al., 1998).
So far, only 5 suggestive QTL for glycolytic potential have been described including 1 on SSC7 in a Meishan x Pietrain population (Reiner et al., 2002), and 4 on SSC11, 15, and 17 in a Berkshire x Yorkshire intercross (Malek et al., 2001). Milan et al. (2000) convincingly showed the causative mutation (R200Q) underlying the increased glycogen and low 24-pH on SSC15 in Hampshire and Hampshire-synthetic lines. Moreover, Malek et al. (2001) detected 2 significant QTL for glycogen on SSC11 and 15 in a Berkshire x Yorkshire intercross, of which 1 on SSC15 was at the 5% genome-wise significance level. These were not observed in this study. The major reason might be different measuring times (30 min in this study vs. 48 h in Malek et al., 2001) and the different genetic basis of founder breeds.
Eight 1% genome-wise significant QTL for glycolytic potential, total glycogen, and residual glycogen were mapped to 3 adjacent regions on SSC3, 6, and 7 (Table 2) in this study. The Erhualian alleles at these loci were associated with less content of glycolytic potential, total glycogen, and residual glycogen. Another two 5% genome-wise QTL for glycolytic potential and total glycogen and 1 suggestive QTL for residual glycogen were detected at 130 to 132 cM on SSC1. These QTL showed a paternal expression pattern, and the paternal allele decreased phenotypic values. Suggestive associations with glycolytic potential were identified at 6 positions on SSC4, 5, 6, 13, and 16. To our knowledge, this is the first time to identify the above loci affecting glycogen-related traits on the chromosomes mentioned above. It should be noted that glycolytic potential is associated with 24-h pH and a negative correlation of –0.42 (P < 0.0001) between the 2 traits was observed in this study (data not shown). In those regions associated with glycolytic potential, QTL for 24-h pH have also been found (Ovilo et al., 2002; Beeckmann et al., 2003; Yue et al., 2003). However, we did not observe co-localization of QTL for glycolytic potential and 24-h pH in this study. This might be caused by the fact that glycolytic potential is not a unique determining factor of ultimate pH, and a little glycogen was not transformed to lactate and conserved in the meat even at 48 h postmortem (Malek et al., 2001).
Both a numerous-markers porcine linkage map (Davoli et al., 2002) and a high-resolution human-pig comparative map (Demars et al., 2006) in the confidence interval on SSC7 allow the identification of positional candidate genes. The pyruvate kinase gene (PKM2), a promising positional candidate gene, plays a crucial role in reduction of glycogen to lactate in mammals. Significant association between the c.39T > C mutation in PKM2 and glycogen content at 1 h postmortem has been found (Fontanesi et al., 2003).
Moreover, there were 2 suggestive QTL including 1 for glucose-6-phosphate content on SSC8 and another for lactate content on SSC5. So far, only 2 suggestive QTL for lactate content have been reported on SSC7 and 17 (Malek et al., 2001; Reiner et al., 2002).
QTL for Pork Temperature
Pork temperature is an important trait in meat quality because high temperature followed by low pH is a major reason for PSE meat. Four suggestive QTL were found for pork temperature in LM and SM, including 3 for 45-min temperature in LM and 1 for 45-min temperature in SM on SSC2, 5, and 6, respectively. To our knowledge, there was only one paper describing QTL for meat temperature before this study (Edwards et al., 2008). They found a QTL for 45-min temperature on SSC9 in LM, and 3 for 24-h temperature on SSC5, 6, and 9 in LM.
At 54 cM on SSC12, we found a QTL for 45-min temperature in SM. This genomic region harbors the solute carrier family 2, member 4 gene (SLC2A4, also known as GLUT4), of which variations showed strong association with 45-min temperature (Grindflek et al., 2002; Otto et al., 2007). Thus, SLC2A4 could be considered a positional candidate gene for 45-min temperature.
In conclusion, we identified a total of 73 QTL for pH, glycolytic potential, and temperature in a large scale White Duroc x Erhualian F2 resource population. Different QTL for pH at different times reflect the involvement of distinct genes in the development of pH. Eleven new 5% genome-wise QTL for glycolytic potential suggested that other genes besides PRKAG3 could affect glycogen reserves in muscle. Chromosome regions of QTL at the 5% genome-wise significance level will be further analyzed, and refinement of QTL positions may lead to their incorporation into marker-assisted selection programs.
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Footnotes |
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2 Both authors contributed equally to this work.
3 Corresponding author: Lushenghuang{at}hotmail.com
Received for publication April 25, 2008. Accepted for publication August 13, 2008.
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LITERATURE CITED |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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