SHORT COMMUNICATION doi:10.1111/j.1365-2052.2009.01907.x Genes located on a SSC17 meat quality QTL region are associated with growth in outbred pig populations
A. M. Ramos*, J. W. M. Bastiaansen†, G. S. Plastow‡ and M. F. Rothschild* *Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA. †Animal Breeding and Genomics Centre, Animal Breeding and Genetics Group, Wageningen University, 6709 PG Wageningen, The Netherlands. ‡Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta T6G 2P5, Canada
Summary The objective of this study was to evaluate the effect of markers developed in eight genes, located in a previously detected meat quality QTL region on SSC17, on growth, fat and meat quality traits collected in commercial pig populations of different genetic backgrounds. The genes had been previously mapped to SSC17 as part of a fine-mapping effort. Association analyses were conducted between each marker and the available phenotypic traits. Results showed that three genes (CTSZ, CSTF1 and C20orf43) were significantly associated with the growth traits. In addition, CTSZ also impacted on meat colour, with the less favourable genotype for growth being associated with darker meat. The differences observed between genotypes were substantial and may be of economic importance to pig producers. These markers may be useful for selecting for faster growth or improved meat quality.
Keywords commercial pig populations, genetic markers, growth.
In the past three decades, traditional selection methods linkage map, including markers in the CYP24A1 (cyto- based on quantitative genetics have been used to select for chrome P450, family 24, subfamily A, polypeptide 1), DOK5 pigs with faster growth and increased percentage of lean (docking protein 5), CSTF1 (cleavage stimulation factor, 3¢ pre- muscle. This strategy is believed to have caused an overall RNA, subunit 1, 50 kDa), C20orf43 (Chromosome 20 open decrease in several meat quality parameters. Genetic reading frame 43), SPO11 (SPO11 meiotic protein covalently markers associated with all these traits are of interest to the bound to DSB-like (Saccharomyces cerevisiae)), RAE1 [RAE1 pig industry because, when used in combination with per- RNA export 1 homolog (Schizosaccharomyces pombe )], GNAS formance data, they may allow faster improvement of the (GNAS complex locus) and CTSZ (cathepsin Z) genes. The traits of economic importance without decline in muscle SSC17 position (in cM) of these genes on the BY population quality. linkage map is given in parenthesis and was CYP24A1 Several QTL for meat quality traits were previously (85.3), DOK5 (88.3), CSTF1 (92.4), C20orf43 (92.6), identified on pig chromosome 17 (SSC17) (Malek et al. SPO11 (97.2), RAE1 (98.5), GNAS (107.3) and CTSZ 2001), using a Berkshire · Yorkshire (BY) resource popu- (108.2). lation. These QTL were for loin meat colour (subjective score To investigate the effects of these markers in outbred pig and 48-h Hunter and Minolta L values), average lactate and populations, several growth, fat and meat quality pheno- average glycolytic potential. A detailed explanation types, as well as DNA samples, were collected in four regarding these phenotypic measurements is provided by commercial pig lines. The measured phenotypes were Malek et al. (2001). Parent of origin QTL for early growth weight at end of test period (kg), days to market weight, traits was also identified in the same SSC17 region lifetime daily gain (g/day), daily gain during test period (Thomsen et al. 2004) and QTL for other growth traits were (g/day), backfat thickness at the P2 position (mm), detected in different SSC17 regions (Pierzchala et al. 2003). Hennessy probe backfat thickness (mm), pH, and Minolta An effort to fine map these QTL was subsequently under- and Japanese colour score (JPCS) measurements. The pH taken by adding several markers to the SSC17 genetic and colour measurements were taken 24 h post-mortem in longissimus dorsi (pH, JPCS) or semimembranosus (ham Address for correspondence Minolta) muscle samples. The Japanese colour score is a M. F. Rothschild, Department of Animal Science and Center for Integ- method used to assess meat colour using a scale from 1 rated Animal Genomics, Iowa State University, Ames, IA 50011, USA. (very pale, light pink meat) to 6 (very dark red meat). The E-mail: [email protected] breed composition of these lines included purebred Landrace Accepted for publication 23 March 2009 (LR) and Large White (LW) as well as crossbred
774 2009 The Authors, Journal compilation 2009 Stichting International Foundation for Animal Genetics, Animal Genetics, 40, 774–778 Genes associated with growth 775
Duroc · Large White (D · LW) and synthetic (SYN) lines. ing were performed using an FDR approach as implemented The number of animals investigated in each line was dif- in the package q-value (Storey & Tibshirani 2003) in R ferent and varied from trait to trait, as some of the studied (http://www.r-project.org). animals did not have phenotypic information for all traits. Significant (P < 0.05) associations with the available The number of animals considered per line varied from 292 growth traits were detected for markers in the CTSZ, CSTF1 to 527 in LR, 163 to 344 in LW, 394 to 629 in D · LW and and C20orf43 genes (Tables 1 and 2), as well as additional 84 to 169 in SYN. Prior to genotyping the entire dataset, associations with meat colour and pH. For each of these each marker was genotyped in a smaller sample of unre- markers, a single favourable genotype associated with faster lated individuals from each line to determine if the marker growth was identified. The results regarding the other was polymorphic in that specific line. markers tested provided no evidence of any significant Association analyses with the available phenotypes were associations with the traits analysed. conducted for all genes using the PCR-RFLP tests developed Animals carrying the CTSZ genotype g.557AA displayed for each gene. Details regarding the PCR-RFLP tests were higher weight at end of test period (P < 0.01) and higher previously described (Ramos et al. 2006) or are provided in average daily gain on test (P < 0.01) and consequently they Table S1. Nomenclature for genotype identification was spent fewer days to reach market weight (P < 0.01). These determined by consulting the adequate rules (http:// results were obtained when data from the lines where the www.hgvs.org/mutnomen/). The details regarding the marker was polymorphic (LR, LW and SYN) were analysed naming of the SNPs according to the official nomenclature together (Table 1). Similar results were observed when each rules are indicated in Table S2. Data were analysed with a line was analysed individually (Table S4), even though the mixed model that included slaughter date and marker associations were less significant. This may possibly be genotype as fixed effects and sire as random effect. Additive explained by the smaller sample size of the dataset available and dominance effects for each marker and trait combina- for each individual line, which decreased the statistical tion were calculated using the mixed model mentioned power to detect associations between this marker and the previously, which also included the additive and dominance traits analysed. Ideally, studies within-line using larger coefficients and are shown in Table S3. The model for datasets should be conducted to investigate the effect of the analyses that combined data from markers polymorphic in CTSZ marker on each individual line. No evidence was more than one pig population also included line as an found for a significant interaction between lines. Recently, a additional fixed effect. Significant differences were declared similar effect of the CTSZ gene on porcine growth traits was when the marker genotype effect was a significant described in an Italian Large White population (Russo et al. (P < 0.05) overall source of variation and/or the P-value for 2008). Moreover, the SNP used by Russo et al. (2008) the difference between the least squares means for each was the same SNP used in this study, allowing a direct marker genotype was <0.05. Corrections for multiple test- comparison of the SNP effect in different studies and
Table 1 Least squares means, standard errors P-values and q-values for the association analysis of CTSZ with growth and meat colour phenotypes in outbred pig populations.
CTSZ genotypic least squares means
Trait g.557AA g.557AG g.557GG P-value q-value
Weight at end test period (kg) 112.4 ± 0.58a,e 111.4 ± 0.40b,c 110.3 ± 0.49f,d 0.005 0.18 (216)* (580) (294) Days until market weight 155.5 ± 1.03e 157.0 ± 0.77a 158.6 ± 0.90f,b 0.02 0.24 (139) (336) (181) Life time daily gain (g/day) 667.0 ± 3.21c 662.2 ± 2.08 657.8 ± 2.64d 0.06 0.36 (216) (580) (294) Daily gain on test period (g/day) 887.4 ± 5.57a,e 877.0 ± 3.54b 869.6 ± 4.52f 0.04 0.36 (189) (517) (267) Ham Minolta L value** 47.33 ± 0.44 47.70 ± 0.31e 46.62 ± 0.37f 0.02 0.24 (112) (279) (157) Japanese colour score*** 3.30 ± 0.07a 3.41 ± 0.05b 3.38 ± 0.06 0.22 0.66 (136) (365) (190)
Data derived from Landrace, Large White and one synthetic line of pigs were jointly analysed. Significance levels for the differences between genotypic means: a, b = P < 0.1; c, d = P < 0.05; e, f = P < 0.01. *Number of animals; **Minolta lightness (L*) score, light reflection measurement taken on the surface of meat (lower values indicate darker meat); ***Subjective score of pork colour (six classes, higher values indicate darker meat)