Integration of molecular genetics in selection programs for swine (original) (raw)
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Molecular approaches in pig breeding to improve meat quality
This article reviews the advances in molecular genetics that have led to the identification of genes and markers associated with meat quality in pig. The development of a considerable number of annotated livestock genome sequences represents an incredibly rich source of information that can be used to identify candidate genes responsible for complex traits and quantitative trait loci effects. In pig, the huge amount of information emerging from the study of the genome has helped in the acquisition of new knowledge concerning biological systems and it is opening new opportunities for the genetic selection of this specie. Among the new fields of genomics recently developed, functional genomics and proteomics that allow considering many genes and proteins at the same time are very useful tools for a better understanding of the function and regulation of genes, and how these participate in complex networks controlling the phenotypic characteristics of a trait. In particular, global gene expression profiling at the mRNA and protein level can provide a better understanding of gene regulation that underlies biological functions and physiology related to the delivery of a better pig meat quality. Moreover, the possibility to realize an integrated approach of genomics and proteomics with bioinformatics tools is essential to obtain a complete exploitation of the available molecular genetics information. The development of this knowledge will benefit scientists, industry and breeders considering that the efficiency and accuracy of the traditional pig selection schemes will be improved by the implementation of molecular data into breeding programs.
Meat Science, 2004
The effect of three alleles (RN À , rn + and a second mutant allele V199I, denoted rn*) at the PRKAG3 (RN) locus on such meat quality traits as pH, internal reflectance (FOP), Warner-Bratzler shear force, water-holding capacity and cooking loss were studied. M. longissimus dorsi (LD) from a total of 334 crossbreed pigs, entire males and females, Hampshire (H) and Finnish Landrace (L) of three combinations H Â LH, LH Â H and LH Â LH, were used. The PRKAG3 alleles were identified with a DNA test and all possible RN genotypes, RN À /RN À (23%), RN À /rn + (24%), RN À /rn* (33%), rn + /rn + (8%), rn + /rn* (9%) and rn*/rn* (2%), were found. Water, intramuscular fat, protein and glycogen contents were determined. All the three alleles at the RN locus affected the studied technological meat quality traits of pork loin, except for the internal reflectance 24 h post mortem and the shear force. The RN À allele was dominant over the other two alleles, rn + and rn*, in LD with regard to ultimate pH, water-holding capacity and cooking loss, giving lower ultimate pH and water-holding capacity and higher cooking loss. The rn* allele affected ultimate pH in LD of non-carriers of the RN À allele, giving higher ultimate pH. The RN À allele was also dominant over the other two alleles in residual glycogen content in entire male pigs, but not in female pigs, where the rn* allele had a glycogen-lowering effect. The water content was higher and the protein content lower in LD of all RN À /-animals compared with the other genotypes, while no significant differences were found with regard to IMF content. Water-holding capacity, cooking loss and shear force were higher in LD of entire males compared with females. #
Quality pork genes and meat production
Meat Science, 2005
Functional genomics, including analysis of the transcriptome and proteome, provides new opportunities for understanding the molecular processes in muscle and how these influence its conversion to meat. The Quality Pork Genes project was established to identify genes associated with variation in different aspects of raw material (muscle) quality and to then develop genetic tools that could be utilized to improve this quality. DNA polymorphisms identified in the porcine PRKAG3 and CAST genes illustrate the impact that such tools can have in improving meat quality. The resources developed in Quality Pork Genes provide the basis for identifying more of these tools.
Novel Technology to the Genetic Improvement of Swine
2001
The last decade has seen remarkable progress in the understanding of genomes, including those of farm animals such as the pig. The swine industry has played a significant part in these developments, both by providing direct research support and by its rapid uptake of the practical tools that have been generated. The genetic linkage map now contains over 2000 loci including several hundred genes. This information has enabled researchers to search for loci influencing traits of economic importance using genome scans (or quantitative trait loci, QTL, analysis) and candidate gene approaches. QTL for growth and backfat, meat quality traits and reproduction have been identified. The causative mutations for traits such as porcine stress syndrome (HAL or CRC1), acid meat (RN) and coat colour have all been identified. A mutation in the FUT1 gene confers resistance to a common E. coli associated with a postweaning scours. In addition, results obtained with polymorphisms in candidate genes hav...
Genetic parameters of meat quality traits in two pig breeds measured by rapid methods
animal, 2010
To study genetic variation in meat quality traits measured by rapid methods, data were recorded between 2005 and 2008 on samples of M. longissimus dorsi (LD) in Landrace (n 5 3838) and Duroc (n 5 2250) pigs included in the Norwegian pig breeding scheme. In addition, ultimate pH levels in the glycolytic LD (loin muscle) and M. gluteus medius (GM, ham muscle), and in the oxidative m. gluteus profundus (GP, ham muscle) were recorded as an extended data set (n 5 16 732 and n 5 7456 for Landrace and Duroc, respectively) from 1998 to 2008. Data were analysed with a multi-trait animal model using AI-REML methodology. Meat from Duroc had considerably more intramuscular fat (IMF), less moisture and protein, appeared darker with higher colour intensity and had lower drip loss than meat from Landrace. The heritability estimates (s.e. 0.01 to 0.07) for pH in LD (0.19 and 0.27 for Landrace and Duroc, respectively), GM (0.12 and 0.22) and GP (0.19 and 0.38), drip loss (0.23 and 0.33), colour values: L* (lightness) (0.41 and 0.28), a* (redness) (0.46 and 0.43), b* (yellowness) (0.31 and 0.33), IMF (0.50 and 0.62), muscle moisture (0.31 and 0.50) and muscle protein content (0.40 and 0.54) in LD all demonstrated moderate-to-high genetic variation for these traits in both breeds. Near infrared spectroscopy and EZ-DripLoss are modern technologies used in this study for the determination of chemical components and drip loss in meat. These methods gave higher heritabilities than more traditional methods used to measure these traits. The estimated genetic correlations between moisture and IMF in Duroc, and pH and drip loss in Duroc were both 20.89. Interesting differences between the two breeds in numerical value of some genetic correlations were observed, probably reflecting the differences in physiology and selection history between Landrace and Duroc. The estimated genetic correlation between drip loss and pH was much stronger in Duroc than in Landrace (20.89 and 20.63, respectively). This might be due to the high pH in Duroc, whereas Landrace had a lower pH closer to the iso-electric point for muscle proteins. The positive genetic correlation between the L* value in meat and IMF in Duroc (0.50) was an effect of differences in visible marbling, rather than meat colour. For Landrace, this correlation was negative (20.20). IMF content showed favourable genetic correlations to drip loss (20.36 and 20.35 for Landrace and Duroc, respectively).
Genetics and Molecular Research, 2020
The objective of this research was to identify candidate gene markers based on their function related to marbling score and meat quality traits in pigs. A total of 313 commercial pigs with five different Duroc (DR) breed fractions: 1 = 100%DR (n = 227), 2 = 50%DR x 50% Large white (LW)(n = 7), 3 = 50%DR x 50%Landrace (LR)(n = 41), 4 = 75%DR x 25%LW (n = 18), and 5 = 50%DR x 25%LW x 25%LR (n = 20) were measured for marbling score (score 3; MB3 and score 6; MB6), Color (L*), % cooking loss and shear force meat characters. The pigs were slaughtered at around 190 days of age, at an average weight of 122 kg. Five candidate genes (LIPE, LEPR, ADRB3, CAPN1, and CAST) were genotyped by using-RFLP. The genetic parameters were estimated with Bayesian analysis via Gibbs sampling and analyzed by estimated breeding value by BLUP. The breed group had an effect on traits, especially marbling traits, percent cooking loss, and shear force. In Duroc purebreds, the marbling scores were significantly higher than in Duroc crossbreds. Al parameters were significantly higher in 50%DR ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 19 (2): gmr18615 W. Kenchaiwong et al. 2 x 50% Large white (LW) compared with the others. Association analysis showed that the AG genotype of the ADRB3 gene had a higher marbling score than the GG genotype (2.22 vs 1.99 for MB3, 2.92 vs 2.49 for MB6; P < 0.05). The lowest estimated breeding values (EBVs) for color (L*)(3.88) and % cooking loss (2.64) were obtained in the CC genotype of the CAPN1 gene. The GG genotype showed lower shear force and EBVs compared to the AG genotype of CAST gene (4.08 vs 4.85 for shear force (P < 0.05) and-0.03 vs 0.05 for EBV's, P < 0.01). The AG genotype of ADRB3 could be used in marker assisted selection to improve marbling scores. Also, the GG genotype of CAST is the most appropriate for selection for pork tenderness.
Associations of fifty single nucleotide polymorphisms within candidate genes with meatness in pigs
Czech Journal of Animal Science, 2014
The objective of the paper was to classify 50 SNPs (from 17 chromosomes) according to their contribution to the meatness of 293 boars of two breeds (Polish Landrace and Polish Large White) using entropy analysis and standard association analysis. The collected data were classified into two groups (according to the official EUROP procedure) and used for entropy analysis. Associations of single genotypes versus their groups (located at single chromosomes) with the trait studied were estimated by the use of the Generalized Linear Model (GLM). Thus meatness was included as a continuous variable. The most important contributions have been estimated by both approaches for the following SNPs: SULT1A1:g.76G>A (SSC3), PKLR:g.384C>T (SSC4), MYOD1:c.566G>C (SSC2), TNNT3:g.153T>C (SSC2), GAA:g.38T>C (SSC12), LDLRR1:c.459A>G (SSC8), MYF6:g.255T>C (SSC5), CAS:g.499A>C (SSC2), PPARGC:c.678T>A (SSC15). Moreover, interactions among some studied loci are suggested, especial...
Genome-Wide Association Study of Meat Quality Traits in a
2013
Thousands of QTLs for meat quality traits have been identified by linkage mapping studies, but most of them lack precise position or replication between populations, which hinder their application in pig breeding programs. To localize QTLs for meat quality traits to precise genomic regions, we performed a genome-wide association (GWA) study using the Illumina PorcineSNP60K Beadchip in two swine populations: 434 Sutai pigs and 933 F2 pigs from a White Duroc6Erhualian intercross. Meat quality traits, including pH, color, drip loss, moisture content, protein content and intramuscular fat content (IMF), marbling and firmness scores in the M. longissimus (LM) and M. semimembranosus (SM) muscles, were recorded on the two populations. In total, 127 chromosome-wide significant SNPs for these traits were identified. Among them, 11 SNPs reached genome-wise significance level, including 1 on SSC3 for pH, 1 on SSC3 and 3 on SSC15 for drip loss, 3 (unmapped) for color a*, and 2 for IMF each on SSC9 and SSCX. Except for 11 unmapped SNPs, 116 significant SNPs fell into 28 genomic regions of approximately 10 Mb or less. Most of these regions corresponded to previously reported QTL regions and spanned smaller intervals than before. The loci on SSC3 and SSC7 appeared to have pleiotropic effects on several related traits. Besides them, a few QTL signals were replicated between the two populations. Further, we identified thirteen new candidate genes for IMF, marbling and firmness, on the basis of their positions, functional annotations and reported expression patterns. The findings will contribute to further identification of the causal mutation underlying these QTLs and future marker-assisted selection in pigs.
Genetic polymorphism of candidate genes in pig meat production
Acta Agraria Debreceniensis
H-FABP, LEPR and MC5R genes were suggested as candidate genes for fat content in pig meat. The aim of this study was to detect genetic variation in the porcine H-FABP, LEPR and MC5R genes by PCR-RFLP method in a group of pigs. Genotyping of pigs was done by PCRRFLP methods. We identified three genotypes in the set of pigs, HH (0.504), Hh (0.412) and hh (0.084) for H-FABP (HinfI). Allele H showed higher frequency than allele h (0.710 vs. 0.290). Three genotypes were identified for the H-FABP (HaeIII) gene (DD - 0.194, Dd - 0.494, dd - 0.312). The allele D (0.441) showed slightly lower frequency than allele d (0.559). All three genotypes were identified for LEPR (HpaII) in the group of pigs (AA – 0.137, AB - 0.314, BB – 0.549). Higher frequency of LEPR gene was confirmed for allele B (0.706), as compared with allele A (0.294). We identified two genotypes for MC5R (BsaHI) in the group of pigs (AA - 0.348 and AG - 0.652), genotype GG was not found. As conforms with genotype structure, w...