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Wu P, Wang K, Zhou J, Chen D, Yang X, Jiang A, Shen L, Zhang S, Xiao W, Jiang Y, Zhu L, Zeng Y, Xu X, Li X, Tang G. Whole-genome sequencing association analysis reveals the genetic architecture of meat quality traits in Chinese Qingyu pigs. Genome 2020; 63:503-515. [PMID: 32615048 DOI: 10.1139/gen-2019-0227] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The Chinese Qingyu pig breed is an invaluable indigenous genetic resource. However, few studies have investigated the genetic architecture of meat quality traits in Qingyu pigs. Here, 30 purebred Qingyu pigs were subjected to whole-genome sequencing. After quality control, 18 436 759 SNPs were retained. Genome-wide association studies (GWAS) were then performed for meat pH and color at three postmortem time points (45 min, 24 h, and 48 h) using single-marker regression analysis. In total, 11 and 69 SNPs were associated with meat pH and color of the longissimus thoracis muscle (LTM), respectively, while 54 and 29 SNPs were associated with meat pH and color of the semimembranosus muscle (SM), respectively. Seven SNPs associated with pork pH were shared by all three postmortem time points. Several candidate genes for meat traits were identified, including four genes (CXXC5, RYR3, BNIP3, and MYCT1) related to skeletal muscle development, regulation of Ca2+ release in the muscle, and anaerobic respiration, which are promising candidates for selecting superior meat quality traits in Qingyu pigs. To our knowledge, this is the first study investigating the postmortem genetic architecture of pork pH and color in Qingyu pigs. Our findings further the current understanding of the genetic factors influencing meat quality.
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Affiliation(s)
- Pingxian Wu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Kai Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Jie Zhou
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Dejuan Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Xidi Yang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Anan Jiang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Linyuan Shen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Shunhua Zhang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Weihang Xiao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yanzhi Jiang
- College of Life Science, Sichuan Agricultural University, Yaan 625014, Sichuan, China
| | - Li Zhu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yangshuang Zeng
- Sichuan Animal Husbandry Station, Chengdu, 610041, Sichuan, China
| | - Xu Xu
- Sichuan Animal Husbandry Station, Chengdu, 610041, Sichuan, China
| | - Xuewei Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Guoqing Tang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
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Hlongwane NL, Hadebe K, Soma P, Dzomba EF, Muchadeyi FC. Genome Wide Assessment of Genetic Variation and Population Distinctiveness of the Pig Family in South Africa. Front Genet 2020; 11:344. [PMID: 32457791 PMCID: PMC7221027 DOI: 10.3389/fgene.2020.00344] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/23/2020] [Indexed: 12/12/2022] Open
Abstract
Genetic diversity is of great importance and a prerequisite for genetic improvement and conservation programs in pigs and other livestock populations. The present study provides a genome wide analysis of the genetic variability and population structure of pig populations from different production systems in South Africa relative to global populations. A total of 234 pigs sampled in South Africa and consisting of village (n = 91), commercial (n = 60), indigenous (n = 40), Asian (n = 5) and wild (n = 38) populations were genotyped using Porcine SNP60K BeadChip. In addition, 389 genotypes representing village and commercial pigs from America, Europe, and Asia were accessed from a previous study and used to compare population clustering and relationships of South African pigs with global populations. Moderate heterozygosity levels, ranging from 0.204 for Warthogs to 0.371 for village pigs sampled from Capricorn municipality in Eastern Cape province of South Africa were observed. Principal Component Analysis of the South African pigs resulted in four distinct clusters of (i) Duroc; (ii) Vietnamese; (iii) Bush pig and Warthog and (iv) a cluster with the rest of the commercial (SA Large White and Landrace), village, Wild Boar and indigenous breeds of Koelbroek and Windsnyer. The clustering demonstrated alignment with genetic similarities, geographic location and production systems. The PCA with the global populations also resulted in four clusters that where populated with (i) all the village populations, wild boars, SA indigenous and the large white and landraces; (ii) Durocs (iii) Chinese and Vietnamese pigs and (iv) Warthog and Bush pig. K = 10 (The number of population units) was the most probable ADMIXTURE based clustering, which grouped animals according to their populations with the exception of the village pigs that showed presence of admixture. AMOVA reported 19.92%-98.62% of the genetic variation to be within populations. Sub structuring was observed between South African commercial populations as well as between Indigenous and commercial breeds. Population pairwise F ST analysis showed genetic differentiation (P ≤ 0.05) between the village, commercial and wild populations. A per marker per population pairwise F ST analysis revealed SNPs associated with QTLs for traits such as meat quality, cytoskeletal and muscle development, glucose metabolism processes and growth factors between both domestic populations as well as between wild and domestic breeds. Overall, the study provided a baseline understanding of porcine diversity and an important foundation for porcine genomics of South African populations.
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Affiliation(s)
- Nompilo Lucia Hlongwane
- Biotechnology Platform, Agricultural Research Council, Onderstepoort, South Africa
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermartizburg, South Africa
| | - Khanyisile Hadebe
- Biotechnology Platform, Agricultural Research Council, Onderstepoort, South Africa
| | - Pranisha Soma
- Animal Production Institute, Agricultural Research Council, Irene, South Africa
| | - Edgar Farai Dzomba
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermartizburg, South Africa
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Jang D, Yoon J, Taye M, Lee W, Kwon T, Shim S, Kim H. Multivariate genome-wide association studies on tenderness of Berkshire and Duroc pig breeds. Genes Genomics 2018; 40:701-705. [PMID: 29934809 DOI: 10.1007/s13258-018-0672-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2017] [Accepted: 02/16/2018] [Indexed: 11/24/2022]
Abstract
Genome-wide association studies (GWAS) have been steadily used for identification of genomic links to disease and various economical traits. Of those traits, a tenderness of pork is one of the most important factors in quality evaluation of consumers. In this study, we use two pig breed populations; Berkshire is known for its excellent meat quality and Duroc which is known for its high intramuscular fat content in meat. Multivariate genome-wide association studies (MV-GWAS) was executed to compare SNPs of two pigs to find out what genetic variants occur the tenderness of pork. Through MV-GWAS, we have identified candidate genes and the association of biological pathways involved in the tenderness of pork. From these direct and indirect associations, we displayed the usefulness of simple statistical models and their potential contribution to improving the meat quality of pork. We identified a candidate gene related to the tenderness in only Berkshire. Furthermore, several of the biological pathways involved in tenderness in both Berkshire and Duroc were found. The candidate genes identified in this study will be helpful to use them in breeding programs for improving pork quality.
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Affiliation(s)
- Dongsung Jang
- Interdisciplinary Program in Agricultural Genomics, Seoul National University, Seoul, Republic of Korea
| | - Joon Yoon
- Department of Natural Science, Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Mengistie Taye
- Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.,College of Agriculture and Environmental Sciences, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia
| | - Wonseok Lee
- Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
| | - Taehyung Kwon
- Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
| | - Seunghyun Shim
- LAS Inc., 16, Arayuk-ro, Gochon-eup, Gimpo-si, Gyeonggi-do, Republic of Korea
| | - Heebal Kim
- Department of Natural Science, Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea. .,Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea. .,Institute for Biomedical Sciences, Shinshu University, Nagano, Japan.
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Feeding patterns, growth performance and carcass traits in group-housed growing-finishing pigs: the effect of terminal sire line, halothane genotype and age. ACTA ACUST UNITED AC 2016. [DOI: 10.1017/s1357729800053601] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
AbstractThe effects of terminal sire line, halothane genotype and age on feeding patterns and growth performance were studied in 208 castrated growing-finishing pigs distributed in two batches. In batch 1 (no. = 130), pigs came from crosses of NN Landrace × Large White sows with a Pietrain Nn (Pi-Nn) or a Large White × Pietrain Nn terminal sire line (LwPi-Nn). In batch 2 (no. = 78), the same sows were used but crossed with three different terminal sire lines : a Pietrain nn (Pi-nn), and two Pietrain NN (Pi-NNa and Pi-NNb). Growth performance and feeding patterns of the progeny (Nn or NN for the halothane gene) were measured from 67 to 166 days of age. Pigs were housed in groups of 10 and 13 individuals in Batch 1 and 2, respectively, with a random mixed-breed and halothane genotype sample in each group (space allowance 1·3 m2 per pig and 1·1 m2 per pig, respectively). Feeding patterns were monitored with a computerized food intake recording system (IVOG®-station) and every 3 weeks pigs were weighed and backfat and loin-muscle depth were ultrasonically recorded (PIGLOG®). Carcass quality was assessed with the Fat-o-Meater grading probe. In batch 1, halothane genotype did not have a significant effect on any of the feeding patterns recorded, but Nn individuals had a significantly higher body weight (P <0·05), loin-muscle depth (P <0·05) and lower backfat thickness (P <0·01) in the last measurement taken, 3/4 carcass loin depth (P <0·05) and lower carcass last rib backfat (P <0·05) than NN pigs. Terminal sire line had a significant effect on all feeding patterns recorded except for feeding rate, Pi-Nn sired pigs showing a significantly higher food intake per visit (P <0·05) and feeder occupation time per visit (P <0·05) and lower number of visits (P <0·001) compared with LwPi-Nn sired pigs which, in turn, showed significantly higher food intake per day (P <0·001) and feeder occupation time per day (P <0·01). Terminal sire also affected growth performance and body composition, Pi-Nn sired pigs having a significantly lower body weight (P <0·001) and backfat thickness (P <0·001) but higher killing-out proportion and 3/4 loin depth (P <0·01) than LwPi-Nn sired pigs. In batch 2, Pi-NNb sired pigs showed a significantly lower food intake per day compared with the progeny of the other two terminal sires lines at some of the age measurements taken (P <0·05). The rest of the feeding patterns was not affected by terminal sire line. Body and carcass weights were also significantly lower (P <0·01) for Pi-NNb sired pigs, but their killing-out proportion was higher than Pi-NNa sired pigs. With regard to these variables, Pi-nn sired pigs held an intermediate position between the two NN terminal sire lines. In both batches, age was associated with a significant increase in food intake per visit and per day and feeding rate (P <0·001) and a decrease in feeder occupation time per visit and per day and frequency of visits to the feeder (P <0·001). Overall, the present results suggest differences between terminal sire lines for feeding patterns and confirm their evolution with age from short and frequent meals to long and larger ones in growing-finishing pigs. Under our conditions, the effects of terminal sire line on feeding patterns and growth performance surpassed those of the halothane genotype.
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Lee T, Shin DH, Cho S, Kang HS, Kim SH, Lee HK, Kim H, Seo KS. Genome-wide Association Study of Integrated Meat Quality-related Traits of the Duroc Pig Breed. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2014; 27:303-9. [PMID: 25049955 PMCID: PMC4093258 DOI: 10.5713/ajas.2013.13385] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Revised: 11/23/2013] [Accepted: 09/07/2013] [Indexed: 11/27/2022]
Abstract
The increasing importance of meat quality has implications for animal breeding programs. Research has revealed much about the genetic background of pigs, and many studies have revealed the importance of various genetic factors. Since meat quality is a complex trait which is affected by many factors, consideration of the overall phenotype is very useful to study meat quality. For integrating the phenotypes, we used principle component analysis (PCA). The significant SNPs refer to results of the GRAMMAR method against PC1, PC2 and PC3 of 14 meat quality traits of 181 Duroc pigs. The Genome-wide association study (GWAS) found 26 potential SNPs affecting various meat quality traits. The loci identified are located in or near 23 genes. The SNPs associated with meat quality are in or near five genes (ANK1, BMP6, SHH, PIP4K2A, and FOXN2) and have been reported previously. Twenty-five of the significant SNPs also located in meat quality-related QTL regions, these result supported the QTL effect indirectly. Each single gene typically affects multiple traits. Therefore, it is a useful approach to use integrated traits for the various traits at the same time. This innovative approach using integrated traits could be applied on other GWAS of complex-traits including meat-quality, and the results will contribute to improving meat-quality of pork.
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Affiliation(s)
- Taeheon Lee
- C&K genomics, Seoul National University Research Park, Seoul 151-919, Korea
| | - Dong-Hyun Shin
- C&K genomics, Seoul National University Research Park, Seoul 151-919, Korea
| | - Seoae Cho
- C&K genomics, Seoul National University Research Park, Seoul 151-919, Korea
| | - Hyun Sung Kang
- Department of Animal Science and Technology, College of Life Science and Natural Resources, Sunchon National University, Suncheon, 540-742, Korea
| | - Sung Hoon Kim
- Genomic Informatics Center, Hankyong National University, Anseong 456-749, Korea
| | - Hak-Kyo Lee
- Genomic Informatics Center, Hankyong National University, Anseong 456-749, Korea
| | - Heebal Kim
- C&K genomics, Seoul National University Research Park, Seoul 151-919, Korea
| | - Kang-Seok Seo
- Department of Animal Science and Technology, College of Life Science and Natural Resources, Sunchon National University, Suncheon, 540-742, Korea
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Ma J, Yang J, Zhou L, Zhang Z, Ma H, Xie X, Zhang F, Xiong X, Cui L, Yang H, Liu X, Duan Y, Xiao S, Ai H, Ren J, Huang L. Genome-wide association study of meat quality traits in a White Duroc×Erhualian F2 intercross and Chinese Sutai pigs. PLoS One 2013; 8:e64047. [PMID: 23724019 PMCID: PMC3665833 DOI: 10.1371/journal.pone.0064047] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2012] [Accepted: 04/07/2013] [Indexed: 12/31/2022] Open
Abstract
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 Duroc×Erhualian 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.
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Affiliation(s)
- Junwu Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Jie Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Lisheng Zhou
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Zhiyan Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Huanban Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xianhua Xie
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Feng Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xinwei Xiong
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Leilei Cui
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Hui Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xianxian Liu
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Yanyu Duan
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Huashui Ai
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Jun Ren
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
- * E-mail:
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Pinheiro REE, Cardoso EC, Júnior MHK, Muratori MCS, Lopes JB, Farias LA, Teixeira MDPF. Qualidade da carne de suínos mestiços comerciais e sem raça definida criados em regime intensivo. REVISTA BRASILEIRA DE SAÚDE E PRODUÇÃO ANIMAL 2013. [DOI: 10.1590/s1519-99402013000100016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
A pesquisa foi realizada com o objetivo de verificar o efeito da criação intensiva em suínos nativos sem raça definida (SRD) de ambos os sexos sobre a qualidade da carne em comparação aos mestiços comerciais. Foram utilizados no experimento 20 suínos sem raça definida, sendo dez fêmeas e dez machos castrados e dez suínos mestiços comerciais. As variáveis analisadas no experimento foram medidas de carcaça, e análises físicas e químicas dos cortes de lombo. Suínos melhorados mostraram área de gordura subcutânea e área de olho de lombo maior. A comparação entre as medidas de área de olho de lombo e área de gordura subcutânea podem ser utilizadas com indicativo da relação carne e gordura. Houve o efeito do sexo nos suínos sem raça definida, onde as fêmeas apresentaram melhores índices de composição tecidual, centesimal e na perda de peso por cozimento. O principal depósito de gordura nos animais machos sem raça definida foi a subcutânea, verificado no corte do lombo. Os resultados deste trabalho permitiram demonstrar que existe uma importante diferença em relação a deposição de gordura entre suínos mestiços comerciais e os SRD, no entanto mantendo aceitáveis os níveis nutricionais da composição centesimal da carne dos SRD. Devem ser realizados novos estudos, com diferentes idades e pesos de abates, incluindo análises sensoriais.
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Weschenfelder AV, Torrey S, Devillers N, Crowe T, Bassols A, Saco Y, Piñeiro M, Saucier L, Faucitano L. Effects of trailer design on animal welfare parameters and carcass and meat quality of three Pietrain crosses being transported over a long distance. J Anim Sci 2013; 90:3220-31. [PMID: 22966081 DOI: 10.2527/jas.2012-4676] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
This study aimed at evaluating the effects of trailer design on stress responses and meat quality traits of 3 different pig crosses: 50% Pietrain breeding with halothane (HAL)(Nn) (50Nn); 50% Pietrain breeding with HAL(NN) (50NN); and 25% Pietrain breeding with HAL(NN) genotype (25NN). Over a 6-wk period, pigs (120 pigs/crossbreed) were transported for 7 h in either a pot-belly (PB) or flat-deck (FD) trailer (10 pigs/crossbreed(-1)·trailer(-1)·wk(-1)). Temperature (T) and relative humidity (RH) were monitored in each trailer. Behaviors during loading and unloading, time to load and unload, and latency to rest in lairage were recorded, whereas a sub-population of pigs (4 pigs/crossbreed(-1)·trailer(-1)·wk(-1)) was equipped with gastro-intestinal tract (GIT) temperature monitors. Blood samples were collected at exsanguination for measurement of cortisol, creatine kinase (CK), lactate, haptoglobin, and Pig-MAP concentrations. Meat quality data were collected at 24 h postmortem from the LM and semimembranosus (SM) and adductor (AD) muscles of all 360 pigs. Greater T were recorded in the PB trailer during transportation (P = 0.006) and unloading (P < 0.001). Delta GIT temperature was greater (P = 0.01) in pigs unloaded from the PB. At loading, pigs tended to move backwards more (P = 0.06) when loaded on the FD than the PB trailer. At unloading, an interaction was found between trailer type and crossbreed type, with a greater (P < 0.01) frequency of overlaps in 50NN and 25NN pigs and slips/falls in 50Nn and 50NN pigs from the FD than the PB trailer. Cortisol concentrations at slaughter were greater (P = 0.02) in pigs transported in the PB than FD trailer. Greater lactate concentrations were found in 50Nn and 50NN pigs (P = 0.003) and greater CK concentrations (P < 0.001) in 50Nn pigs. As expected, 50Nn pigs produced leaner (P < 0.001) carcasses, with greater (P = 0.01) dressing percentages, as well as lower (P < 0.001) ultimate pH values and greater (P < 0.001) drip loss percentages in the LM and greater (P = 0.002) drip losses and a paler color (greater L* values, P = 0.02) in the SM than 50NN pigs. When used for long distance transportation under controlled conditions, the PB trailer produced no detrimental effects on animal welfare or pork quality. Pigs with 50% Pietrain crossbreeding appear to be more responsive to transport stress, having the potential to produce acceptable carcass and pork quality, provided pigs are free of the HAL gene.
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Affiliation(s)
- A V Weschenfelder
- Agriculture and Agri-Food Canada, Dairy and Swine and Development Research Centre, Sherbrooke, QC, J1M 0C8, Canada
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Chan JT, Omana DA, Betti M. Effect of ultimate pH and freezing on the biochemical properties of proteins in turkey breast meat. Food Chem 2011. [DOI: 10.1016/j.foodchem.2010.12.095] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Feeding diets based on barley or triticale during fattening of high-meat PIC pigs: Effects on carcass characteristics and meat quality parameters. ACTA VET-BEOGRAD 2011. [DOI: 10.2298/avb1101067t] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Lin CS, Hsu CW. Differentially transcribed genes in skeletal muscle of Duroc and Taoyuan pigs. J Anim Sci 2008; 83:2075-86. [PMID: 16100062 DOI: 10.2527/2005.8392075x] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The objective of this study was to compare gene transcription profiles of LM between two pig breeds, Duroc and Taoyuan, which display dramatically different postnatal muscle growth. We isolated LM from neonatal pigs, and the Duroc muscle length and mass were greater (P < 0.01) than for Taoyuan pigs; however, insignificant differences in the muscle fiber area and the percentage of fiber types were found. A human high-density complementary DNA (cDNA) microarray consisting of 9,182 probes was used to compare gene transcription profiles of LM between the two breeds. The results showed that the transcription level of 73 genes and 44 genes in Duroc LM were upregulated and down-regulated by at least 1.75-fold (P < 0.05) compared with Taoyuan, respectively. The strongly upregulated genes in Duroc pigs included those encoding the complex of myofibrillar proteins (e.g., myosin light and heavy chains, and troponin), ribosomal proteins, transcription regulatory proteins (e.g., skeletal muscle LIM protein 1 [SLIM1] and high-mobility group proteins), and energy metabolic enzymes (e.g., electron-transferring flavo-protein dehydrogenase, NADH dehydrogenase, malate dehydrogenase, and ATP synthases). The highly transcribed genes that encode energy metabolic enzymes indicate a more glycolytic metabolism in Duroc LM, thereby favoring carbohydrates rather than lipids for use as energy substrates in this tissue. The over-transcribed genes that encode skeletal muscle-predominant proteins or transcription regulators that control myogenesis and/or muscle growth suggest a general mechanism for the observed higher rate of postnatal muscle growth in Duroc pigs. The transcription of one such gene, SLIM1, was more highly transcribed (P < 0.01) in Duroc LM at birth and at postnatal d 7 than in Taoyuan. The transcription of SLIM1 increased (P < 0.05) in Duroc LM from neonate through 7 d of age, whereas its transcription remained essentially constant in Taoyuan during this period. These results suggest that SLIM1 may be useful for the development of markers associated with the postnatal muscle growth of pigs.
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Affiliation(s)
- C S Lin
- Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan, Republic of China.
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Abstract
Pig breeding programs traditionally focus on the genetic improvement of production and reproduction traits that have a clear economic value. Because citizens and consumers increasingly attach value to traits that have little or no direct relationship to production costs or to the price of a product, pig breeding organizations want to pay more attention to societally important traits, such as the welfare and health of pigs, the ecological effects of pork production, and the healthiness and sensory quality of pork. Most societally important traits have an economic and a noneconomic value and are sufficiently heritable for effective genetic selection, although many genetic and phenotypic (co)-variances still have to be estimated. However, it often is not clear to a pig breeding organization how it may deal with the noneconomic value of breeding-goal traits. In this study, a retrospective selection-index method is proposed to obtain the proper weights for societally important traits in the breeding goal. First, the genetic-progress space for each breeding-goal trait is explored by increasing the weights, in a stepwise manner, to each societally important trait in the breeding goal, starting from zero. Subsequently, a pig breeding organization can adopt the resulting genetic-progress scenario that it considers most sustainable or most acceptable. The weights underlying the adopted scenario are considered to be the proper breeding-goal weights. The noneconomic value of each societally important breeding-goal trait is found by deducting its economic value from its obtained weight and is thereby expressed in monetary units. In addition to obtaining weights for societally important breeding-goal traits, the proposed method offers the possibility to estimate the societal costs of selecting for economic traits only, as well as the societal benefits and the economic costs of selecting for traits with a noneconomic value. The method is therefore a useful tool for the development of sustainable breeding goals. An example has been worked out for a sow-line breeding program.
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Andersen HJ, Oksbjerg N, Young JF, Therkildsen M. Feeding and meat quality – a future approach. Meat Sci 2005; 70:543-54. [DOI: 10.1016/j.meatsci.2004.07.015] [Citation(s) in RCA: 133] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2004] [Revised: 07/12/2004] [Accepted: 07/15/2004] [Indexed: 11/24/2022]
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Toldra F, Flores M. Analysis of Meat Quality. FOOD SCIENCE AND TECHNOLOGY 2004. [DOI: 10.1201/b11081-54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Fàbrega E, Manteca X, Font J, Gispert M, Carrión D, Velarde A, Ruiz-de-la-Torre JL, Diestre A. A comparison of halothane homozygous negative and positive pietrain sire lines in relation to carcass and meat quality, and welfare traits. Meat Sci 2004; 66:777-87. [PMID: 22061008 DOI: 10.1016/s0309-1740(03)00128-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2002] [Accepted: 05/16/2003] [Indexed: 11/15/2022]
Affiliation(s)
- E Fàbrega
- Institut de Recerca i Tecnologia Agroalimentàries, Centre de Tecnologia de la Carn, Granja Camps i Armet, 17121 Monells, Girona, Spain
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Garnier JP, Klont R, Plastow G. The potential impact of current animal research on the meat industry and consumer attitudes towards meat. Meat Sci 2003; 63:79-88. [DOI: 10.1016/s0309-1740(02)00059-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2001] [Revised: 02/18/2002] [Accepted: 02/20/2002] [Indexed: 11/25/2022]
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