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Sows from five commercial herds were weaned in the fall and winter and used to ascertain the potential application of hormonal therapy to stimulate subsequent litter size born. At weaning sows within parity (1, 2, and 3 through 6) and lactation length classification (early weaned, [is less than or equal to] 14 d; conventionally weaned, [is greater than] 14 d) were randomly assigned to treatment. Treatments were injection with P.G. 600 (400 IU PMSG with 200 IU hCG) at weaning or no treatment. Sows were individually observed for estrus and mated following protocol for each herd. Breeding, culling, and farrowing data were collected. Treatment with P.G. 600 did not change subsequent rebreeding performance for sows at parity 1 or parities 3 through 6. However, conventionally weaned parity-2 sows treated with P.G. 600 were more likely (P [is less than] .05) to return to estrus than conventionally weaned controls (99.0 vs 93.6%, respectively). For parity-1 and parity-2 sows, treatment did not significantly change the likelihood for farrow percentage. However, the likelihood to farrow a litter was greater (P [is less than] .05) among P.G. 600-treated sows at parities 3 to 6 that were conventionally weaned (84.4 vs 71.3%, respectively). Subsequent litter birth weight for parity-1 sows treated with P.G. 600 was lower (P [is less than] .02) than for controls (15.6 vs 16.6 kg, respectively). Subsequent litter size at birth was not affected by treatment for parity-1 or parity-2 sows compared with controls. However, early-weaned sows at parities 3 through 6 treated with P.G. 600 had more (P [is less than] .06) total number born than controls (12.4 vs 10.6, respectively). Treatment with P.G. 600 improved reproductive function within specific parity and lactation length classification for sows weaned in the fall and winter. Key Words: Hormones, Lactation Duration, Pigs, Seasons, Therapy

The identification of genomic regions that affect additive genetic variation and contain genes involved in controlling growth and fat deposition has enormous impact in the farm animal industry (e.g., carcass merit and meat quality). Therefore, a genomewide association study was implemented in an F2 pig population using a 60,000 SNP marker panel for traits related to growth and fat deposition. Estimated genomic EBV were linearly transformed to calculate SNP effects and to identify genomic positions possibly associated with the genetic variability of each trait. Genomic segments were then defined considering the markers included in a region 1 Mb up- and downstream from the SNP with the smallest P-value and a false discovery rate < 0.05 for each trait. The significance for each 2-Mb segment was tested using the Bonferroni correction. Significant SNP were detected on SSC2, SSC3, SSC5, and SSC6, but 2-Mb segment significant effects were observed on SSC3 for weight at birth (wt_birth) and on SSC6 for 10th-rib backfat and last-rib backfat measured by ultrasound at different ages. Furthermore, a 6-Mb segment on SSC6 was also considered because the 2-Mb segments for 10 different fat deposition traits were overlapped. Although the segment effects for each trait remain significant, the proportion of additive variance explained by this larger segment was slightly smaller in some traits. In general, the results confirm the presence of genetic variability for wt_birth on SSC3 (18.0-20.2 Mb) and for fat deposition traits on SSC6 (133.8-136.0 Mb). Within these regions, fibrosin (FBRS) and myosin light chain, phosphorylatable, fast skeletal muscle (MYLPF) genes could be considered as candidates for the wt_birth signal on SSC3, and the SERPINE1 mRNAbinding protein 1 gene (SERBP1) may be a candidate for the fat deposition trait signals on SSC6. [ABSTRACT FROM AUTHOR]

Genome-wide association ( GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis ( MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits. [ABSTRACT FROM AUTHOR]

Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a metaanalysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining z-scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [CAPN1] and calpastatin [CAST]), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, ? 3 noncatalytic subunit [PRKAG3]). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial [ACSF3]) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [GYS1] and ferritin, light polypeptide [FTL]). Thus, implementation of MA-GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations. [ABSTRACT FROM AUTHOR]

Pigs from the F2 generation of a Duroc x Pietrain resource population were evaluated to discover QTL affecting carcass composition and meat quality traits. Carcass composition phenotypes included primal cut weights, skeletal characteristics, backfat thickness, and LM area. Meat quality data included LM pH, temperature, objective and subjective color information, marbling and firmness scores, and drip loss. Addition- ally, chops were analyzed for moisture, protein, and fat composition as well as cook yield and Warner-Bratzler shear force measurements. Palatability of chops was determined by a trained sensory panel. A total of 510 F2 animals were genotyped for 124 microsatellite markers evenly spaced across the genome. Data were analyzed with line cross, least squares regression interval, mapping methods using sex and litter as fixed effects and carcass weight or slaughter age as covariates. Significance thresholds of the F-statistic for single QTL with additive, dominance, or imprinted effects were determined on chromosome- and genome-wise levels by permutation tests. A total of 94 QTL for 35 of the 38 traits analyzed were found to be significant at the 5% chromo- some-wise level. Of these 94 QTL, 44 were significant at the 1% chromosome-wise, 28 of these 44 were also significant at the 5% genome-wise, and 14 of these 28 were also significant at the 1% genome-wise significance thresholds. Putative QTL were discovered for 45-min pH and pH decline from 45 mm to 24 h on SSC 3, marbling score and carcass backfat on SSC 6, carcass length and number of ribs on SSC 7, marbling score on SSC 12, and color measurements and tenderness score on SSC 15. These results will facilitate fine mapping efforts to identify genes controlling carcass composition and meat quality traits that can be incorporated into marker-assisted selection programs to accelerate genetic improvement in pig populations. [ABSTRACT FROM AUTHOR]

Pigs from the F2 generation of a Duroc x Pietrain resource population were evaluated to discover QTL affecting growth and composition traits. Body weight and ultrasound estimates of 10th-rib backfat, last-rib backfat, and LM area were serially measured throughout development. Estimates of fat-free total lean, total body fat, empty body protein, empty body lipid, and ADG from 10 to 22 wk of age were calculated, and random regression analyses were performed to estimate individual animal phenotypes representing intercept and linear rates of increase in these serial traits. A total of 510 F2 animals were genotyped for 124 micro-satellite markers evenly spaced across the genome. Data were analyzed with line cross, least squares regression, interval mapping methods using sex and litter as fixed effects. Significance thresholds of the F-statistic for single QTL with additive, dominance, or imprinted effects were determined at the chromosome- and genome-wise levels by permutation tests. A total of 43 QTL for 22 of the 29 measured traits were found to be significant at the 5% chromosome-wise level. Of these 43 QTL, 20 were significant at the 1% chromosome-wise significance threshold, 14 of these 20 were also significant at the 5% genome-wise significance threshold, and 10 of these 14 were also significant at the 1% genome-wise significance threshold. A total of 22 QTL for the animal random regression terms were found to be significant at the 5% chromosome-wise level. Of these 22 QTL, 6 were significant at the 1% chromosome-wise significance threshold, 4 of these 6 were also significant at the 5% genome-wise significance threshold, and 3 of these 4 were also significant at the 1% genome-wise significance threshold. Putative QTL were discovered for 10th-rib and last-rib backfat on SSC 6, body composition traits on SSC 9, backfat and lipid composition traits on SSC 11, 10th-rib backfat and total body fat tissue on SSC 12, and linear regression of last-rib backfat and total body fat tissue on SSC 8. These results will facilitate fine-mapping efforts to identify genes controlling growth and body composition of pigs that can be incorporated into marker-assisted selection programs to accelerate genetic improvement in pig populations. [ABSTRACT FROM AUTHOR]

Meat quality is essential for consumer acceptance and ultimately impacts pork production profitability, and it is subject to genetic control. We performed genomewide association analysis of pork quality traits to increase our understanding of die genetic basis of variation in these traits. Thirty-eight meat quality and carcass traits were recorded in 948 F2 pigs from the Michigan State University Duroc x Pietrain F2 resource population. The F0 Fp and 336 F2 pigs were genotyped with the Illumina Porcine SNP60 beadchip, and the remaining F2 animals were genotyped with the GeneSeek Genomic Profiler for Porcine LD chip. Monomorphic SNP and low-quality genotypes where discarded, and the remaining missing genotypes where imputed (accuracy = 0.968). A total of 44,911 SNP remained for analysis. Analysis was performed using linear mixed effects models using the R gwaR package. Fixed effects of sex, contemporary group, and age at slaughter and a random polygenic effect with variance proportional to marker relationship matrix G were included. Type I error rate was controlled at false discover rate = 5%. Ten putative QTL regions were found for 16 meat quality and carcass traits. Table 030 shows for each trait the chromosomal location for the QTL, physical peak position, the g-value, and the total number of annotated genes found in the region. These regions can now be further evaluated to search for functional candidate genes. For instance, a QTL associated with backfat thickness was identified on chromosome 6. This region includes genes that encode the enzymes phosphoglucomutase 1 and acyl-CoA dehydrogenase C4 to C12 straight chain, which are involved in pathways for glycogenolysis and lipolysis, respectively. The QTL and genes in the regions should be further investigated to assess their potential to improve pork quality. [ABSTRACT FROM AUTHOR]