Smithfield Premium Genetics Group

Rose Hill, NC, United States

Smithfield Premium Genetics Group

Rose Hill, NC, United States
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Fix J.S.,North Carolina State University | Cassady J.P.,North Carolina State University | Herring W.O.,Smithfield Premium Genetics Group | Holl J.W.,Smithfield Premium Genetics Group | And 2 more authors.
Livestock Science | Year: 2010

The objective of this study was to estimate the effect of piglet birth weight on future BW, growth, backfat, and longissimus muscle area of pigs in a commercial U.S. production system. Pigs (n = 5727) at a commercial farm were individually weighed and identified within 24 h of birth. Weights were collected prior to weaning (n = 4108), after finisher placement (n = 3439), and 7 (n = 1622) and 16 (n = 1586) weeks into finishing; hot carcass weight was also collected (n = 1693). Average daily gain during lactation, nursery, finishing, and overall (birth to 16 weeks into finishing) was calculated. During BW collection 16 weeks into finishing, real-time ultrasound backfat thickness and longissimus muscle area were measured. Sex × birth weight (linear and quadratic) interactions were observed for BW at weaning and finisher placement and daily gain during pre-weaning and nursery. Linear birth weight × cross foster interactions were observed for weaning weight and pre-weaning gain. Linear and quadratic effects of birth weight on BW at weaning, finisher placement, 7 and 16 weeks into finishing, and hot carcass weight and average daily gain during pre-weaning, nursery, finishing, and total were observed. For all measures of BW and average daily gain, as birth weight increased subsequent BW and average daily gain increased at a decreasing rate; however, for the sex × birth weight (linear and quadratic) interactions, heavier birth weight barrows were lighter and grew slower than gilts of comparable birth weight. Worth noting, the birth weight × sex interactions described very few pigs in the extreme portion of the birth weight distribution. For birth weight × cross foster interactions, non-cross fostered pigs were increasingly heavier and faster growing as birth weight increased compared to cross fostered pigs. Heavier birth weight pigs tended to have increased backfat depth (P = 0.07). Linear and quadratic effects of birth weight on longissimus muscle area were observed; as birth weight increased muscling increased at a decreasing rate. Regardless of interactions or period of production, increased birth weight resulted in heavier future BW, faster daily gain along with larger longissimus muscle area prior to harvest. In all instances the magnitude of the negative effect of birth weight increased as birth weight decreased.


Fix J.S.,North Carolina State University | Cassady J.P.,North Carolina State University | Holl J.W.,Smithfield Premium Genetics Group | Herring W.O.,Smithfield Premium Genetics Group | And 2 more authors.
Livestock Science | Year: 2010

The objective of this study was to determine the effect of individual piglet birth weight on mortality and pig quality in a U.S. commercial production system. Pigs used in this study were farrowed from Large White × Landrace sows (n= 463) bred to Duroc boars during a 4. week period at a commercial sow farm. Within 24. h of birth, all pigs (born alive = 5727 and stillborns = 513) were weighed and individually indentified. A portion of pigs (16.7%) were cross-fostered to reduce litter size variation during lactation. Individual mortality was recorded daily during the suckling phase. Pigs were weighed 2. days prior to weaning (18.7 ± 2.1. days of age), finisher placement (74.8 ± 1.9. days of age), and 16. weeks into finishing (172.8 ± 1.8. days of age). During BW collections, an inventory of all live pigs was conducted, and pigs were given a quality score based on visual evaluation of BW and health (3 = healthy pig; 2 = slightly small and/or slightly unthrifty; 1 small and/or unthrifty). Survival was analyzed for 4 distinct time periods (prenatal, pre-weaning, nursery phase, and finishing phase). Data were analyzed using a logit (survival) or cumulative logit (quality score) function. Birth weight linear effects on prenatal, pre-weaning, and nursery survival as observed mortality probability increased as birth weight decreased. However birth weight did not impact the likelihood of survival during finishing. As birth weight decreased, the likelihood of pigs being poorer quality, quality score (1 or 2), at weaning, finisher placement, and 16. weeks into finishing, increased. As birth weight increased the likelihood of a pig being full value at the end of the finishing phase increased. Reduced individual piglet birth weight, was associated with reduced pig quality and likelihood of prenatal, pre-weaning, and nursery survival. Because of the negative impact of birth weight on pre-weaning and nursery survival and pig quality in finishing, as birth weight decreased pigs were less likely to be full value at harvest. © 2010 Elsevier B.V.


Lindholm-Perry A.K.,U.S. Department of Agriculture | Rohrer G.A.,U.S. Department of Agriculture | Kuehn L.A.,U.S. Department of Agriculture | Keele J.W.,U.S. Department of Agriculture | And 4 more authors.
BMC Genetics | Year: 2010

Background: A back curvature defect similar to kyphosis in humans has been observed in swine herds. The defect ranges from mild to severe curvature of the thoracic vertebrate in split carcasses and has an estimated heritability of 0.3. The objective of this study was to identify genomic regions that affect this trait.Results: Single nucleotide polymorphism (SNP) associations performed with 198 SNPs and microsatellite markers in a Duroc-Landrace-Yorkshire resource population (U.S. Meat Animal Research Center, USMARC resource population) of swine provided regions of association with this trait on 15 chromosomes. Positional candidate genes, especially those involved in human skeletal development pathways, were selected for SNP identification. SNPs in 16 candidate genes were genotyped in an F2 population (n = 371) and the USMARC resource herd (n = 1,257) with kyphosis scores. SNPs in KCNN2 on SSC2, RYR1 and PLOD1 on SSC6 and MYST4 on SSC14 were significantly associated with kyphosis in the resource population of swine (P ≤ 0.05). SNPs in CER1 and CDH7 on SSC1, PSMA5 on SSC4, HOXC6 and HOXC8 on SSC5, ADAMTS18 on SSC6 and SOX9 on SSC12 were significantly associated with the kyphosis trait in the F2 population of swine (P ≤ 0.05).Conclusions: These data suggest that this kyphosis trait may be affected by several loci and that these may differ by population. Carcass value could be improved by effectively removing this undesirable trait from pig populations. © 2010 Lindholm-Perry et al; licensee BioMed Central Ltd.


Chen C.Y.,University of Georgia | Misztal I.,University of Georgia | Tsuruta S.,University of Georgia | Zumbach B.,University of Georgia | And 3 more authors.
Journal of Animal Breeding and Genetics | Year: 2010

Genetic parameters for daily feed intake (DFI, g/day) and daily gain (DG, g/day) were estimated using records of 1916 Duroc boars from electronic feeder stations. Management was limited and resulted in varied ranges of age and weight on test. Boars were housed in 102 pens, each equipped with one feeder, and allowed ad libitum feeding. Weekly averages of DFI and DG were used due to large variation in daily records. Six traits were defined as DFI and DG during 85-106 (period 1), 107-128 (period 2) and 129-150 days of age (period 3). A six-trait model included age as a linear and a quadratic covariate for DFI and a linear covariate for DG with a fixed effect of year-week-pen and random effects of litter, additive genetic animal and permanent environmental animal. Variance components were estimated by a Bayesian approach using Gibbs sampling algorithm. Estimates of heritability for respective periods were 18%, 12% and 10% for DFI and 21%, 11% and 10% for DG. Genetic correlations between DFI and DG in the same period were 0.70, 0.73 and 0.32 for the respective periods. DFI and DG obtained from automatic feeders can be analysed to reveal variation across testing periods by using weekly averages when many monthly averages are incomplete. © 2009 Blackwell Verlag GmbH.


Chen C.Y.,University of Georgia | Misztal I.,University of Georgia | Tsuruta S.,University of Georgia | Herring W.O.,Smithfield Premium Genetics Group | And 2 more authors.
Journal of Animal Breeding and Genetics | Year: 2010

Social genetic relationships among average daily gain (ADG, g) and feeding pattern as daily feed intake (DFI, g), daily feeder occupation time (DOT, min), and daily feeding rate (DFR, g/min) were examined using records of 547 Duroc boars. Single-trait animal models were fitted differently for traits, including or excluding social genetic effects, random or fixed pen effects, with covariates of pen sizes and initial age or weight. Genetic parameters for feeding pattern were estimated by restricted maximum likelihood. Six sets of parameters for ADG based on literature estimates were used due to difficulty in untangling confounded effects. Positive and negative signs of direct-social genetic covariances were interpreted as heritable cooperation and competition, respectively. Dominant and subordinate pigs were classified as pigs with higher direct and social genetic values, respectively. Correlations of estimated breeding values between ADG and DFI, DOT, and DFR were 0.46, 0.04 and 0.29 for dominant pigs. Given heritable cooperation, subordinate pigs tended to increase feed intake (r=0.36) and eating rate (r =0.25). Given heritable competition, subordinate pigs fail to compensate for the competition with decreased feed intake (r = -0.53). The slow eating rate (r = -0.31) was considered as a consequence of eating during less busy hour of feeding. © 2009 Blackwell Verlag GmbH.


Zumbach B.,University of Georgia | Misztal I.,University of Georgia | Chen C.Y.,University of Georgia | Tsuruta S.,University of Georgia | And 4 more authors.
Journal of Animal Breeding and Genetics | Year: 2010

This study examined the utility of serial weights from FIRE (Feed Intake Recording Equipment, Osborne Industries, Inc., Osborne, KS, USA) stations for an analysis of daily gain. Data included 884 132 body weight records from 3888 purebred Duroc pigs. Pigs entered the feeder station at age 77-149 days and left at age 95-184 days. A substantial number of records were abnormal, showing body weight close to 0 or up to twice the average weight. Plots of body weights for some animals indicated two parallel growth curves. Initial editing used a robust regression, which was a two-step procedure. In the first step, a quadratic growth curve was estimated assuming small or 0 weights for points far away from the curve; the process is iterative. In the second step, weights more than 1.5 SD from the estimated growth curve were treated as outliers. The retained body weight records (607 597) were averaged to create average daily weight (170 443) and then used to calculate daily gains (152 636). Additional editing steps included retaining only animals with ≥50 body weight records and SD of the daily gain ≤2 kg, followed by removing records outside 3 SD from the mean for given age, across all the animals - the resulting data set included 69 068 records of daily gain from 1921 animals. Daily gain based on daily, weekly and bi-weekly intervals was analysed using repeatability models. Heritability estimates were 0.04, 6 and 9%, respectively. The last two estimates correspond to heritability of 28% for a 12 week interval. For daily gain averaged weekly, the estimate of heritability obtained with a random regression model varied from 0.07 to 0.10. After extensive editing, body weight records from automatic feeding stations are useful for genetic analyses of daily gain from weekly or bi-weekly but not daily intervals. © 2009 Blackwell Verlag GmbH.


Badke Y.M.,Michigan State University | Bates R.O.,Michigan State University | Ernst C.W.,Michigan State University | Fix J.,Smithfield Premium Genetics Group | Steibel J.P.,Michigan State University
G3: Genes, Genomes, Genetics | Year: 2014

Genomic selection has the potential to increase genetic progress. Genotype imputation of high-density single-nucleotide polymorphism (SNP) genotypes can improve the cost efficiency of genomic breeding value (GEBV) prediction for pig breeding. Consequently, the objectives of this work were to: (1) estimate accuracy of genomic evaluation and GEBV for three traits in a Yorkshire population and (2) quantify the loss of accuracy of genomic evaluation and GEBV when genotypes were imputed under two scenarios: a high-cost, high-accuracy scenario in which only selection candidates were imputed from a low-density platform and a low-cost, low-accuracy scenario in which all animals were imputed using a small reference panel of haplotypes. Phenotypes and genotypes obtained with the PorcineSNP60 BeadChip were available for 983 Yorkshire boars. Genotypes of selection candidates were masked and imputed using tagSNP in the GeneSeek Genomic Profiler (10K). Imputation was performed with BEAGLE using 128 or 1800 haplotypes as reference panels. GEBV were obtained through an animal-centric ridge regression model using deregressed breeding values as response variables. Accuracy of genomic evaluation was estimated as the correlation between estimated breeding values and GEBV in a 10-fold cross validation design. Accuracy of genomic evaluation using observed genotypes was high for all traits (0.6520.68). Using genotypes imputed from a large reference panel (accuracy: R2 = 0.95) for genomic evaluation did not significantly decrease accuracy, whereas a scenario with genotypes imputed from a small reference panel (R2 = 0.88) did show a significant decrease in accuracy. Genomic evaluation based on imputed genotypes in selection candidates can be implemented at a fraction of the cost of a genomic evaluation using observed genotypes and still yield virtually the same accuracy. On the other side, using a very small reference panel of haplotypes to impute training animals and candidates for selection results in lower accuracy of genomic evaluation. ©2014 Badke et al.


Engblom L.,Iowa State University | Calderon Diaz J.A.,Iowa State University | Nikkila M.,Iowa State University | Gray K.,Smithfield Premium Genetics Group | And 5 more authors.
Journal of Animal Breeding and Genetics | Year: 2016

Sow longevity is a key component for efficient and profitable pig farming; however, approximately 50% of sows are removed annually from a breeding herd. There is no consensus in the scientific literature regarding a definition for sow longevity; however, it has been suggested that it can be measured using several methods such as stayability and economic indicators such as lifetime piglets produced. Sow longevity can be improved by genetic selection; however, it is rarely included in genetic evaluations. One reason is elongated time intervals required to collect complete lifetime data. The effect of genetic parameter estimation software in handling incomplete data (censoring) and possible early indicator traits were evaluated analysing a 30% censored data set (12 725 pedigreed Landrace × Large White sows that included approximately 30% censored data) with DMU6, THRGIBBS1F90 and GIBBS2CEN. Heritability estimates were low for all the traits evaluated. The results show that the binary stayability traits benefited from being analysed with a threshold model compared to analysing with a linear model. Sires were ranked very similarly regardless if the program handled censoring when all available data were included. Accumulated born alive and stayability were good indicators for lifetime born alive traits. Number of piglets born alive within each parity could be used as an early indicator trait for sow longevity. © 2016 Blackwell Verlag GmbH.


Chen C.Y.,University of Georgia | Misztal I.,University of Georgia | Tsuruta S.,University of Georgia | Herring W.O.,Smithfield Premium Genetics Group | And 2 more authors.
Journal of Animal Science | Year: 2010

Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-yearseason) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth. © 2010 American Society of Animal Science. All rights reserved.


PubMed | Smithfield Premium Genetics Group, Iowa State University and University of Georgia
Type: Journal Article | Journal: Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie | Year: 2016

Sow longevity is a key component for efficient and profitable pig farming; however, approximately 50% of sows are removed annually from a breeding herd. There is no consensus in the scientific literature regarding a definition for sow longevity; however, it has been suggested that it can be measured using several methods such as stayability and economic indicators such as lifetime piglets produced. Sow longevity can be improved by genetic selection; however, it is rarely included in genetic evaluations. One reason is elongated time intervals required to collect complete lifetime data. The effect of genetic parameter estimation software in handling incomplete data (censoring) and possible early indicator traits were evaluated analysing a 30% censored data set (12725 pedigreed LandraceLarge White sows that included approximately 30% censored data) with DMU6, THRGIBBS1F90 and GIBBS2CEN. Heritability estimates were low for all the traits evaluated. The results show that the binary stayability traits benefited from being analysed with a threshold model compared to analysing with a linear model. Sires were ranked very similarly regardless if the program handled censoring when all available data were included. Accumulated born alive and stayability were good indicators for lifetime born alive traits. Number of piglets born alive within each parity could be used as an early indicator trait for sow longevity.

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