@article{usala_macciotta_bergamaschi_maltecca_fix_schwab_shull_tiezzi_2021, title={Genetic Parameters for Tolerance to Heat Stress in Crossbred Swine Carcass Traits}, volume={11}, ISSN={["1664-8021"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85101217596&partnerID=MN8TOARS}, DOI={10.3389/fgene.2020.612815}, abstractNote={Data for loin and backfat depth, as well as carcass growth of 126,051 three-way crossbred pigs raised between 2015 and 2019, were combined with climate records of air temperature, relative humidity, and temperature–humidity index. Environmental covariates with the largest impact on the studied traits were incorporated in a random regression model that also included genomic information. Genetic control of tolerance to heat stress and the presence of genotype by environment interaction were detected. Its magnitude was more substantial for loin depth and carcass growth, but all the traits studied showed a different impact of heat stress and different magnitude of genotype by environment interaction. For backfat depth, heritability was larger under comfortable conditions (no heat stress), as compared to heat stress conditions. Genetic correlations between extreme values of environmental conditions were lower (∼0.5 to negative) for growth and loin depth. Based on the solutions obtained from the model, sires were ranked on their breeding value for general performance and tolerance to heat stress. Antagonism between overall performance and tolerance to heat stress was moderate. Still, the models tested can provide valuable information to identify genetic material that is resilient and can perform equally when environmental conditions change. Overall, the results obtained from this study suggest the existence of genotype by environment interaction for carcass traits, as a possible genetic contributor to heat tolerance in swine.}, journal={FRONTIERS IN GENETICS}, author={Usala, Maria and Macciotta, Nicolo Pietro Paolo and Bergamaschi, Matteo and Maltecca, Christian and Fix, Justin and Schwab, Clint and Shull, Caleb and Tiezzi, Francesco}, year={2021}, month={Feb} }
 @article{maltecca_dunn_he_mcnulty_schillebeeckx_schwab_shull_fix_tiezzi_2021, title={Microbial composition differs between production systems and is associated with growth performance and carcass quality in pigs}, volume={3}, ISSN={["2524-4671"]}, url={https://doi.org/10.1186/s42523-021-00118-z}, DOI={10.1186/s42523-021-00118-z}, abstractNote={Abstract
                Background
                The role of the microbiome in livestock production has been highlighted in recent research. Currently, little is known about the microbiome's impact across different systems of production in swine, particularly between selection nucleus and commercial populations. In this paper, we investigated fecal microbial composition in nucleus versus commercial systems at different time points.
              
                Results
                We identified microbial OTUs associated with growth and carcass composition in each of the two populations, as well as the subset common to both. The two systems were represented by individuals with sizeable microbial diversity at weaning. At later times microbial composition varied between commercial and nucleus, with species of the genus Lactobacillus more prominent in the nucleus population. In the commercial populations, OTUs of the genera Lactobacillus and Peptococcus were associated with an increase in both growth rate and fatness. In the nucleus population, members of the genus Succinivibrio were negatively correlated with all growth and carcass traits, while OTUs of the genus Roseburia had a positive association with growth parameters. Lactobacillus and Peptococcus OTUs showed consistent effects for fat deposition and daily gain in both nucleus and commercial populations. Similarly, OTUs of the Blautia genus were positively associated with daily gain and fat deposition. In contrast, an increase in the abundance of the Bacteroides genus was negatively associated with growth performance parameters.
              
                Conclusions
                The current study provides a first characterization of microbial communities' value throughout the pork production systems. It also provides information for incorporating microbial composition into the selection process in the quest for affordable and sustainable protein production in swine.
              }, number={1}, journal={ANIMAL MICROBIOME}, publisher={Springer Science and Business Media LLC}, author={Maltecca, Christian and Dunn, Rob and He, Yuqing and McNulty, Nathan P. and Schillebeeckx, Constantino and Schwab, Clint and Shull, Caleb and Fix, Justin and Tiezzi, Francesco}, year={2021}, month={Aug} }
 @article{tiezzi_fix_schwab_shull_maltecca_2021, title={Gut microbiome mediates host genomic effects on phenotypes: a case study with fat deposition in pigs}, volume={19}, ISSN={["2001-0370"]}, url={https://doi.org/10.1016/j.csbj.2020.12.038}, DOI={10.1016/j.csbj.2020.12.038}, abstractNote={A large number of studies have highlighted the importance of gut microbiome composition in shaping fat deposition in mammals. Several studies have also highlighted how host genome controls the abundance of certain species that make up the gut microbiota. We propose a systematic approach to infer how the host genome can control the gut microbiome, which in turn contributes to the host phenotype determination. We implemented a mediation test that can be applied to measured and latent dependent variables to describe fat deposition in swine (Sus scrofa). In this study, we identify several host genomic features having a microbiome-mediated effects on fat deposition. This demonstrates how the host genome can affect the phenotypic trait by inducing a change in gut microbiome composition that leads to a change in the phenotype. Host genomic variants identified through our analysis are different than the ones detected in a traditional genome-wide association study. In addition, the use of latent dependent variables allows for the discovery of additional host genomic features that do not show a significant effect on the measured variables. Microbiome-mediated host genomic effects can help understand the genetic determination of fat deposition. Since their contribution to the overall genetic variance is usually not included in association studies, they can contribute to filling the missing heritability gap and provide further insights into the host genome – gut microbiome interplay. Further studies should focus on the portability of these effects to other populations as well as their preservation when pro-/pre-/anti-biotics are used (i.e. remediation).}, journal={COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL}, author={Tiezzi, Francesco and Fix, Justin and Schwab, Clint and Shull, Caleb and Maltecca, Christian}, year={2021}, pages={530–544} }
 @article{bergamaschi_maltecca_schillebeeckx_mcnulty_schwab_shull_fix_tiezzi_2020, title={Heritability and genome-wide association of swine gut microbiome features with growth and fatness parameters}, volume={10}, ISSN={["2045-2322"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85086790625&partnerID=MN8TOARS}, DOI={10.1038/s41598-020-66791-3}, abstractNote={AbstractDespite recent efforts to characterize longitudinal variation in the swine gut microbiome, the extent to which a host’s genome impacts the composition of its gut microbiome is not yet well understood in pigs. The objectives of this study were: i) to identify pig gut microbiome features associated with growth and fatness, ii) to estimate the heritability of those features, and, iii) to conduct a genome-wide association study exploring the relationship between those features and single nucleotide polymorphisms (SNP) in the pig genome. A total of 1,028 pigs were characterized. Animals were genotyped with the Illumina PorcineSNP60 Beadchip. Microbiome samples from fecal swabs were obtained at weaning (Wean), at mid-test during the growth trial (MidTest), and at the end of the growth trial (OffTest). Average daily gain was calculated from birth to week 14 of the growth trial, from weaning to week 14, from week 14 to week 22, and from week 14 to harvest. Backfat and loin depth were also measured at weeks 14 and 22. Heritability estimates (±SE) of Operational Taxonomic Units ranged from 0.025 (±0.0002) to 0.139 (±0.003), from 0.029 (±0.003) to 0.289 (±0.004), and from 0.025 (±0.003) to 0.545 (±0.034) at Wean, MidTest, and OffTest, respectively. Several SNP were significantly associated with taxa at the three time points. These SNP were located in genomic regions containing a total of 68 genes. This study provides new evidence linking gut microbiome composition with growth and carcass traits in swine, while also identifying putative host genetic markers associated with significant differences in the abundance of several prevalent microbiome features.}, number={1}, journal={SCIENTIFIC REPORTS}, author={Bergamaschi, Matteo and Maltecca, Christian and Schillebeeckx, Constantino and McNulty, Nathan P. and Schwab, Clint and Shull, Caleb and Fix, Justin and Tiezzi, Francesco}, year={2020}, month={Jun} }
 @article{khanal_maltecca_schwab_fix_bergamaschi_tiezzi_2020, title={Modeling host-microbiome interactions for the prediction of meat quality and carcass composition traits in swine}, volume={52}, ISBN={1297-9686}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85088852317&partnerID=MN8TOARS}, DOI={10.1186/s12711-020-00561-7}, abstractNote={Abstract
Background
The objectives of this study were to evaluate genomic and microbial predictions of phenotypes for meat quality and carcass traits in swine, and to evaluate the contribution of host-microbiome interactions to the prediction. Data were collected from Duroc-sired three-way crossbred individuals (n = 1123) that were genotyped with a 60 k SNP chip. Phenotypic information and fecal 16S rRNA microbial sequences at three stages of growth (Wean, Mid-test, and Off-test) were available for all these individuals. We used fourfold cross-validation with animals grouped based on sire relatedness. Five models with three sets of predictors (full, informatively reduced, and randomly reduced) were evaluated. ‘Full’ included information from all genetic markers and all operational taxonomic units (OTU), while ‘informatively reduced’ and ‘randomly reduced’ represented a reduced number of markers and OTU based on significance preselection and random sampling, respectively. The baseline model included the fixed effects of dam line, sex and contemporary group and the random effect of pen. The other four models were constructed by including only genomic information, only microbiome information, both genomic and microbiome information, and microbiome and genomic information and their interaction.

Results
Inclusion of microbiome information increased predictive ability of phenotype for most traits, in particular when microbiome information collected at a later growth stage was used. Inclusion of microbiome information resulted in higher accuracies and lower mean squared errors for fat-related traits (fat depth, belly weight, intramuscular fat and subjective marbling), objective color measures (Minolta a*, Minolta b* and Minolta L*) and carcass daily gain. Informative selection of markers increased predictive ability but decreasing the number of informatively reduced OTU did not improve model performance. The proportion of variation explained by the host-genome-by-microbiome interaction was highest for fat depth (~ 20% at Mid-test and Off-test) and shearing force (~ 20% consistently at Wean, Mid-test and Off-test), although the inclusion of the interaction term did not increase the accuracy of predictions significantly.

Conclusions
This study provides novel insight on the use of microbiome information for the phenotypic prediction of meat quality and carcass traits in swine. Inclusion of microbiome information in the model improved predictive ability of phenotypes for fat deposition and color traits whereas including a genome-by-microbiome term did not improve prediction accuracy significantly.
}, number={1}, journal={GENETICS SELECTION EVOLUTION}, author={Khanal, Piush and Maltecca, Christian and Schwab, Clint and Fix, Justin and Bergamaschi, Matteo and Tiezzi, Francesco}, year={2020} }
 @article{bergamaschi_maltecca_fix_schwab_tiezzi_2020, title={Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs}, volume={98}, ISSN={["1525-3163"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85078371039&partnerID=MN8TOARS}, DOI={10.1093/jas/skz360}, abstractNote={AbstractCarcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3,532 were genotyped using the Illumina PorcineSNP60K Beadchip. After quality control, 36,328 SNPs were available and were used to perform an ssGWAS. A bootstrap analysis (n = 1,000) and a signal enrichment analysis were performed to declare SNP significance. Genome regions were based on the variance explained by significant 10-SNP sliding windows. Estimates of PB heritability (SE) were 0.42 (0.019) for BF, 0.39 (0.020) for LD, and 0.35 (0.021) for ADG. Estimates of CB heritability were 0.49 (0.042) for BF, 0.27 (0.029) for LD, and 0.12 (0.021) for ADG. Genetic correlations (SE) across the two populations were 0.81 (0.02), 0.79 (0.04), and 0.56 (0.05), for BF, LD, and ADG, respectively. The variance explained by significant regions for each trait in PBs ranged from 1.51% to 1.35% for BF, from 4.02% to 3.18% for LD, and from 2.26% to 1.45% for ADG. In CBs, the variance explained by significant regions ranged from 1.88% to 1.37% for BF, from 1.29% to 1.23% for LD, and from 1.54% to 1.32% for ADG. In this study, we have described regions of the genome that determine carcass quality and growth traits of PB and CB pigs. These results provide evidence that there are overlapping and nonoverlapping regions in the genome influencing carcass quality and growth traits in PBs and three-way CB pigs.}, number={1}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Bergamaschi, Matteo and Maltecca, Christian and Fix, Justin and Schwab, Clint and Tiezzi, Francesco}, year={2020}, month={Jan} }
 @article{fix_cassady_holl_herring_culbertson_see_2010, title={Effect of piglet birth weight on survival and quality of commercial market swine}, volume={132}, ISSN={["1878-0490"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77954658643&partnerID=MN8TOARS}, DOI={10.1016/j.livsci.2010.05.007}, abstractNote={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.}, number={1-3}, journal={LIVESTOCK SCIENCE}, author={Fix, J. S. and Cassady, J. P. and Holl, J. W. and Herring, W. O. and Culbertson, M. S. and See, M. T.}, year={2010}, month={Aug}, pages={98–106} }
 @article{fix_cassady_heugten_hanson_see_2010, title={Differences in lean growth performance of pigs sampled from 1980 and 2005 commercial swine fed 1980 and 2005 representative feeding programs}, volume={128}, ISSN={["1878-0490"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-76349085628&partnerID=MN8TOARS}, DOI={10.1016/j.livsci.2009.11.006}, abstractNote={The objective of this study was to assess how changes in genetics and feeding programs over 25 years in the U.S. commercial swine industry have impacted lean growth performance. Genetic samples (GS) of pigs (n = 162) from the commercial industries in 1980 and 2005 were randomly assigned to 1 of 2 feeding programs (FP) representative of 1980 or 2005. Pigs were placed 3 per pen (n = 54) at approximately 4 weeks of age and were harvested when average BW of the pen exceeded 116 kg. Real-time ultrasound measures for backfat depth and longissimus muscle area at the 10th rib were collected every 4 weeks, beginning at week 8 (group 1) or week 10 (group 2) until harvest. Average daily gain, ADFI, and G:F were calculated for the nursery period (7.0 ± 0.4 to 26.9 ± 0.7 kg BW), finishing period (26.9 ± 0.7 to 119 ± 0.7 kg BW), and overall (7.0 ± 0.4 to 116 ± 0.7 kg BW). Lean ADG and lean G:F were calculated for the period of first real-time ultrasound to harvest (42.7 ± 1.0 kg to 116 kg BW). Pigs from 2005 vs. 1980 GS and pigs fed 2005 vs. 1980 FP reached final BW of 116 kg sooner; 11 and 12 d, respectively. For ADG during finishing and overall, GS × FP interactions were observed, where 1980 GS pigs fed 1980 vs. 2005 FP showed increases of 7.0 and 6.3%, respectively; however, 2005 GS pigs fed 1980 vs. 2005 FP had increases of 12.6 and 12.3%, respectively. Pigs from the 2005 GS had greater ADG during finishing and overall, increased lean ADG, with no difference in ADFI during finishing, overall, and lean gain period or reduced ADFI during nursery which led to greater G:F and lean G:F. Pigs fed 2005 FP had increased ADG during all periods, with reduced ADFI during finishing, overall, and the lean gain test period which led to greater lean G:F and G:F during all portions of the trial. Although via different methods, changes over the past 25 years in the U.S. swine industry with respect to both genetics and feeding programs have resulted in a 15% reduction in days to harvest and a 45% improvement in lean efficiency.}, number={1-3}, journal={LIVESTOCK SCIENCE}, author={Fix, J. S. and Cassady, J. P. and Heugten, E. and Hanson, D. J. and See, M. T.}, year={2010}, month={Mar}, pages={108–114} }
 @article{fix_cassady_herring_holl_culbertson_see_2010, title={Effect of piglet birth weight on body weight, growth, backfat, and longissimus muscle area of commercial market swine}, volume={127}, ISSN={["1878-0490"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-70449519415&partnerID=MN8TOARS}, DOI={10.1016/j.livsci.2009.08.007}, abstractNote={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.}, number={1}, journal={LIVESTOCK SCIENCE}, author={Fix, J. S. and Cassady, J. P. and Herring, W. O. and Holl, J. W. and Culbertson, M. S. and See, M. T.}, year={2010}, month={Jan}, pages={51–59} }