@article{obermier_howard_gray_knauer_2023, title={The impact of functional teat number on reproductive throughput in swine}, volume={7}, ISSN={["2573-2102"]}, DOI={10.1093/tas/txad100}, abstractNote={Abstract The objective was to evaluate the impact of functional teat number on reproductive throughput in swine. Data included 735 multiparous Landrace × Large White F1 females. Sow underlined traits consisted of total teat number (TT), functional teat number (FT), nonfunctional teat number (NFT), and number of functional mammary glands (FMG). Weaning traits were calculated for both the biological and the nurse dam. For the biological dam, litter size at weaning (LSW) included a sow’s biological piglets regardless of cross-fostering. For nurse dam, number weaned (NW) included the piglets a sow weaned. For the biological dam, piglet survival (PS) was calculated as litter size at weaning / (total number born × 100). Linear regression estimates were calculated in RStudio v. 1.1.456 and variance components were estimated using GIBBS3F90. Average total number born, number born alive, TT, FT, NFT, and FMG were 14.22, 13.12, 14.43, 13.96, 0.42, and 10.7, respectively. An increase in one FT enhanced (P < 0.05) LSW by 0.32 piglets and NW by 0.33 piglets. Similarly, an increase in one FT improved (P < 0.05) PS by 1.63% and reduced (P < 0.05) preweaning mortality by 2.73%. However, an increase in one FT reduced (P < 0.05) average piglet weaning weight (WW) for biological and nurse dams by 35 and 94 g, respectively. Yet an increase in one FT enhanced (P < 0.05) litter weaning weight (LWW) for biological and nurse dams by 1.3 and 1.5 kg, respectively. Heritability estimates for TT, FT, NFT, FMG, WW, LWW, LSW, and PS were 0.25, 0.22, 0.53, 0.18, 0.21, 0.22, 0.16, and 0.18, respectively. Genetic correlation estimates between FT with TT, NFT, and FMG were 0.79, 0.09, and 0.28, respectively. Estimated genetic correlations between TT with WW, LWW, LSW, and PS were 0.37, 0.38, 0.11, and −0.19, respectively. Genetic correlation estimates between FT with WW, LWW, LSW, and PS were 0.44, 0.49, 0.39, and 0.35, respectively. Results suggest increasing functional teat number would enhance both piglet survival and reproductive throughput.}, number={1}, journal={TRANSLATIONAL ANIMAL SCIENCE}, author={Obermier, Dalton R. and Howard, Jeremy Thomas and Gray, Kent A. and Knauer, Mark T.}, year={2023}, month={Jan} } @article{he_tiezzi_howard_huang_gray_maltecca_2022, title={Exploring the role of gut microbiota in host feeding behavior among breeds in swine}, volume={22}, ISSN={["1471-2180"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85122218151&partnerID=MN8TOARS}, DOI={10.1186/s12866-021-02409-6}, abstractNote={Abstract Background The interplay between the gut microbiota and feeding behavior has consequences for host metabolism and health. The present study aimed to explore gut microbiota overall influence on feeding behavior traits and to identify specific microbes associated with the traits in three commercial swine breeds at three growth stages. Feeding behavior measures were obtained from 651 pigs of three breeds (Duroc, Landrace, and Large White) from an average 73 to 163 days of age. Seven feeding behavior traits covered the information of feed intake, feeder occupation time, feeding rate, and the number of visits to the feeder. Rectal swabs were collected from each pig at 73 ± 3, 123 ± 4, and 158 ± 4 days of age. DNA was extracted and subjected to 16 S rRNA gene sequencing. Results Differences in feeding behavior traits among breeds during each period were found. The proportion of phenotypic variances of feeding behavior explained by the gut microbial composition was small to moderate (ranged from 0.09 to 0.31). A total of 21, 10, and 35 amplicon sequence variants were found to be significantly (q-value < 0.05) associated with feeding behavior traits for Duroc, Landrace, and Large White across the three sampling time points. The identified amplicon sequence variants were annotated to five phyla, with Firmicutes being the most abundant. Those amplicon sequence variants were assigned to 28 genera, mainly including Christensenellaceae_R-7_group, Ruminococcaceae_UCG-004, Dorea, Ruminococcaceae_UCG-014, and Marvinbryantia. Conclusions This study demonstrated the importance of the gut microbial composition in interacting with the host feeding behavior and identified multiple archaea and bacteria associated with feeding behavior measures in pigs from either Duroc, Landrace, or Large White breeds at three growth stages. Our study provides insight into the interaction between gut microbiota and feeding behavior and highlights the genetic background and age effects in swine microbial studies. }, number={1}, journal={BMC MICROBIOLOGY}, author={He, Yuqing and Tiezzi, Francesco and Howard, Jeremy and Huang, Yijian and Gray, Kent and Maltecca, Christian}, year={2022}, month={Jan} } @article{he_tiezzi_howard_maltecca_2021, title={Predicting body weight in growing pigs from feeding behavior data using machine learning algorithms}, volume={184}, ISSN={["1872-7107"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85104932146&partnerID=MN8TOARS}, DOI={10.1016/j.compag.2021.106085}, abstractNote={A timely and accurate estimation of body weight in finishing pigs is critical in determining profits by allowing pork producers to make informed marketing decisions on group-housed pigs while reducing labor and feed costs. This study investigated the usefulness of feeding behavior data in predicting the body weight of pigs at the finishing stage. We obtained data on 655 pigs of three breeds (Duroc, Landrace, and Large White) from 75 to 166 days of age. Feeding behavior, feed intake, and body weight information were recorded when a pig visited the Feed Intake Recording Equipment in each pen. Data collected from 75 to 158 days of age were split into six slices of 14 days each and used to calibrate predictive models. LASSO regression and two machine learning algorithms (Random Forest and Long Short-term Memory network) were selected to forecast the body weight of pigs aged from 159 to 166 days using four scenarios: individual-informed predictive scenario, individual- and group-informed predictive scenario, breed-specific individual- and group-informed predictive scenario, and group-informed predictive scenario. We developed four models for each scenario: Model_Age included only age, Model_FB included only feeding behavior variables, Model_Age_FB and Model_Age_FB_FI added feeding behavior and feed intake measures on the basis of Model_Age as predictors. Pearson's correlation, root mean squared error, and binary diagnostic tests were used to assess predictive performance. The greatest correlation was 0.87, and the highest accuracy was 0.89 for the individual-informed prediction, while they were 0.84 and 0.85 for the individual- and group-informed predictions, respectively. The least root mean squared error of both scenarios was about 10 kg. The best prediction performed by Model_FB had a correlation of 0.83, an accuracy of 0.74, and a root mean squared error of 14.3 kg in the individual-informed prediction. The effect of the addition of feeding behavior and feed intake data varied across algorithms and scenarios from a small to moderate improvement in predictive performance. We also found differences in predictive performance associated with the time slices or pigs used in the training set, the algorithm employed, and the breed group considered. Overall, this study's findings connect the dynamics of feeding behavior to body growth and provide a promising picture of the involvement of feeding behavior data in predicting the body weight of group-housed pigs.}, journal={COMPUTERS AND ELECTRONICS IN AGRICULTURE}, author={He, Yuqing and Tiezzi, Francesco and Howard, Jeremy and Maltecca, Christian}, year={2021}, month={May} } @article{tiezzi_bergamaschi_howard_maltecca_2020, title={43 Feed efficiency and behavior are associated with gut microbiome in three breeds of pigs}, volume={98}, ISSN={0021-8812 1525-3163}, url={http://dx.doi.org/10.1093/jas/skaa278.044}, DOI={10.1093/jas/skaa278.044}, abstractNote={Abstract Feed efficiency and behavior are important traits in the pork industry for economic, welfare, and environmental aspects. The gut microbiota plays an important role in nutrient digestibility and it is likely to influence these traits. The aim of this study was to characterize the feed efficiency, feeding behavior and gut microbiome relationships of pigs belonging to three different breeds. Individual body weight, feed intake and rate of Duroc (n = 222), Landrace (n = 244), and Large White (n = 221) pigs were recorded. Rectal fecal samples were collected from each animal at three time points (T1, start of trial; T2, mid-trial; T3, end of trial) and used for microbiome 16S rRNA gene sequencing. Individual feed intake and body weight were edited to obtain average daily gain (ADG), average daily feed intake (ADFI), feed conversion ratio (FCR), average daily feeding rate (ADFR), average feed intake per visit (AFIV), average daily number of visits to feeder (ANVD), average daily occupation time (AOTD), average occupation time per visit (AOTV). The impact of gut microbiome on the traits studied was present and seemed to depend on the breed and the time point of recording. At T1, Oscillibacter and Phascolarctobacterium had negative impact on ANVD and ADFI in Duroc, Ruminococcus had negative impact on ADFI in Landrace and Parvimonas, Escherichia and Anaerovibrio had negative impact on ADFI and ANVD in Large White. At T2, Lactobacillus showed a positive impact on ADFR in Landrace and on ADFI in Large White. At T3, Ruminococcus, Faecalibacterium and Dorea had a positive impact on ADFI in Duroc, Staphylococcous had positive impact on ADFR in Landrace and Peptoniphilus had negative impact on ADFI in Large White. Gut microbiome may have an heterogenous impact on the regulation of feeding behavior and feed efficiency depending on the host genotype.}, number={Supplement_4}, journal={Journal of Animal Science}, publisher={Oxford University Press (OUP)}, author={Tiezzi, Francesco and Bergamaschi, Matteo and Howard, Jeremy and Maltecca, Christian}, year={2020}, month={Nov}, pages={24–24} } @article{tiezzi_brito_howard_huang_gray_schwab_fix_maltecca_2020, title={Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs}, volume={11}, ISSN={["1664-8021"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85087889959&partnerID=MN8TOARS}, DOI={10.3389/fgene.2020.00629}, abstractNote={Improving swine climatic resilience through genomic selection has the potential to minimize welfare issues and increase the industry profitability. The main objective of this study was to investigate the genetic and genomic determinism of tolerance to heat stress in four independent purebred populations of swine. Three female reproductive traits were investigated: total number of piglets born (TNB), number of piglets born alive (NBA) and average birth weight (ABW). More than 80,000 phenotypic and 12,000 genotyped individuals were included in this study. Genomic random-regression models were fitted regressing the phenotypes of interest on a set of 95 environmental covariates extracted from public weather station records. The models yielded estimates of (genomic) reactions norms for individual pigs, as indicator of heat tolerance. Heat tolerance is a heritable trait, although the heritabilities are larger under comfortable than heat-stress conditions (larger than 0.05 vs. 0.02 for TNB; 0.10 vs. 0.05 for NBA; larger than 0.20 vs. 0.10 for ABW). TNB showed the lowest genetic correlation (-38%) between divergent climatic conditions, being the trait with the strongest impact of genotype by environment interaction, while NBA and ABW showed values slightly negative or equal to zero reporting a milder impact of the genotype by environment interaction. After estimating genetic parameters, a genome-wide association study was performed based on the single-step GBLUP method. Heat tolerance was observed to be a highly polygenic trait. Multiple and non-overlapping genomic regions were identified for each trait based on the genomic breeding values for reproductive performance under comfortable or heat stress conditions. Relevant regions were found on chromosomes (SSC) 1, 3, 5, 6, 9, 11, and 12, although there were important regions across all autosomal chromosomes. The genomic region located on SSC9 appears to be of particular interest since it was identified for two traits (TNB and NBA) and in two independent populations. Heat tolerance based on reproductive performance indicators is a heritable trait and genetic progress for heat tolerance can be achieved through genetic or genomic selection. Various genomic regions and candidate genes with important biological functions were identified, which will be of great value for future functional genomic studies.}, journal={FRONTIERS IN GENETICS}, author={Tiezzi, Francesco and Brito, Luiz F. and Howard, Jeremy and Huang, Yi Jian and Gray, Kent and Schwab, Clint and Fix, Justin and Maltecca, Christian}, year={2020}, month={Jun} } @article{baes_makanjuola_miglior_marras_howard_fleming_maltecca_2019, title={Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance}, volume={102}, ISSN={["1525-3198"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85059948091&partnerID=MN8TOARS}, DOI={10.3168/jds.2018-15520}, abstractNote={Inbreeding depression is a growing concern in livestock because it can detrimentally affect animal fitness, health, and production levels. Genomic information can be used to more effectively capture variance in Mendelian sampling, thereby enabling more accurate estimation of inbreeding, but further progress is still required. The calculation of inbreeding for herd management purposes is largely still done using pedigree information only, although inbreeding coefficients calculated in this manner have been shown to be less accurate than genomic inbreeding measures. Continuous stretches of homozygous genotypes, so called runs of homozygosity, have been shown to provide a better estimate of autozygosity at the genomic level than conventional measures based on inbreeding coefficients calculated through conventional pedigree information or even genomic relationship matrices. For improved and targeted management of genomic inbreeding at the population level, the development of methods that incorporate genomic information in mate selection programs may provide a more precise tool for reducing the detrimental effects of inbreeding in dairy herds. Additionally, a better understanding of the genomic architecture of inbreeding and incorporating that knowledge into breeding programs could significantly refine current practices. Opportunities to maintain high levels of genetic progress in traits of interest while managing homozygosity and sustaining acceptable levels of heterozygosity in highly selected dairy populations exist and should be examined more closely for continued sustainability of both the dairy cattle population as well as the dairy industry. The inclusion of precise genomic measures of inbreeding, such as runs of homozygosity, inbreeding, and mating programs, may provide a path forward. In this symposium review article, we describe traditional measures of inbreeding and the recent developments made toward more precise measures of homozygosity using genomic information. The effects of homozygosity resulting from inbreeding on phenotypes, the identification and mapping of detrimental homozygosity haplotypes, management of inbreeding with genomic data, and areas in need of further research are discussed.}, number={3}, journal={JOURNAL OF DAIRY SCIENCE}, author={Baes, Christine F. and Makanjuola, Bayode O. and Miglior, Filippo and Marras, Gabriele and Howard, Jeremy T. and Fleming, Allison and Maltecca, Christian}, year={2019}, month={Mar}, pages={2807–2817} } @article{howard_ashwell_baynes_brooks_yeatts_maltecca_2017, title={Gene co-expression network analysis identifies porcine genes associated with variation in metabolizing fenbendazole and flunixin meglumine in the liver}, volume={7}, ISSN={2045-2322}, url={http://dx.doi.org/10.1038/s41598-017-01526-5}, DOI={10.1038/s41598-017-01526-5}, abstractNote={AbstractIdentifying individual genetic variation in drug metabolism pathways is of importance not only in livestock, but also in humans in order to provide the ultimate goal of giving the right drug at the right dose at the right time. Our objective was to identify individual genes and gene networks involved in metabolizing fenbendazole (FBZ) and flunixin meglumine (FLU) in swine liver. The population consisted of female and castrated male pigs that were sired by boars represented by 4 breeds. Progeny were randomly placed into groups: no drug (UNT), FLU or FBZ administered. Liver transcriptome profiles from 60 animals with extreme (i.e. fast or slow drug metabolism) pharmacokinetic (PK) profiles were generated from RNA sequencing. Multiple cytochrome P450 (CYP1A1, CYP2A19 and CYP2C36) genes displayed different transcript levels across treated versus UNT. Weighted gene co-expression network analysis identified 5 and 3 modules of genes correlated with PK parameters and a portion of these were enriched for biological processes relevant to drug metabolism for FBZ and FLU, respectively. Genes within identified modules were shown to have a higher transcript level relationship (i.e. connectivity) in treated versus UNT animals. Investigation into the identified genes would allow for greater insight into FBZ and FLU metabolism.}, number={1}, journal={Scientific Reports}, publisher={Springer Nature}, author={Howard, Jeremy T. and Ashwell, Melissa S. and Baynes, Ronald E. and Brooks, James D. and Yeatts, James L. and Maltecca, Christian}, year={2017}, month={May} } @article{howard_tiezzi_pryce_maltecca_2017, title={Geno-Diver: A combined coalescence and forward-in-time simulator for populations undergoing selection for complex traits}, volume={134}, ISSN={["1439-0388"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85018945915&partnerID=MN8TOARS}, DOI={10.1111/jbg.12277}, abstractNote={SummaryGeno‐Diver is a combined coalescence and forward‐in‐time simulator designed to simulate complex traits with a quantitative and/or fitness component and implement multiple selection and mating strategies utilizing pedigree or genomic information. The simulation is carried out in two steps. The first step generates whole‐genome sequence data for founder individuals. A variety of trait architectures can be generated for quantitative and fitness traits along with their covariance. The second step generates new individuals forward‐in‐time based on a variety of selection and mating scenarios. Genetic values are predicted for individuals utilizing pedigree or genomic information. Relationship matrices and their associated inverses are generated using computationally efficient routines. We benchmarked Geno‐Diver with a previous simulation program and described how to simulate a traditional quantitative trait along with a quantitative and fitness trait. A user manual with examples, source code in C++11 and executable versions of Geno‐Diver for Linux are freely available at https://github.com/jeremyhoward/Geno-Diver.}, number={6}, journal={JOURNAL OF ANIMAL BREEDING AND GENETICS}, author={Howard, J. T. and Tiezzi, F. and Pryce, J. E. and Maltecca, C.}, year={2017}, month={Dec}, pages={553–563} } @misc{howard_pryce_baes_maltecca_2017, title={Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability}, volume={100}, ISSN={["1525-3198"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85020250647&partnerID=MN8TOARS}, DOI={10.3168/jds.2017-12787}, abstractNote={Traditionally, pedigree-based relationship coefficients have been used to manage the inbreeding and degree of inbreeding depression that exists within a population. The widespread incorporation of genomic information in dairy cattle genetic evaluations allows for the opportunity to develop and implement methods to manage populations at the genomic level. As a result, the realized proportion of the genome that 2 individuals share can be more accurately estimated instead of using pedigree information to estimate the expected proportion of shared alleles. Furthermore, genomic information allows genome-wide relationship or inbreeding estimates to be augmented to characterize relationships for specific regions of the genome. Region-specific stretches can be used to more effectively manage areas of low genetic diversity or areas that, when homozygous, result in reduced performance across economically important traits. The use of region-specific metrics should allow breeders to more precisely manage the trade-off between the genetic value of the progeny and undesirable side effects associated with inbreeding. Methods tailored toward more effectively identifying regions affected by inbreeding and their associated use to manage the genome at the herd level, however, still need to be developed. We have reviewed topics related to inbreeding, measures of relatedness, genetic diversity and methods to manage populations at the genomic level, and we discuss future challenges related to managing populations through implementing genomic methods at the herd and population levels.}, number={8}, journal={JOURNAL OF DAIRY SCIENCE}, author={Howard, Jeremy T. and Pryce, Jennie E. and Baes, Christine and Maltecca, Christian}, year={2017}, month={Aug}, pages={6009–6024} } @article{howard_tiezzi_huang_gray_maltecca_2016, title={A method for the identification of unfavorable haplotypes contained within runs of homozygosity that impact fitness traits and its application to different swine nucleus lines.}, volume={94}, ISSN={["1525-3163"]}, DOI={10.2527/jas2016.94supplement426a}, number={S4}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Howard, J. T. and Tiezzi, F. and Huang, Y. and Gray, K. A. and Maltecca, C.}, year={2016}, month={Sep}, pages={26–27} } @article{howard_tiezzi_huang_gray_maltecca_2016, title={Characterization and management of long runs of homozygosity in parental nucleus lines and their associated crossbred progeny}, volume={48}, ISSN={["1297-9686"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84996878800&partnerID=MN8TOARS}, DOI={10.1186/s12711-016-0269-y}, abstractNote={In nucleus populations, regions of the genome that have a high frequency of runs of homozygosity (ROH) occur and are associated with a reduction in genetic diversity, as well as adverse effects on fitness. It is currently unclear whether, and to what extent, ROH stretches persist in the crossbred genome and how genomic management in the nucleus population might impact low diversity regions and its implications on the crossbred genome.We calculated a ROH statistic based on lengths of 5 (ROH5) or 10 (ROH10) Mb across the genome for genotyped Landrace (LA), Large White (LW) and Duroc (DU) dams. We simulated crossbred dam (LA × LW) and market [DU × (LA × LW)] animal genotypes based on observed parental genotypes and the ROH frequency was tabulated. We conducted a simulation using observed genotypes to determine the impact of minimizing parental relationships on multiple diversity metrics within nucleus herds, i.e. pedigree-(A), SNP-by-SNP relationship matrix or ROH relationship matrix. Genome-wide metrics included, pedigree inbreeding, heterozygosity and proportion of the genome in ROH of at least 5 Mb. Lastly, the genome was split into bins of increasing ROH5 frequency and, within each bin, heterozygosity, ROH5 and length (Mb) of ROH were evaluated.We detected regions showing high frequencies of either ROH5 and/or ROH10 across both LW and LA on SSC1, SSC4, and SSC14, and across all breeds on SSC9. Long haplotypes were shared across parental breeds and thus, regions of ROH persisted in crossbred animals. Averaged across replicates and breeds, progeny had higher levels of heterozygosity (0.0056 ± 0.002%) and lower proportion of the genome in a ROH of at least 5 Mb (-0.015 ± 0.003%) than their parental genomes when genomic relationships were constrained, while pedigree relationships resulted in negligible differences at the genomic level. Across all breeds, only genomic data was able to target low diversity regions.We show that long stretches of ROH present in the parents persist in crossbred animals. Furthermore, compared to using pedigree relationships, using genomic information to constrain parental relationships resulted in maintaining more genetic diversity and more effectively targeted low diversity regions.}, number={1}, journal={GENETICS SELECTION EVOLUTION}, publisher={BioMed Central}, author={Howard, Jeremy T. and Tiezzi, Francesco and Huang, Yijian and Gray, Kent A. and Maltecca, Christian}, year={2016}, month={Nov} } @article{howard_maltecca_haile-mariam_hayes_pryce_2015, title={Characterizing homozygosity across United States, New Zealand and Australian Jersey cow and bull populations}, volume={16}, ISSN={["1471-2164"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85019258044&partnerID=MN8TOARS}, DOI={10.1186/s12864-015-1352-4}, abstractNote={Dairy cattle breeding objectives are in general similar across countries, but environment and management conditions may vary, giving rise to slightly different selection pressures applied to a given trait. This potentially leads to different selection pressures to loci across the genome that, if large enough, may give rise to differential regions with high levels of homozygosity. The objective of this study was to characterize differences and similarities in the location and frequency of homozygosity related measures of Jersey dairy cows and bulls from the United States (US), Australia (AU) and New Zealand (NZ). The populations consisted of a subset of genotyped Jersey cows born in US (n = 1047) and AU (n = 886) and Jersey bulls progeny tested from the US (n = 736), AU (n = 306) and NZ (n = 768). Differences and similarities across populations were characterized using a principal component analysis (PCA) and a run of homozygosity (ROH) statistic (ROH45), which counts the frequency of a single nucleotide polymorphism (SNP) being in a ROH of at least 45 SNP. Regions that exhibited high frequencies of ROH45 and those that had significantly different ROH45 frequencies between populations were investigated for their association with milk yield traits. Within sex, the PCA revealed slight differentiation between the populations, with the greatest occurring between the US and NZ bulls. Regions with high levels of ROH45 for all populations were detected on BTA3 and BTA7 while several other regions differed in ROH45 frequency across populations, the largest number occurring for the US and NZ bull contrast. In addition, multiple regions with different ROH45 frequencies across populations were found to be associated with milk yield traits. Multiple regions exhibited differential ROH45 across AU, NZ and US cow and bull populations, an interpretation is that locations of the genome are undergoing differential directional selection. Two regions on BTA3 and BTA7 had high ROH45 frequencies across all populations and will be investigated further to determine the gene(s) undergoing directional selection.}, number={1}, journal={BMC GENOMICS}, author={Howard, Jeremy T. and Maltecca, Christian and Haile-Mariam, Mekonnen and Hayes, Ben J. and Pryce, Jennie E.}, year={2015}, month={Mar} } @article{howard_o’nan_maltecca_baynes_ashwell_2015, title={Differential Gene Expression across Breed and Sex in Commercial Pigs Administered Fenbendazole and Flunixin Meglumine}, volume={10}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0137830}, DOI={10.1371/journal.pone.0137830}, abstractNote={Characterizing the variability in transcript levels across breeds and sex in swine for genes that play a role in drug metabolism may shed light on breed and sex differences in drug metabolism. The objective of the study is to determine if there is heterogeneity between swine breeds and sex in transcript levels for genes previously shown to play a role in drug metabolism for animals administered flunixin meglumine or fenbendazole. Crossbred nursery female and castrated male pigs (n = 169) spread across 5 groups were utilized. Sires (n = 15) of the pigs were purebred Duroc, Landrace, Yorkshire or Hampshire boars mated to a common sow population. Animals were randomly placed into the following treatments: no drug (control), flunixin meglumine, or fenbendazole. One hour after the second dosing, animals were sacrificed and liver samples collected. Quantitative Real-Time PCR was used to measure liver gene expression of the following genes: SULT1A1, ABCB1, CYP1A2, CYP2E1, CYP3A22 and CYP3A29. The control animals were used to investigate baseline transcript level differences across breed and sex. Post drug administration transcript differences across breed and sex were investigated by comparing animals administered the drug to the controls. Contrasts to determine fold change were constructed from a model that included fixed and random effects within each drug. Significant (P-value <0.007) basal transcript differences were found across breeds for SULT1A1, CYP3A29 and CYP3A22. Across drugs, significant (P-value <0.0038) transcript differences existed between animals given a drug and controls across breeds and sex for ABCB1, PS and CYP1A2. Significant (P <0.0038) transcript differences across breeds were found for CYP2E1 and SULT1A1 for flunixin meglumine and fenbendazole, respectively. The current analysis found transcript level differences across swine breeds and sex for multiple genes, which provides greater insight into the relationship between flunixin meglumine and fenbendazole and known drug metabolizing genes.}, number={9}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Howard, Jeremy T. and O’Nan, Audrey T. and Maltecca, Christian and Baynes, Ronald E. and Ashwell, Melissa S.}, editor={Kobeissy, Firas HEditor}, year={2015}, month={Sep}, pages={e0137830} } @article{howard_jiao_tiezzi_huang_gray_maltecca_2015, title={Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars}, volume={16}, ISSN={["1471-2156"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84930210856&partnerID=MN8TOARS}, DOI={10.1186/s12863-015-0218-8}, abstractNote={Feed intake and growth are economically important traits in swine production. Previous genome wide association studies (GWAS) have utilized average daily gain or daily feed intake to identify regions that impact growth and feed intake across time. The use of longitudinal models in GWAS studies, such as random regression, allows for SNPs having a heterogeneous effect across the trajectory to be characterized. The objective of this study is therefore to conduct a single step GWAS (ssGWAS) on the animal polynomial coefficients for feed intake and growth.Corrected daily feed intake (DFI Adj) and average daily weight measurements (DBW Avg) on 8981 (n=525,240 observations) and 5643 (n=283,607 observations) animals were utilized in a random regression model using Legendre polynomials (order=2) and a relationship matrix that included genotyped and un-genotyped animals. A ssGWAS was conducted on the animal polynomials coefficients (intercept, linear and quadratic) for animals with genotypes (DFIAdj: n=855; DBWAvg: n=590). Regions were characterized based on the variance of 10-SNP sliding windows GEBV (WGEBV). A bootstrap analysis (n=1000) was conducted to declare significance. Heritability estimates for the traits trajectory ranged from 0.34-0.52 to 0.07-0.23 for DBWAvg and DFIAdj, respectively. Genetic correlations across age classes were large and positive for both DBWAvg and DFIAdj, albeit age classes at the beginning had a small to moderate genetic correlation with age classes towards the end of the trajectory for both traits. The WGEBV variance explained by significant regions (P<0.001) for each polynomial coefficient ranged from 0.2-0.9 to 0.3-1.01% for DBWAvg and DFIAdj, respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95% for DBWAvg and DFIAdj. Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior.We have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBWAvg and DFIAdj. These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times.}, number={1}, journal={BMC GENETICS}, publisher={BioMed Central Ltd}, author={Howard, Jeremy T. and Jiao, Shihui and Tiezzi, Francesco and Huang, Yijian and Gray, Kent A. and Maltecca, Christian}, year={2015}, month={May} } @article{howard_haile-mariam_pryce_maltecca_2015, title={Investigation of regions impacting inbreeding depression and their association with the additive genetic effect for United States and Australia Jersey dairy cattle}, volume={16}, ISSN={["1471-2164"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84945200087&partnerID=MN8TOARS}, DOI={10.1186/s12864-015-2001-7}, abstractNote={Variation in environment, management practices, nutrition or selection objectives has led to a variety of different choices being made in the use of genetic material between countries. Differences in genome-level homozygosity between countries may give rise to regions that result in inbreeding depression to differ. The objective of this study was to characterize regions that have an impact on a runs of homozygosity (ROH) metric and estimate their association with the additive genetic effect of milk (MY), fat (FY) and protein yield (PY) and calving interval (CI) using Australia (AU) and United States (US) Jersey cows. Genotyped cows with phenotypes on MY, FY and PY (n = 6751 US; n = 3974 AU) and CI (n = 5816 US; n = 3905 AU) were used in a two-stage analysis. A ROH statistic (ROH4Mb), which counts the frequency of a SNP being in a ROH of at least 4 Mb was calculated across the genome. In the first stage, residuals were obtained from a model that accounted for the portion explained by the estimated breeding value. In the second stage, these residuals were regressed on ROH4Mb using a single marker regression model and a gradient boosted machine (GBM) algorithm. The relationship between the additive and ROH4Mb of a region was characterized based on the (co)variance of 500 kb estimated genomic breeding values derived from a Bayesian LASSO analysis. Phenotypes to determine ROH4Mb and additive effects were residuals from the two-stage approach and yield deviations, respectively. Associations between yield traits and ROH4Mb were found for regions on BTA13, BTA23 and BTA25 for the US population and BTA3, BTA7, BTA17 for the AU population. Only one association (BTA7) was found for CI and ROH4Mb for the US population. Multiple potential epistatic interactions were characterized based on the GBM analysis. Lastly, the covariance sign between ROH4Mb and additive SNP effect of a region was heterogeneous across the genome. We identified multiple genomic regions associated with ROH4Mb in US and AU Jersey females. The covariance of regions impacting ROH4Mb and the additive genetic effect were positive and negative, which provides evidence that the homozygosity effect is location dependent.}, number={1}, journal={BMC GENOMICS}, author={Howard, Jeremy T. and Haile-Mariam, Mekonnen and Pryce, Jennie E. and Maltecca, Christian}, year={2015}, month={Oct} }