@article{he_tiezzi_jiang_howard_huang_gray_choi_maltecca_2022, title={Exploring methods to summarize gut microbiota composition for microbiability estimation and phenotypic prediction in swine}, volume={100}, ISSN={["1525-3163"]}, url={https://doi.org/10.1093/jas/skac231}, DOI={10.1093/jas/skac231}, abstractNote={Abstract}, number={9}, journal={JOURNAL OF ANIMAL SCIENCE}, author={He, Yuqing and Tiezzi, Francesco and Jiang, Jicai and Howard, Jeremy and Huang, Yijian and Gray, Kent and Choi, Jung-Woo and Maltecca, Christian}, year={2022}, month={Sep} }
 @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}, 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_jiang_howard_huang_gray_choi_maltecca_2022, title={Use of Host Feeding Behavior and Gut Microbiome Data in Estimating Variance Components and Predicting Growth and Body Composition Traits in Swine}, volume={13}, ISSN={["2073-4425"]}, url={https://doi.org/10.3390/genes13050767}, DOI={10.3390/genes13050767}, abstractNote={The purpose of this study was to investigate the use of feeding behavior in conjunction with gut microbiome sampled at two growth stages in predicting growth and body composition traits of finishing pigs. Six hundred and fifty-one purebred boars of three breeds: Duroc (DR), Landrace (LR), and Large White (LW), were studied. Feeding activities were recorded individually from 99 to 163 days of age. The 16S rRNA gene sequences were obtained from each pig at 123 ± 4 and 158 ± 4 days of age. When pigs reached market weight, body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content were measured on live animals. Three models including feeding behavior (Model_FB), gut microbiota (Model_M), or both (Model_FB_M) as predictors, were investigated. Prediction accuracies were evaluated through cross-validation across genetic backgrounds using the leave-one-breed-out strategy and across rearing environments using the leave-one-room-out approach. The proportions of phenotypic variance of growth and body composition traits explained by feeding behavior ranged from 0.02 to 0.30, and from 0.20 to 0.52 when using gut microbiota composition. Overall prediction accuracy (averaged over traits and time points) of phenotypes was 0.24 and 0.33 for Model_FB, 0.27 and 0.19 for Model_M, and 0.40 and 0.35 for Model_FB_M for the across-breed and across-room scenarios, respectively. This study shows how feeding behavior and gut microbiota composition provide non-redundant information in predicting growth in swine.}, number={5}, journal={GENES}, publisher={MDPI AG}, author={He, Yuqing and Tiezzi, Francesco and Jiang, Jicai and Howard, Jeremy T. and Huang, Yijian and Gray, Kent and Choi, Jung-Woo and Maltecca, Christian}, year={2022}, month={May} }
 @article{telles_simon_scallan_gould_papich_he_lee_lidbury_steiner_kathrani_et al._2021, title={Evaluation of gastrointestinal transit times and pH in healthy cats using a continuous pH monitoring system}, volume={12}, ISSN={["1532-2750"]}, DOI={10.1177/1098612X211062096}, abstractNote={Objectives The aim of this study was to characterize gastrointestinal (GI) transit times and pH in healthy cats. }, journal={JOURNAL OF FELINE MEDICINE AND SURGERY}, author={Telles, Naila J. and Simon, Bradley T. and Scallan, Elizabeth M. and Gould, Emily N. and Papich, Mark G. and He, Yuqing and Lee, Mu-Tien and Lidbury, Jonathan A. and Steiner, Jorg M. and Kathrani, Aarti and et al.}, year={2021}, month={Dec} }
 @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}, 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} }
 @misc{he_maltecca_tiezzi_2021, title={Potential Use of Gut Microbiota Composition as a Biomarker of Heat Stress in Monogastric Species: A Review}, volume={11}, ISSN={["2076-2615"]}, url={https://doi.org/10.3390/ani11061833}, DOI={10.3390/ani11061833}, abstractNote={Heat stress is a current challenge for livestock production, and its impact could dramatically increase if global temperatures continue to climb. Exposure of agricultural animals to high ambient temperatures and humidity would lead to substantial economic losses because it compromises animal performance, productivity, health, and welfare. The gut microbiota plays essential roles in nutrient absorption, energy balance, and immune defenses through profound symbiotic interactions with the host. The homeostasis of those diverse gut microorganisms is critical for the host’s overall health and welfare status and also is sensitive to environmental stressors, like heat stress, reflected in altered composition and functionality. This article aims to summarize the research progress on the interactions between heat stress and gut microbiome and discuss the potential use of the gut microbiota composition as a biomarker of heat stress in monogastric animal species. A comprehensive understanding of the gut microbiota’s role in responding to or regulating physiological activities induced by heat stress would contribute to developing mitigation strategies.}, number={6}, journal={ANIMALS}, publisher={MDPI AG}, author={He, Yuqing and Maltecca, Christian and Tiezzi, Francesco}, year={2021}, month={Jun} }
 @article{he_tiezzi_maltecca_2020, title={249 Predicting body weight of finishing pigs using machine and deep learning algorithms}, volume={98}, ISSN={0021-8812 1525-3163}, url={http://dx.doi.org/10.1093/jas/skaa278.324}, DOI={10.1093/jas/skaa278.324}, abstractNote={Abstract}, number={Supplement_4}, journal={Journal of Animal Science}, publisher={Oxford University Press (OUP)}, author={He, Yuqing and Tiezzi, Francesco and Maltecca, Christian}, year={2020}, month={Nov}, pages={176–176} }
 @article{he_maltecca_tiezzi_soto_flowers_2020, title={Transcriptome analysis identifies genes and co-expression networks underlying heat tolerance in pigs}, volume={21}, ISSN={["1471-2156"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85083872520&partnerID=MN8TOARS}, DOI={10.1186/s12863-020-00852-4}, abstractNote={Abstract}, number={1}, journal={BMC GENETICS}, author={He, Yuqing and Maltecca, Christian and Tiezzi, Francesco and Soto, Emmanuel Lozada and Flowers, William L.}, year={2020}, month={Apr} }