A full list of publications can be found here: https://scholar.google.com/citations?user=ezFUr0AAAAAJ&hl=en 

55. W.E. Brown, M.J. Martin, C. Siberski, J.E. Koltes, F. Peñagaricano, K.A. Weigel, and H.M. White. 2022. Predicting dry matter intake in mid-lactation Holstein cows using point-in-time data streams available on dairy farms. Accepted at Journal of Dairy Science.

54. M. de Souza, D. A. Koltes, H. Beiki, M. A. Sales, T. Tsai, C. V. Maxwell, J. Zhao, and J. E. Koltes^. 2022. Early life exposure of pigs to topsoil alters miRNA and mRNA expression in peripheral blood mononuclear cells.  Accepted at Frontiers in Geneticshttps://www.frontiersin.org/articles/10.3389/fgene.2022.886875/abstract

53. SL Fanalli, BPM da Silva, JD Gomes, Vivian Vezzoni de Almeida, Felipe André Oliveira Freitas, Gabriel Costa Monteiro Moreira, Bárbara Silva-Vignato, Juliana Afonso, James Reecy, James Koltes, Dawn Koltes, Luciana Correia Almeida Regitano, Dorian J. Garrick, Júlio Cesar de Carvalho Baileiro, Ariana Nascimento Meira, Luciana Freitas, Luiz Lehmann Coutinho, Heidge Fukumasu, Gerson Barreto Mourao, Severino Matias de Alencar, Albino Luchiari Filho, and Aline Silva Mello Cesar.2022.  Differential gene expression associated with soybean oil level in the diet of pigs.  Animals 12(13): 1632. https://www.mdpi.com/2076-2615/12/13/1632 

52. SL Fanalli, BPM da Silva, Julia Dezen Gomes, Fernanda Nery Ciconello, Vivian Vezzoni de Almeida, Felipe André Oliveira Freitas, Gabriel Costa Monteiro Moreira, Bárbara Silva-Vignato, Juliana Afonso, James M Reecy, James Koltes, Dawn Koltes, Luciana Correia Almeida Regitano, Júlio Cesar de Carvalho Baileiro, Luciana Freitas, Luiz Lehmann Coutinho, Heidge Fukumasu, Severino Matias de Alencar, Albino Luchiari Filho, and Aline Silva Mello Cesar.  2022. Effect of dietary soybean oil inclusion on liver-related transcription factors in a pig model of metabolic diseases. Scientific Reports. 12, article number: 10318. https://www.nature.com/articles/s41598-022-14069-1 

51. Souza MM, Niciura SCM, Rocha MIP, Pan Z, Zhou H, Bruscadin JJ, Diniz WJS, Afonso J, Oliveira PSN, Mourão GB, Zerlotini A, Coutinho LL, Koltes JE, and LCA Regitano. 2022. Epigenome screen suggests DNA methylation may affect beef tenderness through signal transduction in Bos Indicus. Epigenetics & Chromatin. 15: article number: 15. https://doi.org/10.1186/s13072-022-00449-4

50. Khanal, P., K.L. Parker Gaddis, M.J. Vandehaar, K.A. Weigel, H.M. White, F. Peñagaricano, J.E. Koltes, J.E.P. Santos, R.L. Baldwin, J.F. Burchard, J.W. Dürr, and R. J. Tempelman. 2022. Multiple trait random regression modeling of feed efficiency in US Holsteins. Accepted at Journal of Dairy Science

49. Andrade BGN, Donatoni FA, Cuadrat RRC, Cardoso TF, Malheiros J, de Oliveira PSN, Petrini J, Mourão GB, Coutinho LL, Reecy J, Koltes JE, Zerlotini Neto A, de Medeiros SR, Berndt A, Palhares JCP, Afli H and LCA Regitano Regitano. Stool and ruminal microbiome components associated with methane emission and feed efficiency in Nelore beef cattle. 2022. In press at Frontiers in Genetics

 48. C.J. Cooper, M.S. Mayes, M. Healey, B.M. Goetz, L.H. Baumgard, and J.E. Koltes^. 2022. Associations of wearable sensor measures with feed intake, production traits, lactation and environmental parameters impacting feed efficiency in dairy cattle. In press at Frontiers in Animal Science.

 47. Stephan T, Burgess SM, Cheng H, Danko CG, Gill CA, Jarvis ED, Koepfli K-P, Koltes JE, Lyons E, Ronald P, Ryder OA, Schriml LM, Soltis P, VandeWoude S, Zhou H, Ostrander EA, and EK Karlsson. 2022. Darwinian Genomics and Diversity in the Tree of Life. Proceedings of the National Academy of Science. 119 (4) e2115644119; https://doi.org/10.1073/pnas.2115644119  

46. C.J. Cooper and JE Koltes^. 2021. Opportunities to harness high-throughput and novel sensing phenotypes to improve feed efficiency in dairy cattle.  Animals 12(1) 15.  An invited review for the special edition on Smart Farming in Dairy Production.  

45. Lucas KM, Koltes DA, Meyer LR, Tucker JD, Hubbell III DS, Powell JG, Apple JK, and JE Koltes^. Identification of breed differences in known and novel fescue toxicosis associated phenotypes in crossbred beef cows. 2021.  Animals 11(10), 2830. https://www.mdpi.com/2076-2615/11/10/2830   

44. E. A. Palmer, PAS, E. B. Kegley, PAS, P. A. Beck, PAS, J. J. Ball, PAS, J.E. Koltes, S. K. Chewning, M. D. Cravey, and J. G. Powell. 2021. Effect of a combination of live yeast and yeast cell wall products supplemented before and after weaning on heifer growth performance, immune function, and body temperature. Applied Animal Science. 37(6), 710-721.  https://doi.org/10.15232/aas.2021-02189  

43. B Petry, GCM Moreira, AGL Copola, MM Souza, FC da Veiga, EC Jorge, JO Peixoto, MC Ledur, JE Koltes, and LL Coutinho. SAP30gene is a probable regulator of muscle hypertrophy in chickens.  2021.  Front. Genet., 27 September 2021  https://doi.org/10.3389/fgene.2021.709937  

42. Chinchilla-Vargas J, Kramer LM, Tucker JD, Hubbell, DS III, Powell JG, Lester TD, Backes EA, Anschutz K, Decker JE, Stalder KJ, Rothschild MF, and JE Koltes^. 2020. Genetic basis of blood-based phenotypes and their relationship with performance and environment in beef cattle at weaning. Frontiers in Genetics. 11: 717. doi: 10.3389/fgene.2020.00717. eCollection 2020  

41. Crook TS, Beck PA, Gadberry MS, Sims MB, Stewart CB, Shelton C, Koltes J, Kegley EB, Powell J, McLean DJ, and Chapman JD. 2020. Influence of an immune modulatory feed supplement on performance and immune function of beef cows and calves preweaning. Journal of Animal Science. 98 (3):skaa073.doi: 10.1093/jas/skaa073  

40. Lima AO, Koltes JE, Diniz WJS, de Oliveira PSN, Cesar ASM, Tizioto PC, Afonso J, de Souza MM, Petrini J, Rocha MIP, Cardoso TF, Neto AZ, Coutinho LL, Mourao GB, and LCA Regitano. 2020. Potential biomarkers for feed efficiency-related traits in Nelore cattle identified by co-expression network and integrative genomics analyses. Frontiers in Genetics 11:189. doi: 10.3389/fgene.2020.00189. eCollection 2020


39. Andrade BGN, Bressani FA, Cuadrat RC, Tizioto PC, Oliveira PSN, Mourao GB, LL Coutinho, Reecy JM, Koltes JE, Walsh P, Berndt A, Palhares JCP, and Regitano LCA. 2019.  The Nelore rumen and fecal microbiomes: Structure and inter-dependency of bacterial and archaeal populations.  Accepted at the Journal of Animal Science and Biotechnology

38. Koltes JE, John B Cole, Nick VL Serão, Molly E McCue, Jennifer Woodward, Hongwei Zhang, Stephanie D McKay, Joan K Lunney, Luke M Kramer, Ryan N Dilger, Ryan Reuter, Mark Schroeder, Roxanne Clemmens, Brenda M Murdoch, Caird E Rexroad III, Guilherme JM Rosa, Reluca G Mateescu, Stephen N. White, Mulumebet Worku, and James M Reecy. 2019. A vision for development and utilization of high-throughput phenotyping and big data analytics in livestock.  Frontiers in Genetics. https://www.frontiersin.org/articles/10.3389/fgene.2019.01197/abstract

37. Ramirez BC, Xin H, Beermann DH, Halbur PG, Hansen SL, Peschel JM, Rademacher CJ, Reecy JM, Ross JW, Shepherd TP, and JE Koltes.  2019. At the intersection of industry and academia: How do we facilitate productive precision livestock farming in practice?  Animals 9; 635. DOI:  https://doi.org/10.3390/ani9090635

36. Oliveira PSN, LL Coutinho, Cesar ASM, Diniz WJD, De Souza MM, Andrade BGN, Koltes JE, Mourao GB, Zeriotini-Neto A, Reecy JM, and Regitano LCA. 2019. Co-expression networks reveals potential regulatory roles of miRNAs in fatty acids composition of Nelore cattle.  Frontiers in Genetics. 11. https://doi.org/10.3389/fgene.2019.00651

35. Koltes J.E., Arora, I., Gupta R., Nguyen D.C., Schiad M., Kim J., Kimple M.E., and S. Bhatnagar.  2019.  A gene expression network analysis of the pancreatic islets from lean and obese mice identifies complement 1q like-3 secreted proteinas a  regulator of b-cell function.  Scientific Reports. 9, Article number: 10119.  https://www.nature.com/articles/s41598-019-46219-3

34. Goncalves, T.M., LCA Regitano, J.E. Koltes, A.S.M. Cesar, S.C.S Andrade, G.B. Mourao, G. Gasparin, GCM Moreira, E Fritz-Waters, JM Reecy and LL Coutinho. 2018.  Gene co-expression analysis indicates potential pathways and regulators of beef tenderness in Nellore Cattle.  Frontiers in Genomics  https://doi.org/10.3389/fgene.2018.00441

33. Gupta R, Nguyen DC, Schaid MD, Lei X, Balamurugan AN, Wong GW, Kim JA, Koltes JE, Kimple ME, Bhatnagar S. 2018.  Complement 1q like-3 protein inhibits insulin secretion from pancreatic β-cells via the cell adhesion G protein-coupled receptor BAI3. J Biol Chem. 2018 Sep 18. pii: jbc.RA118.005403. doi: 10.1074/jbc.RA118.005403.  http://www.jbc.org/content/early/2018/09/18/jbc.RA118.005403.long

32. Cesar ASM, Regitano LCA, Reecy JM, Poleti MD, Oliveira PSN, de Oliveira GB, Moreira GCM, Mudadu MA, Tizioto PC, Koltes JE, Fritz-Waters E, Kramer L, Garrick D, Beiki H, Geistlinger L, Mourão GB, Zerlotini A, Coutinho LL. 2018.  Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.   BMC Genomics. 2018 Jun 27;19(1):499. doi: 10.1186/s12864-018-4871-y.

31. Koltes J.E., Koltes D.A., Mote B.E., Tucker J., and D.S. Hubbell III.  2018. Automated collection of heat stress data in livestock: new technologies and opportunities. Translational Animal Sciencehttps://doi.org/10.1093/tas/txy061

30. Oliveira G., LCA Regitano, ASM Cesar, JM Reecy, KY Degaki, MD Poleti, AM Felício, JE Koltes, and LL Coutinho.  2018. Integrative analysis of microRNAs and mRNAs revealed regulation of intramuscular fat deposition in Nelore cattle.  BMC Genomics 19:126. https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4514-3

29. Iamartino D, E.L. Nicolazzi, C.P. Van Tassell, J.M. Reecy, E.R. Fritz-Waters, J.E. Koltes, S. Biffani, T.S. Sonstegard, S.G. Schroeder, P. Ajmone-Marsan, R. Negrini, R. Pasquariello, P. Ramelli, A. Coletta, J.F. Garcia, A. Ali, L. Ramunno, G. Cosenza, D.A. de Oliveira, M.G. Drummond, E. Bastianetto, A. Davassi, F. Brew, A. Pirani, and J.L. Williams.  2017.  Design and validation of a 90k SNP genotyping assay for the Water Buffalo (Bubalus bubalis). PLOS One 12(10): e0185220 https://doi.org/10.1371/journal.pone.0185220. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0185220

28.Yazwinski T.A., Tucker C.A., Powell J., Beck P., Wray E., Jones L., Koltes J.E., and Weingartz C.  2017.  A Fecal egg count reduction test with cattle treated 118 days earlier with saline, albendazole in combination with doramectin or an extended release formulation of eprinomectin. Bovine Practitioner 51: 28-33.

27. Bao H., A. Kommadath, I. Choi, J.M. Reecy, J.E. Koltes, E. Fritz-Waters, C.J. Eisley, R.R.R. Rowland, C.K. Tuggle, J.C.M. Dekkers, J.K. Lunney, L.L. Guan, P. Stothard, and G.S. Plastow.  2017. Genetic architecture of gene expression underlying variation in host response to porcine reproductive and respiratory syndrome virus infection.  Scientific Reports. 7:46203.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385538/

26. J.B. Cole, J.M. Bormann, C.A. Gill, H. Khatib, J.E. Koltes, C. Maltecca, and F. Miglior.  2017. Resilience of Livestock to Changing Environments.  Journal of Animal Science.   95: 1777-1779.  https://www.animalsciencepublications.org/publications/jas/abstracts/95/4/1777/preview/pdf

25. Jia C., Kong X., Koltes JE, Gou X., Yang S., Yan D., Lu S., and Z. Wei. 2016. Gene Co-expression network analysis unraveling transcriptional regulation of high-altitude adaptation of Tibetan pig.  PLOS One.  Dec 9;11(12):e0168161. doi: 10.1371/journal.pone.0168161. eCollection 2016.  http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168161

24. Cesar ASM, Regitano LCA, Poleti MD, Andrade SCS, Tizioto PC, Oliveira PSN, Felicio AM, Nascimento ML, Chaves AS, Lanna DPD, Tullio RR, Nassu RT, Koltes JE, Fritz-Waters E, Mourao GB, Zeriotini-Neto A, Reecy JM, and LL Coutinho.  2016. Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content.  2016. BMC Genomics.  7:961.  https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-3306-x

23. Kramer, L.M., J.E. Koltes, E.R. Fritz-Waters, M. Mayes, A. Markey, D.J. Garrick, N.T. Weeks and J.M. Reecy. 2016. Identification of epistatic interactions among fatty acid traits in Angus sired cattle. BMC Genomics. 17:891.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100273/

22. Fleming, D.S., J.E. Koltes, E.R. Fritz-Waters, J.M. Reecy, M.F. Rothschild, C.J. Schmidt, C.M. Ashwell, M.E. Persia and S.J. Lamont.  2016.  Single nucleotide variant discovery of highly inbred Leghorn and Fayoumi chicken breeds using pooled whole genome resequencing data reveals insights into phenotypic differences.  BMC Genomics.  17: 812.  https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-3147-7

21. Buchanan, J.W., J.M. Reecy, D.J. Garrick, J.E. Koltes, M. Saatchi, Q. Duan, D.C. Beitz, and R.G. Mateescu.  2016.  Deriving gene networks from SNP associated with triacylglycerol and phospholipid fatty acid fractions from ribeyes of Angus catle.  In press at Frontiers in Genetics.  7:116. doi: 10.3389/fgene.2016.00116. eCollection 2016.  http://journal.frontiersin.org/article/10.3389/fgene.2016.00116/abstract

20. Boddicker, R.L.*, J.E. Koltes*, E.R. Fritz-Waters, L. Koesterke, T. Yin, V. Mani, J.M. Reecy, D. Nettleton, L.H. Baumgard, N.K. Gabler, and J.W. Ross.  2016.  Genome-Wide Methylation Profile Following Prenatal and Postnatal Dietary n-3 Fatty Acid Supplementation in Pigs.  Animal Genetics. Aug 25. doi: 10.1111/age.12468.  http://onlinelibrary.wiley.com/doi/10.1111/age.12468/abstract

19. Weeks N.T., G.R. Luecke, B.M. Groth, M. Kraeva, L. Ma, L.M. Kramer, J.E. Koltes and J.M. Reecy.  2016.  High performance epistasis detection in quantitative trait GWAS.   International Journal of High Performance Computing Applications.  1-16.  DOI: 10.1177/1094342016658110  http://hpc.sagepub.com/content/early/2016/07/12/1094342016658110.full.pdf?ijkey=RZHEcHkE7gCzoBV&keytype=finite                                                                                                                                                    An article was recently published about this work:  https://www.nersc.gov/news-publications/nersc-news/science-news/2016/researchers-use-edison-to-improve-performance-energy-efficiency-of-bioinformatics-application/

18. Fleming, D.S., J.E. Koltes, A.D. Markey, C.J. Schmidt, C.M. Ashwell, M.F. Rothschild, J.M. Reecy, M.E. Persia and S.J. Lamont.  2016. Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600k genotyping array.  BMC Genomics 17: 407. http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-2711-5

17. Schroyen, M., Eisley C.J., J.E. Koltes, E. Fritz-Waters, Choi I., Plastow G.S., Guan L.L., Stothard P., Bao H., Kommadath A., Reecy J.M., Lunney J.K., Rowland R.R.R., Dekkers J.C.M., and Tuggle C.K.  2016.  Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRS) reveals pathway differences between pigs with alternate genotypes for a major host response QTL. BMC Genomics 17: 196. http://www.biomedcentral.com/1471-2164/17/196

16. Luecke, G.R., N.T. Weeks, B.M. Groth, M. Kraeva, L. Ma, L.M. Kramer, J.E. Koltes and J.M. Reecy.  2015.  Fast epistasis detection in large-scale GWAS for Intel Xeon Phi Clusters.  Trustcom/BigDataSE/ISPA IEEE, 3: 228-235. doi:10.1109/Trustcom.2015.637. http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7345653&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7345653

 15.  Schroyen, M., J.P. Steibel, J.E. Koltes, I. Choi, N.E. Raney, C. Eisley, E. Fritz-Waters, J.M. Reecy, J.C.M. Dekkers, R.R.R. Rowland, J.K. Lunney, C.W. Ernst, and C.K. Tuggle.  2015. Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection.  BMC Genomics 16: 516.  http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-1741-8

14.  Cesar, A.S.M., Regitano L.C.A., Koltes J.E., Fritz-Waters E., Gasparin G., Mourao G.B., Oliveira P.S.N., Reecy J.M., and LL Coutinho.  2015.  Putative regulatory factors associated with intramuscular fat content.  PLOS ONE. 10(6):e0128350. doi: 10.1371/journal.pone.0128350. eCollection 2015.  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456163/

 13.  Koltes J.E. *, Fritz-Waters E.*, Eisley C.J., Choi I., Bao, H., Kommadath A., Serão N.V.L., Boddicker N., Abrams S.M., Schroyen M., Loyd H., Tuggle C.K., Plastow G.S., Guan L.L.,  Stothard P., Lunney J.K., Liu P., Carpenter S., Rowland R.R.R., J.C.M. Dekkers, and J.M. Reecy.  2015.  Identification of a putative quantitative trait nucleotide in Guanylate Binding Protein 5 for host response to PRRS virus infection. BMC Genomics. 16:412.  http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-1635-9

 12.  Koltes, J.E., D. Kumar, R.S. Kataria, V.L. Cooper, and J.M. Reecy. Transcriptional profiling of PRKG2-null growth plate identifies down-stream targets of PRKG2. 2015. BMC Research Notes. 8:177.  http://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-015-1136-6

 11.  Pilcher, C., Jones C.,Schroyen M., Severin A., Tuggle C.K., Patience J.F., and J.E. Koltes. 2015.  Gene expression profiling of longissimus dorsi and adipose tissue in pigs with differing post-weaning growth rates.  Journal of Animal Science. 93(5): 2134-43.  http://www.ncbi.nlm.nih.gov/pubmed/26020309

 10. Yang, X.*, Koltes, J.E*., Park, C.A., Chen, D., and JM Reecy. Gene co-expression network analysis provides novel insights into important factors involved in myostatin regulation across developmental timepoints in mouse skeletal muscle.  2015. PLoS One. Feb 19: 10(2):e0117607. doi: 10.1371/journal.pone.0117607  http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0117607

 9. Baes C.F., Dolezal M.A., Bapst B., Fritz-Waters E., Koltes J.E., Jansen S., Flury C., Signer-Hasler H., Stricker C., Fernando R., Fries R., Moll J., Garrick D.J., Reecy J.M., and Gredler B. Evaluation of variant identification methods for whole genome sequencing data in dairy cattle. 2014. BMC Genomics. Nov 1; 15:948.  http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-15-948

 8.   Koesterke,L., J.E. Koltes, N.T. Weeks, K. Milfeld, M. Vaughn,J.M. Reecy and D. Stanzione. Discovery of biological networks using an optimized PCIT algorithm on Stampede’s Intel Xeon and Xeon Phi processors. 2014.Concurrency and Computation Practice and Experience.  26: 2178-2190.  http://onlinelibrary.wiley.com/doi/10.1002/cpe.3252/abstract  This paper does not show up on pubmed as it is in a computing journal.  The paper has been cited 4 times. 

 7.  Koesterke,L., J.E. Koltes, N.T. Weeks, K. Milfeld, M. Vaughn,J.M. Reecy and D. Stanzione. Optimizing the PCIT algorithm on Stampede’s Xeon and Xeon Phi processors for faster discovery of biological networks. 2013Proceedings of the XSEDE2013 Conference.  ACM. New York, NY, USA. doi>10.1145/2484762.2484794.  This paper does not show up on pubmed as it is in a computing journal.  This paper won an award as best lightning talk at the XSEDE 2013 conference, has been downloaded more than 120 times and cited twice. http://dl.acm.org/citation.cfm?id=2484794

 6. Hu, Z-L*, Koltes, J.E.*, Park, C.A., Fritz, E.R., and J.M. Reecy.  Invited Review: Bioinformatics approaches to livestock animal genomics research. CABI Reviews. 2011, 6: 1-15.  http://www.cabi.org/cabreviews/search/?q=Bioinformatics+approaches+to+livestock+animal+genomics+research

 5.  Lavine, J.A., Raess, P.W., Stapleton, D.S., Rabaglia, M.E., Suhonen, J.I., Schueler, K.L., Koltes, J.E., Dawson, J.A., Yandell, B.S., Samuelson, L.C., Beinfeld, M.C., Belt Davis, D., Hellerstein, M.K., Keller, M.P. and A.D. Attie.  Cholecystokinin is upregulated in obese islets and expands b-cell mass by increasing b-cell survival. Endocrinology. 2010. 151(8): 3577-88.  http://press.endocrine.org/doi/full/10.1210/en.2010-0233

 4.  Koltes, J.E., B.P. Mishra, D. Kumar, R.S. Kataria, L.R. Totir, R.L. Fernando, R. Cobbold, D. Steffen, W. Coppieters, M. Georges, and J.M. Reecy.  A Nonsense mutation in the Kinase domain of cGMP-dependant, type II protein kinase (PRKG2) is the causative mutation for Angus dwarfism. Proceedings of the National Academy of Science. 2009, 106 (46): 19250-5.  http://www.pnas.org/content/106/46/19250.long

 3.  Koltes, J.E., Z-L. Hu, E. Fritz, and J.M. Reecy.  BEAP: BLAST extension and alignment program- a tool for contig construction and analysis of preliminary genome sequence. BMC Research Notes.  2009, 2:11.  http://bmcresnotes.biomedcentral.com/articles/10.1186/1756-0500-2-11

 2.  Alexander, L.J., L.A. Kuehn, T.L.P. Smith, L. Matukumalli, B. Mote, J.E. Koltes, J. Reecy, T.W. Geary, and M.D. MacNeil.  A Limousin specific myostatin allele affects longissimus muscle area and fatty acid profiles in a Wagyu-Limousin F2 population.  J. Animal Science.  2009, 87(5):1576-81.  http://www.ncbi.nlm.nih.gov/pubmed/?term=19213716

 1.  Tshipuliso, N.O.M, L.J. Alexander, T.W. Geary, W.M. Snelling, D.C. Rule, J.E. Koltes, B.E. Mote, and M.D. MacNeil.  Mapping QTL for fatty acid composition that segregate between Japaneese Black and Limousin breeds.  South African Journal of Animal Science.  2008. 38 (2): 126-130.  http://www.sasas.co.za/mapping-qtl-fatty-acid-composition-segregates-between-japanese-black-and-limousin-cattle-breeds


SELECTED ABSTRACTS

52. CJ Siberski-Cooper, J Chinchilla-Vargas, LM Kramer, KS Lim, MS Mayes, and JE Koltes.  2022. Genome Wide Association Study of Blood Based Cell Counts in Holstein Cows.  Proceedings of the 12th World Congress of Genetics Applied to Livestock Production. Rotterdam, The Netherlands 

51. Lopes, K. Houlahan, F.S. Schenkel, D. Tulpan, F. Miglior, M. Sargolzaei, J. Koltes, and C.F. Baes. 2022. Estimates of genetic parameters for environmental efficiency traits for first lactation Holsteins. Submitted to the ICAR meeting proceedings.

50. Baes C.F., G. Kistenmaker, R. Baldwin, A. Butty, J. Burchard, O. Gonzalez-Recio, J. Lassen, M. VandeHaar, D. Segelke, R. Tempelman, K. Weigel, J. Koltes, F. Miblior, RDGP Consortium partners, FFAR Consortium Partners. 2022. International collaboration to improve sustainability and resilience in dairy: Current and future studies.  Proc. Of the National ADSA meeting. Kansas City, MO, USA.

49. Pandey, S. J. Shearer, Y. Park, A. Ankita, R. Pathak and J. Koltes.  2022. Bluetooth-enabled Multimodal Sensor Boards, Data Collection Software Stack, and Machine Learning Model to Identify Early Signs of Lameness in Dairy Cattle.  Submitted to the Proc. of the 21st International Symposium & 13th International Conference on Lameness in Ruminants.  Bloomington, MN, USA.

48. Pathak R., J. Shearer, J. Koltes, Y. Park, A. Ankita, and S. Pandey.  2022. Audio signal Analysis of Cow Vocalizations in Python’s Librosa with Gradient Boosting Algorithms to Identify Abnormal Sound Signatures in Lame Cows. Submitted to the Proc. of the 21st International Symposium & 13th International Conference on Lameness in Ruminants.  Bloomington, MN, USA.

47. M.M. de Souza, P. Plummer, H. Beiki, J. Schleining,  J. Shearer, M. Calvo-Lorenzo, and J.E. Koltes.  2022.  Global transcriptomic evaluation of the hoof lamina in beef cattle with altered mobility.  Submitted to the Proc. of the 21st International Symposium & 13th International Conference on Lameness in Ruminants.  Bloomington, MN, USA.

46. Cooper C.J. and J.E. Koltes. 2022. Managing the Flood of Dairy Data: A Graduate Student’s Perspective. Proc. of Plant and Animal Genome XXIX. San Diego, CA, USA.  (Invited for Talk)

45. Koltes J.E. Opportunities to apply and learn from deep phenotyping in dairy cattle. 2021. American Society of Animal Science Association Annual meeting. Louisville, KY, USA.


44. M. J. VandeHaar, R.J. Tempelman, J.E. Koltes, R. Appuhamy, H.M. White, K.A. Weigel, R. Baldwin, P. Van Raden, F. Peñagaricano, J. Santos, J.W. Durr, E. Nicolazzi & J. F. Burchard and K. L. Parker Gaddis. Improving dairy feed efficiency, sustainability, and profitability by impacting farmer’s breeding and culling decisions.  2021. Submitted to the ICAR meeting proceedings. 

43. Parker Gaddis, K. L., P. M. VanRaden, R. J. Tempelman, K. A. Weigel, H. M. White, F. Peñagaricano, J. E. Koltes, J. E. P. Santos, R. L. Baldwin, J. F. Burchard, J. W. Dürr, and M. J. VandeHaar. Implementation of Feed Saved evaluations in the US. 2021. Proc of the Interbull meeting proceedings. Leeuwarden, The Netherlands, April 26-30, 2021.

42. Parker Gaddis, K. L., P. M. VanRaden, R. J. Tempelman, K. A. Weigel, H. M. White, F. Peñagaricano, J. E. Koltes, J. E. P. Santos, R. L. Baldwin, J. F. Burchard, J. W. Dürr, and M. J. VandeHaar. Genomic evaluations for Feed Saved in Holsteins. 2021. Proc. Of the National ADSA virtual meeting.

41. Combs, GJ, Cavani, L, Baier, FS, Martin, MJ, Erb, SJ, VandeHaar, MJ, Koltes, JE, Weigel, KA, Peñagaricano, F, and HM White. Evaluation of the use of intravaginal temperature monitors to assess postprandial body temperature changes. 2021.  Proc. Of the National ADSA virtual meeting. 

40. Khanal, P., Parker Gaddis, K. L., P. M. VanRaden, K. A. Weigel, H. M. White, F. Peñagaricano, J. E. Koltes, J. E. P. Santos, R. L. Baldwin, J. F. Burchard, J. W. Dürr, M. J. VandeHaar, and R.J. Tempelman. Multiple trait random regression modelling of feed efficiency in dairy cattle. 2021.  Proc. Of the National ADSA virtual meeting.

39. M.J. Oconitrillo, H. K. J. P. Wickramasinghe, N. Stepanchenko, CJ Siberski, JE Koltes and J. A. D. R. N. Appuhamy. The Effects of a Zinc-Methionine Supplementation on Blood Zinc Status and Production Performance of High Producing Dairy Cows. 2021.  Proc. Of the National ADSA virtual meeting.

38. KM Lucas, M Saatchi, and JE Koltes. Characterizing growth and carcass traits in beef x dairy crossbred animals. 2021. Proc. Of the National ADSA virtual meeting.

37. C.J. Siberski, M.S. Mayes, P.J. Gorden, A. Copeland, M. Healy, B.M Goetz, H. Beiki, L.M. Kramer, L.H. Baumgard, P. Dixon, and J.E. Koltes. Inclusion of automated sensor data as a predictor of feed intake increases the variance explained by a random forest model. Proc. Of the National ASAS meeting. 2020 Madison, WI, USA.

36. A.E. Jantzi, C.J. Siberski, B.M Goetz, M. Healy, K.P. Hayman, P.J. Gorden, L.H. Baumgard, and J.E. Koltes. Milking collar activity data is associated with health events and feed intake in lactating Holstein cattle. 2020 Proc. Of the National ASAS meeting. Madison, WI, USA.

35. C.J. Siberski, M.S. Mayes, P.J. Gorden, A. Copeland, M. Healy, B.M Goetz, H. Beiki, L.M. Kramer, L.H. Baumgard, P. Dixon, and J.E. Koltes. Predicting heath events and feed intake using sensor data in lactating Holstein cows. 2020. Proc. Of the National ADSA meeting. West Palm Beach, FL, USA.


34. M. J. VandeHaar, R. J. Tempelman, J.E. Koltes, H. M. White, K. A. Weigel, E. Connor, P. Van Raden, F. Peñagaricano, J. Santos, K. Parker Gaddis, J. Burchard, and J. Durr. Improving dairy feed efficiency, sustainability, and profitability by impacting farmer's breeding and culling decisions. 2020. ICAR Annual Conference. Leeuwarden, The Netherlands.

33. Beiki, H., J.E. Koltes, Z-L. Hu, J. M. Reecy. Analysis of Divergent Transcription Events Across Cattle Tissues. 2020.  Proc. of Plant and Animal Genome XXVIII.  San Diego, CA, USA.

32. MM de Souza, H Beiki, DA Koltes, JG Powell, JA Atchley, LM Meyer, J Tucker, DS Hubbell, III, and JE Koltes. Effect of toxic fescue on whole blood gene expression in beef cattle. 2020  Proc. of Plant and Animal Genome XXVIII.  San Diego, CA, USA.

31. Chinchilla-Vargas J, L. M. Kramer , J. D. Tucker , D. S. Hubbell III, J. G. Powell, T. D. Lester, E. A. Backes, K. Anschutz, J. E. Decker,  K. J. Stalder, M. F. Rothschild, and J.E. Koltes. Blood traits in beef cattle and their relationship with production traits at weaning. 2020 Proc. of Plant and Animal Genome XXVIII.  San Diego, CA, USA.

30. Petry, B, Copola, A.G.L, Moreira, G.C.M, Godoy, T.F, Jorge, E.C, Peixoto, J.O, Ledur, M.C, Koltes, J.E, Coutinho, L.L Functional analysis indicates SAP30 as putative causal gene for muscle growth in chicken. 2020 Proc. of Plant and Animal Genome XXVIII.  San Diego, CA, USA.

29. Beiki, H., J. Koltes, Z. Hu, J. Reecy Analysis of Alternative Splicing Events Across Cattle Tissues by Genome-Wide Integration of PacBio Iso-seq and RNA-Seq Data. 2019. Proceedings of the 37th International Society of Animal Genetics.  Lleida, Spain.   

28. M. de Souza, D. Koltes, H. Beiki, T. Tsai, M. Sales, C. Maxwell, J. Zhao, and J. Koltes.  miRNA and mRNA differential expression in peripheral blood mononuclear cells of pigs exposed to topsoil in early life. 2019. Proceedings of the 37th International Society of Animal Genetics.  Lleida, Spain.   

27. Koltes J. Automated collection and processing of data in livestock farms. 2019. Proc. Of the National ADSA meeting.  Cincinnati, OH, USA.

26. Koltes J, Arora I, Gupta R., Nguyen D.C., and S. Bhatnagar.  A Gene Expression Network Analysis Of The Pancreatic Islets From Lean And Obese Mice Identifies Complement 1q-like-3 Secreted Protein As A Regulator Of beta cell Function.  2019. American Diabetes Association Meeting.  San Francisco, CA, USA.

25. Siberski C., Goetz B., Baumgard L.H., and J.E. Koltes.  Preliminary exploration of relationships of automated sensor data  with  feed  intake and efficiency in lactating dairy cattle.  2019. Proc. Of the Midwest ASAS meeting. Omaha, NE, USA.

24. Chinchilla-Vargas J, Kramer L. M. , Tucker J. D., Hubbell D. S. III, Powell J. G., Lester T. D., Backes E. A., Anschutz K., Stalder  K. J., Rothschild M. F.,  and J. E.  Koltes. Peripheral blood parameters as proxies of performance in beef cattle: Heritability and genetic correlations between peripheral blood parameters and performance phenotypes. 2019. Proc. Of the Midwest ASAS meeting. Omaha, NE, USA

23.  Beiki, H., Z. Hu, J.M. Reecy, J.E. Koltes. Analysis of the Cattle Tissue-specific Expression by Genome-wide Integration of RNA-seq data. 2019.  Proc. of Plant and Animal Genome XXVII.  San Diego, CA, USA.

22.  Cesar A.S.M., Regitano L.C.A., Poteti M.D., Oliveira G.B., Oliveira P.P.N., Koltes J.E., Fritz-Waters E., Reecy J.M., and L.L. Coutinho. 2018. MiRNA expression quantitative trait loci (miR-eQTL) regions identified in Nellore steers with whole genome imputed sequence variants.  23rd Annual Meeting of RNA Society. Berkeley, CA, USA.

21. Serao NVL, Koltes JE, Schmitz-Esser S, and DH Poole.  2018. Investigating host-genetic mechanisms associated with fescue- and heat-stress tolerance in cattle.   Proc. of Plant and Animal Genome XXVI.  San Diego, CA, USA.

20.  Ratton A, Chewning SK, Meyer LR, Atchley JA, Powell JG, Tucker J, Hubbell DS III, Zhao J, and J.E. Koltes.  2018. Toxic fescue exposure alters vaginal microbial communities of crossbred beef cows. Proc. Of the Midwest ASAS meeting. Omaha, NE, USA.

19. Chewning S.K., Meyer L.R., Atchley J.A., Powell J.G., Tucker J., Hubbell D.S. III, Zhao J., and J.E. Koltes.  2018. Analysis of fecal microbiome of crossbred beef cows grazing toxic or novel fescue. Proc. Of the Midwest ASAS meeting. Omaha, NE, USA.

18. Sales M.A., Tsai T.C., Maxwell C.V., Koltes D.A. and J.E. Koltes.  Identification of differentially expressed microRNA in peripheral blood mononuclear cells of topsoil-exposed piglets.  Proc. Of the National ASAS meeting.  Baltimore, MD, USA. https://dl.sciencesocieties.org/publications/jas/abstracts/95/supplement4/369a

17. Chewning S., Koltes D.A., Powell J.G., Meyer L.M., Tucker J., Hubbell, III D.S., Chewning J., and J.E. Koltes. 2017.  Analysis of serial vaginal temperature measurements in crossbred beef cattle grazing novel or toxic fescue.  Proc. Of the National ASAS meeting.  Baltimore, MD, USA. https://asas.confex.com/asas/annual17/webprogram/Paper21804.html

16. Koltes J.E. 2017. Automated collection of heat stress data in livestock: new technologies and opportunities.  Proc. Of the National ASAS meeting.  Baltimore, MD, USA. https://asas.confex.com/asas/annual17/webprogram/Paper22174.html

15. Tsai T.C., M.A. Sales, D.A. Koltes, C. Maxwell, and J.E. Koltes.  2017. Differential gene expression in peripheral mononuclear cells of pigs exposed to topsoil in early life.  Proc. Of the National ASAS meeting.  Baltimore, MD, USA.  https://asas.confex.com/asas/annual17/webprogram/Paper21763.html

14. Cesar A.S.M., Regitano L.C.A., Poleti M.D., Oliveira G.B., Oliveira P.P.N., Koltes J.E., Fritz-Waters E., Reecy J.M. and L.L. Coutinho. 2017. MiRNA expression quantitative trait loci (eQTL-miRNA) regions identified in whole Nellore steers genome.  Proceedings of the 36th International Society of Animal Genetics.  Dublin, Ireland.

13. Koltes D.A., Chewning S.K., Powell J.G., Meyer L.M., Tucker J., Hubbell, III D.S., and J.E. Koltes. 2017.  In search of novel phenotypes and biomarkers associated with tall fescue and heat tolerance in crossbred beef cattle.  Proc. of Plant and Animal Genome XXV.  San Diego, CA, USA.  https://pag.confex.com/pag/xxv/webprogram/Paper26539.html

12. Fritz-Waters E.R., Reecy J.M., and J.E. Koltes. 2017.  Facilitating comparative functional genomics through data reuse with livestock EpiDB.  Proc. of Plant and Animal Genome XXV.  San Diego, CA, USA.  https://pag.confex.com/pag/xxv/webprogram/Paper25740.html

11. Bao H., Kommadath A., Choi I., Reecy J.M., Koltes J.E., Fritz-Waters E., Eisley C, Rowland R.R.R., Tuggle C.K., Dekkers J.C.M., Guan L., Stothard P., Plastow. G.S., and J.K. Lunney.  2016.  Associations between cis-expression quantitative trait loci (cis-eQTL) markers and host response to porcine reproductive and respiratory syndrome virus (PRRS) infection.  Proceedings of the International Veterinary Immunology Symposium.  Gold Coast, Australia.  

10. Koltes, J.E., Reecy J.M., Lyons E., McCarthy, F., Vaughn M., Carson J.P., Fritz-Waters E., and Williams J. 2016.  Bioinformatics resources for animal genomics using CyVerse cyberinfrastructure.  Proceedings of the 35th International Society of Animal Genetics.  Salt Lake City, USA.    http://www.isag.us/docs/Proceedings/ISAG_Proceedings_2016.pdf

9. Fritz-Waters E., Reecy J.M., Vaughn M., Carson J.P., and Koltes, J.E., 2016.  Mining functional genomics and epigenetics data with livestock EpiDB.  Proceedings of the 35th International Society of Animal Genetics.  Salt Lake City, USA.   http://www.isag.us/docs/Proceedings/ISAG_Proceedings_2016.pdf

8. Seibert J.T., Boddicker R.L., Koltes J.E., Nettleton D., Reecy J.M., Baumgard L.H., Ross J.W.  2016. Alterations in CpG Methylation as a result of prenatal heat stress exposure in pigs.   Proceedings of the Society for the Study of Reproduction meeting.  San Diego, CA, USA.

7. Koltes, J.E., Fritz-Waters E., and Reecy J.M.  2016.  Differential expression of small RNAs and mRNAs in bovine skeletal muscle with extreme saturated fatty acid levels.  Proc of Plant and Animal Genome XXIV.  San Diego, CA, USA.  https://pag.confex.com/pag/xxiv/webprogram/Paper21440.html

6. Koltes, J.E., Fritz-Waters E., and Reecy J.M.  2016.  EpiDB: an omics data resource for cattle.  Proc of Plant and Animal Genome XXIV.  San Diego, CA, USA.      https://pag.confex.com/pag/xxiv/webprogram/Paper21766.html

5. Cesar A. S. M., Regitano L. C. A., Lanna D.P.D., Poleti M.D., Koltes, J.E, Reecy J. M., Fritz-Waters, E. R., Kramer L., Garrick D., Mudadu M.A., Tullio R.R., and Coutinho, L. L.  2016.  Expression quantitative trait loci (eQTL) hotspot regions from whole genome analysis of Nellore steers.  Proc of Plant and Animal Genome XXIV.  San Diego, CA, USA.     https://pag.confex.com/pag/xxiv/webprogram/Paper18847.html

4. The FAANG Bioinformatics & Data Analysis Consortium. 2015. Towards common standardized procedures for the Functional Annotation of Animal Genomes (FAANG).  Proceedings of the Gathering on Functional Annotation of Animal Genomes (GO-FAANG) workshop.  Washington D.C., USA.     

3. Koltes, J.E., Fritz-Waters E., and Reecy J.M.  2015.  Livestock EpiDB: A resource for mining functional NGS data.  Proceedings of the Gathering on Functional Annotation of Animal Genomes (GO-FAANG) workshop.  Washington D.C., USA.

2. Schroyen, M., Eisley C.J., Koltes J.E. , Fritz-Waters E., Choi I., Plastow G.S., Guan L.L., Stothard P., Reecy J.M., Lunney J.K., Rowland R.R.R., Dekkers J.C.M., and Tuggle C.K.  2015.  Bioinformatic analyses of early host response to Porcine Reproductive and Respiratory Syndrome (PRRS) virus reveals pathway differences between pigs with alternate genotypes for a major host response QTL. Proc of the 2015 North American PRRS Symposium.  

1. Cesar A. S. M., Regitano L. C. A., Lanna D.P.D., Poleti M.D., Andrade S.C.S., do Nascimento M.L., Chaves A.S., Koltes, J.E, Reecy J. M., Fritz-Waters, E. R., Tullio R.R., and Coutinho, L. L.  2015.  Functional annotation of Logissimus dorsi transcriptome muscle with extreme values of oleic acid content.  Proceedings of the Next Generation Sequencing USA Congress and co-located Single Cell Genomics & Transcriptomics USA Congress. Boston, MA, USA.

SELECTED INDUSTRY REPORTS 

5. Koltes JE and Siberski-Cooper CJ. Sensors could send feed efficiency to the next stratosphere. 2022 Hoard’s Dairyman July 2022 p353.

4. Parker Gaddis K. L,.  P. M. VanRaden, R. J. Tempelman, K. A. Weigel, H. M. White, F. Peñagaricano, J. E. Koltes, J. E. P. Santos, R. L. Baldwin, J. F. Burchard, J. W. Dürr, and M. J. VandeHaar. 2021.  Implementation of Feed Saved evaluations in the US.  Interbull Bulletin No. 44 Leeuwarden, The Netherlands, April 26-30, 2021

3. Christensen A, Cooper D, Fourdraine R, Griffiths B, Mathis C, Koltes J, Quick A, and M Utts. Farming out data-driven decisions. Hoard’s Dairyman March 25, 2020 p. 185. Written as part of the Virtual Dairy Brain Coordinated Innovation Network advisory group for the corresponding USDA NIFA project.

2. Su H., J.E. Koltes, and D. Garrick. 2016. Evaluating sequence-based customized SNP in addition to GeneSeek LD chip for predicting birth weight in beef cattle.  Iowa State University Animal Industry Report.

1. Flemming, D.S., J.E. Koltes, A.D. Markey, C.J. Schmidt, C.M. Ashwell, M.F. Rothschild, M.E. Persia, J.M. Reecy and S.J. Lamont.  2015.  Genomes of African chickens show evolutionary response to environmental stress.  Iowa State University Animal Industry Report.

*Indicates co-first authorship


Popular Press articles related to Dr. Koltes's research area

Discussion on opportunities to use genetics to improve Dairy Beef.  DocTalk online Nov 30, 2021 (aired at a later date on RFDTV and online: https://www.youtube.com/watch?v=OvwI1waevL8

Precision Technologies as a tool to predict feed intake/efficiency.  ISU Dairy Extension Webinar online Apr. 12, 2021. https://www.youtube.com/watch?v=BiUZqEhkzSw

What’s new in the December 2020 Dairy Genetic Evaluations.  ISU Dairy Extension Monthly Webinar. (virtual presentation: December 8, 2020) https://www.youtube.com/watch?v=AaQKPmM5my4

http://pbcommercial.com/news/area-digest/early-shedding-correlates-better-cattle-breeding-performance-experts-say

https://www.nersc.gov/news-publications/nersc-news/science-news/2016/researchers-use-edison-to-improve-performance-energy-efficiency-of-bioinformatics-application/

http://www.progressivecattle.com/topics/reproduction/7682-now-s-the-time-to-assess-your-breeding-goals

http://www.mafg.net/NewsDetail.aspx?NewsID=5053&utm_source=March+17%2C+2017+issue+11&utm_campaign=17-11+enewsletter&utm_medium=email

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