Matt Spangler

Photo of Matt Spangler
Areas of Expertise
Beef Cattle
Breeding & Genetics
Extension

Matt Spangler Professor
Beef Genetics Specialist

Appointment:
60% Extension, 10% Teaching, 30% Research (2015-present)
60% Extension, 20% Teaching, 20% Research (2012-2015)
70% Extension, 30% Teaching (2008-2012)

Research Interests:
New trait development
Combining molecular and quantitative information for genetic prediction
Genotyping strategies

Teaching Experience:
Primary Instructor, The University of Nebraska, January 2008 – Present.
Beef Cattle Merchandising (8 semesters)
Beef Industry Scholars: Study Tour (8 semesters)
Linear Models in Animal Breeding (5 semesters; online)
History and Perspectives in Animal Breeding (4 semesters; online)

Other Teaching Activities
UNL Teaching Herd Coordinator, January 2008 – Present
Nebraska Beef Industry Scholars Program Coordinator, January 2008-Present
Current Undergraduate Advisees: 7
Graduate Committees (Current): Ph.D.=2
Graduate Committees (Completed): M.S. =3
Graduate Committees (Completed): Ph.D. =3
Graduate Student Advisor (Current): M.S.=3; MAS=1;PhD=2
Graduate Student Advisor (Completed): M.S.=3
Undergraduate Honors Thesis Advisor (Completed)=1
Visiting Scholars: Current = 1; Completed=1
Postdoctoral Students: Current=1

Biographical Data

Education
2003 - 2006; The University of Georgia, Ph.D. 2006
2001 - 2003; Iowa State University, M.S. 2003
1999 - 2001; Kansas State University, B.S. 2001
1997 - 1999; Butler County Community College, A.S. 1999

Employment History
Professor of Animal Science/Extension Beef Genetics Specialist, University of Nebraska-Lincoln (2018-present)
Associate Professor of Animal Science/Extension Beef Genetics Specialist, University of Nebraska-Lincoln (2012-2018)
Assistant Professor of Animal Science/Extension Beef Genetics Specialist, University of Nebraska-Lincoln (2008-2012)
Assistant Professor of Animal Science, University of Tennessee at Martin (2007)

Honors and Awards Received
Cattlemen Business Weekly, Top 10 Beef Industry Leaders Under 40. 2011.
Outstanding New Specialist, Nebraska Cooperative Extension Association, 2011.
Holling Family Junior Faculty Teaching Award, UNL College of Agriculture and Natural Resources, 2012.
Wendell Burgher Beef Industry Award, UNL Institute of Agriculture and Natural Resources, 2013-2015.
Nebraska Beef Industry Endowment Award, Nebraska Cattlemen Research and Education Foundation, 2013 & 2014.
Beef Improvement Federation Appreciation Award, Beef Improvement Federation, 2014.
Outstanding Young Extension Specialist Award, Midwest American Society of Animal Science, 2015.
Beef Improvement Federation Continuing Service Award, Beef Improvement Federation, 2017.
Gamma Sigma Delta Award for Excellence in Extension, UNL Gamma Sigma Delta, 2018.

Professional and Honorary Societies
American Society of Animal Science (ASAS)
Gamma Sigma Delta
Nebraska Cattlemen

Honors and Awards of Graduate Students Under My Direction
BIF Roy Wallace Scholarship (2018)
Larrick/Whitmore Travel Scholarship, UNL, 2012 (1), 2014 (2), 2016 (1), 2018 (1)
UNL Graduate College Travel Grant, 2016.
Frank Baker Memorial Essay Contest, Beef Improvement Federation, 2012, 2016 (2).
Shear Miles Fellowship, UNL Institute of Agriculture and Natural Resources, 2012.
Gamma Sigma Delta, inducted for membership, 2012 (1), 2016 (1), 2017 (1).
BIF Reg. Scholarship, 2013 (2)
American Association of Animal Science Annual Meeting Presidents Pick Abstract, 2013.

Referred Journals
In the following list of publications a '*' indicates that the publication was a collaboration with a current or former undergraduate, graduate, or post-doctoral student.

1. Sapp, R. L., M. L. Spangler, R. Rekaya, and J. K. Bertrand. 2005. A simulation study for analysis of uncertain binary responses: Application to first insemination success in beef cattle. Genet. Sel. Evol. 37:615-634.
2. Spangler, M. L., R. L. Sapp, R. Rekaya, and J. K. Bertrand. 2006. Success at first insemination in Australian Angus cattle: Analysis of uncertain binary responses. J. Anim. Sci. 84:20-24.
3. Spangler, M. L., J. K. Bertrand, and R. Rekaya. 2007. Combining molecular test information and correlated phenotypic records for breeding value estimation. J. Anim. Sci. 85:641-649.
4. Spangler, M. L., R. L. Sapp, M. D. MacNeil, J. K. Bertrand, and R. Rekaya. 2008. Different methods of selecting animals for genotyping to maximize the amount of genetic information known in the population. J. Anim. Sci. 86:2471-2479.
5. Spangler, M. L., K. R. Robbins, M. D. MacNeil, J. K. Bertrand, and R. Rekaya. 2009. Ant colony optimization as an alternative method for genotype sampling. Anim. Genetics 40: 308-314.
6. Kachman, S.D., M. L. Spangler, G. L. Bennett, K. J. Hanford, L. A. Kuehn, W. M. Snelling, R. M. Thallman, M. Saatchi, and D. J. Garrick, R.D. Schnabel, J.F. Taylor, and E. J. Pollak. 2013. Comparison of molecular breeding values based on within- and across-breed training in beef cattle. Genetics Sel. Evol. 45:30.
7. Tart, J.K., R.K. Johnson, J.W. Bundy, N.N. Ferdinand, J.R. Wood, A.M. McKnite, P.S. Miller, M.F.R. Rothschild, M.L. Spangler, D.J. Garrick, S.D. Kachman, and D.C. Ciobanu. 2013. Genome-wide prediction of age at puberty and reproductive longevity in sows. Anim. Genetics 44: 387-397.
8. Howard*, J.T, S. D. Kachman, M.K. Nielsen, T. L. Mader, and M. L. Spangler. 2013. The effect of Myostatin genotype on body temperature during extreme temperature events. J. Anim. Sci. 91: 3051-3058.
9. Howard*, J.T., S. D. Kachman, W.M. Snelling, E.J Pollak, D. C. Ciobanu, L. A. Kuehn, and M. L. Spangler. 2014. Beef cattle body temperature during climatic stress: A genome wide association study. International J. Biometeorology 58:1665:1672.
10. Alhberg*, C.M., L. N. Schiermiester*, J. T. Howard*, C. Calkins, and M.L. Spangler. 2014. Genome wide association study of cholesterol and poly- and mono-unsaturated fatty acids, protein, and mineral content of beef from crossbred cattle. Meat Sci. 98: 804-814.
11. Mahdi Saatchi, Jonathan E Beever, Jared E. Decker, Dan B. Faulkner, Harvey C Freetly, Stephanie L Hansen, Helen Yampara-Iquise, Kristen A Johnson, Stephen D Kachman, Monty S Kerley, JaeWoo Kim, Daniel D Loy, Elisa Marques, Holly L Neibergs, E John Pollak, Robert D Schnabel, Christopher M Seabury, Daniel W Shike, Warren M Snelling, Matthew L Spangler, Robert L Weaber, Dorian J Garrick and Jeremy F Taylor. 2014. QTL, candidate genes, metabolic and signaling pathways associated with growth, metabolic mid-test weight, feed intake and feed efficiency in beef cattle. BMC Genomics 15:1004.
12. Chandrasekhar Natarajan, Federico G. Hoffmann, Hayley C. Lanier, Zachary A. Cheviron, Matthew L. Spangler, Roy E. Weber, Angela Fago, and Jay F. Storz . 2015. Intraspecific Polymorphism, Interspecific Divergence, and the Origins of Function-Altering Mutations in Deer Mouse Hemoglobin. Mol. Bio. Evol. 32: 978-997.
13. Schiermiester*, L.N., R.M. Thallman, L.A. Kuehn, S.D. Kachman, and M.L. Spangler. 2015. Estimation of breed-specific heterosis effects for birth, weaning and yearling weight in cattle. J. Anim. Sci. 93: 46-52. (One of the top 10 cited articles in JAS in 2015).
14. Lucot, K.L., M.L. Spangler, M.D. Trenhaile, S.D. Kachman, and D.C. Ciobanu. 2015. Evaluation of reduced subsets of Single Nucleotide Polymorphisms for the prediction of age at puberty and reproductive longevity in sows. Anim. Genetics 46:403-409.
15. Boyd, B. M., S.D. Shackelford, K.E. Hales, T.M. Brown-Brandl, M.L. Bremer, M.L. Spangler, T. L. Wheeler, D. King, and G.E. Erickson. 2015. Effects of shade and feeding zilpaterol hydrochloride to finishing steers on performance, carcass quality, heat stress, mobility, and body temperature. J. Anim. Sci. 93:5801-5811.
16. Ahlberg*, C.M., L.A. Kuehn, R.M. Thallman, S.D. Kachman, W.M. Snelling, and M.L. Spangler. 2016. Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multi-breed population. J. Anim. Sci. 94: .1857-1864.
17. Torres-Vázquez*, J.A., and M.L. Spangler. 2016. Genetic parameters for docility, weaning weight, yearling weight and intramuscular fat percentage in Hereford cattle. J. Anim. Sci. 94:21-27.
18. Seabury, C.M., D.L. Oldeschulte, M. Saatchi, J.E. Beever, J.E. Decker, Y.A. Halley, E.K. Bhattarai, M. Molaei, H.C. Freetly, S.L. Hansen, H. Yampara-Iquise, K.A. Johnson, M. S. Kerley, J. Kim, D.D. Loy, E. Marques, H.L. Neibergs, R. D. Schnabel, D.W. Shike, M.L. Spangler, R.L. Weaber, D.J. Garrick, and J.F. Taylor. 2017. Genome-Wide Association Study For Feed Efficiency and Growth Traits in U.S. Beef Cattle. BMC Genomics 18:386.
19. Ochsner*, K.P., M.D. MacNeil, R.M. Lewis, and M.L. Spangler. 2017. Economic selection index development for Beefmaster cattle I: Terminal breeding objective. J. Anim. Sci. 95:1063-1070.
20. Ochsner*, K.P., M.D. MacNeil, R.M. Lewis, and M.L. Spangler. 2017. Economic selection index development for Beefmaster cattle II: General-purpose breeding objective. J. Anim. Sci. 95:1913-1920.
21. Wijesena, H., C.A. Lents, Jean-Jack Riethoven, M. Trenhaile-Grannemann, J. Thorson, B. Keel, P. Miller, M.L. Spangler, S.D. Kachman, and D. Ciobanu. 2017. GENOMICS SYMPOSIUM: Using Genomic Approaches to Uncover Sources of Variation in Age at Puberty and Reproductive Longevity in Sows. J. Anim. Sci. 95 4196-4205
22. Lee*, J., S. D. Kachman, and M. L. Spangler. 2017. The impact of training strategies on the accuracy of genomic predictors in U.S. Red Angus cattle. J. Anim. Sci. 95:3406-3414.
23. Yu, Haipeng, Matthew L. Spangler, Ronald M. Lewis, and Gota Morota. 2017. Genomic relatedness strengthens genetic connectedness across management units. G3. 7:3543-3556.
24. He, Jun, Jiaqi Xu, Xiao-Lin Wu, Stewart Bauck, Jungjae Lee, Gota Morota, Stephen D. Kachman, and Matthew L. Spangler. 2018. Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins. Genetica. 146:137-149.
25. Paz, Henry A., Kristin E. Hales, James E. Wells, Larry A. Kuehn, Harvey C. Freetly, Elaine D. Berry, Michael D. Flythe, Matthew L. Spangler, and Samodha C. Fernando. 2018. Rumen bacterial community structure impacts feed efficiency in beef cattle. J. Anim. Sci. 96:1045-105.
26. Speidel, S.E., B. A. Buckley, R. J. Boldt, R. M. Enns, J. Lee, M. L. Spangler, M. G. Thomas. 2018. Genome wide association study of Stayability and Heifer Pregnancy in Red Angus Cattle. J. Anim. Sci. 96:846-853.
27. Schweer*, K.R., S.D. Kachman, L.A. Kuehn, H.C. Freetly, E.J. Pollak, and M.L. Spangler. 218. Genome-wide association study for feed efficiency traits using SNP and haplotype models. J. Anim. Sci. 96:2086-2098.
28. Howard*, J.T., T. A. Rathje, C. E. Bruns, D. F Wilson-Wells, S. D. Kachman, and M. L. Spangler. 2018. The impact of truncating data on predictive ability for single-step genomic best linear unbiased prediction. J. Anim. Breed. and Genetics (accepted)
29. Rovadoscki, G.A., S. F. N. Pertille, A. B. Alvarenga, A. S. M. Cesar, F. Pértille, J. Petrini, Vamilton Franzo, G. Morota, M. L. Spangler, L. F. B. Pinto, G. G. P. Carvalho, D. P. D. Lanna, L. L. Coutinho, and G. B. Mourão. 2018. Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês Sheep. BMC Genomics 19:375.
30. Alvarenga, Amanda Botelho, Gregori Alberto Rovadoscki, Juliana Petrini, Luiz Lehmann Coutinho, Gota Morota, Matthew L. Spangler, Luís Fernando Batista Pinto, Gleidson Giordano Pinto de Carvalho, and Gerson Barreto Mourão. 2018. Linkage disequilibrium in Brazilian Santa Inês breed, Ovis aries. Sci. Rep. 8:8851.
31. Yu, Haipeng, Matthew L. Spangler, Ronald M. Lewis, and Gota Morota. 2018. Do stronger measures of genomic connectedness enhance prediction accuracies across management units? J. Anim. Sci. (accepted)
32. Howard*, J.T., T. A. Rathje, C. E. Bruns, D. F Wilson-Wells, S. D. Kachman, and M. L. Spangler. 2018. The impact of selective genotyping on the response to selection using single-step genomic best linear unbiased prediction. J. Anim. Sci. (accepted)