Brief Summary of Minutes of Annual Meeting

NCERA-225: Implementation and Strategies for National Beef Cattle Genetic Evaluation

Business Meeting November 1, 2022 via Zoom

Chair: Dr. Brittney Keel

Secretary: Dr. Cedric

The meeting was called to order by chair Brittney Keel at 4:18 PM on Tuesday, November 1, 2022.

Administrative Advisor Dr. Joe Cassady made the announcement that he had been approached by USDA to continue in his supervisory role and that he was happy to do so. He highlighted that objectives for the group should continue to be the same: working together within the group and building additional collaborations.

Dr. Brittney Keel announced that the project has been renewed for another 5 years and that members need to be sure to go to the NIMSS website and update participation. She announced that she would be needing station reports to put together the annual report.

Dr. Cedric Gondro offered to host the NCERA-225 meeting at Michigan State University in 2023, and Dr. Daniela Lourenco volunteered to be secretary. By unanimous decision, Dr. Cedric Gondro was elected chairperson and Dr. Daniela Lourenco was elected secretary.

Attendees present at the business meeting were: Brittney Keel (USMARC), Mark Thallman (USMARC), Warren Snelling (USMARC), Larry Kuehn (USMARC), Cedric Gondro (Michigan State Universoty), Jenny Bormann (Kansas State University), Daniela Lourenco (University of Georgia), and Ryan Boldt (IGS).

Meeting adjourned at 4:37 PM.

Accomplishments

Objective 1: Provide a venue for the discussion and exchange of information for the many disconnected and diverse research activities--biological, genomic, statistical, computational, and economical--that support National Cattle Evaluation (NCE).

• The previous NCERA-225 meeting was held virtually in December 2021. The 2022 meeting, held virtually on November 1, 2022, covers the timeframe from the January through December 2022. Efforts were made to hold the meeting in-person, but continued travel restrictions due to COVID-19 did not make that possible for many members. Therefore, the meeting was held virtually to ensure adequate attendance.
• During the reporting period, members of the group were active in NBCEC, the NBCEC Brown Bagger Series, and the BIF board and annual meeting.
• This committee’s meeting is one of the only places where leaders in the area of genetic evaluation in the beef industry meet on an annual basis. The most pioneering methods and technologies are discussed and debated. Ideas from the meeting help inform research priorities and activities for the coming year.
• Training of the next generation of producers and scientists is critical for advancements in the field of genetic evaluation. Committee members were involved in teaching activities such as undergraduate curriculum and graduate student training in addition to outreach to producer groups.

Objective 2: Develop through this exchange new tools for delivery and use of beef cattle genetic research, including genomic information, to beef breed associations and beef cattle producers.

• The 2022 NCERA-225 annual meeting provided in-depth discussion on new avenues for development of new traits and tools for selection.
• Continued collaborations between committee members as well as beef breed associations and genetic evaluation groups have led to enhanced single breed evaluations as well as development of prototype multi-breed genetic evaluations with genomic enhancement. Specific examples include:
• USMARC and UNL members collaborate on applying results from low-pass genomic sequencing to problems in cattle evaluation programs.
• USMARC and UNL members estimated genetic parameters, heterosis, and breed effects for body condition score and mature cow weight to parameterize a multi-breed evaluation for these traits. IGS is currently prototyping this evaluation.
• CSU and USMARC members collaborated on pooled genotyping for late feedlot death due to heart failure to determine genetic susceptibility and inheritance.
• USMARC and CSU collaborated in initial stages to develop methods for recording variable methane emissions and grazing behaviors in beef cattle.
• UNL and USMARC members collaborated to test a multi-variate framework for genetic evaluation using pooled data.
• Committee members continue to collaborate on the development of genetic understanding and/or EPDs for novel traits, including early indicators for longevity; muscle and meat quality; biomarkers for traits such as BRD susceptibility, RFI, and temperament; software and data pipelines for improved genomic investigations; characterization of major histology complexes in cattle; effects of climate on genetic evaluations; among other traits.

Objective 3: Update the beef cattle industry on current developments in beef breeding and genetics research including changes in genomics tools and analyses.

• Committee members R. Weaber and M. Spangler led the 2022 Brown Brown Bagger Series of webinars to provide education content to county, district, regional and state extension educators and breed association technical staff on new and emerging issues/developments in beef cattle genetic evaluation. This series is nationally known for its educational content. The 2022 series featured committee member S. Speidel. The series recordings and agenda is available here: http://www.nbcec.org/professionals/brownbag.html
• Committee members M. Spangler, R. Weaber, M. Rolf, and J. Decker collaborate with other researchers to maintain and expand the availability of beef genetics extension materials available online at eBEEF.org .
• A wide range of committee members interface beef producers and various organization involved in selection and genetic improvement via presentations, symposia or trade publications. A list of those are included is included with the annual report (see publications – abstracts and proceedings as well as presentations sections).

Objective 4: Collaborate with appropriate groups (e.g. BIF and USDA/NIFA funded integrated projects) on research and outreach.

• A number of committee members are routinely engaged in genetic evaluation system development and deployment for various breed associations. This engagement leads to the direct incorporation of novel research and development into national cattle evaluation systems.
• Several committee members serve on the BIF board of directors: M. Rolf, M. Enns, M. Spangler, R. Weaber, and W. Snelling.
• Committee members B. Golden, L. Kuehn, M. Spangler, M. Thallman, R. Weaber, and W. Snelling completed testing of iGENDEC software to enable customizable economic index construction and are now working with BIF to implement the package.

Impacts

1. Committee members published 33 peer reviewed articles as part of their own research or as co-authors by supporting research stations outside this group.
2. Research efforts were communicated through 37 published abstracts or proceedings at various conferences, domestically and internationally, thereby supporting graduate education and/or disseminating their own expertise to stations outside the group on topics of cattle evaluation.
3. Continued and new collaborations among committee members as well as stations outside of this group will result in enhanced knowledge for breed associations to implement genetic evaluations.
4. Graduate and undergraduate training relative to quantitative genetics and beef cattle evaluations will ensure future research and improvements for cattle producers can occur in genetic evaluations.

Publications

Peer reviewed

1. Abdollahi-Arpanahi, R., D. Lourenco, and I. Misztal. (2022) A comprehensive study on core size and type on prediction accuracy of algorithm of proven and young in single-step GBLUP evaluation. Genet Sel Evol 54:34. doi: 10.1186/s12711-022-00726-6.
2. Aherin, D.G., R.L. Weaber, D.L. Pendell, J.L. Heier Stamm and R.L. Larson. (2022) Stochastic, individual-based systems model of beef cow-calf production: model development and validation. Transl Anim Sci. doi: 10.1093/tas/txac155.
3. Baller, J.L., S.D. Kachman, L.A. Kuehn, and M.L. Spangler. (2022) Using pooled data for genomic prediction in a bivariate framework with missing data. J Anim Breed Genet 139(5):489-501. doi: 10.1111/jbg.12727.
4. Bermann, M., D. Lourenco, and I. Misztal. (2022) Efficient approximation of reliabilities for single-step genomic BLUP models with the Algorithm for Proven and Young. J Anim Sci 100(1):skab353. doi: 10.1093/jas/skab353.
5. Bermann, M., D. Lourenco, N. Forneris, A. Legarra, and I. Misztal. (2022) On the equivalence between marker effect models and breeding value models and direct genomic values with the Algorithm for Proven and Young. Genet Sel Evol 54:52. doi: 10.1186/s12711-022-00741-7.
6. Bermann, M., A. Cesarani, I. Misztal, and D. Lourenco. (2022) Past, present, and future developments in single-step genomic models. Italian J Anim Sci 21(1):673-685. doi: 10.1080/1828051X.2022.2053366.
7. Butler, M., A.R. Hartman, J. Bormann, R.L. Weaber, D. Grieger, and M.M. Rolf. (2021) Genetic parameter estimation of beef bull semen attributes. J Anim Sci 99(2):skab013. doi: 10.1093/jas/skab013.
8. Butler, M., A.R. Hartman, J. Bormann, R.L. Weaber, D. Grieger, and M.M. Rolf. (2022) Genome wide association study of beef bull semen attributes. BMC Genomics 23:74. doi: 10.1186/s12864-021-08256-z.
9. Campos, G.S., F.F. Cardoso, C.C.G. Gomes, R. Domingues, L.C.A. Regitano, M.C.S. Oliveira, H.N. Oliveira, R. Carvalheiro, L.G. Albuquerque, S. Miller, I. Misztal, and D. Lourenco. (2022) Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related American sires. J Anim Sci 100(2):skac009. doi: 10.1093/jas/skac009.
10. Flesch, E., T. Graves, J. Thomson, K. Proffitt, and R. Garrott. (2022) Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks. Ecosphere 13(3):e3972. doi: 10.1002/ecs2.3972.
11. Garcia, A., I. Aguilar, A. Legarra, S. Miller, S. Tsuruta, I. Misztal, and D. Lourenco. (2021) Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genet Sel Evol 54:66. doi: 10.1186/s12711-022-00752-4.
12. Giess, L.K., B.R. Jensen, J.M. Bormann, M.M. Rolf, and R.L. Weaber. (2021) Genetic parameter estimates for feet and leg traits in Red Angus cattle. J Anim Sci 99(11): skab256. doi: 10.1093/jas/skab256.
13. Han, J., J. Siegford, G. de los Campos, R.J. Tempelman, C. Gondro, and J.P. Steibel. (2022) Analysis of social interactions in group-housed animals using dyadic linear models. Appl Anim Behav Sci 256:105747. doi: 10.1016/j.applanim.
14. Hay, E.A., S. Toghiani, A.J. Roberts, T. Paim, L.A. Kuehn, and H.D. Blackburn. (2022)

Genetic architecture of a composite beef cattle population. J Anim Sci 2022. Article 230. doi: 10.1093/jas/skac230.

15. Heaton, M.P., G.P. Harhay, A.S. Bassett, H.J. Clark, J.M. Carlson, E.E. Jobman,

H.R. Sadd, M.C. Pelster, A.M. Workman, L.A. Kuehn, T.S. Kalbfleisch, H. Piscatelli, M. Carrie, G.M. Krafsur, D.M. Grotelueschen, and B.L. Vander Ley. (2022) Association

of ARRDC3 and NFIA variants with bovine congestive heart failure in feedlot cattle.

F1000Research. 11. Article 385. doi: 10.12688/f1000research.109488.1.

16. Hille, M.M., M.L. Spangler, M.L. Clawson, K.D. Heath, H.L.X. Vu, R.E.S. Rogers, and J.D. Loy. (2022) A five year randomized controlled trial to asses the efficacy and antibody responses to a commercial and autogenous vaccine for the prevention of bovine keratoconjunctivitis. Vaccines 10:916. doi: 10.3390/vaccines10060916.
17. Holder, A.L., M.A. Gross, A.N. Moehlenpah, C.L. Goad, M.M. Rolf, R.S. Walker, J.K. Rogers, and D.L. Lalman. (2022) Effects of diet on feed intake, weight change, and gas emissions in mature Angus cows. J Anim Sci 100(10):1-9. doi: 10.1093/jas/skac257.
18. Hollifield, M.K., M. Bermann, D. Lourenco, and I. Misztal. (2022) Impact of blending the genomic relationship matrix with different levels of pedigree relationships or the identity matrix on genetic evaluations. J Dairy Sci Comm. doi: 10.3168/jdsc.2022-0229.
19. Jang, S., D. Lourenco, S. Miller. (2022) Inclusion of Sire by Herd interaction effect in the genomic evaluation for weaning weight of American Angus. J Anim Sci 100(3):skac057. doi: 10.1093/jas/skac057.
20. Junqueira, V.S., D. Lourenco, Y. Masuda, F.F. Cardoso, P.S. Lopes, F.F. Silva, and I. Misztal. (2022) Is single-step genomic REML with algorithm for proven and young more efficient when less generations of data are present? J Anim Sci 100(5):skac082. doi: 10.1093/jas/skac082.
21. LaKamp, A.D., R.L. Weaber, J.M. Bormann, and M.M. Rolf. (2022) Relationships between enteric methane production and economically important traits in beef cattle. Livest Sci 265 (2022):105102. doi: 10.1016/j.livsci.2022.105102.
22. McWhorter, T.M., M. Bermann, A.L.S. Garcia, A. Legarra, I. Aguilar, I. Misztal, and D. Lourenco. (2022) Implication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP. J Anim Breed Genet 140(1):60-78. doi: 10.1111/jbg.12734.
23. Misztal, I., Y. Steyn, and D. Lourenco. (2022) Genomic evaluation with multibreed and crossbred data. JDS Comm 3(2):156-159. doi: 10.3168/jdsc.2021-0177.
24. Nawaz, M.Y., P.A. Bernardes, R.P. Savegnago, D. Lim, S.H. Lee, and C. Gondro. (2022) Evaluation of whole-genome sequence imputation strategies in Korean Hanwoo cattle. Animals 12:2265. doi: 10.3390/ani12172265.
25. Ribeiro, A.M.F., L.P. Sanglard, W.M. Snelling, R.M. Thallman, L.A. Kuehn, and M.L. Spangler. (2022) Genetic parameters, heterosis, and breed effects for body condition score and mature cow weight in beef cattle. J Anim Sci 100:skac017. doi: 10.1093/jas/skac017.
26. Ribeiro, A.M.F., L.P. Sanglard, H.R. Wijesena, D.C. Ciobanu, S. Horvath, and M.L. Spangler. (2022) DNA methylation profile in beef cattle is influenced by additive genetics and age. Sci Reports 12:12016. doi: 10.1038/s41598-022-16350-9.
27. Sanglard, L.P., L.A. Kuehn, W.M. Snelling, and M.L. Spangler. (2022) Influence of environmental factors and genetic variation on mitochondrial DNA copy number. J Anim Sci 100(5):skac059. doi: 10.1093/jas/skac059.
28. Schumacher, M., H. DelCurto-Wyffels, J. Thomson, and J. Boles. (2022) Fat deposition and fat effects on meat quality—a review. Animals 12(12):1550. doi: 10.3390/ani12121550.
29. See, G.M., J.S. Fix, C.R. Schwab, and M.L. Spangler. (2022) Imputation of non-genotyped F₁ dams to improve genetic gain in swine crossbreeding programs. J Anim Sci 100:skac148. doi: 10.1093/jas/skac148.
30. Seo D., D.H. Lee, S. Jin, J.I. Won, D. Lim, M. Park, T.H. Kim, H.K. Lee,S. Kim, I. Choi, J.H. Lee, C. Gondro, and S.H. Lee. (2022) Long-term artificial selection of Hanwoo (Korean) cattle left genetic signatures for the breeding traits and has altered the genomic structure. Sci Reports 12:6438. doi: 10.1038/s41598-022-09425-0.
31. Silva, T.L., C. Gondro, P.A.S. Fonseca, D.A. da Silva, G. Vargas, H.H.R. Neves, I. Carvalho Filho, C.S. Teixeira, L.G. Albuquerque, and R. Carhalheiro. (2022) Testicular hypoplasia in Nellora cattle: genetic analysis and functional analysis of genome-wide association study results. J Anim Breed Genet. doi: 10.1111/jbg.12747.
32. Singh, A., A. Kumar, C. Gondro, A.K. Pandey, T. Dutt, and B.P. Mishra. (2022) Genome wide scan to identify potential genomic regions associated with milk protein and minerals in Vrindavani cattle. Front Vet Sci 9:760364. doi: 10.3389/fvets.2022.760364.
33. Snelling, W.M., R.M. Thallman, M.L. Spangler, and L.A. Kuehn. (2022) Breeding sustainable beef cows. Animals 12:1745. doi: 10.3390/ani12141745.

Abstracts and proceedings

1. Abdollahi Arpanahi, R., D. Lourenco, and I. Misztal. 2022. Investigating the impact of APY core size and definition in single-step GBLUP evaluations. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
2. Bermann, M., A. Cesarani, D. Lourenco, and I. Misztal. 2022. Young Scholar Award Talk: Computing Strategies for National Beef Cattle Evaluations. American Society of Animal Science Annual Meeting, Oklahoma City, OK.
3. Bermann, M., D. Lourenco, A. Cesarani, and I. Misztal. 2022. ACCF90GS2: software for fast approximation of reliabilities of estimated breeding values in single-step GBLUP. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
4. Bermann, M., I. Misztal, D. Lourenco, I. Aguilar, and A. Legarra, A. 2022. Definition of reliabilities for models with metafounders. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
5. Bullock, K.D., M.L. Spangler, R.L. Weaber, T.N. Rowan, M.M. Rolf, J.E. Decker, D.D. Loy, B.L. Golden, J.J. White and A.L. Van Eenennaam. 2022. Conducting a National Beef Cattle Genetics Outreach Program. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
6. Campos, G.S., D.A. Silva, H.H.R. Neves, D. Lourenco, G.A.F. Júnior, L.F.S. Fonseca, L.G. Albuquerque, and R. Carvalheiro. 2022. Including selected sequence variants in genomic predictions for age at first calving in Nellore cattle. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
7. Carroll, A.L., M.L. Spangler, D.L. Morris, and P.J. Kononoff. 2022. Estimating between-animal variance of energy utilization in lactating Jersey cows. J Dairy Sci.
8. Cuyabano, B.C.D., D. Boichard, P. Croiseau, T. Tribout, V. Ducrocq, and C. Gondro. 2022. Measures to quantify the accuracy and the erosion of genomic predicted breeding values. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
9. Garcia, A., S. Miller, S. Tsuruta, D. Lourenco, I. Misztal, D. Lu, and K. Retallick. 2022. Updating the core animals in the algorithm for proven and young in the American Angus Association national evaluations. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
10. Guinan, F.L., G.R. Wiggans, J.W. Dürr, H.D. Norman, J.B. Cole, C.P. Van Tassell, I. Misztal, and D. Lourenco. 2022. Changes in genetic trends for dairy cattle in the U.S. since the implementation of genomic selection. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
11. Hay, E.H.A., S. Toghiani, A.J. Roberts, T. Paim, L.A. Kuehn, and H. Blackburn. 2022. Genetic architecture of a composite beef cattle population. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
12. Hidalgo, J., I. Misztal, S. Tsuruta, M. Bermann, A. Garcia, K. Retallick, and D. 2022. Decreasing computing cost of categorical data analysis. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
13. Hollifield, M.K., M. Bermann, D. Lourenco, and I. Misztal. 2022. Exploring the statistical nature of independent chromosome segments. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
14. Hollifield, M.K., M. Bermann, D. Lourenco, and I. Misztal. 2022. Exploring the Statistical Nature of Independent Chromosome Segments. American Society of Animal Science Annual Meeting, Oklahoma City, OK.
15. Hollifield, M.K., M. Bermann, D. Lourenco, and I. Misztal. 2022. Impact of blending the genomic relationship matrix with different levels of pedigree relationships or the identity matrix on genetic evaluations. American Dairy Science Association Annual Meeting, Kansas City, MO.
16. Lakamp, A.D., A.C. Neujahr, M.M. Hille, J.D. Loy, S.C. Fernando, and M.L. Spangler. 2022. Variance component estimation of longitudinal alpha diversity metrics of the ocular microbiome in preweaned beef cattle. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
17. Lourenco, D., S. Tsuruta, I. Aguilar, Y. Masuda, M. Bermann, A. Legarra, and I. Misztal. 2022. Recent updates in the BLUPF90 software suite. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
18. Lourenco, D., S. Tsuruta, I. Aguilar, A. Legarra, and I. Misztal. 2022. Single-step GWAS: association mapping accounting for phenotypes on genotyped and non-genotyped individuals. Plant and Animal Genome Conference XXIX, San Diego, CA (Virtual).
19. Macciotta, N.P.P. C. Dimauro, D. Lourenco, A. Cesarani, L. Degano, and D. Vicario. 2022. Strategies for choosing core animals in APY and their impact on the accuracy of single-step genomic predictions. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
20. Makanjuola, B.O., G. Rovere, B.C.D. Cuyabanoooooooooo, S.H. le, and Gondro. 2022. Inccludiingg environmental variables into genomic models for carcass traits in Hanwoo beef cattle. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
21. Nawaz, M.Y., and C. Gondro. 2022. Improving accuracy of genomic prediction in distant populations by collecting sequence data over generations. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
22. Ostrovski, H., R.P. Savegnago, W. Huang, and C. Gondro. 2022. Investigating new technologies for on-site real-time sequencing for any animal scientist. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
23. Rovere, G., B.C.D. Cuyabano, B. Makanjuola, S. Kelly, and C. Gondro. 2022. Phenotypic and genetic trends in American Angus associated with climate variability. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
24. Russell, C.A., L.A.Kuehn, W.M. Snelling, and M.L. Spangler. 2022. Genetic prediction for growth traits in beef cattle using selected variants from imputed low-pass sequence data. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
25. Sanglard, L.P., L.A.Kuehn, W.M. Snelling, and M.L. Spangler. 2022. Genotype concordance between SNP chip and imputed low-pass whole-genome sequence in beef cattle. J Anim Sci.
26. Sanglard, L.P., G.M. See, and M.L. Spangler. 2022. Including gene-edited individuals in genetic evaluations can bias estimated breeding values in their progeny. J. Anim Sci.
27. Sanglard, L.P. L.A. Kuehn, W.M. Snelling, and M.L. Spangler. 2022. Mitochondrial DNA copy number as a potential indicator of growth and carcass traits in beef cattle. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
28. Schaff, N., J. Dafoe, D.L. Boss, J.M. Thomson, and J.A.Boles. 2022. PSIII-5 Late-Breaking: Genetic evaluation of energy efficiency in Bos taurus cows classified by residual feed intake. J Anim Sci, 100, Supp. 4, 35-36. doi: 10.1093/jas/skac313.051.
29. See, G.M., J.S. Fix, C.R.Schwab, and M.L. Spangler. 2022. Filling information gaps in swine crossbreeding schemes by imputing non-genotyped F₁ animals to improve genetic gain. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
30. Silva, T.L., C. Gondro, P.A.S. Fonseca, D.A. da Silva, V. Giovana, H.H.R. Neves, I. Carvalho Filho, C.S. Teixeira, L.G. Albuquerque, and R. Carvalheiro. 2022. Genetic mechanisms underlying feet and leg conformation in Nellore cattle: prioritization of GWAS results. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
31. Spangler, M.L., B.L. Golden, S. Newman, L.A. Kuehn, W.M. Snelling, R.M. Thallman, and R.L. Weaber. 2022. iGENDEC: A web-based decision support tool for economic index construction. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
32. Spangler, M.L. 2022. An animal breeder’s view of under-utilized tools to improve fertility in beef herds. Proc. Applied Reproductive Strategies in Beef Cattle.
33. Thomson, J.M., M.L. Schumacher, and J.A. Boles. 2022. 043 Utilizing RNAseq ro investigate molecular mechanisms impacting meat quality and carcass characteristics in beef steers. Animal-science proceedings 13, no. 3, 296-297. doi: 10.1016/j.anscip.2022.07.053.
34. Tsuruta, S., D.A.L. Lourenco, and I. Misztal. 2022. Efficient genetic progress for quantitative traits through genomic selection. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.
35. Tsuruta S., D. Lourenco, and I. Misztal. 2022. Genetic gain for quantitative traits by genomic selection – a simulation study. Aquaculture 2022, San Diego, CA.
36. Tsuruta S., D. Lourenco, and I. Misztal. 2022. Genetic progress for quantitative traits by genomic selection – a simulation study. Plant and Animal Genome Conference XXIX, San Diego, CA (Virtual).
37. Valasek, H.F., B.L. Golden, and M.L. Spangler. 2022. Impact of planning horizon length on the relative emphasis of traits in economic breeding goals. Proc. 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, NL.

Presentations

1. Lourenco, D. Single-step GWAS: association mapping accounting for phenotypes on genotyped and non-genotyped individuals. Plant and Animal Genome Conference XXIX. Vitrual, 2022.
2. Lourenco, D. Leveraging genomics to reshape animal improvement. Advances in Genome Biology and Technology in Agriculture, San Diego, CA, 2022.
3. Lourenco, D. BLUPF90: updates and best practices. University of Florida, 2022.
4. Lourenco, D. Are threshold models feasible for routine genetic evaluations? Purdue University, 2022.
5. Lourenco, D. Single-step GWAS: accounting for the data structure of farm animal populations. Iowa State University, 2022.
6. Lourenco, D. Recent updates in the BLUPF90 software suite. 12^th World Congress on Genetics Applied to Livestock Production, Rotterdam, The Netherlands, 2022.
7. Lourenco, D. Advances in beef cattle genomic evaluations in the US. Daejon University, South Korea, 2022.
8. Lourenco, D. Experiences with genomic selection across species. 19^th Asian-Australian Association of Animal Production, South Korea, 2022.
9. Lourenco, D. Experiences with genomic selection across species. INRAE, 2022.
10. Lourenco, D. Positive and negative aspects of genomic selection. SimMelhor, Vicosa, Brazil, 2022.
11. Weaber, R.L. Emerging Technologies and Focus on the Future. Allied Genetic Resources Producer Conference. Manhattan, KS, 2022.
12. Weaber, R.L. Building a Profitable Cow Herd: Cow Size-A Measurement of Herd Efficiency. LRF Stockman’s School. Aldam, South Africa, 2022.
13. Weaber, R.L. Building better cattle: heritability and selection for improved feet and leg structure. Purina Genetic Summit. Grey Summit, MO, 2022.
14. Weaber, R.L. Using Beef on Dairy data to increase accuracy of selection decisions for carcass traits. Beef Improvement Federation Annual Research Symposium. Las Cruces, NM, 2022.
15. Weaber, R.L. Using commercial Beef on Dairy data to drive genetic improvement. Beef X Dairy Symposium. Texas Tech University, Lubbock, TX, 2022.
16. Weaber, R.L. Using commercial Beef on Dairy data to drive genetic improvement. Beef X Dairy Symposium. Texas Tech University, Lubbock, TX, 2022.

Book chapters

1. Thomson, J.M. 2022. Sustainability of Wild Populations: A Conservation Genetics Perspective. In: Meyers, R.A. (eds) Encyclopedia of Sustainability Science and Technology. Springer, New York, NY.

Extension

1. Weaber, R.L. and M.L. Spangler. Application of advanced genetic technology in beef cattle. King Ranch Institute of Ranch Management. Kingsville, TX. February 24-25, 2022.