Brief Summary of Minutes of Annual Meeting

AGENDA

Tuesday, October 29 – Station reports, Tour and discussion with Hershey executives, presentation by Isaac Hagen and Hershey staff

Wednesday, October 30 – Station reports, presentation by Nicolas Lopez-Villalobos, farm tours (Wanner’s Pride and Joy farm, Warwick Manor Farm)

Thursday, October 31 – Business meeting

Business Meeting

Discussions

• Potential transition from coordinating committee to multi-state project
• Review NIMSS project website
• Report by Lakshmi Matukumalli from NIFA
• Discussion on next years meeting in New Zealand
• Joe West will be retiring

Resolutions

• Albert DeVries was nominated as the new secretary
• Christian Maltecca was nominated as the new chair
• The next meeting will be held October 25-29, 2020 in New Zealand

Submitted by Brad Heins, Chair and acting secretary

Objective 1: Recommend breeding strategies for optimal use of breed resources, maintenance and (or) exploitation of within-breed (additive and non-additive) genetic variation

• Comparison of pure Holstein with Montbéliarde and Viking Red crossbreds (Leslie Hansen and Bradley Heins, University of Minnesota)
• Comparison of pure Holstein with Jersey, Montbéliarde, Normande and Viking Red crossbreds (Bradley Heins, University of Minnesota)
• Evaluation of crossbreeding in organic dairy farms (Bradley Heins, University of Minnesota; Chad Dechow, Pennsylvania State University)
• Genomic predictions for crossbred dairy cattle (Paul VanRaden, USDA-ARS; Bradley Heins, University of Minnesota; Chad Dechow, Pennsylvania State University)

Objective 2: Capture phenotypic data for novel and economically important traits to elucidate their genetic regulation and potential for genomic selection

• Genetic analysis of feed efficiency (Kent Weigel, University of Wisconsin; Paul VanRaden, USDA)
• Identification of genetic mechanisms underlying mastitis resistance and relationship to mammary microbiota (Heather Huson, Cornell University)
• Genetic analysis of digital cushion thickness in Holstein and Jersey breeds (Heather Huson, Cornell University)
• Effects of dietary components on gene expression and rumen microbiome in preweaned dairy heifers (Rebecca Cockrum, Virginia Tech)
• Genetic analysis of bovine respiratory disease (Kent Weigel, University of Wisconsin)
• Elucidating the genetic basis and mechanism of complex diseases and traits (Li Ma, University of Maryland)
• Genomic prediction for milk-production and feed-efficiency traits within North American dairy herds (Kent Weigel, University of Wisconsin)

Objective 3: Collaborate with the National Animal Germplasm Program (NAGP) Dairy Committee, Animal Genomics and Improvement Laboratory (AGIL), and the Council on Dairy Cattle Breeding (CDCB) to improve genetic variation of dairy and optimize economic merit indices

• Genomic evaluations using single-step GBLUP (Ignacy Misztal, University of Georgia)
• Recovery of a lost Holstein male lineage (Chad Dechow, Pennsylvania State University)
• Genetic dissection of dairy bull fertility: from fine mapping to genomic prediction (Francisco Peñagaricano, University of Florida)
• New reference map ARS-UCD1 replaced UMD3 and 80,000 instead of 60,000 markers and QTLs used in genomic predictions since December 2018 (Paul VanRaden, USDA-ARS)
• Early first calving (EFC) as a new trait for selection. (Paul VanRaden, USDA-ARS)
• Revision of Net Merit $ to include feed intake, early first calving, heifer livability, increased body weight maintenance cost, and reduced value of productive life due to faster genetic trend (Paul VanRaden, USDA-ARS)

Objective 4: Develop variant discovery strategies to incorporate functional –omics data into breeding schemes for economically important traits

• To review historic and current genetic diversity in the populations with particular interest in inbreeding levels and signatures of selection (Li Ma, University of Maryland)
• Developing statistical approaches and computing tools to boost the power of current and next-generation sequencing-based genetic studies (Li Ma, University of Maryland)

Objective 5: Carry out interdisciplinary collaborations to improve dairy cow and calf health through increased partnerships with researchers, industry and stakeholders

• The crossbred cattle project is a collaboration among 3 multistate groups (NY, MN, and PA) as well as a commercial AI company in New Zealand.
• Lactation curves of Crossbred and Holstein Diary cattle (MN and NZ)

Abdalla, E.A., F.B. Lopes, T.M. Byrem, K.A. Weigel, and G.J.M. Rosa. 2019. Genomic prediction of bovine leukosis incidence in a US Holstein population. Livestock Science 225:73–77. doi:10.1016/j.livsci.2019.05.004. 

Abdollahi-Arpanahi, R., M.R. Carvalho, E.S. Ribeiro, and F. Peñagaricano. 2019. Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle. Journal of Dairy Science 102:10020–10029. doi:10.3168/jds.2019-17068.

Bradford, H. L., Y. Masuda, J. B. Cole, I. Misztal, and P. M. VanRaden. 2019. Modeling pedigree accuracy and uncertain parentage in single-step genomic evaluations of simulated and US Holstein datasets. J. Dairy Sci. 102:2308–2318. https://doi.org/10.3168/jds.2018-15419

Bradford, H. L., Y. Masuda, P. M. VanRaden, A. Legarra, I. Misztal. 2019. Modeling missing pedigree in single-step genomic BLUP. J. Dairy Sci. 102:2336–2346. https://doi.org/10.3168/jds.2018-15434

Carvalho, M.R., F. Peñagaricano, J.E.P. Santos, T.J. DeVries, B.W. McBride, and E.S. Ribeiro. 2019. Long-term effects of postpartum clinical disease on milk production, reproduction, and culling of dairy cows. Journal of Dairy Science 102:11701–11717. doi:10.3168/jds.2019-17025.

Cole, J.B. and Null, D.J. Short communication: Phenotypic and genetic effects of the polled haplotype on yield, longevity, and fertility in US Brown Swiss, Holstein, and Jersey cattle. J. Dairy Sci. 102 (9):8247-8250. 2019.

Cole. J.B., and VanRaden, P.M. Symposium review: Possibilities in an age of genomics: The future of selection indices. J. Dairy Sci. 101(4):3686–3701. 2018.

Costa, A., N. Lopez-Villalobos, N.W. Sneddon, L. Shalloo, M. Franzoi, M. De Marchi, and M. Penasa. 2019. Invited review: Milk lactose—Current status and future challenges in dairy cattle. Journal of Dairy Science 102:5883–5898. doi:10.3168/jds.2018-15955.

Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. F. Baes, F. Miglior, I. Misztal, and F. S. Schenkel. 2019. Genetics and genomics of reproductive disorders in Canadian Holstein cattle. J. Dairy Sci. 102:1341-1353. https://doi.org/10.3168/jds.2018-15038

Guarini, A. R., D. A. L. Lourenco, L. F. Brito, M. Sargolzaei, C. F. Baes, F. Miglior, S. Tsuruta, I. Misztal, and F. S. Schenkel. 2019. Use of a single-step approach for integrating foreign information into national genomic evaluation in Holstein cattle. J. Dairy Sci. 102:8175-8183. https://doi.org/10.3168/jds.2018-15819

Guarini, A. R., M. Sargolzaei, L. F. Brito, V. Kroezen, D. A. L. Lourenco, C. F. Baes, F. Miglior, J. B. Cole, and F. S. Schenkel. 2019. Estimating the effect of the deleterious recessive haplotypes AH1 and AH2 on reproduction performance of Ayrshire cattle. J. Dairy Sci. 102:5315-5322. https://doi.org/10.3168/jds.2018-15366

Handcock, R.C., N. Lopez-Villalobos, L.R. McNaughton, P.J. Back, G.R. Edwards, and R.E. Hickson. 2019. Positive relationships between body weight of dairy heifers and their first-lactation and accumulated three-parity lactation production. Journal of Dairy Science 102:4577–4589. doi:10.3168/jds.2018-15229.

Jiang, J., Ma, L., Prakapenka, D., VanRaden, P.M., Cole, J.B., and Da, Y. A large-scale genome-wide association study in U.S. Holstein cattle. Front. Genet. 10:412. 2019.

Li, B., L. Fang, D.J. Null, J. Hutchison, E. Connor, P.M. VanRaden, M. Vandehaar, R. Tempelman, and K.A. Weigel. 2019. High-density genome-wide association study for residual feed intake in Holstein dairy cattle. Journal of Dairy Science 102. doi:10.3168/jds.2019-16645.

Ma, L., Sonstegard, T.S., Cole, J.B., Van Tassell, C.P., Wiggans, G.R., Crooker, B.A., Tan, C., Prakapenka, D., Liu, G.E., and Da, Y. Genome changes due to artificial selection in U.S. Holstein cattle. BMC Genomics 20:128. 2019.

Ma, L., Sonstegard, T.S., Cole, J.B. et al. Genome changes due to artificial selection in U.S. Holstein cattle. BMC Genomics 20, 128 (2019). https://doi.org/10.1186/s12864-019-5459-x

Ma, L., J.B. Cole, Y. Da, and P.M. VanRaden. 2019. Symposium review: Genetics, genome-wide association study, and genetic improvement of dairy fertility traits. Journal of Dairy Science 102:3735–3743. doi:10.3168/jds.2018-15269.

Miles, A.M., McArt, J.A.A., Leal Yepes, F.A., Stambuk, C.R., Virkler, P.D., Huson, H.J., (2018) Udder and teat conformational risk factors for elevated somatic cell count and clinical mastitis in New York Holsteins. Preventative Veterinary Medicine epub Dec 15; Feb 163:7-13.

Mueller, M.L., Cole, J.B., Sonstegard, T.S., and Van Eenennaamn, A.L. Comparison of gene editing versus conventional breeding to introgress the POLLED allele into the US dairy cattle population. J. Dairy Sci. 102(5):4215–4226. 2019.

Nani, J.P., Rezende, F.M. & Peñagaricano, F. Predicting male fertility in dairy cattle using markers with large effect and functional annotation data. BMC Genomics 20, 258 (2019). https://doi.org/10.1186/s12864-019-5644-y

Oliveira, H. R., L. F. Brito, D. A. L. Lourenco, F. F. Silva, J. Jamrozik, L. R. Schaeffer, and F. S. Schenkel. 2019. Invited review: Advances and applications of random regression models: From quantitative genetics to genomics. J. Dairy Sci. 102:7664-7683. https://doi.org/10.3168/jds.2019-16265

Oliveira, H. R., L. F. Brito, M. Sargolzaei, F. F. Silva, J. Jamrozik, D. A. L. Lourenco, and F. S. Schenkel. 2019. Impact of including information from bulls and their daughters in the training population of multiple‐step genomic evaluations in dairy cattle: a simulation study. J. Anim. Breed. Genet. In Press. https://doi.org/10.1111/jbg.12407

Oliveira H. R., L. F. Brito, F. F. Silva, D. A. L. Lourenco, J. Jamrozik, and F. S. Schenkel. 2019. Genomic prediction of lactation curves for milk, fat, protein, and somatic cell score in Holstein cattle. J. Dairy Sci. 102:452-463. https://doi.org/10.3168/jds.2018-15159

Oliveira, H. R., D. A. L. Lourenco, Y. Masuda, I. Misztal, S. Tsuruta, J. Jamrozik, L. F. Brito, F. F. Silva, and F. S. Schenkel. 2019. Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle. J. Dairy Sci. 102:2365–2377. https://doi.org/10.3168/jds.2018-15466

Oliveira, H. R., D. A. L. Lourenco, Y. Masuda, I. Misztal, S. Tsuruta, J. Jamrozik, L. F. Brito, F. F. Silva, J. P. Cant, and F. S. Schenkel. 2019. Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle. J. Dairy Sci. In Press. https://doi.org/10.3168/jds.2019-16821

Oliveira, H. R., J. P. Cant, L. F. Brito, F. L. B. Feitosa, T. C. S. Chud, P. A. S. Fonseca, J. Jamrozik, F. F. Silva, D. A. L. Lourenco, and F. S. Schenkel. 2019. Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle. J. Dairy Sci. 102:8159-8174. https://doi.org/10.3168/jds.2019-16451

Pacheco, H.A., S. da Silva, A. Sigdel, C.K. Mak, K.N. Galvão, R.A. Texeira, L.T. Dias, and F. Peñagaricano. 2018. Gene Mapping and Gene-Set Analysis for Milk Fever Incidence in Holstein Dairy Cattle. Frontiers in Genetics 9:465. doi:10.3389/fgene.2018.00465.

Pereira, G.M., and B.J. Heins. 2019. Activity and rumination of Holstein and crossbred cows in an organic grazing and low-input conventional dairy herd. Translational Animal Science 3:txz106. https://doi.org/10.1093/tas/txz106

Rezende, F.M., J.P. Nani, and F. Peñagaricano. 2019. Genomic prediction of bull fertility in US Jersey dairy cattle. Journal of Dairy Science 102:3230–3240. doi:10.3168/jds.2018-15810.

Santos, D.J., Cole, J.B., Lawlor, T.J., VanRaden, P.V., Tonhati, H., and Ma, L. Variance of gametic diversity and its use in selection programs. J. Dairy Sci. 102(6):5279-5294. 2019.

Schmitt, M.R., VanRaden, P.M., and De Vries, A. Ranking sires using genetic selection indices based on financial investment methods versus lifetime net merit. J. Dairy Sci. 102(10):9060–9075. 2019.

Shonka-Martin, B., A. Hazel, B. Heins, and L.B. Hansen. 2019a. Three-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein compared with Holstein cows for dry matter intake, body traits, and production. Journal of dairy science 102:871–882. https://doi.org/10.3168/jds.2018-15318

Shonka-Martin, B., B.J. Heins, and L.B. Hansen. 2019b. Three-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein compared with Holstein cows for feed efficiency, income over feed cost, and residual feed intake. Journal of dairy science 102:3661–3673. https://doi.org/10.3168/jds.2018-15682

Sigdel, A., R. Abdollahi-Arpanahi, I. Aguilar, and F. Peñagaricano. 2019. Whole Genome Mapping Reveals Novel Genes and Pathways Involved in Milk Production Under Heat Stress in US Holstein Cows. Frontiers in Genetics 10:928. doi:10.3389/fgene.2019.00928.

Stambuk, C.R., McArt, J.A.A., Bicalho, R.C., Miles, A.M., Huson, H.J., (2018) A longitudinal study of digital cushion thickness and its function as a predictor for compromised locomotion and hoof lesions in Holstein cows. Translational Animal Science epub Sept 27, 2018; Jan 3:1:9

VanRaden, P.M., Bickhart, D.M., and O'Connell, J.R. Calling known variants and identifying new variants while rapidly aligning sequence data. J. Dairy Sci. 102(4):3216–3229. 2019.

Veronese, A., O. Marques, R. Moreira, A.L. Belli, R.S. Bisinotto, T.R. Bilby, F. Peñagaricano, and R.C. Chebel. 2019a. Genomic merit for reproductive traits. I: Estrous characteristics and fertility in Holstein heifers. Journal of Dairy Science 102:6624–6638. doi:10.3168/jds.2018-15205.

Veronese, A., O. Marques, F. Peñagaricano, R.S. Bisinotto, K.G. Pohler, T.R. Bilby, and R.C. Chebel. 2019b. Genomic merit for reproductive traits. II: Physiological responses of Holstein heifers. Journal of Dairy Science 102:6639–6648. doi:10.3168/jds.2018-15245.

Williams, K.T., K.A. Weigel, W.K. Coblentz, N.M. Esser, H. Schlesser, P.C. Hoffman, H. Su, and M.S. Akins. 2019. Effect of diet energy density and genomic residual feed intake on prebred dairy heifer feed efficiency, growth, and manure excretion. Journal of Dairy Science 102:4041–4050. doi:10.3168/jds.2018-15504.