IDENTIFYING LOCAL ADAPTATION AND CREATING REGION-SPECIFIC GENOMIC PREDICTIONS IN BEEF CATTLE

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: AFRI COMPETITIVE GRANT
• Reporting Frequency: Annual
• Accession No.: 1008909
• Grant No.: 2016-68004-24827
• Cumulative Award Amt.: $3,000,000.00
• Proposal No.: 2015-08789
• Project Start Date: Mar 1, 2016
• Project End Date: Feb 28, 2021
• Grant Year: 2017
• Program Code: [A5161]- Global Food Security: Breeding and Genomics

Recipient Organization
UNIVERSITY OF MISSOURI
(N/A)
COLUMBIA,MO 65211

Performing Department
Office of Sponsored Programs A

Non Technical Summary
Cattle poorly adapted to their environment result in lost revenue and jeopardize the stability of the food supply. Large scale genetic data (i.e. genomic data) now allows us to rigorously analyze genetic adaptations and avoid the breeding of animals that will not thrive.We will use genomic methods to precisely identify DNA variants responsible for local adaption to tolerate biotic and abiotic threats to production, enhance resilience of beef production, and enhance beef quality and quantity. The project will achieve three objectives:Identify DNA variants responsible for regional genetic adaptationCreate geographic region-specific genomic predictions, focusing on adaptation variants from Objective 1.Educate the next generation of beef producers to fully embrace and properly use animal breeding tools.Analyzing more than 170,000 cattle with ~15 million high-accuracy DNA variants, we will use selection mapping to identify detailed chromosome regions (e.g. genes) responsible for local adaptation. We will also identify gene-by-environment interactions using multiple statistical methods. When local genetic adaptations exist, ranking animals using a regional genetic evaluation will be different from national cattle evaluations. Focusing on loci under regional genetic adaptation selection or with gene-by-environment interactions, we will develop region-specific genomic predictions. These genomic predictions will allow rapid identification of cattle best suited to an environment. Beef producers have not embraced appropriate animal breeding practices and new technologies, limiting genetic improvement of efficient, high quality beef cattle. We will create engaging curriculum for youth and undergraduate education, including internships, to train the next generation of beef producers.

Animal Health Component

80%

Research Effort Categories

Basic

20%

Applied

80%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
303	3310	1080	100%

Knowledge Area
303 - Genetic Improvement of Animals;

Subject Of Investigation
3310 - Beef cattle, live animal;

Field Of Science
1080 - Genetics;

Keywords

adaptation

education

gene-by-environment

genomic prediction

qtl

selection

technology adoption

Goals / Objectives
Of the major livestock sectors, beef cattle are the most exposed to abiotic and biotic stressors. While poultry, swine, and dairy operations typically keep the animals in consistent and protected confinement, provided necessary medical care, and provide a balanced total mixed ration diet allowing the environment of the animals to be maximally controlled, beef cows are grazed on range or pastures where they are exposed to a myriad of environmental stressors (National Research Council. Committees On Animal Nutrition, 1981).Beef cattle that are poorly adapted to the environment in which they live result in lost revenues and jeopardize the stability of the United States food supply. One prominent example in the U.S. beef industry is susceptibility to fescue toxicosis. Fescue has an endophyte fungus which produces ergot-like alkaloids which are toxic to animals. These toxins cause vasoconstriction, reduced appetite, poor reproduction, slowed growth, and exacerbate heat stress. In 1993, it was estimated that fescue toxicosis cost the U.S. beef industry $609 million annually (Hoveland, 1993). After adjusting for inflation, this translates to $998 million in 2014 dollars, but this adjustment ignores increased feeder calf and crop prices, so the true current cost is even greater. Losses also occur due to poor adaptation to high altitude, humid, arid, hot, and cold environments (Hohenboken et al., 2005). However, these issues can be alleviated, because there is ample variation in taurine cattle populations to make improvement. One of the ways for animals to cope with fescue and heat stress is to shed their winter hair coat in the spring, and hair shedding is a heritable trait (Gray et al., 2011). Genetic variance is appreciable for other adaptive traits, such as pulmonary arterial pressure with a heritability of 0.34 (Shirley et al., 2008). While indicine cattle have been used to breed cattle adapted to hot climates, this is not optimal and does not address when the stressors are not heat. Further, beef from indicine cattle has reduced palatability (O'Connor et al., 1997), thus decreasing demand and limiting the profits and sustainability of producers who use indicine genetics. As genetic variation is present within taurine cattle for adaptation to the various U.S. environments, the sustainable strategy is to utilize existing variation through artificial selection. What is needed are breeding decision tools to identify taurine animals adapted to regional environments, even when we do not necessarily know the traits leading to that adaptation.The beef industry has the most distributed breeding decision structure compared to all other major agricultural species, plants and animals included. Rather than germplasm and breeding populations controlled by large companies with highly trained breeders making the selection decisions, in the beef industry there are approximately 742,500 cow-calf operations and every operation makes their own breeding decisions. (In the United States there are 29.7 million beef cows divided by 40 head per operation into 742,500 operations. See http://www.ers.usda.gov/topics/animal-products/cattle-beef/background.aspx and http://www.beefusa.org/beefindustrystatistics.aspx.) Furthermore, these beef producers do not typically use optimal breeding practices. For example, a BEEF magazine article from January 29, 2014 reported a survey that found beef producers are more likely to select animals using actual trait records than use the more accurate genetic predictions (expected progeny differences, EPDs), and they are also more likely to select on individual traits and EPDs than use optimal economic selection indexes. The accuracy of selection decisions is higher when genetic predictions are used, thus response to selection will be more rapid. Vice versa, the accuracy of selection on actual trait measurements is limited by the heritability of the trait and is further reduced by the failure to correct for confounding environmental effects and is therefore far less accurate. Use of these faulty practices would likely lead to the dismissal of a plant or animal breeder in other agricultural sectors. A major educational effort is needed to enable and persuade the next generation of beef producers to understand and adopt these optimal breeding practices to ensure that beef production in the United States increases economic prosperity, national resilience and food security.Overview of ObjectivesThe overall goal of this project is to create tools, genomic predictions, which will allow beef producers to identify and breed cattle which are adapted to their production environment. Briefly summarized, our objectives are to:1. Identify genomic variants or loci responsible for regional adaptation.2. Create geographic region-specific genomic predictions, focusing on regional adaptation variants from Objective 1.3. Educate the next generation of beef producers to fully embrace and properly use animal breeding tools.

Project Methods
Using high-density SNP genotype data for over 130,000 Angus, 15,000 Hereford, 25,000 Simmental, 4,500 Gelbvieh, 12,000 Red Angus and 2,240 Limousin samples, we will impute the existing SNP data up to more than ~15M SNPs. Using 15M SNPs in our genome-wide analyses will enable a detailed analysis of the genome.Based on the geographic regions described in Leighton, Willham, and Berger (1982), we will initially define 9 U.S. regions. We can also use the PRISM data to refine geographic regions using k-means clustering of reported variables to group 4 km resolution locations into larger regions with similar environments. We will assign membership of a genotyped animal to a region based on multiple criteria.All selection scan analyses will be conducted within a single breed; analyses will be repeated for each of the 6 breeds. If an animal is not adapted to the environment, the animal will underperform and will be excluded from the breeding population. This selection causes the frequency of these DNA variants to be significantly different between regional populations.We will use hapFLK and TreeSelect to identify genomic loci that have diverged between geographic regions due to local genetic adaptation selection.We will fit 8 environmental variables from the PRISM data in which an animal was born as the dependent variable in a linear mixed-model GWAS. This analysis will identify DNA variants significantly associated with an environmental variable, and thus responding to selection for that environmental stressor.Focusing on selection scans at whole genome sequence resolution is powerful for several reasons. First, it allows us to use existing genotype data without the need to phenotype and genotype new samples as part of a controlled experiment. Second, selection mapping allows us to utilize the past 150 years of history and local adaptation of cattle in the United States. Third, selection mapping allows us to identify local adaptation loci that have responded to pressures that we could not measure or would not hypothesize as driving local adaptation. We can further expand our knowledge of the biology of local adaptation in beef cattle based only on genomic data.We will further look for gene-by-environment interactions and will use local adaptation selection scan and the gene-by-environment results to develop genomic predictions for adaptation to the variety of production environments that exist in the United States.We will conduct a genetic prediction (EPD) environmental interaction analysis by looking for regional differences in EPD values for cows that repeatedly produce in a region versus those that fail to rebreed 425 days after delivering their first calf.We will use GCTA to estimate the gene-by-environment variance between the recorded phenotypes and the environmental data from the PRISM dataset.Using the geographic region assignments, we will perform within-region breed-specific genome-wide association analyses of traits most exposed to abiotic and biotic stress. We will use the BOLT-LMM software for single trait GWAA, as it has decreased requirements and improved power.To further increase our power, we will perform multiple-trait meta-analyses of univariate GWAA or we will perform multivariate GWAA.Because we have stratified these GWAA by environment, we can use the random effects meta-analysis model in the METASOFT software to test if effect sizes between regions are significantly heterogeneous with Cochran's Q statistic.We will analyze gene-by-environment interactions using a linear mixed-model genotype-by-environment interaction GWAA using the GWAF package in R, focusing on environmental factors with the largest gene-by-environment variance components from the GCTA analysis.One of the phenotypes most involved in regional adaptation is an animal's ability to shed its winter coat at the appropriate time. We will collect DNA samples on 6,921 animals with hair coat scores. Cattle with phenotypes and blood samples will be genotyped using a SNP assay containing ~35,000 SNPs used for imputation and ~195,000 SNPs that are loss-of-function mutations and other functional variants. We will impute the samples to full genome sequence level data. Linear mixed-model GWAA will identify variants that are strongly associated with hair shedding.The ultimate goal and deliverable of the research portion of this project are region-specific genomic predictions that will be used to identify and select regionally adapted beef cattle. When gene-by-environment interactions are present, the ranking of animals in a regional genetic evaluation will be different from national cattle evaluations.We will create three curricula to train the next generation of livestock breeders. Current curricula focus on genetics basics, but do not fully broach bad habits of beef cattle breeding. The deficit model of science communication has not proven effective. Rather, we will build our education model on the Unified Theory of Acceptance and Use of Technology. Thus, our curriculum will focus on:Trust and effectiveness of beef breeding best practices and technologies.Simplicity of using selection indexes and genomic technologies.The profit and sustainability outcomes of using best practices and technology.We will build a youth curriculum of 4 modules which will include instruction in applied and practical beef breeding.As part of this project we will sponsor a national youth essay contest. Participants will be asked to answer the prompt "What does it mean to be a beef breeder in the 21st century".We will construct an undergraduate curriculum covering the same types of topics as the youth curriculum (see above), but we will design the curriculum so that it is appropriate for a university setting. Curriculum will be to meet the outlined learning outcomes of: 1) reinforcement of animal breeding concepts; 2) determination of animal breeding best practices under different scenarios; 3) improved written and oral communication skills; and 4) experience with different social media outlets for information dissemination.In order to impact the social influence aspect of beef breeding best practice and technology adoption and increase student involvement, each student enrolled in the course will be required to post one item regarding beef breeding on the social media platform of their choice.Each student will also be required to write an essay for the course on a relevant beef breeding topic, helping them to think deeply about beef genetics and develop communication skills. Essays will be published on the A Steak in Genomics blog. Students will give an oral presentation summarizing their essay to improve oral communication skills.Collaborator Smith and co-workers developed a successful reproductive management internship program. As part of the internship, the students will attend 4 beef genetics training sessions. Furthermore, interns will act as genetic consultants to the participating beef farms and ranches.How results will be analyzed, assessed, and interpreted Importantly, the research statistics use null and alternative hypotheses allowing us to produce robust, significant, biologically meaningful results. We will create genomic predictions using only the SNPs identified as involved with local adaptation to increase signal and reduce noise. Genomic predictions will be assessed using common measures of accuracy and predictive ability.The overall evaluation will seek to determine: 1) Knowledge gained from curriculum and internship training, 2) How teachers and students perceive the efficacy and effectiveness of beef breeding curriculum, 3) Changes in student learning before and after engaging in the curriculum, 4) Perceptions of the efficacy/effectiveness of the breeding curriculum, 5) Student outreach for beef breeding curriculum, 6) Efficacy/effectiveness of breeding internship program.

Progress 03/01/16 to 02/28/21

Outputs
Target Audience:Using curriculum development, internships, popular press, social media, industry presentations, and scientific presentations we reach a broad audience. That audience includes breed associations, allied industry partners, extension professionals, farmers, ranchers, graduate students, undergraduate students, youth interested in beef cattle, animal scientists, and genomic scientists. Changes/Problems:Dr. Anna Ball, a co-PD on the grant took a new position at the University of Illinois in 2019. Prior to this, Dr. Ball was a Provost's Faculty Fellow. Thus, the educational work that she proposed and was assigned to lead, especially the evaluation of youth and undergraduate curriculum was not completed as timely as planned. Further, the bovine reference genome was in the process of being updated at the beginning of the grant and that delayed some of the research activity. Finally, we had some issues in recruiting and retaining postdoctoral researchers. These problems lead to us requesting two no-cost extensions. However, with the additional time we were able to achieve the objectives of the grant. The additional time also allowed us to maximize our impact on the beef industry. What opportunities for training and professional development has the project provided?This grant has been very successful in providing training opportunities for graduate students. There have been ten graduate students who have participated in this grant during their graduate training (Amy Abrams, Amanda Bowling, Victoria Chambers, Harly Durbin, Savannah Moore, Sara Nilson, Troy Rowan, Jenna Slaughter, Johanna Smith, Miranda Wilson). Two postdoctoral fellows (Camila Urbano Braz and Natalie Halbert) were also supported and trained as part of the grant. Dr. Amy Abrams is now an assistant professor of Animal Science at Berry College in Georgia. Amy's involvement in the undergraduate curriculum design helped prepare her for this role. Dr. Troy Rowan is an assistant professor at the University of Tennessee Institute for Agriculture. Troy Rowan was also a visiting scholar at the Roslin Institute with John Hickey. Troy also gave a podium presentation at the very presigious and competitive CSHL Biology of Genomes Conference, and his talk was very well received. Dr. Harly Durbin is a data scientist at ‎Syngenta. Harly was also an intern at Angus Genetics Inc. during her PhD and helped develop the Angus hair shedding research genetic prediction. Research activities performed at Texas A&M University provided graduate student and postdoctoral training that has resulted in 3 manuscripts, one of which is published, and two that are awaiting approval for submission. Both Miranda Wilson and Johanna Smith are expected to matriculate in 2021. There were also six undergraduate students who also participated and assisted in the grant (Brian Arisman, Katherine Barnett, Natalie Barr, Aaron Mott, Katelyn Robinson, Will Shaffer). How have the results been disseminated to communities of interest?We have used a variety of approaches to share results of this project. These include scientific publications, scientific presentations at conferences (CSHL Biology of Genomes; International Conference on Quantitative Genetics 6; GSA Population, Evolutionary, and Quantitative Genetics Conference; Plant and Animal Genomes Conference; American Society of Animal Science conferences), numerous extension presentations, popular press articles, blog posts, social media, websites, public television, and student defense seminars shared via Zoom (https://youtu.be/g18YGHFk8d0). Results were even shared using youth speaking contests (https://youtu.be/oBDVi350lYU). What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Most selection decisions in the beef industry have been focused on revenue, with little attention towards costs, especially costs due to varying environmental conditions and stressors. Our grant has prototyped genetic predictions for environmental stress to improve the sustainability and resilience of beef production. Through data from our grant and Harly Durbin's internship, Angus Genetics Inc. launched a new research Hair Shedding EPD, which allows producers to select cattle better adapted to heat and humidity, and thus achieve higher productivity. This has been a productive public-private partnership which has jump-started industry adoption of this novel genetic prediction of heat tolerance. This change in action (adoption of hair shedding genetic prediction technology) will enable a change in condition for better heat tolerance of cattle in the beef industry. Other industry partners will follow, using the 12,000 animals we have phenotyped and genotyped for hair shedding genomic prediction. Further, by sharing genotypes generated by the grant with breed associations, farmers and ranchers received free genomic enhanced EPDs (genomic predictions) for ~11,000 cattle (~1,000 were previously genotyped) for a whole suite of traits. DNA variants identified from Troy Rowan's selection mapping work have been included on the latest Neogen GeneSeek Genomic Profiler SNP array, called the GGP-100K. The preferential inclusion of these SNPs on the array is a real-world impact of this research. These markers will make the array more informative, as these SNPs are changing in allele frequency due to the selection decisions of farmers and ranchers. As part of the grant, we created a new imputation pipeline for cattle, described in Rowan et al. 2019. This new imputation process takes an animal's genotypes for tens of thousands of DNA markers and infers genotypes for 834,000 DNA markers. This greater marker density increases the power and precision of genome-wide association studies. This change in knowledge and change in action has led to improved genomic analyses for this project and other projects as well. For example, the SNP array data generated by Grant No. 2017-67007-26143 ("Breeding climate-smart beef cattle", PI Dr. Raluca Mateescu) has also been imputed to 834,000 SNPs using this pipeline. Beef Cattle are a tremendous model organism for genotype-by-environment and local adaptation studies in mammals. The research, led by Chris Seabury, Johanna Smith, and Natalie Halbert at Texas A&M, has identified multi-breed pleiotropic QTL, which can be applied to modern genomic selection schemes.More specifically, in U.S. Red Angus and Gelbvieh beef cattle alone, we detected 69 pleiotropic growth associations, which includes both the main effects and the GxE effects. Moreover, while our analyses primarily focused on growth traits, we also performed similar analyses for carcass traits and scrotal circumference in U.S. Gelbvieh beef cattle; thereby resulting in the detection of 11 main effect loci, and 42 GxE loci. Additionally, all large-sample analyses also generally revealed higher heritability estimates than previously reported for many of the analyzed traits. This research, along with the genotype-by-environment genome wide association studies done by Camila Braz at the University of Missouri, has also highlighted the role of neurotransmitters and the immune system in allowing cattle (and possibly mammals in general) to cope with abiotic and biotic stressors. One of the aspects of the grant that was more challenging than expected was the creation of ecoregion-specific genomic predictions. Our initial efforts use multivariate models in which phenotypes from different ecoregions were fit as different traits. However, the lack of replication of genotypes across environments which is often seen in plant data made it difficult for these models to converge and give consistent results. Whether in large datasets of 1 million animals in the Angus Genetics Inc. data or in smaller datasets, it was often difficult to get these multivariate models to converge. However, we have now used a model that works well. In this approach, two relationship matrices are fit: the first is the typical genomic relationship matrix and the second is a modified genotype-by-environment relationship matrix. In the GxE matrix, if two animals are in the same ecoregion, their relatedness coefficient is equal to that from the genomic relationship matrix. If two animals are in different ecoregions, their relationship coefficient is set to zero. In this approach, not only are we able to produce predictions of ecoregion-specific effects, but in many cases the accuracy of purely additive genetic effects also increases. The prediction of genotype-by-environment effects will continue in Grant No.2021-67021-33448 ("III: Small: DATAg: How Genotype, Environment and Management Interact to Influence Animal Size: An evaluation of James' Interpretation of Bergmann's Rule in Bos taurus Cattle"). In this new grant we will investigate genotype-by-environment, genotype-by-management, and genotype-by-environment-by-management genetic predictions in beef cattle, which will allow us to create context-specific genomic predictions, such as ecoregion-specific genomic predictions or management-specific genomic predictions, of cattle performance. We created a youth curriculum and undergraduate curriculum to educate the next generation of beef farmers and ranchers. The undergraduate course has been taught five times as an online class and is now available through Agriculture Interactive Distance Education Alliance (AG*IDEA). The undergraduate class is offered every summer. Students appreciate the applied nature of the course and the opportunity to think through various scenarios. A four-unit beef genetics curriculum was designed for a target audience of Junior and Senior level students enrolled in a secondary educational Animal Science course. The curriculum includes the following units: a). Genetics and inheritance; b). Introduction to EPD's; c). EPD's, economic index, and genetic technology; and d). Using genetic information for selection. The curriculum includes 4 lessons with labs, student references, lesson plans, and PowerPoints. It also includes a pre-test and a post-quiz for each lesson. High school agriculture teachers made the following comments about the beef genetics curriculum that they piloted in their classrooms: "This curriculum was very easy to follow. The alignment worked fairly smooth with utilizing the labs. I thought the real-world scenarios worked well with being able to apply them to the students outcomes." "I felt that this was a positive way to introduce students to the world of genomics and start to engage interest in this side of animal Science." Test Score Data: These four lessons were pilot tested in a rural Missouri high school Animal Science class consisting of 12 students. The following pre-post test score averages were reported: Lesson Average Pre-Test Score (25 points possible) Average Post-Test Score (25 points possible) 1-Genetics and Inheritance 14 20 2-Introduction to EPD's 15 21 3-EPD's, Economic Indexes, and Genetic Technology 13 18 4-Using Genetic Information for Selection 12 22 Following the pilot of the four lessons, the curriculum was reviewed and revised by a panel of experts. This panel included Animal Science faculty and graduate students as well as Agricultural Education and Leadership faculty and graduate students. The youth curriculum, including lesson plans, handouts, slide decks, lab activities, and assessments is freely available on the web for use by agriculture educators. Pieces of the four modules have been downloaded from 40 to 74 times. We also educated University of Missouri Reproduction Interns on the proper use of genetic tools to select beef cattle for more sustainable production (51 interns in total).

Publications

• Type: Journal Articles Status: Published Year Published: 2018 Citation: Gandolfi B., Alhaddad H., Abdi M., Bach L.H., Creighton E.K., Davis B.W., Decker J.E., Dodman N.H., Ginns E.I., Grahn J.C., Grahn R.A., Haase B., Haggstrom J., Hamilton M.J., Helps C.R., Kurushima J.D., Lohi H., Longeri M., Malik R., Meurs K.M., Montague M.J., Mullikin J.C., Murphy W.J., Nilson S.M., Pedersen N.C., Peterson C.B., Rusbridge C., Saif R., Shelton G.D., Warren W.C., Wasim M., Lyons L.A. (2018). Applications and efficiencies of the first cat 63K DNA array. Scientific Reports, 8, 7024. http://doi.org/10.1038/s41598-018-25438-0
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Braz, C.U., Taylor, J.F., Decker, J.E., Bresolin, T., Espigolan, R., Garcia, D.A., Gordo, D.G.M., Magalh�es, A.F.B., de Albuquerque, L.G. and de Oliveira, H.N., 2018. Polymorphism analysis in genes associated with meat tenderness in Nelore cattle. Meta Gene, 18, pp.73-78.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Rowan, T.N., Hoff, J.L., Crum, T.E., Taylor, J.F., Schnabel, R.D. and Decker, J.E., 2019. A multi-breed reference panel and additional rare variants maximize imputation accuracy in cattle. Genetics Selection Evolution, 51(1), pp.1-16.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Hoff, J.L., Decker, J.E., Schnabel, R.D., Seabury, C.M., Neibergs, H.L. and Taylor, J.F., 2019. QTL-mapping and genomic prediction for bovine respiratory disease in US Holsteins using sequence imputation and feature selection. BMC genomics, 20(1), p.555.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). EPDs 101: Use Information to Improve Your Herd. The Cattlemen
• Type: Other Status: Published Year Published: 2018 Citation: Crum, T., & Decker, J. E. (2018). Breed Composition: its like chocolates, you can't tell what's inside just by looking...SimTalk, 26, 3439. https://issuu.com/asapublications/docs/march_2018_simtalk/36
• Type: Other Status: Published Year Published: 2018 Citation: Rowan, T., & Decker, J. E. (2018). Searching for Environmental Adaptation in Beef Cattle. SimTalk, 25, 2829.https://issuu.com/asapublications/docs/late_20fall_20simtalk_202017/30
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). Do We Overvalue Accuracy? MWI Producer Outlook.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). EPDs and reasonable expectations in commercial crossbred operations. In . Presented at the Applied Reproductive Strategies in Beef Cattle, Ruidoso, New Mexico.http://www.appliedreprostrategies.com/2018/newsroom.html#JaredDecker2018
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Knickmeyer, E. R., Thomas, J. M., McLean, M., Cierna, L., Locke, J. W., Bonacker, R. C., ... Patterson, D. J. (2018). The University of Missouri internship in bovine reproductive management. In . Presented at the American Society of AnimalScience Annual Meeting, Vancouver, BC.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Patterson, D. J., Brown, D. S., Smith, M. F., Lamberson, W. R., Taylor, J. F., Spencer, T. E., ... Decker, J. E. (2018). The National Center for Applied Reproduction and Genomics (NCARG) in beef cattle. In . Presented at the American Society of Animal Science Annual Meeting., Vancouver, BC
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018, June). Impact of Adaptability Grant: Identifying Local Adaptation and Creating Region-specificGenomic Predictions in Beef Cattle. Beef Improvement Federation. Loveland, Colorado: Beef Improvement Federation.http://www.bifconference.com/bif2018/newsroom.html
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018, April). Integrating Genomics into the US Beef Industry. Department of Animal Science, North Carolina State University. Raleigh, North Carolina: Department of Animal Science, North Carolina State University
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Rowan, T. N., Durbin, H. J., Nilson, S. M., Seabury, C. M., Schnabel, R. D., & Decker, J. E. (2018, May). Local genetic adaptation in United States Bos taurus beef cattle. Genetics Society of America. Madison, Wisconsin: Genetics Society of America.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Nilson, S. M., Rowan, T. N., Seabury, C. M., Schnabel, R. D., & Decker, J. E. (2018, May). Developing environmental region-specific genomic predictions for beef cattle breeds. Genetics Society of America. Madison, Wisconsin: Genetics Society of America.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Neibergs, H.L., Kiser, J.N., Neupane, M., Seabury, C.M., Taylor, J.F., Cornmesser, M.A., McGuirk, S., Blackburn, R., Consortium, B.R.D. and Womack, J.E., 2018. 204 Genome-Wide Association Analysis Identifies QTL Associated with Clinical and Sub-Clinical Bovine Respiratory Disease. Journal of Animal Science, 96(suppl_2), pp.108-109.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Yurchenko, A.A., Daetwyler, H.D., Yudin, N., Schnabel, R.D., Vander Jagt, C.J., Soloshenko, V., Lhasaranov, B., Popov, R., Taylor, J.F. and Larkin, D.M., 2018. Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation. Scientific reports, 8.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Taylor, J.F., Schnabel, R.D. and Sutovsky, P., 2018. Identification of genomic variants causing sperm abnormalities and reduced male fertility. Animal reproduction science, 194, pp.57-62.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Taylor, J.F., Schnabel, R.D. and Sutovsky, P., 2018. Genomics of bull fertility. animal, 12(s1), pp.s172-s183.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Bouwman, A.C., Daetwyler, H.D., Chamberlain, A.J., Ponce, C.H., Sargolzaei, M., Schenkel, F.S., Sahana, G., Govignon-Gion, A., Boitard, S., Dolezal, M. and Pausch, H., 2018. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nature genetics, 50(3), p.362.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Marley, K.B., Kuehn, L.A., Keele, J.W., Wileman, B.W. and Gonda, M.G., 2018. Genetic variation in humoral response to an Escherichia coli O157: H7 vaccine in beef cattle. PloS one, 13(5), p.e0197347.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Smith, J.L., Wilson, M.L., Nilson, S.M., Rowan, T.N., Oldeschulte, D.L., Schnabel, R.D., Decker, J.E. and Seabury, C.M., 2019. Genome-wide association and genotype by environment interactions for growth traits in US Gelbvieh cattle. BMC genomics, 20(1), pp.1-13.
• Type: Other Status: Published Year Published: 2019 Citation: Durbin, H.J. and Decker J.E., 2019. Hair Shedding Scores, Brangus Journal, May 2019. https://issuu.com/gobrangus/docs/2019_may_brangus_journal_web/57
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Rosen, B.D., Bickhart, D.M., Schnabel, R.D., Koren, S., Elsik, C.G., Tseng, E., Rowan, T.N., Low, W.Y., Zimin, A., Couldrey, C. and Hall, R., 2020. De novo assembly of the cattle reference genome with single-molecule sequencing. Gigascience, 9(3), p.giaa021.
• Type: Journal Articles Status: Published Year Published: 2021 Citation: Abrams, A.N., McDaneld, T.G., Keele, J.W., Chitko-McKown, C.G., Kuehn, L.A. and Gonda, M.G., 2021. Evaluating Accuracy of DNA Pool Construction Based on White Blood Cell Counts. Frontiers in Genetics, 12, p.94.
• Type: Journal Articles Status: Published Year Published: 2017 Citation: Whitacre, L.K., Hoff, J.L., Schnabel, R.D., Albarella, S., Ciotola, F., Peretti, V., Strozzi, F., Ferrandi, C., Ramunno, L., Sonstegard, T.S. and Williams, J.L., 2017. Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis. Scientific reports, 7(1), pp.1-9.
• Type: Journal Articles Status: Submitted Year Published: 2021 Citation: Arisman, B.C., Rowan, T.N., Thomas, J.M., Durbin, H.J., Patterson, D.J. and Decker, J.E., 2020. Evaluation of Zoetis GeneMax Advantage genomic predictions in commercial Bos taurus Angus cattle. bioRxiv.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Durbin, H. J., Yampara-Iquise, H., Schnabel, R. D., & Decker, J. E. (2018, May). Impact of early summer hair shedding on susceptibility to fescue toxicosis and heat stress in taurine cattle. Genetics Society of America. Madison, Wisconsin:Genetics Society of America.
• Type: Websites Status: Published Year Published: 2020 Citation: Gonda M. Beef Cattle Breeding Instruction. https://www.sdstate.edu/animal-science/beef-cattle-breeding-instruction
• Type: Journal Articles Status: Under Review Year Published: 2021 Citation: Rowan, T.N., Durbin, H.J., Seabury, C.M., Schnabel, R.D. and Decker, J.E., 2020. Powerful detection of polygenic selection and environmental adaptation in US beef cattle populations. bioRxiv. https://doi.org/10.1101/2020.03.11.988121 Under Review at PLOS Genetics.
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Durbin, H.J., Lu, D., Yampara-Iquise, H., Miller, S.P. and Decker, J.E., 2020. Development of a genetic evaluation for hair shedding in American Angus cattle to improve thermotolerance. Genetics Selection Evolution, 52(1), pp.1-14.
• Type: Journal Articles Status: Under Review Year Published: 2021 Citation: Braz, C.U., Rowan, T.N., Schnabel, R.D. and Decker, J.E., 2020. Extensive genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle. bioRxiv. https://doi.org/10.1101/2020.01.09.900902 Under Review at Scientific Reports.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Decker JE. (2019) Matching Cows Genetics to the Environment Using Genomics. Department of Animal Science, University of Illinois.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Decker JE (2019) Environmental Region-Specific Genomic Prediction in Beef Cattle. Plant and Animal Genome XXVII. (Oral Presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Decker JE, Rowan TN, Nilson S, Durbin HJ, Braz CU, Schnabel RD, Seabury CM. Matching Cows Genetics to the Environment Using Genomics. American Society of Animal Science, July 8, 2019. https://doi.org/10.1093/jas/skz258.067 (Oral Presentation)
• Type: Other Status: Published Year Published: 2021 Citation: Decker J.E. (2021) Matching Cattle Genetics to the Environment. Missouri Red Angus Association Membership Meeting. Springfield, Missouri. April 23, 2021.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Decker JE, Patterson DJ, Arisman B, Rowan TN, Thomas JM, Brown DS, Lamberson WR, et al. National Center for Applied Reproduction and Genomics (NCARG) Evaluates Accuracy of Genomic Prediction in Commercial Angus Cattle. American Society of Animal Science, July 8, 2019. https://doi.org/10.1093/jas/skz258.173 (Oral Presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Decker JE (2020) Matching Cows Genetics to the Environment Using Genomics. Plant and Animal Genome XXVIII (Oral Presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Decker JE (2020) Matching Genetics to Environment Using Genomics Synthesis of results from USDA-NIFA Food Security Grant on Local Adaptation in Beef Cattle. The 6th International Conference of Quantitative Genetics , November 10, 2020. (Oral Presentation)
• Type: Other Status: Published Year Published: 2021 Citation: Decker J.E. (2021) Combining Quantitative Genetics and Population Genomics to Improve Beef Sustainability. University of Guelph CGIL Genetics Seminar. January 22, 2021.
• Type: Other Status: Published Year Published: 2021 Citation: Decker J.E. (2021) Hair Shedding Genetic and Genomic Prediction. NCERA-225 Meeting. January 22, 2021.
• Type: Other Status: Published Year Published: 2020 Citation: Decker J.E. (2020) Impact of genetic adaptation to environment on beef cattle. Southern Section ASAS Extension Seminar. November 11, 2020.
• Type: Other Status: Published Year Published: 2020 Citation: Decker J.E. (2020) Implementing Hair Shedding EPDs. University of Missouri CAFNR Virtual Field Day. https://youtu.be/Jmz9xBGdxH8 September 24, 2020.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Braz CU, de Oliveira HN, Rowan TN, Schnabel RD, Decker JE. Exploring Alternative Genome-Wide Approaches to Analyze SNP Data for Complex Traits in Beef Cattle. Plant and Animal Genome XXVIII San Diego, CA. January 14, 2020.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Durbin HJ, Rowan TN, Miller SP, Decker JE. Leveraging Genotype-by-Environment Interactions across Discrete Environmental Regions to Select More Sustainable Beef Cattle. Plant and Animal Genome XXVIII San Diego, CA. January 13, 2020.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Vargas JC, Kramer L, Tucker J, Hubbell DS III, Powell JG, Lester TD, Backes EA, Anschutz K, Decker JE, Stalder KJ, Rothschild MF, Koltes JE. Blood Traits in Beef Cattle and Their Relationship with Production Traits at Weaning. Plant and Animal Genome XXVIII San Diego, CA. January 13, 2020.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Nilson, SM, Rowan TN, Schnabel RD, and Decker JE. Genomic Predictions for Selecting Locally Adapted Beef Cattle. In Gordon Research Conference Ecological and Evolutionary Genomics. Manchester, NH, 2019.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Rowan, TN, Schnabel RD, and Decker JE. Detecting Signatures of Selection and Local Adaptation in United States Bos Taurus Beef Cattle. In CSHL Biology of Genomes. Cold Spring Harbor, NY, 2019.
• Type: Other Status: Published Year Published: 2020 Citation: Mateescu R. and Decker J.E. Cool Genes for Hot Cattle. NCBA Cattle Industry Convention Cattlemens College, San Antonio, TX. February 5, 2020.
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Chinchilla-Vargas, J., Kramer, L.M., Tucker, J.D., Hubbell III, D.S., Powell, J.G., Lester, T.D., Backes, E.A., Anschutz, K., Decker, J.E., Stalder, K.J. and Rothschild, M.F., 2020. Genetic basis of blood-based traits and their relationship with performance and environment in beef cattle at weaning. Frontiers in genetics, 11, p.717.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Smith, J., Seabury C.M., 2020. Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle. Texas A&M College of Veterinary Medicine Research Symposium, College Station, TX.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Smith, J., Seabury C.M., 2019. Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle. Texas A&M College of Veterinary Medicine Research Symposium, College Station, TX.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Smith, J., Seabury C.M., 2019. Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle. Texas A&M Student Research Week, College Station, TX.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Smith, J., Seabury C.M., 2019. Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle. Plant and Animal Genome Conference 2019, San Diego, CA.
• Type: Theses/Dissertations Status: Published Year Published: 2020 Citation: Rowan, Troy. "Leveraging large scale beef cattle genomic data to identify the architecture of polygenic selection and local adaptation." PhD dissertation., University of Missouri, 2020.
• Type: Theses/Dissertations Status: Published Year Published: 2020 Citation: Durbin, Harly. "Genomics of seasonal hair shedding and ecoregion-specific growth to identify environmentally-adapted beef cattle." PhD Dissertation., University of Missouri, 2020
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Nilson, SM, Rowan TN, Schnabel RD, and Decker JE. Genomic Predictions for Selecting Locally Adapted Beef Cattle. In CSHL Biology of Genomes. Cold Spring Harbor, NY, 2019.
• Type: Theses/Dissertations Status: Published Year Published: 2019 Citation: Abrams, A. 2019. Integration of molecular techniques for the investigation of bovine respiratory disease. PhD Dissertation, South Dakota State University, Brookings.
• Type: Other Status: Published Year Published: 2019 Citation: Durbin HJ, Decker JE. 2019. Hair Shedding Scores: A tool to match cows to their environment. SimTalk 30(2) p. 26 https://issuu.com/asapublications/docs/simtalk_march_2019/28
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Durbin, HJ, Schnabel RD, Rowan TN, Yampara-Iquise H, and Decker JE. Using Citizen Science to Identify Cattle for a Changing Climate. In CSHL Biology of Genomes. Cold Spring Harbor, NY, 2019.
• Type: Other Status: Published Year Published: 2018 Citation: Durbin HJ, Decker JE. 2019. Hair Shedding Scores: A tool to match cows to their environment. Brangus Journal 66(7) p. 18 https://issuu.com/gobrangus/docs/november_2018_brangus_journal_web/18
• Type: Other Status: Published Year Published: 2019 Citation: Durbin, HJ. "Economic Selection Indexes" Mizzou Repro YouTube. https://www.youtube.com/watch?v=qKvuTiBKYNA
• Type: Other Status: Published Year Published: 2019 Citation: Durbin, H. J. 2019. EPDs for environmental adaptation. Thompson Research Center Field Day, Spickard, MO. September, 2019.
• Type: Other Status: Published Year Published: 2018 Citation: Durbin, H. J. 2018. Hair Shedding Scores: A Tool to Select Heat Tolerant Cattle. Thompson Research Center Field Day, Spickard, MO. September, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Durbin, H. J. 2018. Hair Shedding Scores: A Tool to Select Heat Tolerant Cattle. Southwest Research Center Field Day, Mt Vernon, MO. August, 2018.
• Type: Other Status: Published Year Published: 2020 Citation: Durbin H.J. 2020. Using hair shedding scores to select heat tolerant cattle. Southeast Missouri Cattlemen's Spring Meeting, Jackson, MO. 2020.
• Type: Other Status: Published Year Published: 2020 Citation: Durbin H, Decker J. 2020. New hair-shedding EPD will improve profitability through heat tolerance. Angus Beef Bulletin. January 2020. http://www.angusbeefbulletin.com/ArticlePDF/0120-Sorting-Gate.pdf
• Type: Other Status: Published Year Published: 2021 Citation: Durbin HJ, Decker JE. 2020. Hair Shedding Scores in Brangus Cattle. Brangus Journal 69(3) p. 26. https://issuu.com/gobrangus/docs/2021_april_brangus_journal-compressed_2/s/11944019
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Taylor, Jeremy F., Kristen H. Taylor, and Jared E. Decker. "Holsteins are the genomic selection poster cows." Proceedings of the National Academy of Sciences (2016): 201608144.
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Taylor, Jeremy F., Lynsey K. Whitacre, Jesse L. Hoff, Polyana C. Tizioto, JaeWoo Kim, Jared E. Decker, and Robert D. Schnabel. "Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals." Genetics Selection Evolution 48, no. 1 (2016): 59
• Type: Theses/Dissertations Status: Published Year Published: 2016 Citation: Wilson, Miranda. "Multivariate genome-wide association studies and genomic predictions in multiple breeds and crossbred animals." MS thesis., University of Missouri--Columbia, 2016.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Wilson, Miranda L, Robert D. Schnabel, Robert Weaber, Jeremy F. Taylor, and Jared E. Decker. "Using Haplotype Based Models for Genomic Predictions in Crossbred Animals." In The Allied Genetics Conference. Orlando, FL. July 13-17, 2016.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Whitacre Lynsey K., Mark L. Wildhaber, Gary S. Johnson, J.M. Downs, T. Mhlanga-Mutangadura, Vernon M. Tabor, D. Fenner, and Jared E. Decker. "Genomic Variation and Population Structure of the Threatened Neosho Madtom (Noturus placidus)." In The Allied Genetics Conference. Orlando, FL. July 13-17, 2016.
• Type: Websites Status: Published Year Published: 2021 Citation: A Steak in Genomics. http://blog.steakgenomics.org/, 2016-2021
• Type: Websites Status: Published Year Published: 2021 Citation: eBEEF.org, Beef Genetics eXtension Community of Practice. 2016-2021
• Type: Other Status: Published Year Published: 2017 Citation: Decker, Jared E. and Jane Parish. Hair shedding scores: A tool to select heat tolerant cattle. eBEEF.org, an eXtention Community of Practice http://articles.extension.org/pages/74069/hair-shedding-scores:-a-tool-to-select-heat-tolerant-cattle.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Rowan T. N., S. M. Nilson, H. J. Durbin, C. M. Seabury, R. D. Schnabel, J. E. Decker. (2017) Local genetic adaptation in United States Bos taurus cattle. Gordon Research Conference on Quantitative Genetics and Genomics, Galveston, TX. February 26-March 3, 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Hoff J.L., J. E. Decker, R. D. Schnabel, C. M. Seabury, H. L. Neibergs, R. Hagevoort, J. F. Taylor and the Bovine Respiratory Disease Complex Coordinated Agricultural Project Research Team. (2017) Enhancement of QTL-Mapping and Genomic Prediction for Bovine Respiratory Disease Using Sequence Imputation and Feature Selection. Plant and Animal Genome XXV. San Diego, CA. January 14-18, 2017.
• Type: Theses/Dissertations Status: Published Year Published: 2017 Citation: Whitacre L. 2017. Alternative applications of whole genome de novo assembly in animal genomics. Diss. University of Missouri-Columbia, 2017.
• Type: Journal Articles Status: Published Year Published: 2017 Citation: MacNeil, M. D., F. F. Cardoso, and E. Hay. 2017. Genotype by environment interaction effects in genetic evaluation of preweaning gain for Line 1 Hereford cattle from Miles City, Montana1. J. Anim. Sci. 95:38333838. doi:10.2527/jas.2017.1829. Available from: https://academic.oup.com/jas/article/95/9/3833/4702432
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. Sho-Me Group Inc. Hermann, Missouri. February 2, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. Oklahoma Cattlemens Meeting, Dewey, OK. January 17, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. KMOA Cattlemens Meeting, Springfield, MO. January 18, 2018.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Decker J. E., M. L. Wilson, R.D. Schnabel, R. Weaber, J. F. Taylor. (2017) Using haplotype-based models and feature selection for genomic predictions in crossbred animals and multiple breeds. Gordon Research Conference on Quantitative Genetics and Genomics. February 26-March 3, 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Hoff J., J. E. Decker, R. D. Schnabel, P. Tizioto, C. Seabury, H. Neibergs, R. Hagevoort, the Bovine Respiratory Disease Consortium, J. F. Taylor. (2017) Enhancement of QTL-Mapping and Genomic Prediction for Bovine Respiratory Disease using Sequence Imputation and Feature Selection. Gordon Research Conference on Quantitative Genetics and Genomics, Galveston, TX. February 26-March 3, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Matching Genetics to Environment. Boone County Cattlemen's meeting, Columbia, MO. December 5, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Durbin, H. J. and J. E. Decker. 2017. Hair Shedding in Cattle. Thompson Research Center Field Day, Spickard, MO. September 21, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Local Adaptation in Cattle. Southwest Research Center Field Day, Mt. Vernon, MO. September 9, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Understanding and Using Breed Selection Indexes. Texas Beef Cattle Short Course, College Station, TX. August 7, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Local genetic adaptation project. Beef Improvement Federation Symposium, Athens, GA. June 1, 2017.
• Type: Other Status: Published Year Published: 2018 Citation: Lyndorff, C.R. (2018) Composites deserve more acceptance. SimTalk. January 2018. https://issuu.com/asapublications/docs/january_simtalk_2018/22
• Type: Other Status: Published Year Published: 2018 Citation: Erickson, G. (2018) Youth describes how beef producers can excel in the 21st century. BEEF Daily. January 10 2018. https://www.beefmagazine.com/ranching/youth-describes-how-beef-producers-can-excel-21st-century
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Crum, T.E., Schnabel, R.D., Decker, J.E., Regitano, L.C. and Taylor, J.F., 2019. CRUMBLER: a tool for the prediction of ancestry in cattle. PloS one, 14(8), p.e0221471.

Progress 03/01/18 to 02/28/19

Outputs
Target Audience:Using curriculum development, internships, popular press, social media, industry presentations, and scientific presentations we reach a broad audience. That audience includes breed associations, allied industry partners, extension professionals, farmers, ranchers, graduate students, undergraduate students, youth interested in beef cattle, animal scientists, and genomic scientists. Changes/Problems:We had issues identifying software that could fit multivariate models to the scale needed in this project. This has been resolved with the use of BLUPF90. We have had some minor issues getting certain models to converge in BLUPF90. We are able to resolve this challenge by slightly changing the models. However, there are more severe issues that may require a no cost extension. 1) Anna Ball was leading the evaluation of Objective 3, the educational efforts. In July 2019, Dr. Ball took an adminstrative position at the University of Illinios and is no longer a member of the proposal. This may require a second no-cost extension to complete the educational work. 2) The bovine reference genome (UCD-ARS 1.2) was released much later that expected. To further complicate this, the latest run of the 1000 Bull Genomes data was released much later than expected. It would be scientifically most responsible to use the current, largest and most accurate genomic resources to complete this research. This issume may also require a second no-cost extension. What opportunities for training and professional development has the project provided?The grant provided training and professional development for eight graduate students. The three graduate students at the University of Missouri attended the Genetic Society of America's Population, Evolutionary, and Quantative Genetics Conference in Madison, Wisconsin. This conference is significant because it increased the breadth of the students knowledge outside of that typically addressed in agriculture settings. Graduate students also attended Beef Improvement Federation Symposium in Fort Collins, CO, 11th BIF Genetic Prediction Workshop in Kansas City, MO, and Troy Rowan attended the International Plant and Animal Genome Conference in San Diego, CA, supported by an NSRP-8 Jorgensen Travel Award in Bioinformatics. Attendance at these conferences exposed graduate students to the latest in beef cattle and animal genomics research while providing a forum for networking with leaders in the field. Graduate students also had several opportunities to present to audiences of beef producers. This taught them how to present complex topics to lay audiences. To date, the grant has provided training opportunities for three graduate students at Texas A&M as follows: Johanna Smith (B.S., PhD Candidate); Miranda Wilson (M.S., PhD Candidate); David Oldeschulte (B.S., PhD Candidate). Johanna Smith has been a lead graduate student; with mentoring by a more senior student (Miranda Wilson M.S.). Ms Wilson has provided analytical support and support for data processing, as well as QTL alignment. Mr. Oldeschulte has provided general programming support (i.e., python scripting) for data compilation, manipulation, and visualization How have the results been disseminated to communities of interest?Popular press articles were written to educate beef producers about the topic. Decker, Troy Rowan, and Harly J. Durbin published public-interest pieces on initial outcomes of local adaptation research in the SimTalk magazine. SimTalk is distributed to thousands of registered Simmental breeders and commercial cattle producers nationwide. Extension presentations by members of the group have reached hundreds of producers across Missouri and surrounding states. Presentations were made at several national meetings, including Beef Improvement Federdation Symposium in 2018 and Applied Reproductive Strategies in Beef Cattle conference in 2018. Scientific presentations were also made. Graduate students presented posters on research directly related to this project at the PEQG meeting in Madison, WI. Jared Decker and Troy Rowan presented talks related to objectives 1 & 2 at the Plant and Animal Genome Conference. These presentations reached hundreds of scientists working in a diverse range of fields: from agricultural genomics to model organisms to evolutionary and quantitative genetics. A preprint of our imputation work was posted on bioRxiv. GxE GWAS was submitted for publication. Our group has presented at multiple youth-focused Extension field days (Southwest Center and Bradford Center). At these events, graduate students talked generally about best practices for using selection tools like EPDs and genomics as well as ongoing research related to this project. Our group's graduate students also developed a hands-on genetics workshop for high school students at the University of Missouri's Animal Science Experience Day. Graduate students also developed and administered a written test and practical for the genetics section of the University of Missouri's Academic Decathlon. John Tummons conducted two statewide workshops for agriculture teachers and state education leaders to roll out the youth curriculum What do you plan to do during the next reporting period to accomplish the goals?We will continue to analyze the three breed datasets to identify additional loci contributing to local adaptation. We will use Generation Proxy Selection Mapping, a novel method for detecting alleles changing frequency in a region-specific manner. Environmental association analyses and GxE GWAS will be repeated with sequence-level imputed genotypes (30 million SNPs) to pinpoint possible causal variants. As we conclude analyses, our focus will shift towards preparing high-impact publications of our results. Our group will attend multiple meetings where we will continue to disseminate our results to the wider scientific community. We have identified more effective software for fitting region-specific genomic predictions (BLUPF90). This is allowing us to fit more sophesticated and appropriate models to create region-specific genomic predictions. We are currently analyzing Red Angus data, and will be replicating this in Simmental and Gelbvieh. We are analyzing Red Angus growth data and Gelbvieh carcass data at Texas A&M to identify genotype-by-environment associations. At the University of Missouri, we are analyzing Simmental growth data using GxE GWAS and variance GWAS to identify genotype-by-environment interactions. The undergraduate online applied beef breeding course will again be offered at SDSU. Extension presentations will continue to be an important outlet for delivering results of this research to producers in the field.

Impacts
What was accomplished under these goals? At the University of Missouri, we continued to collect and analyze data for objectives 1 and 2. Thousands of additional hair shedding phenotype and genotype data were collected. We continued to assess different models for creating region-specific genomic predictions. Identification of signatures of selection either in a time-specific or environment-specific manner were very successful. We continue to refine these analyses and prepare for presentations and publication. Using 850K imputed genotypes, we have identified dozens of genomic regions associated with continuous environmental variables (temperature, precipitation, and elevation) and discrete environmental zones of the United States. The genomic architecture underlying local adaptation appears to be quite complex, controlled by hundreds of small-effect loci across the genome that largely differ between the three breeds analyzed (Red Angus, Simmental, and Gelbvieh). One major shared signature of local adaptation was identified in all three datasets. Loci identified in local adaptation selection scans have been added to the newest version of GeneSeek's genomic selection genotyping chip. This will allow potentially adaptive variants to be directly genotyped in thousands of individuals. Directly genotyping these variants will benefit the future implementation of region-specific genomic predictions by breed associations. Among the three main goals of the project, the team members as Texas A&M have focused on objective 1, which is to identify genomic variants or loci responsible for regional adaptation. We used an analytical approach to genome-wide association that involves the investigation of genotype-by-environment (GxE) interactions. Prior to March 1 2019, we detected significant GxE interactions for growth traits in U.S. Gelbvieh beef cattle (Smith et al., 2019), and began work in Red Angus. We have detected pleiotropic QTL across several growth traits (BW, WW, YW) for U.S. Gelbvieh and Red Angus beef cattle; several of which were also detected for feed efficiency and growth traits in U.S. Angus, Hereford, and SimAngus beef cattle (Smith et al., 2019; Seabury et al. 2017, PMID: 28521758). In addition to growth traits in U.S. Gelbvieh and Red Angus (BW, WW, YW), we have also investigated GxE interactions in relation to Gelbvieh carcass traits. For every trait and U.S. beef breed investigated to date, we have detected significant genotype-by-environment interactions, thus identifying specific genomic variants responsible for regional adaptation(s). Within the next calendar year we plan to submit all current manuscripts in preparation, and also investigate genomic predictions with and without the detected GxE interactions. The undergraduate curriculum was one again offered as an online course at SDSU by Michael Gonda. The typical evaluation data was collected as part of this offering. A 4-lesson youth curriculum was written, pilot tested, and released to 4-H and FFA instructors nationwide. The curriculum includes a pre-post test, and each lesson includes a lesson plan, student reference, assessment, power point, and lab activity. We invited 11 high school agriculture teachers and state directors of 4-H youth livestock programming to pilot the curriculum. We used the evaluation to revise the curriculum, then shared online at https://missouri.box.com/s/b8pa2kho9ankgrq18165nhuvbfxvngyf. The curriculum is currently being used by both preservice and inservice agriculture teachers across Missouri

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Nilson, S. M., Rowan, T. N., Seabury, C. M., Schnabel, R. D., & Decker, J. E. (2018, May). Developing environmental region-specific genomic predictions for beef cattle breeds. Genetics Society of America. Madison, Wisconsin: Genetics Society of America.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Durbin, H. J., Yampara-Iquise, H., Schnabel, R. D., & Decker, J. E. (2018, May). Impact of early summer hair shedding on susceptibility to fescue toxicosis and heat stress in taurine cattle. Genetics Society of America. Madison, Wisconsin:Genetics Society of America.
• Type: Websites Status: Published Year Published: 2019 Citation: A Steak in Genomics. http://blog.steakgenomics.org/
• Type: Websites Status: Published Year Published: 2018 Citation: eBEEF.org
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Neibergs, H.L., Kiser, J.N., Neupane, M., Seabury, C.M., Taylor, J.F., Cornmesser, M.A., McGuirk, S., Blackburn, R., Consortium, B.R.D. and Womack, J.E., 2018. 204 Genome-Wide Association Analysis Identifies QTL Associated with Clinical and Sub-Clinical Bovine Respiratory Disease. Journal of Animal Science, 96(suppl_2), pp.108-109.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Yurchenko, A.A., Daetwyler, H.D., Yudin, N., Schnabel, R.D., Vander Jagt, C.J., Soloshenko, V., Lhasaranov, B., Popov, R., Taylor, J.F. and Larkin, D.M., 2018. Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation. Scientific reports, 8.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Taylor, J.F., Schnabel, R.D. and Sutovsky, P., 2018. Identification of genomic variants causing sperm abnormalities and reduced male fertility. Animal reproduction science, 194, pp.57-62.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Taylor, J.F., Schnabel, R.D. and Sutovsky, P., 2018. Genomics of bull fertility. animal, 12(s1), pp.s172-s183.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Bouwman, A.C., Daetwyler, H.D., Chamberlain, A.J., Ponce, C.H., Sargolzaei, M., Schenkel, F.S., Sahana, G., Govignon-Gion, A., Boitard, S., Dolezal, M. and Pausch, H., 2018. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nature genetics, 50(3), p.362.
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Marley, K.B., Kuehn, L.A., Keele, J.W., Wileman, B.W. and Gonda, M.G., 2018. Genetic variation in humoral response to an Escherichia coli O157: H7 vaccine in beef cattle. PloS one, 13(5), p.e0197347.
• Type: Journal Articles Status: Submitted Year Published: 2019 Citation: Johanna L. Smith, Miranda L. Wilson, Sara M. Nilson, Troy N. Rowan, David L. Oldeschulte, Robert D. Schnabel, Jared E. Decker and Christopher M. Seabury*. Genome-wide association and genotype-by-environment interactions for growth traits in U.S. Gelbvieh cattle. BMC Genomics in press 2019.
• Type: Journal Articles Status: Under Review Year Published: 2018 Citation: Crum, T. E., Schnabel, R. D., Decker, J. E., Regitano, L. C., & Taylor, J. F. (2018). CRUMBLER: A tool for the Prediction of Ancestry in Cattle. bioRxiv, 396341. http://doi.org/10.1101/396341
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Gandolfi B., Alhaddad H., Abdi M., Bach L.H., Creighton E.K., Davis B.W., Decker J.E., Dodman N.H., Ginns E.I., Grahn J.C., Grahn R.A., Haase B., Haggstrom J., Hamilton M.J., Helps C.R., Kurushima J.D., Lohi H., Longeri M., Malik R., Meurs K.M., Montague M.J., Mullikin J.C., Murphy W.J., Nilson S.M., Pedersen N.C., Peterson C.B., Rusbridge C., Saif R., Shelton G.D., Warren W.C., Wasim M., Lyons L.A. (2018). Applications and efficiencies of the first cat 63K DNA array. Scientific Reports, 8, 7024. http://doi.org/10.1038/s41598-018-25438-0
• Type: Journal Articles Status: Published Year Published: 2018 Citation: Braz, C.U., Taylor, J.F., Decker, J.E., Bresolin, T., Espigolan, R., Garcia, D.A., Gordo, D.G.M., Magalh�es, A.F.B., de Albuquerque, L.G. and de Oliveira, H.N., 2018. Polymorphism analysis in genes associated with meat tenderness in Nelore cattle. Meta Gene, 18, pp.73-78.
• Type: Journal Articles Status: Submitted Year Published: 2019 Citation: Rowan, T.N., Hoff, J.L., Crum, T.E., Taylor, J.F., Schnabel, R.D. and Decker, J.E., 2019. A Multi-Breed Reference Panel and Additional Rare Variation Maximizes Imputation Accuracy in Cattle. bioRxiv, p.517144.
• Type: Journal Articles Status: Under Review Year Published: 2019 Citation: Hoff, J.L., Decker, J.E., Schnabel, R.D., Seabury, C.M., Neibergs, H.L. and Taylor, J.F., 2019. QTL-mapping and genomic prediction for bovine respiratory disease in US Holsteins using sequence imputation and feature selection. BMC genomics, 20(1), p.555.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). EPDs 101: Use Information to Improve Your Herd. The Cattlemen
• Type: Other Status: Published Year Published: 2018 Citation: Crum, T., & Decker, J. E. (2018). Breed Composition: its like chocolates, you can't tell what's inside just by looking...SimTalk, 26, 3439. https://issuu.com/asapublications/docs/march_2018_simtalk/36
• Type: Other Status: Published Year Published: 2018 Citation: Rowan, T., & Decker, J. E. (2018). Searching for Environmental Adaptation in Beef Cattle. SimTalk, 25, 2829.https://issuu.com/asapublications/docs/late_20fall_20simtalk_202017/30
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). Do We Overvalue Accuracy? MWI Producer Outlook.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018). EPDs and reasonable expectations in commercial crossbred operations. In . Presented at the Applied Reproductive Strategies in Beef Cattle, Ruidoso, New Mexico.http://www.appliedreprostrategies.com/2018/newsroom.html#JaredDecker2018
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Knickmeyer, E. R., Thomas, J. M., McLean, M., Cierna, L., Locke, J. W., Bonacker, R. C., ... Patterson, D. J. (2018). The University of Missouri internship in bovine reproductive management. In . Presented at the American Society of AnimalScience Annual Meeting, Vancouver, BC.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Patterson, D. J., Brown, D. S., Smith, M. F., Lamberson, W. R., Taylor, J. F., Spencer, T. E., ... Decker, J. E. (2018). The National Center for Applied Reproduction and Genomics (NCARG) in beef cattle. In . Presented at the American Society of Animal Science Annual Meeting., Vancouver, BC
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018, June). Impact of Adaptability Grant: Identifying Local Adaptation and Creating Region-specificGenomic Predictions in Beef Cattle. Beef Improvement Federation. Loveland, Colorado: Beef Improvement Federation.http://www.bifconference.com/bif2018/newsroom.html
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Decker, J. E. (2018, April). Integrating Genomics into the US Beef Industry. Department of Animal Science, North Carolina State University. Raleigh, North Carolina: Department of Animal Science, North Carolina State University
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Rowan, T. N., Durbin, H. J., Nilson, S. M., Seabury, C. M., Schnabel, R. D., & Decker, J. E. (2018, May). Local genetic adaptation in United States Bos taurus beef cattle. Genetics Society of America. Madison, Wisconsin: Genetics Society of America.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Shaffer, W., Patterson, D. J., Schnabel, R. D., Taylor, J. F., & Decker, J. E. (2018, May). Genomic prediction of puberty and reproductive traits in beef cattle and its accuracy in admixed individuals. Genetics Society of America. Madison, Wisconsin: Genetics Society of America

Progress 03/01/17 to 02/28/18

Outputs
Target Audience:Using curriculum development, internships, essay contests, popular press, social media, and industry presentations we reach a broad audience. That audience includes breed associations, allied industry partners, extension professionals, farmers, ranchers, graduate students, undergraduate students, and youth interested in beef cattle. Changes/Problems:The unanticipated delay in the release of the bovine reference genome has slowed us down in some regards. However, we have pushed forwards with several analyses on the previous version of the reference genome. The re-analysis of sequence data on the new reference genome has also limited our use of whole-genome imputed data. However, we do anticipate being able to complete these analyses on a timely basis. We have also used a set of 850,000 SNPs for many analyses, which have provided very detailed results. What opportunities for training and professional development has the project provided?The grant has provided support for 3 graduate students to attend scientific conferences and industry meetings. This allow the graduate students to network with both researchers and cattle producers. Additionally, students as South Dakota State and University of Missouri have gained valuable experience in curriculum design. How have the results been disseminated to communities of interest?We have given presentations at scientific meetings, such as the Gordon Research Conference on Quantitative Genetics and Genomics. Dr. Decker has also presented at several industry meetings, including the Beef Improvement Federation Symposium in Athens, GA. What do you plan to do during the next reporting period to accomplish the goals?In the next reporting period, results will be presented at the Population, Evolution, and Quantitative Genetics Conference in Madison, WI and at the Beef Improvement Federation Symposium. Analyses of hair shedding, signatures of selection, genotype-by-environment GWAS, and genomic prediction will continue. Multiple publications will be submitted in year 3, in addition to the conference presentations.

Impacts
What was accomplished under these goals? Objective 1. In year two, we continued to work onour pipeline to impute SNP assay genotypes to tens of millions of variants from whole genome resequencing data. We completed preliminary selection scans using FLK, pca-selection,associations with environmental variables, and birth date selection mapping in Simmental and Gelbvieh cattle. We discovered signal across the entire genome for local adaptationselection. Objective 2. Researchers at the University of Missouri and Texas A&M completed gene-by-environment genome-wide association analyses in over 10,000 Gelbvieh cattle. Our hair shedding research continued. We continued to collect phenotypes and genotyped additional animals, bringing the total to over 6,000 cattle. Weperformed preliminary genome-wide association analyses of hair shedding. We also created preliminary genomic prediction analyses with the same Gelbvieh data set. Objective 3. We continued toanalyze and interpret the results of our producer survey. We completed survey collection. Design of youth curriculum began in year two. In the summer of year two, Dr. Gonda taught the first round of theundergraduate curriculum at South Dakota State University. Wetrained our second set of interns regarding the use of EPDs and indexes in beef cattle. Finally, we will published the results of our first essay contest.

Publications

• Type: Websites Status: Published Year Published: 2017 Citation: A Steak in Genomics. http://blog.steakgenomics.org/
• Type: Websites Status: Published Year Published: 2017 Citation: eBEEF.org
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Decker J. E., M. L. Wilson, R.D. Schnabel, R. Weaber, J. F. Taylor. (2017) Using haplotype-based models and feature selection for genomic predictions in crossbred animals and multiple breeds. Gordon Research Conference on Quantitative Genetics and Genomics. February 26-March 3, 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Hoff J., J. E. Decker, R. D. Schnabel, P. Tizioto, C. Seabury, H. Neibergs, R. Hagevoort, the Bovine Respiratory Disease Consortium, J. F. Taylor. (2017) Enhancement of QTL-Mapping and Genomic Prediction for Bovine Respiratory Disease using Sequence Imputation and Feature Selection. Gordon Research Conference on Quantitative Genetics and Genomics, Galveston, TX. February 26-March 3, 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Rowan T. N., S. M. Nilson, H. J. Durbin, C. M. Seabury, R. D. Schnabel, J. E. Decker. (2017) Local genetic adaptation in United States Bos taurus cattle. Gordon Research Conference on Quantitative Genetics and Genomics, Galveston, TX. February 26-March 3, 2017.
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Hoff J.L., J. E. Decker, R. D. Schnabel, C. M. Seabury, H. L. Neibergs, R. Hagevoort, J. F. Taylor and the Bovine Respiratory Disease Complex Coordinated Agricultural Project Research Team. (2017) Enhancement of QTL-Mapping and Genomic Prediction for Bovine Respiratory Disease Using Sequence Imputation and Feature Selection. Plant and Animal Genome XXV. San Diego, CA. January 14-18, 2017.
• Type: Theses/Dissertations Status: Published Year Published: 2017 Citation: Whitacre L. 2017. Alternative applications of whole genome de novo assembly in animal genomics. Diss. University of Missouri-Columbia, 2017.
• Type: Journal Articles Status: Published Year Published: 2017 Citation: MacNeil, M. D., F. F. Cardoso, and E. Hay. 2017. Genotype by environment interaction effects in genetic evaluation of preweaning gain for Line 1 Hereford cattle from Miles City, Montana1. J. Anim. Sci. 95:38333838. doi:10.2527/jas.2017.1829. Available from: https://academic.oup.com/jas/article/95/9/3833/4702432
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. Sho-Me Group Inc. Hermann, Missouri. February 2, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. Oklahoma Cattlemens Meeting, Dewey, OK. January 17, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2018. Genetics for Cow Efficiency and Profit. KMOA Cattlemens Meeting, Springfield, MO. January 18, 2018.
• Type: Other Status: Published Year Published: 2018 Citation: Decker, J. E. 2017. Matching Genetics to Environment. Boone County Cattlemen's meeting, Columbia, MO. December 5, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Durbin, H. J. and J. E. Decker. 2017. Hair Shedding in Cattle. Thompson Research Center Field Day, Spickard, MO. September 21, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Local Adaptation in Cattle. Southwest Research Center Field Day, Mt. Vernon, MO. September 9, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Understanding and Using Breed Selection Indexes. Texas Beef Cattle Short Course, College Station, TX. August 7, 2017.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, J. E. 2017. Local genetic adaptation project. Beef Improvement Federation Symposium, Athens, GA. June 1, 2017.
• Type: Other Status: Published Year Published: 2018 Citation: Lyndorff, C.R. (2018) Composites deserve more acceptance. SimTalk. January 2018. https://issuu.com/asapublications/docs/january_simtalk_2018/22
• Type: Other Status: Published Year Published: 2018 Citation: Erickson, G. (2018) Youth describes how beef producers can excel in the 21st century. BEEF Daily. January 10 2018. https://www.beefmagazine.com/ranching/youth-describes-how-beef-producers-can-excel-21st-century

Progress 03/01/16 to 02/28/17

Outputs
Target Audience:Using curriculum development, internships, essay contests, popular press, and social media we will reach a broad audience. That audience will include breed associations, allied industry partners, extension professionals, farmers, ranchers, graduate students, undergraduate students, and youth interested in beef cattle. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?This grant has helped train four PhD students, one Masters student, and one undergraduate student. How have the results been disseminated to communities of interest?In the first year of the grant, PD Decker gave 21 presentations to approximately 1,000 people on beef genetics, genomics or local adaptation. Highlights include presentations at the GeneSeek Innovation Seminar, American Simmental Association Fall Focus, Beefmaster Breeders United Convention, and Montana Stockgrowers Convention. We have published a fact sheet titled "Hair shedding scores: A tool to select heat tolerant cattle" on eBEEF.org, an eXtention Community of Practice (http://articles.extension.org/pages/74069/hair-shedding-scores:-a-tool-to-select-heat-tolerant-cattle). We also keep producers and industry professionals aware of project developments through PD Decker's blog, A Steak in Genomics. A Steak in Genomics had 11,349 page views in the first year of the grant. What do you plan to do during the next reporting period to accomplish the goals?YEAR TWO: Objective 1. In year two, we will finish creating our pipeline to impute SNP assay genotypes to tens of millions of variants from whole-genome resequencing data. Our graduate research assistants have already demonstrated the ability to develop computer pipelines. We will also complete selection scans using FLK, TreeSelect, and associations with environmental variables. Most of the effort in year two will be towards interpreting the results of these analyses. YEAR TWO: Objective 2. We will finish up analyses looking at which traits make cows successful or unsuccessful and look for gene-by-environment interactions with phenotypic records of these traits. We will also use variance analysis to look for traits with a strong genetic-by-environment variance term. Researchers at the University of Missouri and Texas A&M will also focus on gene-by-environment genome-wide association analyses in year two. One of the results of the cow failure/success outcome in year one has helped us identify fat thickness as an important trait to analyze for gene-by-environment associations. In the second half of year two, we will perform genome-wide association analyses of hair shedding. Finally, we will begin creating region-specific genomic predictions of production traits strongly affected by the environment. YEAR TWO: Objective 3. We will analyze and interpret the results of our producer survey. This will not only impact the design of our youth curriculum, but will also help refine our undergraduate curriculum. Design of youth curriculum will begin in earnest in year two. We will also test and refine this curriculum in year two. In the summer of year two, we will also have the opportunity to teach our undergraduate curriculum at South Dakota State University. We will also train our second set of interns. Finally, we will published the results of our first essay contest and in December through February of year two we will deploy our second essay contest.

Impacts
What was accomplished under these goals? Objective 1 We have downloaded and analyzed data from the PRISM database. In our exploratory analyses, we realized that when creating geographic clusters, many of the climate measures provided redundant information. In our analysis, we used 30-year Normal Annual Precipitation, 30-year Normal Annual Temperature, and Terrain Elevation. Using three clusters was the most strongly support from k-means analysis. In order to compare with historical analyses and to have more homogenous regions, we also clustered the United States into nine regions based on these three variables. We can match data to its geographic location either via its address or via zip code. We have also created a computer pipeline in which we can process, quality control, phase and merge large genotype data sets automatically in a manner of minutes. We have already run the genotype data from the American Simmental Association through this pipeline. In three minutes and eighteen seconds, we processed seven assays, which included 11,418 samples. It takes between 15 to 50 seconds to process an individual assay. We have started to run selection scans with the 10,935 Simmental samples genotyped at 919,968 SNPs that passed our quality filters and imputation steps. We first run principal component analysis. This exploratory analysis allows us to make sure no errors occurred during preprocessing of the data and there are no anomalies in the data. For instance, if the allele coding is wrong for one of the assays, we will spot this issue when visualizing the principal component analysis. Further, the principal component analysis identifies population and family structure within the data. The EIGENSOFT software package contains a program that can take the SNP loadings from the principal component analysis and test whether the SNPs have diverged in allele frequency more than expected due to drift, and are thus under selection. These loci are under selection between different breeds (Angus versus Simmental) or between different families within the Simmental breed. If we find overlap between these between-family selected variants and the between-region selected variants, we know that we need to be cautious in assigning a local adaptation function to these variants, as they may simply be family differences. Objective 2 We have completed the initial analysis comparing cows that successfully reproduce for three consecutive years versus those that fail to rebreed after having one calf with data from the American Hereford Association. Birth weight (BW), calving ease direct (CED), and calving ease maternal (CEM) which are measures of dystocia (calving difficulties) are associated with sustained reproductive success. If a cow's reproductive tract is damaged during parturition, it is more difficult for her tract to heal and for her to rebreed in a timely manner. Thus, these results agree with our current understanding. However, we see cattle producers put considerable emphasis on calving ease direct, but these results suggest that calving ease maternal is just as important. The association between maternal milk and sustained reproductive success may be an effect of breeders selection decisions for increased milking potential of their cows. We often hear beef breeders discussing the selection of "easier fleshing" cattle. We interpret the fat thickness EPD's association with sustained reproductive success to be a quantitative measure of "easier fleshing". Although fat thickness is typically considered a carcass trait, these results suggest that it may have an important impact on a cow's ability to store energy as fat. However, we did not see any regional trends when we plotted the difference in average EPD values between the failure and success cows. This implies that there is no difference is the additive genetic merit (EPD) between cows in different regional environments. However, national cattle evaluations used to estimate EPDs only model additive genetic effects and any nonadditive or genetic interaction effects add to the residual variance. Thus, gene-by-environment interactions would not be included in the EPDs and would not be observed. However, if we plotted phenotypic differences (rather than EPD differences), we may observe regional differences. Through our team's online presence (A Steak in Genomics) and with help from our breed association partners, we have recruited approximately 8,000 cattle to participate in our hair shedding research. We have created what we believe is a win-win situation. Beef breeders collect hair shedding scores on their cattle for three years in a row and send a DNA sample (either hair card or blood card) to the University of Missouri. We then send these samples off for genotyping, and use the hair shedding data and genotypes to perform a genome-wide association study of hair shedding. We also share these genotypes with the participating breed associations, and these breed associations use the data to produce genomic-enhanced EPDs. Thus, by participating in the project, the beef producers get free genomic-enhanced EPDs. We have already received the first year of hair shedding scores, DNA cards, and genotyping at GeneSeek has been completed for 2,186 of these samples. We continue to work with producers to complete submission of hair shedding scores and DNA samples. We are steadily inventorying these samples at the University of Missouri and submitting them for genotyping at GeneSeek. Objective 3 In order to create a youth curriculum that accurately corrects misconceptions in the beef industry, we first needed a clear picture of the attitudes and practices of beef breeders. We have created a survey that is a stable, reliable, and valid instrument to capture attitudes and barriers toward EPD use. The survey was developed in the fall of 2016 and was tested with producers at a regional field day in November to estimate reliability on the summated constructs and to gain feedback. In December and January, we contacted a group of agriculture teachers who were beef producers. We conducted a test-retest (same survey, two different times) with those producers to estimate the stability of the non-summated constructs and again asked for feedback. The survey is now completely developed and we are in the process of launching response collection. This survey will provide insight into the barriers of EPD use and will inform many decision makers and industry professions on how to help beef producers. We launched our first essay contest. We secured sponsorships from GeneSeek and Zoetis so that we could offer a first prize of $500, a second prize of $300, and a third prize of $200. The blog post (http://blog.steakgenomics.org/2016/12/essay-contest.html) announcing the essay contest has received 1,060 page views. Twenty youth have submitted essays to the contest, answering the prompt "What does it mean to be a beef breeder in the 21st century?" Members of the grant team, advisory board members, and extension professionals will judge essays. The winning essay will be published in one of BEEF Magazine's online newsletters and the second through fifth place essays will be published on A Steak in Genomics. Development has started on our undergraduate curriculum. The syllabus and lesson plans for three of the nine modules have been created. The curriculum will be taught for the first time the summer of 2017 at South Dakota State University. In 2016, we supported our first cohort of F.B. Miller interns. These interns were taught the basics of how EPDs work, why selection based on EPDs is superior to phenotypic selection, real-world examples of increased production from using EPDs, the advantages of genomic enhanced EPDs, maximizing profit by selecting animals using economic selection indexes, the simplicity of using selection indexes, and practice in selecting artificial insemination sires using selection indexes.

Publications

• Type: Journal Articles Status: Published Year Published: 2016 Citation: Taylor, Jeremy F., Kristen H. Taylor, and Jared E. Decker. "Holsteins are the genomic selection poster cows." Proceedings of the National Academy of Sciences (2016): 201608144.
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Taylor, Jeremy F., Lynsey K. Whitacre, Jesse L. Hoff, Polyana C. Tizioto, JaeWoo Kim, Jared E. Decker, and Robert D. Schnabel. "Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals." Genetics Selection Evolution 48, no. 1 (2016): 59
• Type: Theses/Dissertations Status: Published Year Published: 2016 Citation: Wilson, Miranda. "Multivariate genome-wide association studies and genomic predictions in multiple breeds and crossbred animals." MS thesis., University of Missouri--Columbia, 2016.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Wilson, Miranda L, Robert D. Schnabel, Robert Weaber, Jeremy F. Taylor, and Jared E. Decker. "Using Haplotype Based Models for Genomic Predictions in Crossbred Animals." In The Allied Genetics Conference. Orlando, FL. July 13-17, 2016.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Whitacre Lynsey K., Mark L. Wildhaber, Gary S. Johnson, J.M. Downs, T. Mhlanga-Mutangadura, Vernon M. Tabor, D. Fenner, and Jared E. Decker. "Genomic Variation and Population Structure of the Threatened Neosho Madtom (Noturus placidus)." In The Allied Genetics Conference. Orlando, FL. July 13-17, 2016.
• Type: Websites Status: Published Year Published: 2016 Citation: A Steak in Genomics. http://blog.steakgenomics.org/
• Type: Websites Status: Published Year Published: 2016 Citation: eBEEF.org, Beef Genetics eXtension Community of Practice.
• Type: Other Status: Published Year Published: 2017 Citation: Decker, Jared E. and Jane Parish. Hair shedding scores: A tool to select heat tolerant cattle. eBEEF.org, an eXtention Community of Practice http://articles.extension.org/pages/74069/hair-shedding-scores:-a-tool-to-select-heat-tolerant-cattle.