Research Project: Genomes to Phenomes in Beef Cattle Research

Location: Genetics and Animal Breeding

2024 Annual Report

Objectives
Objective 1. Improve genomic resource and annotation tools for beef cattle and sheep. Sub-objective 1A: Create pangenome resources for cattle. Improve accuracy of imputed cattle genotypes by using pangenome resources. Sub-objective 1B: Improve annotation of assemblies through FAANG cooperation. Objective 2. Develop systems to improve performance through combined genetic and genomic characterization, heterosis, selection and analytical approaches. Sub-objective 2A: Characterize genetic, genomic and phenotypic variance among and within diverse and influential beef cattle populations toward improved sustainable breeding and management decisions. Sub-objective 2B: Estimate correlated responses to reducing an index of natural loss-of-function (LOF) alleles on reproduction, health, longevity, and traditional beef production traits. Sub-objective 2C: Examine whether sequence changes that affect protein structure or expression (functional and structural variants) also effect traits important to beef cattle production efficiency and sustainability. Sub-objective 2D: Develop strategies to incorporate commercial data into national genetic evaluations. Sub-objective 2E: Investigate interactions of beef breeds with management systems in diverse environments. Sub-objective 2F: Develop improved statistical methods for quantitative genetic and genomic analysis of beef cattle data. Objective 3. New methods for metagenome assembly, analysis, and characterization. New methods for characterizing genome function of microbes, protists and parasites. Sub-objective 3A: Develop methods for combined metagenomic assembly of complete microbial, protist, and parasite genomes from relevant microbiomes related to animals (rumen, gut, feces, environment). Sub-objective 3B: Develop methods and computational models to characterize genome function of microbes, protists and parasites affecting animal health of sheep and cattle. Sub-objective 3C: Profile bacterial populations (16S rRNA gene) in the respiratory tract of weaned beef calves after initiation of an inflammatory response. Sub-objective 3D: Profile bacterial populations (16S rRNA gene) in the digestive tract (rumen) of cattle from source populations from USMARC and Colorado.

Approach
Challenges to sustainability of beef production include aspects of animal health and wellbeing, societal expectations of reduced antibiotic use and/or development of alternatives, and pressure to reduce the environmental impact of production. Advances in genomic and related technologies have opened new avenues to better understand the relationships between variants of animal genomes, production traits, and the microbes that are associated with animal production, health, and well-being. These technologies support and depend on 1) continued improvement in annotation of cattle and sheep genomes, 2) development of research populations with pertinent phenotypes that broadly represent industry genetics, 3) identification of genomic variants segregating in beef cattle populations and assessment of the interaction of variation with production phenotypes as influenced by environment and management, and 4) characterization of microbes and microbiomes relevant to beef production. The proposed Project Plan will modernize and improve the relevance of phenotyped populations in which the effects of variation can be estimated, enhance genome annotation to sharpen the focus for evaluation of effects of variation on phenotype, and extensively characterize the content and impact of microbiomes and key microbes on target traits. Population-independent and population-specific management strategies will be assessed in cooperation with the ARS Beef Grand Challenge and related programs, using advancements in statistical methodology and partnering with commercial producers and other ARS locations. This combination will enable broader understanding of the components contributing to production efficiency, environmental impact, and animal welfare, while developing specific technologies and estimates of across-breed expected progeny difference (EPD) and heterosis effects for release to beef cattle producers.

Progress Report
Objective 1 exceeded expectations with 62 haplotypes of different breeds available for the “Phase 1” pangenome, and with another 42 haplotypes in the quality control stage for “Phase 2”. Assembled cattle pangenomes and tools to construct pangenome from long-read genome assemblies are being evaluated for suitability in developing a pangenome-aware pipeline to impute genotypes from low-coverage sequence. This will provide a comprehensive pangenome that will improve identification of genetic variants by identification of novel variation and elimination of false markers generated by data of individuals that improperly maps to the incomplete current reference genome. The research team cooperated with the international Functional Annotation of Animal Genomes (FAANG) consortium to identify 34,882 unique genes encoding 160,820 transcripts, doubling the number of annotated transcripts and identifying the regulatory regions of each gene and their functional status in a variety of tissues at different developmental stages. This annotation will improve the ability to discriminate functional variants among markers that associate with desirable phenotypes in genomic studies, enhancing the ability to accurately identify superior genetics in genome-enabled selection. Both pangenome and FAANG activities will support continued research of Objective 2, the Germplasm Evaluation Program (GPE) project that continues from the previous project plan cycle with its evaluation of 18 different cattle breeds. This year the GPE project provided semen of Angus and Brahman sires to Texas A&M AgriLife at McGregor, Texas, which was used on 190 Angus, Brahman, and F1 cows. This will augment the GPE project because purebred Brahman cattle cannot sustainably be evaluated at Clay Center, Nebraska, due to the temperate climate, leaving Brahman as the only one of the 18 breeds evaluated for which we do not have progeny of purebred cows. A primary objective of the collaboration with McGregor is to better understand genetic mechanisms in crosses between Brahman and Bos taurus cattle that defy the traditional assumptions of quantitative genetics. This new collaboration complements the shipping of breeding females to the ARS location in El Reno, Oklahoma, and to Beeville, Texas, in 2024. Objective 2 also included release of across-breed expected progeny difference (EPD) adjustment factors in spring 2024 based on an improved model more closely aligned with the models used by most breed associations. In addition, internal genetic evaluation supported improved accuracy of calving ease prediction to enhance the welfare of the GPE herd. Currently the GPE project has approximately 2,700 breeding females, which is short of our target of 3,600-4,000 females. Cow numbers have decreased in recent years due to drought, sending breeding females to cooperators in El Reno, Oklahoma, and Beeville, Texas, and due to an unexpected loss of breeding heifers in 2023. To compensate, we have retained approximately 800 breeding females that were first bred in 2024 and we expect to keep higher numbers of breeding females for the next several years, which will promote the growth of the herd to the target number. We still hope to successfully calve approximately 1,000 animals produced through artificial insemination. We are also planning to sample industry bulls in the next fiscal year (2025) with targets to supplement both our work at Clay Center, Nebraska, in the GPE and to breed females in our collaborating locations. However, initial analyses of growth and carcass data have been completed. Also, work has continued on metagenomic data from rumen samples conducted during the project (see Objective 3). Random regression methods were developed to estimate the contribution of an animal’s relatives (siblings, offspring, cousins, parents…) to a pool of DNA from multiple animals in an effort to provide the industry with more cost-effective tools for employing genomics to improve production and sustainability. The SFA (Selection for Functional Alleles) population is in the second year of utilizing Red Angus bulls in the Meat Animal Research Center (MARC) I composite to generate a higher quality, more marketable composite by improving marbling EPD through imputation of functional alleles associated with this (and other) trait(s). The Red Angus bulls were split into heifer and cow mating groups using their calving ease and birth weight EPD. Analysis of SFA cow weight and cumulative productivity is nearing completion. The analyses are considering genomic additive and dominance effects as well as various measures of genomic inbreeding and heterosis. Low-coverage sequence on GPE and SFA calves was imputed to whole-genome genotypes and used to determine the most likely sires for both sets of calves. Resulting pedigree information was used in analyses of heterosis in GPE cattle. Counts of loss of function alleles in SFA calves were used to select replacement females and bulls. Objective 3 provided new methods and data to incorporate knowledge about the microbial communities of beef cattle and assess their impact on a variety of production traits, animal health, and food safety. Evaluation of the rumen microbial community as part of the Beef Grand Challenge continued with characterization of samples from Clay Center, Nebraska, Miles City, Montana, and El Reno, Oklahoma, in preparation for analysis to identify environment-specific and general contributions of microbial diversity to beef cattle production. The potential for more in-depth studies of microbial function and effects on production traits was pursued by creation of the most comprehensive set of rumen microbial genomes yet produced through metagenomic sequencing and assembly including over 1,200 complete microbial genomes. This effort required the development of novel methods for metagenome assembly in the special case of the extremely complex microbiome of the cattle rumen. The data can now be used to predict metabolic potential of individual rumen microbial communities in an effort to identify “ideal” microbial profiles for enhanced productivity. Evaluation of the microbial communities in the upper respiratory tract of beef calves has continued. This work is part of a National Institute of Food and Agriculture (NIFA) grant with collaborators at Teagasc and Agri-food and Biosciences Institute. Evaluation of the animal’s resident respiratory pathogens including microbial and viral communities in the upper nasal cavity will help us to understand the impact of these pathogens on disease incidence.

Accomplishments
1. Selection to improve carcass traits of beef on dairy cattle using genotypes. Low-cost genotyping platforms and sexed-semen have enabled the production of high breeding value dairy replacement heifers from a fraction of the herd representing the most elite cows. The remainder of the cow herd can then be bred to beef bulls using male-sexed-semen to improve marketability through improved lean growth and carcass quality. Camera carcass data post-harvest and ultrasound carcass estimates pre-harvest (live animals) on beef x dairy animals combined with genotypes and ultrasound on seedstock animals may provide an efficient scheme for selecting beef bulls to mate to dairy cows in the future to maximize carcass value of the progeny. Genotypes are needed to link carcass data from previously harvested beef on dairy cattle to seedstock bull selection candidates because pedigree is typically not available for beef × dairy cattle. ARS researchers at Clay Center, Nebraska, with collaborators from Texas Tech, Washington State, and the American Simmental Association, demonstrated that live animal ultrasound carcass estimates are predictive of post-harvest economically important carcass traits. Accuracy of genetic evaluation of selection candidates without recorded carcass traits were low but are expected to increase with more genotypes and phenotypes on beef x dairy cattle. Genotypes, ultrasound estimates, and camera carcass data on thousands of beef x dairy cattle will enable increased accuracy of selection with periodic infusion of new phenotypes from future generations. Results will enable future beef x dairy selection strategies to improve productivity from beef bulls selected and utilized in these crosses.

2. Improved annotation of the cattle genome in cooperation with the international Functional Annotation of Animal Genomes (FAANG) consortium. Previous annotation of the cattle genome was generally limited to identification of genomic regions that are expressed as RNA, achieved by mapping RNA sequence data to the genome assembly. However, this annotation did not include important regulatory regions such as promoters or enhancers, nor did it provide information of chromatin state among different tissues which indicates active or inactive gene expression. Using a series of assays on tissues selected for purpose by the FAANG consortium, including ARS researchers at Clay Center, Nebraska, 34,882 unique genes encoding 160,820 transcripts were identified including 24,068 lacking annotation in the public reference assembly. Important regulatory features were defined across dozens of cattle tissues in both fetal and adult life stages. This effort resulted in highly refined annotation of the genome to improve the ability to identify functional variants in the background of linked genetic variation, thereby improving the accuracy of genetic testing for phenotypic traits. Mapping of these functional variances will improve opportunities to select for fitness, reproduction, and cattle productivity.

3. Identification of functional genetic mutations associated with heifer puberty and cow fertility. Cattle fertility is a highly complex and polygenic trait, making it difficult to identify and understand the underlying genetic mechanisms contributing to fertility phenotypes. The identification of causal genetic mutations and gene networks serves two significant benefits, it provides both a better understanding of important physiological processes regulating phenotypic differences and improves our ability to select for more desirable phenotypic outcomes. ARS researchers at Clay Center, Nebraska, with collaborators at the University of Queensland, integrated expression-quantitative trait loci (QTL) identified from a large RNA-sequencing dataset with conditional, multi-trait genome wide association analyses of multiple cattle fertility datasets, providing enhanced resolution and increased statistical power to identify causal mutations. Subsequently, 87 putatively functional genes affecting cattle fertility were identified and validated in a separate population. Expression-QTLs were identified for more than 10,000 genes expressed in whole blood. Further analysis revealed an overlap between a set of cattle and previously reported human fertility-related genes, implying the existence of a shared pool of genes that regulate fertility in mammals. This study resulted in a consensus set of functional variants and genes associated with cattle fertility outcomes that offer new insight into the genetic underpinnings of mammalian reproduction. These functional variants will enhance our ability to predict genetic merit for improved cattle fertility.

Review Publications
Lamb, H.J., Nguyen, L.T., Copley, J.P., Engle, B.N., Hayes, B.J., Ross, E.M. 2023. Imputation strategies for genomic prediction using nanopore sequencing. BMC Biology. 21. Article 286. https://doi.org/10.1186/s12915-023-01782-0.
McDaneld, T.G., Eicher, S.D., Dickey, A.M., Kritchevsky, J.E., Bryan, K.A., Chitko-McKown, C.G. 2024. Probiotics in milk replacer affect the microbiome of the lung in neonatal dairy calves. Frontiers in Microbiology. 14. Article 1298570. https://doi.org/10.3389/fmicb.2023.1298570.
Smith, T.P.L., Bickhart, D.M., Boichard, D., Chamberlain, A.J., Djikeng, A., Jiang, Y., Low, W., Pausch, H., Demyda-Peyras, S., Prendergast, J., Schnabel, R.D., Rosen, B.D. 2023. The bovine pangenome consortium: Democratizing production and accessibility of genome assemblies for global cattle breeds and other bovine species. Genome Biology. 24. Article 139. https://doi.org/10.1186/s13059-023-02975-0.
Beiki, H., Murdoch, B.M., Park, C.A., Kern, C., Kontechy, D., Becker, G., Rincon, G., Jiang, H., Zhou, H., Thorne, J., Koltes, J.E., Michal, J.J., Davenport, K.G., Rijnkels, M., Ross, P.J., Hu, R., Corum, S., McKay, S., Smith, T.P.L., Liu, W., Ma, W., Zhang, X., Xu, X., Han, X., Jiang, Z., Hu, Z., Reecy, J.M. 2024. Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology. Gigascience. 13. Article giae019. https://doi.org/10.1093/gigascience/giae019.
Russell, C.A., Kuehn, L.A., Snelling, W.M., Kachman, S.D., Spangler, M.L. 2023. Variance component estimates for growth traits in beef cattle using selected variants from imputed low-pass sequence data. Journal of Animal Science. 101. Article skad274. https://doi.org/10.1093/jas/skad274.
Lakamp, A.D., Ahlberg, C.M., Allwardt, K., Broocks, A., Bruno, K., McPhillips, L., Taylor, A., Krehbiel, C.R., Calvo-Lorenzo, M.S., Richards, C., Place, S.E., DeSilva, U., Kuehn, L.A., Weaber, R.L., Bormann, J.M., Rolf, M.M. 2023. Variance component estimation and genome-wide association of predicted methane production in crossbred beef steers. Journal of Animal Science. 101. Article skad179. https://doi.org/10.1093/jas/skad179.
Dickey, A.M., Schmidt, J.W., Bono, J.L., Guragain, M. 2024. The GEA pipeline for characterizing Escherichia coli and Salmonella genomes. Scientific Reports. 14. Article 13257. https://doi.org/10.1038/s41598-024-63832-z.
Workman, A.M., Harhay, G.P., Groves, J.T., Vander Ley, B.L. 2024. Two bovine hepacivirus genome sequences from U.S. cattle. Journal of Veterinary Diagnostic Investigation. 36(2):274-277. https://doi.org/10.1177/10406387231225656.
Weinroth, M.D., Clawson, M.L., Harhay, G.P., Eppinger, M., Harhay, D.M., Smith, T.P.L., Bono, J.L. 2023. Escherichia coli O157:H7 tir 255 T > A allele strains differ in chromosomal and plasmid composition. Frontiers in Microbiology. 14. Article 1303387. https://doi.org/10.3389/fmicb.2023.1303387.
Workman, A.M., Heaton, M.P., Vander Ley, B., Webster, D., Sherry, L., Bostrom, J.R., Larson, S., Kalbfleisch, T., Harhay, G.P., Jobman, E., Carlson, D., Sonstegard, T.S. 2023. First gene-edited calf with reduced susceptibility to a major viral pathogen. Proceedings of the National Academy of Sciences-Nexus. 2(5). Article pgad125. https://doi.org/10.1093/pnasnexus/pgad125.
Lindholm-Perry, A.K., Keel, B.N., Hales, K.E., Wells, J.E., Kuehn, L.A., Keele, J.W., Crouse, M.S., Nonneman, D.J., Nagaraja, T.G., Lawrence, T.E., Amachawadi, R.G., Carroll, J.A., Burdick Sanchez, N.C., Broadway, P.R. 2024. Ileal epithelial tissue transcript profiles of steers with experimentally induced liver abscesses. Applied Animal Science. 40(3):414-420. https://doi.org/10.15232/aas.2023-02503.
Gupta, S., Kuehn, L.A., Clawson, M.L. 2023. Early detection of infectious bovine keratoconjunctivitis with artificial intelligence. Veterinary Research. https://doi.org/10.1186/s13567-023-01255-w.
Freetly, H.C., Jacobs, D.R., Thallman, R.M., Snelling, W.M., Kuehn, L.A. 2023. Heritability of beef cow metabolizable energy for maintenance. Journal of Animal Science. 101. Article skad145. https://doi.org/10.1093/jas/skad145.
Henniger, M.T., Rowan, T.N., Beever, J.E., Mulon, P., Smith, J.S., Voy, B.H., Wells, J.E., Kuehn, L.A., Myer, P.R. 2023. Validation of a minimally-invasive method for sampling epithelial-associated microorganisms on the rumen wall. Frontiers in Animal Science. 4. Article 1270550. https://doi.org/10.3389/fanim.2023.1270550.
Raynor, E.J., Schilling-Hazlett, A., Place, S.E., Vargas, J.J., Thompson, L.R., Johnston, M.K., Jorns, T.R., Beck, M.R., Kuehn, L.A., Derner, J.D., Stackhouse-Lawson, K. 2024. Snapshot of enteric methane emissions from stocker cattle grazing extensive semiarid rangelands. Rangeland Ecology and Management. 93:77-80. https://doi.org/10.1016/j.rama.2024.01.001.
Fuller, T.D., Bickhart, D.M., Koch, L.M., Kucek, L.K., Ali, S., Mangelson, H., Monteros, M.J., Hernandez, T., Smith, T.P., Riday, H., Sullivan, M.L. 2023. A reference assembly for the legume cover crop hairy vetch (Vicia villosa). GigaByte. https://doi.org/10.46471/gigabyte.98.
Oppert, B.S., Dossey, A.T., Chu, F., Satovic-Vuksi, E., Plohl, M., Koren, S., Olmstead, M.L., Leierer, D., Ragan, G.C., Smith, T.P., Johnston, J. 2023. The genome of the yellow mealworm, Tenebrio molitor: It’s bigger than you think. Genes. 14(12). Article 2209. https://doi.org/10.3390/genes14122209.
Balboa, R.F., Bertola, L., Bruniche-Olsen, A., Rasmussen, M., Liu, X., Besnard, G., Salmona, J., Santander, C.G., He, S., Zinner, D., Heaton, M.P., Smith, T.P., Moltke, I., Albrechtsen, A., Heller, R. et al. 2024. African bush pigs exhibit porous species boundaries and appeared in Madagascar concurrently with human arrival. Nature Communications. 15. Article 172. https://doi.org/10.1038/s41467-023-44105-1.
Liu, X., Lin, L., Sinding, M.S., Bertola, L.D., Hanghoj, K., Quinn, L., Garcia-Erill, G., Rasmussen, M.S., Schubert, M., Pecnerova, P., Balboa, R.F., Li, Z., Heaton, M.P., Smith, T.P.L., Pinto, R., Wang, X., Kuja, J., Bruniche-Olsen, A., Meisner, J., Santander, C.G., Ogutu, J.O., Masembe, C., da Fonseca, R.R., Muwanika, V., Siegismund, H.R., Albrechtsen, A., Moltke, I., Heller, R. 2024. Introgression and disruption of migration routes have shaped the genetic integrity of wildebeest populations. Nature Communications. 15. Article 2921. https://doi.org/10.1038/s41467-024-47015-y.