Location: Genetics and Animal Breeding
2020 Annual Report
Objectives
Objective 1: Improve genomic tools for beef cattle and sheep.
Sub-objective 1A: Complete improved reference assemblies for beef cattle and sheep using genome-wide and locus-targeted approaches, in addition to comparative approaches, to improve accuracy and contiguity.
Sub-objective 1B: Improve annotation of the reference assemblies by conducting specific assays as outlined in the FAANG consortium guidelines, enhanced with parent-of-origin allele expression pattern data.
Sub-objective 1C: Develop comprehensive databases of existing variation with predicted impact of those variations on gene expression and protein sequence.
Objective 2: Develop systems to improve performance through combined genetic and genomic approaches.
Sub-objective 2A: Improve breeding and management decisions by characterizing current genetic and phenotypic variation within and between predominant beef breeds and crosses.
Sub-objective 2B: Identification of genomic variation associated with industry-relevant phenotypes in beef cattle.
Sub-objective 2C: Development of low-input production lines of sheep, including genetic and genomic resource development to support characterization of these lines.
Objective 3: Identify and characterize microbes, microbial populations, and parasites associated with normal and diseased populations.
Sub-objective 3A: Profile microbial populations in the respiratory tract (RT) of cattle throughout the production life-cycle in the context of BRDC.
Sub-objective 3B: Characterize genomic variation among sheep parasites, for correlation with anthelmintic resistance and animal genotype.
Objective 4: Combine products from Objectives 1, 2, and 3 to synthesize a broader knowledge base.
Sub-objective 4A: Synthesize genome annotation from Objective 1 and genetics by selection and assessment of impact of predicted non-functional alleles.
Sub-objective 4B: Synthesize parasite and metagenomics from Objective 3 with genetics and genomics from Objective 2.
Sub-objective 4C: Synthesize variant genotypes and annotation from Objective 1, animal phenotypes from Objective 2, and microbial profiles from Objective 3, by partitioning microbial variation into host genetic and enviromental influences on phenotypic expression.
Approach
Challenges to sustainability of beef and lamb production include aspects of animal health and wellbeing, societal expectations of reduced antibiotic use and/or development of alternatives, and pressure to reduce 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. The technologies support and depend on development of research populations with pertinent phenotypes that broadly sample industry genetics, continuing improvement in annotation of animal genomes, identification and characterization of microbial species relevant to animal production, and continued assessment of the interaction of genome variation and production phenotypes. This project plan will merge previous genetics and genomics projects into a broader systems approach, that will encompass (1) genome annotation and identification of functional variation among genomes, (2) development of phenotyped populations in which the effects of variation can be estimated, (3) characterization of the overall microbial diversity associated with the animals and dependencies of this diversity on animal genome variation, and (4) molecular-level characterization of microbial or parasitic organisms that impact on animal health, productivity, and reproduction. The systems approach will be combined with population management strategies, application of advancements in statistical methodology, and partnering with commercial producers. This combination will enable broader understanding of the components contributing to production efficiency, environmental impact, and animal welfare, while developing specific technologies for release to beef cattle producers and improved strains for the sheep industry.
Progress Report
Outstanding progress was made on the Project Plan this year. For Objective 1, "Improving genomic tools for beef cattle and sheep", progress went well beyond the milestones for this year. Specifically, new analysis approaches were developed with collaborators and exploited in 2020 to create multiple reference-grade genomes of livestock. Genome assemblies were created for three sheep breeds, including the White Dorper and Romanov breeds that form a major part of the Easy-care line of sheep being developed in Objective 2c. These assemblies are of extremely high quality, surpassing the sheep reference genome and being equivalent to the human reference genome in measures of completeness and continuity. In addition, a re-assembly of the Rambouillet ewe used for the current reference genome assembly was prepared that is 20 times more continuous and has higher accuracy of gene definition. These genomes are expected to substantially accelerate genomic research in sheep and are being submitted to the public database. Genome assemblies for the Scottish Highland, Angus, Brahman, and Hereford breeds of cattle were released to the public in this year. Assemblies of the Simmental and Piedmontese breeds are nearing completion for public release in calendar year 2020. Assemblies were also created for related bovid species including yak and water buffalo (already released to public), gaur and bison (to be released in calendar year 2020). The slate of new genome assemblies has launched a new effort called the Bovine Pangenome Consortium, initiated by ARS researchers in Clay Center, Nebraska, to create assemblies for all the cattle breeds on the planet. This consortium already has 80 members from 50 institutions in 18 countries on six continents. The multiple breeds and species assemblies will support enhanced opportunity to use genome comparisons between species and breeds to identify functional variation in genes within the cattle and sheep species.
Additional progress on Objective 1 included support for the international Functional Annotation of Animal Genomes (FAANG) project, specifically producing data in support of efforts to identify genomic elements that regulate gene expression (Objective 1B). A map of an important class of features called "Transcription Start Sites" (TSS) was completed for sheep and complemented by a map of chromatin states that indicate which TSS are active in which tissues. In cattle, 28 tissues were characterized for the specific isoforms of each gene that are expressed, revealing a new level of genomic control in addition to simple abundance (i.e. instead of just "turning on" or "turning off" a gene). For Objective 1C, efforts to either directly genotype or impute genotypes for over 16,000 markers on approximately 20,000 animals born in the last 19 years in the Germplasm Evaluation (GPE) project were completed. This data is being used to support identification of variation directly contributing to phenotype in the other objectives.
Progress on Objective 2, "Develop systems to improve performance through combined genetic and genomic approaches", was equally successful. Based on the large GPE database containing over 50 years of data recording, augmented over the last 8-15 years with novel traits including fertility, respiratory disease, and feed efficiency, an update to the popular across-breed Expected Progeny Difference (EPD) adjustment factor table was released and heavily referenced by commercial and seedstock beef cattle producers and breed associations (Objective 2A). The scope of this objective was expanded beyond the original milestones by efforts in the Beef Grand Challenge program, which evaluated a second calf crop at five collaborating ARS locations to quantify the effects on environment and management variables on the success of EPD predictions, substantially enhancing the value and accuracy of genotype-enabled EPD. Matings within the GPE cattle population continued for all 18 sire breeds, with total number of breeding females increased to 3,500. Selection for calving ease in heifers, taking into account subsequent growth of the calf to yearling age, has progressed such that cow mature weights are reduced 5%. This reduction is predicted to reduce feed requirements of the cow herd and decrease production costs. Fertility indicators and lifetime productivity were recorded for the population, and feed efficiency was recorded on 475 cows and 500 steers. Approximately 3,000 animals were submitted for genotyping to support imputation of 40 million polymorphisms that will impact national cattle evaluation in the future (Objective 2B). Statistical methods to incorporate the genotype data into these evaluations were prototyped and are being evaluated in other ARS and University of Nebraska herds. The sheep component of Objective 2 collected data on the 5th parity on the last group of ewes for the project in Composite IV, Polypay, and Katahdin breed maternal sheep lines. A process was established to convert camera images into maternal behavior traits for formal statistical analysis and evaluation of the success of the mating program. Phenotypic data on udder morphology and subclinical mastitis were collected to enhance the evaluation while creating a low-input sheep production system (Objective 2C).
Progress on Objective 3, to characterize microbial content and flora of sheep and cattle was also substantial. Nasal swabs have now been collected from approximately 6,300 calves at key developmental timepoints like preconditioning, weaning, and prebreeding, including 660 calved with symptoms of respiratory disease (Objective 3A). This data will support the integration of microbial phenotypes with feed efficiency, growth, and health-related phenotypes. The scope of Objective 3A was expanded to include virology testing that is revealing a relationship of bovine coronavirus and mycoplasma with the development of respiratory disease. Further expansion of Objective 3A was facilitated by development, in collaboration with University partners, of a novel technique for examining the immune repertoire of cattle, which is the set of antibody specificities that are "turned on" by infection. This method revealed that a class of antibodies called "ultralong CDR3" are critical components of vaccine success, knowledge which is being used to formulate novel approaches to vaccine development to improve vaccine success rate while also identifying genomic variation in cattle associated with less successful response. Spanning Objectives 3A and 3B, a novel approach for assembling microbial and parasite genomes by sequencing DNA extracted from sheep fecal matter was developed, and more than 100 microbial species were completely assembled without the need for developing culture methods to grow them for individual sequencing. An approach to simultaneously assemble the parasite (nematode worm or coccidia) from the same sequence data has been developed and is being tested, supporting a new approach to more accurately diagnose parasite infection to complete Objective 3B.
The outputs from Objectives 1-3 are feeding into the "grand synthesis" strategy of Objective 4, "Combine products from Objectives 1, 2, and 3 to synthesize a broader knowledge base". Breeding based on selection for or against loss-of-function alleles for this objective is proceeding and genotyping to evaluate success is on schedule. Health, performance, and internal parasitism data was collected on ewes and lambs on schedule. The sheep study was expanded to include mastitis and udder morphometry, as well as incisor wear, Ovine Progressive Pneumonia status, post-weaning health, growth feed intake, and carcass characteristics. In summary, the first two full years (32 total months) of the new project have kept us on track to reach the ambitious goals set for the 5-year Project Plan.
The goals of subordinate project 3040-31000-100-10H, Genomic Analysis of Jersey and Holstein Cattle, have been largely achieved by the production of genome assemblies for both breeds. The assemblies are highly continuous, reference-grade assemblies representing two important dairy breeds of cattle and are in final stages of curation before being made public. Analysis to identify differences between the genomes of beef breeds and dairy breeds of cattle is underway.
Accomplishments
1. Application of pooling individual whole blood samples prior to DNA extraction. Genotyping pooled samples from multiple animals can substantially reduce genotyping costs. However, these methods need to accurately generate equal representation of individuals within pools. ARS researchers at Clay Center, Nebraska, in collaboration with researchers at South Dakota State University, evaluated methods of pooling to determine accuracy of pool construction based on white blood cell counts compared to two common DNA quantification methods. The researchers constructed pools of 50 animals with the target of equal representation of each animal based on number of white blood cells, spectrophotometric readings of DNA, spectrofluorometric readings of DNA, and whole blood volume. The method of pooling whole blood samples based on white blood cell count was more predictive of sample representation compared to pooling based on DNA concentration. Therefore, constructing pools using white blood cell counts prior to DNA extraction may reduce cost associated with genotyping and improve representation of individuals in a pool.
2. Tracking down sources of error when using DNA pooling in genetic evaluation. Pooling DNA from multiple animals can be used to reduce the cost of genetic evaluation and generate expected progeny differences (EPD) that producers use for selection. Relationships between the animals in the pools and candidates for selection are established through allele frequency estimates from genotypes of the pools. The accuracy of these EPD are affected by various errors in the pooling process. ARS researchers at Clay Center, Nebraska, performed experiments to optimize pooling strategies, and demonstrated that pooling equal weight of liver before DNA extraction, or pooling based on extracted DNA estimated concentration, were both effective in estimating allele frequency of the pool as long as at least 10 animals were contained in the pool. These results suggest that pools containing more than 10 animals are robust and can be used to economically decrease genotyping costs in livestock genetic evaluation programs.
3. Verified efficacy of a reference-panel based imputation algorithm. Genomic sequence from influential individuals in a crossbred population representing the eighteen most predominant beef breeds in the United States was combined with publicly available sequence representing beef and dairy breeds. ARS researchers at Clay Center, Nebraska, identified individuals for sequencing with a novel algorithm based on haplotypes inferred from high-density single nucleotide polymorphism (SNP) genotypes. In collaboration with Gencove, Inc., relevant public sequence was also identified and incorporated into a phased haplotype reference panel allowing imputation from low-cost, low-coverage genomic sequence. Sequence variant genotypes imputed with this approach are more accurate than those imputed from SNP assay genotypes (SNP chips). Low-coverage sequence with imputation will enable more comprehensive genotyping at a lower cost than currently available SNP arrays. Producers will be able to genotype a larger portion of animals for genetic evaluation programs, which will improve selection accuracy and increase the genetic gain to improve beef efficiency for the industry at a faster rate.
Review Publications
Rice, E.S., Koren, S., Rhie, A., Heaton, M.P., Kalbfleisch, T., Hardy, T., Hackett, P., Bickhart, D.M., Rosen, B.D., Vander Ley, B., Maurer, N.W., Green, R.E., Phillippy, A.M., Petersen, J.L., Smith, T.P. 2020. Continuous chromosome-scale haplotypes assembled from a single interspecies F1 hybrid of yak and cattle. GigaScience. 9(4):1-9. https://doi.org/10.1093/gigascience/giaa029.
Harhay, D.M., Smith, T.P.L., Harhay, G.P., Loneragan, G.H., Webb, H.E., Bugarel, M., Haley, B.J., Kim, S.W., Van Kessel, J.S. 2018. Complete closed genome sequences of three Salmonella enterica subsp. enterica Serovar Dublin strains isolated from cattle at harvest. Microbiology Resource Announcements. 7:e01334-18. https://doi.org/10.1128/MRA.01334-18.
Mehus, A.A., Dickey, A.M., Smith, T.P., Yeater, K.M., Picklo, M.J. 2019. Next-generation sequencing identifies polyunsaturated fatty acid responsive genes in the juvenile rat cerebellum. Nutrients. https://doi.org/10.3390/nu11020407.
Dong, J., Finn, J.A., Larsen, P.A., Smith, T.P.L., Crowe, J.E. 2019. Structural diversity of ultralong CDRH3s in seven bovine antibody heavy chains. Frontiers in Immunology. 10:558. https://doi.org/10.3389/fimmu.2019.00558.
Oppert, B.S., Stoss, S.P., Monk, A.L., Smith, T.P. 2019. Optimized extraction of insect genomic DNA for long-read sequencing. Methods and Protocols. 2(4):89. https://doi.org/10.3390/mps2040089.
Ault, T.B., Clemmons, B.A., Reese, S.T., Dantas, F.G., Franco, G.A., Smith, T.P.L., Edwards, J.L., Myer, P.R., Pohler, K.G. 2019. Uterine and vaginal bacterial community diversity prior to artificial insemination between pregnant and nonpregnant postpartum cows. Journal of Animal Science. 97(10):4298-4304. https://doi.org/10.1093/jas/skz210.
Ault, T.B., Clemmons, B.A., Reese, S.T., Dantas, F.G., Franco, G.A., Smith, T.P.L., Edwards, J.L., Myer, P.R., Pohler, K.G. 2019. Bacterial taxonomic composition of the postpartum cow uterus and vagina prior to artificial insemination. Journal of Animal Science. 97(10):4305-4313. https://doi.org/10.1093/jas/skz212.
Bickhart, D.M., McClure, J.C., Schnabel, R.D., Rosen, B.D., Medrano, J.F., Smith, T.P.L. 2020. Advances in sequencing technology herald a new frontier in cattle genomics and genome-enabled selection. Journal of Dairy Science. 103(6):5278-5290. https://doi.org/10.3168/jds.2019-17693.
Liu, R., Yee Low, W., Tearle, R., Koren, S., Ghurye, J., Rhie, A., Phillippy, A.M., Rosen, B.D., Bickhart, D.M., Smith, T.P., Hiendleder, S., Williams, J.L. 2019. New insights into mammalian sex chromosome structure and evolution using high-quality sequences from bovine X and Y chromosomes. BMC Genomics. 20:1000. https://doi.org/10.1186/s12864-019-6364-z.
Bickhart, D.M., Watson, M., Koren, S., Panke-Buisse, K., Cersosimo, L.M., Press, M.O., Van Tassell, C.P., Van Kessel, J.S., Haley, B.J., Kim, S., Heiner, C., Suen, G., Bakshy, K., Liachko, I., Sullivan, S.T., Myer, P.R., Ghurye, J., Pop, M., Weimer, P., Phillippy, A., Smith, T.P. 2019. Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation. Genome Biology. 20:153. https://doi.org/10.1186/s13059-019-1760-x.
Harhay, G.P., Harhay, D.M., Bono, J.L., Capik, S.F., DeDonder, K.D., Apley, M.D., Lubbers, B.V., White, B.J., Larson, R.L., Smith, T.P.L. 2019. A computational method to quantify the effects of slipped strand mispairing on bacterial tetranucleotide repeats. Nature Scientific Reports. 9:18087. https://doi.org/10.1038/s41598-019-53866-z.
Yee Low, W., Tearle, R., Bickhart, D.M., Rosen, B.D., Kingan, S.B., Swale, T., Thibaud-Nissen, F., Murphy, T., Young, R., Lefevre, L., Hume, D., Collins, A., Ajmone-Marsan, P., Smith, T.P., Williams, J. 2019. Chromosome-level assembly of the water buffalo genome surpasses human and goat genomes in sequence contiguity. Nature Communications. 10:260. https://doi.org/10.1038/s41467-018-08260-0.
Field, M.A., Rosen, B.D., Dudchenko, O., Chan, E.K.F., Minoche, A.E., Edwards, R.J., Barton, K., Lyons, R.J., Enosi Tuipulotu, D., Hayes, V.M., Omer, A.D., Colaric, Z., Keilwagen, J., Skvortsova, K., Bogdanovic, O., Smith, M.A., Aiden, E.L., Smith, T.P., Zammit, R.A., Ballard, J.O. 2020. Canfam_GSD: Denovochromosome-length genome assembly of the German Shepherd Dog (Canis lupus familiaris) using a combination of long reads, optical mapping, and Hi-C. GigaScience. 9(4):1-12. https://doi.org/10.1093/gigascience/giaa027.
Low, W., Tearle, R., Liu, C., Koren, S., Rhie, A., Bickhart, D.M., Rosen, B.D., Kronenberg, Z.N., Kingan, S.B., Tseng, E., Thibaud-Nissen, F., Martin, F., Billis, K., Ghurye, J., Hastie, A.R., Lee, J., Pang, A., Heaton, M.P., Phillippy, A.M., Hiendleder, S., Smith, T.P., Williams, J.L. 2020. Haplotype-resolved genomes provide insights into structural variation and gene content in Angus and Brahman cattle. Nature Communications. 11:2071. https://doi.org/10.1038/s41467-020-15848-y.
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., Hall, R., Li, W., Rhie, A., Ghurye, J., McKay, S.D., Thibaud-Nissen, F., Hoffman, J., Murdoch, B.M., Snelling, W.M., McDaneld, T.G., Hammond, J.A., Schwartz, J.C., Nandolo, W., Hagen, D.E., Dreischer, C., Schultheiss, S.J., Schroeder, S.G., Phillippy, A.M.,Cole, J.B., Van Tassell, C.P., Liu, G., Smith, T.P.L., Medrano, J.F. 2020. De novo assembly of the cattle reference genome with single-molecule sequencing. GigaScience. 9(3):1-9. https://doi.org/10.1093/gigascience/giaa021.
Warr, A., Affara, N., Aken, B., Beiki, H., Bickhart, D.M., Billis, K., Chow, W., Eory, L., Finlayson, H.A., Flicek, P., Giron, C.G., Griffin, D.K., Hall, R., Hannum, G., Hourlier, T., Howe, K., Hume, D.A., Izuogu, O., Kim, K., Koren, S., Liu, H., Manchanda, N., Martin, F.J., Nonneman, D.J., O'Connor, R.E., Phillippy, A.M., Rohrer, G.A., Rosen, B.D., Rund, L.A., Sargent, C.A., Schook, L.B., Schroeder, S.G., Shwartz, A.S., Skinner, B.M., Talbot, R., Tseng, E., Tuggle, C.K., Watson, M., Smith, T.P., Archibald, A.L. 2020. An improved pig reference genome sequence to enable pig genetics and genomics research. GigaScience. 9(6):giaa051. https://doi.org/10.1093/gigascience/giaa051.
Keel, B.N., Snelling, W.M., Lindholm-Perry, A.K., Oliver, W.T., Kuehn, L.A., Rohrer, G.A. 2020. Using SNP weights derived from gene expression modules to improve GWAS power for feed efficiency in pigs. Frontiers in Genetics. 10:1339. https://doi.org/10.3389/fgene.2019.01339.
Penning, B., Snelling, W.M., Woodward Greene, M.J. 2020. Machine learning in the assessment of meat quality. IEEE IT Professional. 22(3):39-41. https://doi.org/10.1109/mitp.2020.2986123.
Freetly, H.C., Kuehn, L.A., Thallman, R.M., Snelling, W.M. 2020. Heritability and genetic correlations of feed intake, body weight gain, residual gain, and residual feed intake of beef cattle as heifers and cows. Journal of Animal Science. 98(1):1-6. https://doi.org/10.1093/jas/skz394.
Zimmerman, M.J., Kuehn, L.A., Spangler, M.L., Thallman, R.M., Snelling, W.M., Lewis, R.M. 2019. Comparison of different functions to describe growth from weaning to maturity in crossbred beef cattle. Journal of Animal Science. 97(4):1523-1533. https://doi.org/10.1093/jas/skz045.
Freetly, H.C., Dickey, A., Lindholm-Perry, A.K., Thallman, R.M., Keele, J.W., Foote, A.P., Wells, J.E. 2020. Digestive tract microbiota of beef cattle that differed in feed efficiency. Journal of Animal Science. 98(2):1-16. https://doi.org/10.1093/jas/skaa008.
Wynn, E.L., Schuller, G., Loy, J.D., Workman, A.M., McDaneld, T.G., Clawson, M.L. 2020. Differentiation of Mannheimia haemolytica genotype 1 and 2 strains by visible phenotypic characteristics on solid media. Journal of Microbiological Methods. 171. Article 105877. https://doi.org/10.1016/j.mimet.2020.105877.
Liu, S., Yu, Y., Zhang, S., Cole, J.B., Tenesa, A., Wang, T., Mcdaneld, T.G., Ma, L., Liu, G., Fang, L. 2020. Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human. BMC Biology. 18(1). Article 80. https://doi.org/10.1186/s12915-020-00792-6.
Lents, C.A., Freking, B.A. 2019. Intrauterine position and adjacent fetal sex affects fetal and placental growth throughout gestation, but not embryonic viability, in pigs selected for component traits of litter size. Animal Reproduction Science. 209:106139. https://doi.org/10.1016/j.anireprosci.2019.106139.
Rathert, A.R., Meyer, A.M., Foote, A.P., Kern, R.J., Cunningham-Hollinger, H.C., Kuehn, L.A., Lindholm-Perry, A.K. 2020. Ruminal transcript abundance of the centromere-associated protein E gene may influence residual feed intake in beef steers. Animal Genetics. 51(3):453-456. https://doi.org/10.1111/age.12926.
Myer, P.R., McDaneld, T.G., Kuehn, L.A., Dedonder, K.D., Apley, M.D., Capik, S.F., Lubbers, B.V., Harhay, G.P., Harhay, D.M., Keele, J.W., Henniger, M.T., Clemmons, B.A., Smith, T.P.L. 2020. Classification of 16S rRNA reads is improved using a niche-specific database constructed by near-full length sequencing. PLoS One. 15(7):e0235498. https://doi.org/10.1371/journal.pone.0235498.
Paim, T., Hay, E.A., Wilson, C.S., Thomas, M., Kuehn, L.A., Pavia, S.R., McManus, C., Blackburn, H.D. 2020. Dynamics of genomic architecture during composite breed development in cattle. Animal Genetics. 51(2):224-234. https://doi.org/10.1111/age.12907.