1a. Objectives (from AD-416):
The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants.
1b. Approach (from AD-416):
Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative.
3. Progress Report:
This is the final report for the Project 8042-31000-104-00D which will end July 23, 2017. New NP101 project, entitled “Enhancing Genetic Merit of Ruminants through Improved Genome Assembly, Annotation and Selection” is being established. During the life of the project, ARS scientists in Beltsville, Maryland, continued as global leaders for production of DNA sequence information by completing the first mammalian genome assembly based solely on caprine sequence data from a third generation sequence platform (PacBio) and contributing all the sequence for international efforts to assemble genomes and single nucleotide polymorphism (SNP) discovery for Bos indicus cattle, extinct Bos primigenius cattle, water buffalo, and other species. In additional, ARS Scientists in Beltsville, Maryland, developed novel genomic tools for selection. These efforts included development of multiple specialized SNP assays for genomic prediction in beef and dairy cattle breeds, Bos indicus cattle, water buffalo, goat, and other species, including turkey. ARS scientists used genetic data derived from genome sequencing and SNP chips to better understand natural and artificial selection in cattle and goats. This effort included searching for genetic variations (SNPs, short insertions and deletions), recessive lethal alleles, runs of homozygosity, regions of the genome under natural selection. This effort also included a comprehensive screen for candidate regions under positive selection across ruminant populations as a result of geographic adaptation and artificial selection. For example, ARS scientists led the effort to characterize the profound impact of genomic selection on population dynamics in dairy cattle. These also included identifying causative mutations affecting SLICK and fertility haplotypes (HH1, BH2, HH3), as well as mapping genomic regions for tropical adaptation, production, and genetic defects (e.g., limber leg and rectovaginal constriction) in cattle. ARS scientists also completed transcript sequencing (RNAseq) for improved genome annotation, the first reduced representation bisulphite sequencing (RRBS) study for DNA methylation, and the first comprehensive prediction of transcription factor binding sites (TFBS) in the cattle genome. Based on SNP array data and high-throughput sequencing data, ARS scientists performed copy number variation (CNV) discovery and CNV-based population genetics studies. ARS scientists also performed genome-wide association studies (GWAS) between CNV and various production and health traits, and designed an integrated tool (RAPTR-SV) to identify CNV using data derived from various discovery platforms. ARS scientists computed the first genomic predictions that combined CNV and SNP markers. This effort demonstrated that combining CNV and SNP marker information can be beneficial for several traits. Furthermore, ARS scientists developed methods to discover microsatellite or short tandem repeats based on high-throughput sequencing. This analysis identified more than 60,000 microsatellites and made it possible to study selection using microsatellites in cattle. Finally, ARS scientists developed two novel photographic methods and a database system for collecting goat phenotypes, and implemented eight community breeding programs in Uganda and Malawi using that technology. In collaborating with IGGC and ADAPTmap, analysis of signatures from natural selection continued using SNP data derived from the Illumina Caprine50K assay for more than 3,000 goats.
1. Completed a reference genome assembly for Capra hircus (goat) using PacBio sequence data and advanced genome scaffolding technologies. Genome assemblies have been produced for numerous species as a result of advances in sequencing technologies; however, many of the assemblies are fragmented, with many gaps, ambiguities, and errors. This was a team effort of ARS scientists in Beltsville, Maryland, working in tandem with members of the National Human Genome Research Institute (NGHRI), USDA MARC, BioNano Genomics, Phase Genomics, and the PirBright Institute (based in the UK). This reference genome represents a 250-fold improvement in continuity over the previously available goat reference assembly that was generated with a sequencing strategy using second-generation short-read sequencing. The annotation data and scaffold statistics for the new goat reference genome are now publicly available on the NCBI genome portal and the quality of the assembly has been publicly praised by NCBI staff in unaffiliated conference presentations. This technique – described in an article published in Nature Genetics - promises to reduce the cost of generating high-quality reference genome assemblies for other animal and plant species.
2. Identification of the West African origins of Caribbean hair sheep. ARS scientists in Beltsville, Maryland, working with scientists from the University of Nottingham, Recombinetics, USDA DBSFRS, Katahdin Hair Sheep International, and Virginia Tech clarified the contributions of African and European sheep breeds to the ancestry of Caribbean hair sheep. Hair sheep of Caribbean origin have become an important part of the U.S. sheep industry. Their lack of wool eliminates a number of health concerns and drastically reduces the cost of production. More importantly, Caribbean hair sheep demonstrate robust production performance even in the presence of drug-resistant gastrointestinal nematodes, a rising concern to the industry. This study used genotypes from 47,750 autosomal SNPs scored in 290 animals to characterize the population structure of the St. Croix, Barbados Blackbelly, Morada Nova, and Santa Ines and established an objective measure indicating Caribbean hair sheep are derived from Iberian and West African origins. This is a major step towards a better understanding of the source of Caribbean hair sheep resilience in the face of high parasite load.
3. Completed the first single-base-resolution maps of bovine DNA methylation in cattle. DNA methylation plays important functions in individual development and various diseases. However, only limited data exist in cattle. This work evaluated over 1.8 million cytosines and detected thousands of differentially methylated cytosines and hundreds of differentially methylated CG islands. Further analyses revealed that many of them were highly correlated with the expression of genes involved in tissue development. This study provided a baseline dataset and essential information for DNA methylation profiles of cattle.
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Adams, H.A., Sonstegard, T.S., Van Raden, P.M., Null, D.J., Van Tassell, C.P., Larkin, D.M., Lewin, H.A. 2016. Identification of a nonsense mutation in APAF1 that is likely causal for a decrease in reproductive efficiency in Holstein dairy cattle. Journal of Dairy Science. 99(8):6693-6701.
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Zhou, Y., Utsunomiya, Y.T., Xu, L., Hay, E.A., Bickhart, D.M., Carvalheiro, R., Neves, H.H., Van Tassell, C.P., Sonstegard, T.S., Garcia, J., Liu, G. 2016. Comparative analyses across cattle breeds reveal the pitfalls caused by artificial and lineage-differential copy number variations. Scientific Reports. 6:29219.
Zhou, Y., Xu, L., Bickhart, D.M., Hay, E., Schroeder, S.G., Connor, E.E., Leeson, A.J., Sonstegard, T., Van Tassell, C.P., Hong, C., Liu, G. 2016. Reduced representation bisulphite sequencing of the cattle genome reveals DNA methylation patterns. BMC Genomics. 17(1):779.
Hay, E.A., Choi, I., Xu, L., Zhou, Y., Rowland, R., Lunney, J.K., Liu, G. 2017. CNV analysis of host responses to porcine reproductive and respiratory syndrome virus infection. Journal of Genomics. 5:58-63.
Xu, L., Haasl, R.J., Sun, J., Zhou, Y., Bickhart, D.M., Son, J., Van Tassell, C.P., Lwein, H.A., Liu, G. 2016. Systematic profiling of bovine short tandem repeats using whole genome sequencing data. Genome Biology and Evolution. 9(1):20-31.
Xu, L., He, Y., Ding, Y., Sun, G., Carrillo, J., Li, Y., Ghaly, M.M., Ma, L., Zhang, H., Liu, G., Song, J. 2017. Characterization of copy number variation's potential Role in Marek’s disease. International Journal of Molecular Sciences. Available:http://wwww.mdpi.com/1422-0067/18/5/1020/pdf.
Sun, D., Gao, Y., Jiang, S., Yang, S., Hou, Y., Liu, G., Zhang, S., Zhang, Q. 2017. CNV discovery for milk composition traits in dairy cattle using whole genome resequencing. Biomed Central (BMC) Genomics. 18(1):265.
Padhi, A., Shen, B., Jiang, J., Zhou, Y., Liu, G., Ma, L. 2017. Ruminant-specific multiple duplication events of PRDM9 before speciation. BMC Evolutionary Biology. 17:79.
Spangler, G.L., Rosen, B.D., Iiori, M.B., Hanotte, O., Kim, E.S., Sonstegard, T.S., Burke, J.M., Morgan, J.L., Notter, D.R., Van Tassell, C.P. 2017. Whole genome structural analysis of Caribbean hair sheep reveals quantitative link to West African ancestry. PLoS One. 12(6):e0179021.
Bickhart, D.M., Rosen, B.D., Koren, S., Sayre, B.L., Hastie, A.R., Chan, S., Lee, J., Lam, E.T., Liachko, I., Sullivan, S.T., Burton, J., Huson, H.J., Kelley, C.M., Hutchison, J.L., Zhou, Y., Sun, J., Crisa, A., Ponce De Leon, F.A., Schwartz, J.C., Hammond, J.A., Waldbieser, G.C., Schroeder, S.G., Liu, G., Dunham, M., Shendure, J., Sonstegard, T.S., Phillippy, A.M., Van Tassell, C.P., Smith, T.P. 2017. Single-molecule sequencing and conformational capture enable de novo mammalian reference genomes. Nature Genetics. 49(4):643-650.