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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Research Project #433411
Research Project: Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection

Location: Animal Genomics and Improvement Laboratory

2019 Annual Report


Objectives
Objective 1: Develop biological resources and computational tools to enhance characterization of breed-specific bovine and other genomes. De novo reference genome assemblies will be developed for dairy cattle breeds (Holstein and Jersey). In addition, improvements will be made to the existing, but suboptimal, reference assemblies for Bos taurus cattle and Zebu cattle (Bos indicus). These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms segregating in target populations. Genome characterization will be done by state-of-the-art platforms using short- and long-read sequencing of selected animals. Candidate animals will be derived from those populations targeted for genome-based genetic improvement to enable development of novel tools for proper parent and breed composition identification. To complement these studies, epigenomic and metagenomic surveys will be explored to better define DNA methylation and ruminant microbiome, which in turn will improve overall annotation of genes, genetic variation, epigenetic variation and other sequence motifs affecting phenotype expression. Objective 2: Utilize genotypic data to enhance genetic improvement in ruminant production systems. This objective has two components. The first component identifies signatures of selection and evaluates the potential to develop community-based breeding programs based on population structure and management system limitations in goats. The second component requires the optimization and application of statistical methodologies to develop cheap low-density SNP panels that can be used to guide genetic improvement of production traits while maintaining variants enriched by natural selection during adaptation of local breeds to marginal production environments. Objective 3: Characterize functional genetic variation for improved fertility, growth, and environmental sustainability of ruminants. The third objective involves detection of genetic variation affecting fertility, growth and environmental sustainability during early embryonic development or adaptation to climate or disease using whole genome or exome resequencing. The resultant sequence information will be integrated with other database resources that provide basic information about gene expression activity and motif patterns to guide selection of positional candidate genes for further study and validation of functional annotation in ruminants. Sub-objectives for objectives 1,2 and 3 are listed in post plan under related documents.


Approach
Completion of our objectives is expected, in the short term, to improve genome-wide selection in the U.S. dairy industry as well as facilitate 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 sequencing and comparative genomics, quantitative genetics, epigenomics and metagenomics, all of which are components of this project plan and areas of expertise in our group. Efforts to characterize genome activity and structural conservation/variation are an extension of our current research program in applied genomics. This project plan completely leverages the resources derived from the Bovine Genomes, HapMap, 1000 Bull Genomes and FAANG projects, and genotypic data derived from the Council on Dairy Cattle Breeding (CDCB) genome-enhanced genetic evaluations for North American dairy cattle.


Progress Report
For Objective 1, ARS scientists in Beltsville, Maryland, continued as global leaders for production of DNA sequence information by improving the cattle genome assembly based on sequence data from a third-generation sequencing and mapping platforms (PacBio, optical mapping, and Hi-C) and leading international efforts to assemble breed-specific genomes for Holstein, Angus, Brahman, Jersey and other species (water buffalo). ARS scientists also completed transcript sequencing (RNA-Seq/Iso-Seq) for improved genome annotation, the whole genome bisulphite sequencing (WGBS) to study DNA methylation in over 20 somatic tissue. Based on SNP array data and high-throughput sequencing data, ARS scientists performed copy number variation (CNV) discovery and CNV-based population genetics studies in Holstein, water buffalos and goats. ARS scientists completed the first comparative epigenomic study among human, mouse and cattle and evaluated epigenomic contribution to the complex traits. For Objective 2, ARS scientists in Beltsville, Maryland, continued development of genomic tools for selection. These efforts included continued development of specialized SNP assays for genomic prediction in beef and dairy cattle breeds, Bos indicus cattle, water buffalo, goat, and other species. ARS scientists with Indian collaborators are developing genome assemblies and genotyping tools from extensive genome sequence data for use in water buffalo and Bos indicus cattle. In collaborating with IGGC, ADAPTmap, and VarGoat additional SNP have been identified to augment the Illumina Caprine50K assay to enhance utility in more diverse goats. In addition, ARS has worked with the American Jersey Cattle Association to better characterize the U.S. Jersey breed and to add Jersey-specific genomic content to SNP chips that are based predominately on Holstein variants. For Objective 3, ARS scientists analyzed sequencing data to better understand functional genetic variations for improved fertility, growth, and environmental sustainability of ruminants. Using 172 sequenced Holstein bulls and newly assembled immune gene haplotypes, ARS scientists discovered 155 candidate single nucleotide polymorphisms that could distinguish between alleles of cattle immune genes that provide innate resistance to diseases. Of these candidate markers, 124 have been used in custom genotype panels to determine their frequency in a cohort of 1,800 cows. ARS scientists performed association studies between bovine tuberculosis phenotypes and these new genetic markers to see if any of these newly discovered sites is predictive of tuberculosis resistance or susceptibility. Additionally, ARS scientists have sent the custom panel design to other collaborators to test on other animal cohorts.


Accomplishments
1. Candidate bacterial hosts for viruses in the rumen. Better definition of the ruminant microbiome was needed to improve overall, genetic variation, and phenotype expression. In a large international collaboration between scientists from the United Kingdom (Roslin Institute) and the United States (USDA ARS, Pacific Biosciences, Phase Genomics, and the National Institute of Health), ARS researchers in Beltsville, Maryland, assembled 103 medium-quality draft genomes from bacteria and archaea in the cattle rumen and identified 188 novel host-viral interactions of the activity of viruses in the cattle rumen. Using the new assembly methods pioneered by ARS scientists allowed identification of 94 antimicrobial-resistance genes to rumen bacteria.

2. Generation of haplotype-resolved assemblies from hybrid data. Most existing mammalian genome assemblies are a flattened representation of two pairs of chromosomes. These chromosomes often have significant structural variations that make them difficult to represent as a single sequence, cause disruption of the assembly of gene regions, and result in errors in reference genomes. Collaborators at the National Institute of Health with ARS scientists in Beltsville, Maryland, developed a new method called triobinning to assemble each pair of chromosomes individually by using information derived from the parents of the sequenced individual. The separation of chromosomes by parent is 99% accurate and results in more continuous assemblies. The new triobinning method has already been adopted by international research groups and is being used to assemble reference genomes for water buffalo in India and flowering cherry in Japan.

3. Whole genome sequencing of goats as a global resource. Genome-enhanced breeding strategies are needed to bring economic and genetic stability to developing countries dependent on goat resources. Through international collaboration of the AdaptMap consortium, more than 300 goats were DNA sampled by the African Goat Improvement Network (AGIN), and DNA sequencing was completed by ARS scientists in Beltsville, Maryland, as well as through collaboration with the VarGoats project coordinated by scientists at Institut National de la Recherche Agronomique (INRA) and with Roslin Institute at the Scottish Agricultural College. The extensive collaboration has resulted in sequencing total of 829 goats from around the world.

4. First high-resolution maps of DNA methylation in bovine sperm and somatic tissues using sequencing. DNA methylation has important functions in animal production, health, and reproduction. Increased knowledge of methylation patterns is needed to determine functional effects on genomic features. ARS scientists in Beltsville, Maryland, profiled the DNA methylation of cattle sperm through comparison with more than 20 somatic tissues and discovered large differences in methylation patterns among cattle sperm and somatic cells. These first high-resolution maps of DNA methylation for bovine sperm are a comprehensive resource for epigenomic research and enable additional discoveries about the role of DNA methylation in male fertility.


Review Publications
Bertolini, F., Servin, B., Talenti, A., Rochat, E., Kim, E., Oget, C., Palhiere, I., Crisa, A., Catillo, G., Steri, R., Amills, M., Colli, L., Marras, G., Milanesi, M., Nicolazzi, E., Rosen, B.D., Van Tassell, C.P., Guldbrandtsen, B., Sonstegard, T.S., Tosser-Klopp, G., Stella, A., Rothschild, M.F., Joost, S., Crepaldi, P. 2018. Signatures of selection and environmental adaptation across the goat genome post-domestication. Genetic Selection Evolution. 50:57. https://doi.org/10.1186/s12711-018-0421-y.
 Colli, L., Milanesi, M., Talenti, A., Bertolini, F., Chen, M., Crisa, A., Daly, K., Del Corvo, M., Guldbrandtsen, B., Lenstra, J.A., Rosen, B.D., Vajana, E., Catillo, G., Joost, S., Nicolazzi, E., Rochat, E., Rothschild, M.F., Servin, B., Sonstegard, T.S., Steri, R., Van Tassell, C.P., Ajmone-Marsan, P., Crepaldi, P., Stella, A. 2018. Genome-wide SNP profiling of worldwide goat populations reveals a strong partitioning of diversity and highlights post-domestication migration routes. Genetic Selection Evolution. 50:58. https://doi.org/10.1186/s12711-018-0422-x.
 Fang, L., Zhou, Y., Liu, S., Jiang, J., Bickhart, D.M., Null, D.J., Li, B., Schroeder, S.G., Rosen, B.D., Cole, J.B., Van Tassell, C.P., Ma, L., Liu, G. 2019. Comparative analyses of sperm DNA methylomes among human, mouse and cattle provide insights into epigenomic evolution and complex traits. Epigenetics. 14(3):260-276. https://doi.org/10.1080/15592294.2019.1582217.
 Stella, A., Nicolazzi, E.L., Van Tassell, C.P., Rothschild, M., Colli, L., Rosen, B.D., Sonstegard, T.S., Crepaldi, P., Tosser, G., Joost, S., Adaptmap Consortium. 2018. AdaptMap: Exploring goat diversity and adaptation. Genetic Selection Evolution. 50:61. https://doi.org/10.1186/s12711-018-0427-5.
 Liu, M., Fang, L., Liu, S., Pan, M.G., Seroussi, E., Cole, J.B., Ma, L., Chen, H., Liu, G. 2019. Array CGH-based detection of CNV regions and their potential association with reproduction and other economic traits in Holsteins. BMC Genomics. 20:181. https://doi.org/10.1186/s12864-019-5552-1.
 Xu, L., He, Y., Ding, Y., Liu, G., Zhang, H., Cheng, H.H., Taylor, R.L., Song, J. 2018. Genetic assessment of inbred chicken lines indicates genomic signatures of resistance to Marek’s disease. Journal of Animal Science and Biotechnology. 9:65. https://doi.org/10.1186/s40104-018-0281-x.
 Liu, S., Kang, X., Catacchio, C.R., Liu, M., Fang, L., Schroeder, S.G., Li, W., Rosen, B.D., Iamartino, D., Iannuzzi, L., Sonstegard, T.S., Van Tassell, C.P., Ventura, M., Low, W., Williams, J.L., Bickhart, D.M., Liu, G. 2019. Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo (Bubalus bubalis). Functional and Integrative Genomics. 19(3):409–419. https://doi.org/10.1007/s10142-019-00657-4.
 Fang, L., Jiang, J., Li, B., Zhou, Y., Freebern, E., Van Raden, P.M., Cole, J.B., Liu, G., Ma, L. 2019. Genetic and epigenetic architecture of paternal origin contribute to gestation length in cattle. Communications Biology. 2:100. https://doi.org/10.1038/s42003-019-0341-6.
 Johnson, T., Keehan, M., Harland, C., Lopdell, T., Spelman, R.J., Davis, S.R., Rosen, B.D., Smith, T.P., Couldrey, C. 2019. Short communication: Identification of the pseudoautosomal region in the Hereford bovine reference genome assembly ARS-UCD1.2. Journal of Dairy Science. 102(4):3254-3258. https://doi.org/10.3168/jds.2018-15638.
 Liu, M., Li, B., Shi, T., Huang, ., Liu, G., Lan, X., Lei, C., Chen, H. 2019. Copy number variation of bovine SHH gene is associated with body conformation traits in Chinese beef cattle. Journal of Applied Genetics. 60(2):199–207. https://doi.org/10.1007/s13353-019-00496-w.
 Fang, L., Zhou, Y., Liu, S., Jiang, J., Bickhart, D.M., Null, D.J., Li, B., Schroeder, S.G., Rosen, B.D., Cole, J.B., Van Tassell, C.P., Ma, L., Liu, G. 2019. Integrating signals from sperm methylome analysis and genome-wide association study for a better understanding of male fertility in cattle. Epigenomes. 3(2):10. https://doi.org/10.3390/epigenomes3020010.
 Nandolo, W., Meszaros, G., Banda, L.J., Gondwe, T.N., Lamuno, D., Mulindwa, H., Nakimbugwe, H.N., Wurzinger, M., Utsunomiya, Y.T., Woodward Greene, M.J., Liu, M., Liu, G., Van Tassell, C.P., Curik, I., Rosen, B.D., Solkner, J. 2019. Timing and extent of inbreeding in African goats. Frontiers in Genetics. 10:57. https://doi.org/10.3389/fgene.2019.00537.
 Liu, M., Li, B., Peng, W., Ma, Y., Huang, Y., Lan, X., Lei, C., Qi, X., Liu, G., Chen, H. 2019. LncRNA-MEG3 promotes bovine myoblast differentiation by sponging miR-135. Journal of Cellular Physiology. https://doi.org/10.1002/jcp.28469.
 Rexroad III, C.E., Vallet, J.L., Matukumalli, L.K., Ernst, C., Van Tassell, C.P., Cheng, H.H., Reecy, J., Fulton, J., Taylor, J., Lunney, J.K., Liu, J., Cockett, N., Smith, T.P., Van Eenennaam, A., Clutter, A., Telugu, B., Purcell, C., Bickhart, D.M., Blackburn, H.D., Neibergs, H., Wells, K., Boggess, M.V., Sonstegard, T. 2019. Genome to phenome: improving animal health, production, and well-being: a new USDA blueprint for animal genome research 2018–2027. Frontiers in Genetics. 10:327. https://doi.org/10.3389/fgene.2019.00327.
 Xu, L., Yang, L., Wang, L., Zhu, B., Chen, Y., Gao, H., Gao, X., Zhang, L., Liu, G., Li, J. 2019. Probe-based association analysis identifies several deletions associated with average daily gain in beef cattle. BMC Genomics. 20(1):31. https://doi.org/10.1186/s12864-018-5403-5.
 Kurz, J.P., Zhou, Y., Weiss, R.B., Wilson, D.J., Rood, K.J., Liu, G., Wang, Z. 2018. A genome-wide association study for mastitis resistance in phenotypically well-characterized Holstein dairy cattle using a selective genotyping approach. Immunogenetics. 71(1):35-47. https://doi.org/10.1007/s00251-018-1088-9.
 Liu, M., Zhou, Y., Rosen, B.D., Van Tassell, C.P., Stella, A., Tosser, G., Rupp, R., Palhiere, I., Colli, L., Sayre, B., Crepaldi, P., Fang, L., Meszaros, G., Chen, H., Liu, G., Adaptmap Consortium. 2018. Diversity of copy number variation in the worldwide goat population. Heredity. 122:636–646. https://doi.org/10.1038/s41437-018-0150-6.