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.
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 was made on all three objectives of project 8042-31000-001-00D (Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection). For Objective 1 (develop biological resources and computational tools to enhance characterization of breed-specific bovine and other genomes), 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 the third-generation sequencing and mapping platforms (PacBio, Oxford Nanopore, and Hi-C) and leading international efforts to assemble breed-specific genomes for Holstein, Angus, Brahman, Jersey, Highland, Piedmontese, Simmental and other species (water buffalo, yak, gaur, bison). Transcript sequencing and analyses for improved genome annotation were completed as well as whole-genome bisulphite sequencing to study DNA methylation in over 20 somatic tissues. A second-generation, high-quality cattle gene atlas was built, and tissue-specific gene contribution to complex traits was studied. Copy-number variation (CNV) discovery was performed based on new long-read and linked-read sequencing data; CNV discovery based on short-read sequencing and microarray data and association studies were conducted (with collaborators) for Holsteins and goats. For Objective 2 (utilize genotypic data to enhance genetic improvement in ruminant production systems), development of genomic tools for selection continued. Space-Chip, a DNA-chip design software, was enhanced with more detailed weighting on individual markers to allow for more refined genotyping assays that can be customized by breed or subspecies. This enhancement allows for continued development of specialized single-nucleotide polymorphism (SNP) assays for genomic prediction in beef and dairy cattle breeds, Bos indicus cattle, water buffalo, goat, and other species. Genome assemblies and genotyping chips from extensive genome sequence data were developed with Indian collaborators for use in water buffalo and Bos indicus cattle. Additional SNPs were selected in collaboration with the International Goat Genome Consortium, AdaptMap, and VarGoats to augment the Illumina GoatSNP50 BeadChip for enhanced utility in more diverse goat breeds. In addition, differences between U.S. Jerseys and the original cattle from the Isle of Jersey were better determined in collaboration with the American Jersey Cattle Association. For Objective 3 (characterize functional genetic variation for improved fertility, growth, and environmental sustainability of ruminants), sequencing data were analyzed for a better understanding of functional genetic variations. Using 172 sequenced Holstein bulls and newly assembled immune gene haplotypes, 155 candidate SNPs were discovered that allowed distinguishing 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. Association studies were performed between bovine tuberculosis phenotypes and the new genetic markers to see if any were predictive of tuberculosis resistance or susceptibility. Additionally, the custom panel design has been sent to other collaborators to test on other animal cohorts.
1. Genomic assembly of the rumen microbial community. A better definition of the ruminant microbiome will improve the overall annotation of variations that affect 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, 188 novel host-viruses, and 94 antimicrobial-resistance genes that may confer antibiotic resistance to rumen bacteria.
2. A high-quality cattle gene atlas. A gene atlas serves as a primary resource for functional and evolutionary studies as well as genomic improvement in livestock. ARS scientists in Beltsville, Maryland, built a comprehensive gene atlas and studied tissue specificity of genes in cattle. This high-quality cattle gene atlas links gene expression in tissues and complex traits for the first time and provides an important basis for studying genotype-phenotype relationships in livestock.
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