Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection

Goals / 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.

Project Methods
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 10/01/21 to 09/30/22

Outputs
PROGRESS REPORT Objectives (from AD-416): 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 (from AD-416): 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. This is the final report for the Project 8042-31000-001-000D which will end July 23, 2022. New NP101 project, entitled ⿿Accelerating Genetic Improvement of Ruminants Through Enhanced Genome Assembly, Annotation, and Selection⿝ is being established. During the life of the project, 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 the improvement of reference genome assemblies. Assemblies have been released for goat (ARS1), cattle (UCD-ARS1.2), and sheep (ARS-UI_Ramb_v2.0). With a fraction of previous genome assembly costs, the quality of the latest references is far superior to any previous versions and has set a new standard for all other farm animals. The goat assembly was highlighted as the Milestones of the last 20 years of genomic sequencing by the journal of Nature (https://www.nature.com/immersive/d42859-020-00099-0/index.html) . The Bovine Pangenome Consortium was launched to describe the full extent of genetic variation in cattle through the creation of genome assemblies for bovine species of economic and biodiversity importance. Using the trio-binning method, the Consortium has released 15 breed-specific reference assemblies. The genome assemblies were generated from trios of Angus and Brahman, Nelore and Brown Swiss, and Original Braunvieh breeds. Additionally, Highland cattle and yak, Piedmontese cattle and gaur, Simmental cattle and bison, as well as for Holsteins and Jerseys to improve earlier efforts, and tropically adapted indicine breeds (Sahiwal, and Tharparkar). Copy-number variation (CNV) discovery and association studies were performed based on long-read and short-read sequencing data in cattle and goats. DNA methylation has important functions in animal production, health, and reproduction. High-resolution maps of cattle DNA methylation were generated for sperm and over 20 somatic tissues, showing methylation patterns across tissues and species. These high-resolution epigenomic maps for bovine tissues are a novel resource for epigenomic research and enable better understanding of genotype-phenotype relationships in economic traits when combined with gene expression information. Progress was made in the development of microbial genome resources beyond the projections of the original plan. Advances in microbial strain resolution were achieved using cutting edge technologies and newly developed software. This technique, developed by an ARS-led collaboration of industry and international scientists, is applicable to agriculturally- and clinically-relevant metagenomes and it allows for the identification of minor strains of bacterial populations that are as low as 2%. This resolution will enable the identification of potential pathogens before they can proliferate in a sample, or allow for the high-throughput study of microbial evolution in real-time with DNA sequencing. For Objective 2 (utilize genotypic data to enhance genetic improvement in ruminant production systems), ARS scientists collected and characterized a broad representation of African goats. These results included over 2, 400 goats genotyped from over 20 countries, representing over 50 breeds or populations. Two new software solutions for digital phenotyping were developed. Through collaboration with the AdaptMap and VarGoats Consortiums, 4,653 goats were genotyped and 1,372 have been sequenced worldwide. These data were used to study population genetics and positive sections in goats. Additional SNPs were also selected for parentage identification and, 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. ARS scientists, working with scientists in India, developed a high-density genotyping array (the IndiGau chip with 800,000 markers) for Zebu cattle using the Space-Chip software. The IndiGau chip has been used in marker-enhanced genetic improvement and understanding the purity and diversity among Zebu breeds. 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 SNPs were discovered that distinguished alleles of cattle immune genes, and 124 of them were included in custom genotype panels. Genome-wide association studies based on these custom markers reported that two markers predicted increased susceptibility to bovine tuberculosis. Additionally, combining parental genome and epigenome information, 16 and 25 genes were detected as potential candidate markers for male fertility and gestation length, respectively. Association studies were also performed to investigate the genetic basis of seven health traits in dairy cattle and 63 novel SNP markers identified from these studies were submitted to the NCBI⿿s Variation portal for public dissemination. A comprehensive gene atlas was built to study the 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. The FarmGTEx (genotype-tissue expression) Consortium was launched to provide a comprehensive atlas of tissue-specific gene expression and genetic regulation in farm animals. Both cattle and pig GTEx atlases were built based on ~10,000 transcript sequencing analyses in over 100 tissues/cell types among over 40 and 70 breeds, respectively. It described the transcriptome landscape across tissues and reports thousands of variants associated with gene expression and alternative splicing for dozens of major tissues. Additionally, this work allows us to interpret most of significant GWAS loci of economically important traits via integrative genomics analysis. A portal was developed to allow researchers to query gene expression, alternative splicing, and DNA regions associated with particular traits in an easy and uniform way across tissues and to serve as a primary reference source for farm animal genomics and breeding. ACCOMPLISHMENTS 01 Bovine Pangenome Consortium and construction of improved genome assemblies. Breeding better cattle using genomics requires informative reference genomes. Previously, a single Hereford cow provided the sole reference. This deprived researchers and breeders of important information about variation among individuals and breeds. Led by ARS scientists in Beltsville, Maryland; Madison, Wisconsin; and Clay Center, Nebraska, the Bovine Pangenome Consortium developed and improved genome assemblies. The team prioritized cattle breeds having important economic impact and sought to capture appreciable genetic variation. This cutting-edge group grew to over 90 members at 58 institutions in 27 countries. Using the triobinning method, employing two parents and an offspring, the Consortium published 11 breed-specific reference assemblies and is developing methods to incorporate information from those assemblies into a single, graph-based reference genome. They generated genome assemblies from trios from Brahman and Angus, Highland and yak, bison and Simmental, Original Braunvieh, Nellore and Brown Swiss, and Gaur and Piedmontese. They published these assemblies in Nature Communications, GigaScience, the Journal of Heredity. Together, these genome assemblies rival the most complete and accurate vertebrate genomes ever produced. Together, these genome assemblies rival the most complete and accurate vertebrate genomes ever produced. Scientists have already used these assemblies to identify novel trait-associated variation which can be used to increase accuracy of genetic merit prediction and selection for important production traits in target populations. 02 Farm Genotype-Tissue Expression (FarmGTEx) Consortium and the Cattle Gene Atlas. Understanding the regulation of livestock gene expression is important for studying the biological mechanisms that underlie economic traits and for improving animal selection. FarmGTEx is an international collaborative to provide a comprehensive atlas of tissue- specific gene expression and genetic regulation in farm animals. Led by ARS scientists in Beltsville, Maryland, and researchers at the University of Edinburgh in Edinburgh, Scotland, the FarmGTEx Consortium includes over 20 universities and institutes around the world. The pilot phase of FarmGTEx built both cattle and pig GTEx atlases for the research community based on almost ~10,000 publicly available RNA- sequence datasets that represent over 100 tissues and cell types among over 40 and 70 breeds, respectively. The atlases describe the landscape of transcriptome (the RNA expressed by an organism⿿s genome) across tissues and report thousands of variants associated with gene expression and alternative splicing (a process that enables RNA to direct synthesis of different protein variants with different cellular functions or properties) for major tissues. Additionally, this work allows us to interpret most of significant GWAS loci of economically important traits via integrative genomics analysis. Cattle GTEx was accepted for publication in Nature Genetics. A portal was developed to allow researchers to query gene expression, alternative splicing, and DNA regions associated with particular traits in an easy and uniform way across tissues and to serve as a primary reference source for farm animal genomics and breeding. Since December 2020, it has been used over 6,000 times by producers, breeders, and scientists, to improve animal production and health based on genome-enabled selection. 03 Unprecedented resolution of microbial strain differences. The microbiome is the combined genetic material of all microorganisms (bacteria, fungi, protozoa, and viruses) that live in a particular environment. Because those microorganisms exist in large communities that are difficult to assess using old DNA sequencing technologies, ARS scientists in Madison, Wisconsin, led a research project conducted by an international and interdisciplinary team of researchers from four countries (Including the Netherlands, and Israel) and two private U.S. companies (Phase Genomics and Pacific Biosciences) in developing new methods for microbiome screening. Using the latest high accuracy, long- read DNA sequencing technologies, microbial strains could be resolved down to single nucleotide polymorphisms (SNP) in the population. ARS Scientists worked with Bioinformaticians at Pacific Biosciences to develop the open-source software tool, MAGPhase, which automates the process of SNP discovery and validation in the microbiome. The improved accuracy of newer sequencing technologies allows the MAGPhase algorithm to identify clusters of SNPs (or haplotypes) that are representative of divergent strains of microbes that may harbor antibiotic resistance or pathogenesis genes. As a proof of principle analysis, a single sheep gastrointestinal sample was sequenced to great depths with the latest in long-read DNA sequencing. Using MAGPhase and improved genome assembly algorithms, 428 complete microbial genomes were assembled from that single sample, which was a record for a field that celebrated the assembly of 10 genomes from one individual. This accomplishment was of such importance that it was published in the journal, Nature Biotechnology (https://doi.org/10.1038/s41587-021-01130-z), with an accompanying opinion article highlighting its importance in Nature Microbiology (https://doi.org/10.1038/s41564-021-01027-2). The technological advance has already been applied to human microbiome research to better distinguish pathogens from beneficial microbes.

Impacts
(N/A)

Publications

Gao, Y., Li, J., Cai, G., Wang, Y., Yang, W., Li, Y., Zhao, X., Li, R., Gao, Y., Tuo, W., Baldwin, R.L., Li, C., Fang, L., Liu, G.E. 2022. Single- cell transcriptomic and chromatin accessibility analyses of dairy cattle peripheral blood mononuclear cells and their responses to lipopolysaccharide. BMC Genomics. 23:338. https://doi.org/10.1186/s12864- 022-08562-0.
Naji, M.M., Utsunomiya, Y.T., Solkner, J., Rosen, B.D., Meszaros, G. 2021. Assessing Bos taurus introgression in the UOA Bos indicus assembly. Genetics Selection Evolution. 53:96. https://doi.org/10.1186/s12711-021- 00688-1.
Zhang, T., Wang, T., Niu, Q., Xu, L., Chen, Y., Gao, X., Gao, H., Zhang, L. , Liu, G., Li, J., Xu, L. 2022. Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle. BMC Biology. 20(1):79. https://doi.org/10.1186/s12915-022-01269-4.
Yang, L., Gao, Y., Li, M., Park, K., Liu, S., Kang, X., Liu, M., Oswalt, A. , Fang, L., Telugu, B.P., Sattler, C.G., Cole, J.B., Seroussi, E., Xu, L., Li, C., Li, L., Zhang, H., Rosen, B.D., Van Tassell, C.P., Ma, L., Liu, G. 2022. Genome-wide recombination map construction from single sperm sequencing in cattle. BMC Genomics. 23(1):181. https://doi.org/10.1186/ s12864-022-08415-w.
Zhang, T., Wang, T., Niu, Q., Zheng, X., Li, H., Gao, X., Chen, Y., Gao, H. , Liu, G., Zhang, L., Li, J., Xu, L. 2022. Comparative transcriptomics analysis reveals differential expression regulation underlying fatty acid composition in multiple beef cuts. Foods. 11(1):117. https://doi.org/10. 3390/foods11010117.
Zhang, T., Wang, T., Niu, Q., Zheng, X., Li, H., Gao, X., Chen, Y., Gao, H. , Zhang, L., Liu, G., Li, J., Xu, L. 2022. Comparative transcriptomic analysis reveals region-specifc expression patterns in diferent beef cuts. Biomed Central (BMC) Genomics. 23(1):387. https://doi.org/10.1186/s12864- 022-08527-3.
Gao, Y., Liu, S., Baldwin, R.L., Connor, E.E., Cole, J.B., Ma, L., Fang, L. , Li, C., Liu, G. 2022. Functional annotation of regulatory elements in cattle genome reveals the roles of extracellular interaction and dynamic change of chromatin states in rumen development during weaning. Genomics. 114:110296. https://doi.org/10.1016/j.ygeno.2022.110296.
Guo, J., Rui, J., Mao, A., Liu, G., Zhan, S., Li, L., Zhong, T., Wang, L., Cao, J., Chen, Y., Zhang, G., Zheng, H. 2021. Genome-wide association study reveals 14 new SNPs and confirms two structural variants highly associated with the horned/polled phenotype in goats. BMC Genomics. 22:769. https://doi.org/10.1186/s12864-021-08089-w.
Yang, L., Gao, Y., Oswalt, A., Fang, L., Boschiero, C., Neupane, M., Sattler, C.G., Seroussi, E., Xu, L., Li, C., Li, L., Zhang, H., Rosen, B.D. , Van Tassell, C.P., Ma, L., Liu, G. 2022. Towards the detection of copy number variation from single sperm sequencing in cattle. BMC Genomics. 23(1):215. https://doi.org/10.1186/s12864-022-08441-8.
Yang, L., Gao, Y., Boschiero, C., Li, L., Zhang, H., Ma, L., Liu, G. 2021. Insights from initial variant detection by sequencing single sperm in cattle. Dairy. 2(4):649-657. https://doi.org/10.3390/dairy2040050.
Boschiero, C., Gao, Y., Liu, M., Baldwin, R.L., Ma, L., Li, C., Liu, G. 2022. The dynamics of chromatin accessibility prompted by butyrate-induced chromatin modification in bovine cells. Ruminants. 2(2):226-243. https:// doi.org/10.3390/ruminants2020015.
Gao, Y., Ma, L., Liu, G. 2022. Initial analysis of structural variation detections in cattle using long-read sequencing methods. Genes. 13(5):828. https://doi.org/10.3390/genes13050828.
Davenport, K.M., Bickhart, D.M., Worley, K.C., Murali, S.C., Salavati, M., Clark, E.L., Cockett, N., Heaton, M.P., Smith, T.P., Murdoch, B.M., Rosen, B.D. 2022. An improved ovine reference genome assembly to facilitate in depth functional annotation of the sheep genome. Gigascience. 11. Article giab096. https://doi.org/10.1093/gigascience/giab096.
Low, W.Y., Rosen, B.D., Ren, Y., Bickhart, D.M., To, T., Martin, F.J., Billis, K., Sonstegard, T.S., Sullivan, S.T., Hiendleder, S., Williams, J. L., Heaton, M.P., Smith, T.P. 2022. Gaur genome reveals expansion of sperm odorant receptors in domesticated cattle. BMC Genomics. 23(1):344. https:// doi.org/10.1186/s12864-022-08561-1.

Progress 10/01/20 to 09/30/21

Outputs
PROGRESS REPORT Objectives (from AD-416): 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 (from AD-416): 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 the improvement of cattle genome assemblies using sequence data from third-generation sequencing and mapping platforms (PacBio, Oxford Nanopore, and Hi-C) to assemble breed- specific genomes. Assemblies have been released for the Hereford, Holstein, and Jersey breeds. After pioneering the trio-binning method for the generation of fully haplotype-resolved genomes with Angus and Brahman breeds, scientists have generated genome assemblies from trios of Highland cattle and yak, Piedmontese cattle and gaur, and Simmental cattle and bison. Trio-binned haplotype-resolved cattle assemblies are in progress for Holsteins and Jerseys to improve earlier efforts as well as for tropically adapted indicine breeds (Gir, Sahiwal, and Tharparkar). Additionally, the genome of the Rambouillet ewe used for the ovine Functional Annotation of Animal Genomes (FAANG) project was improved by long-read sequencing, and the de novo assembly was released along with assemblies of the White Dorper and Romanov sheep breeds. Transcript sequencing analyses were completed in over 100 tissues/cell types among over 40 breeds. A high-quality cattle genotype-tissue expression (GTEx) atlas was built, and tissue-specific gene contribution to complex traits was studied. Copy-number variation (CNV) discovery was performed based on long-read and short-read sequencing data; CNV discovery based on short- read sequencing and association studies was conducted (with collaborators) for cattle 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, continues to be enhanced and used to design new DNA chips. These improvements enable continued development of specialized single- nucleotide polymorphism (SNP) assays for genomic prediction in a broad range of species. Genome assemblies and genotyping chips from extensive genome sequence data were developed with Indian collaborators for use in water buffalo and indicine cattle. The IndiGau 788K SNP chip was designed using the Space-Chip software, and preliminary results indicate this array will perform well, especially for Indian-derived 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. 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 those candidate markers, 124 have been used in custom genotype panels to determine their frequency in a cohort of 1,800 cows. Genome wide association studies involving the larger cohort found that two of the markers predicted increased susceptibility to bovine tuberculosis and will be useful in future genetic evaluations for tuberculosis resistance. A concurrent study at USDA⿿s Meat Animal Research Center in Clay Center, Nebraska, identified two custom markers that had strong and significant protective effects against persistent infection of bovine viral diarrhea. Combining parental genome and epigenome information, 16 and 25 genes were detected as potential candidate markers for male fertility and gestation length, respectively. Association studies were also performed to investigate the genetic basis of seven health traits in dairy cattle. Six significant associations and 20 candidate genes were identified for cattle health. All markers have been made public to assist in future cattle health and production genomic selection efforts. Record of Any Impact of Maximized Teleworking Requirement: Maximized telework due to COVID-19 severely hindered data generation and minimally affected data analysis to accomplish objectives. No additional samples were collected, no experiments were conducted, and sequencing was significantly reduced since March 2020. Jersey cattle sequencing was put on hold because of shelter-in-place policies. African goat collaborators in Uganda and Malawi have been unable to provide samples for genotyping because of lockdowns and new APHIS restrictions. The hiring of postdoctoral research associates and training of visiting students were severely delayed. Computational analysis of existing data via VPN largely was not affected during telework. ACCOMPLISHMENTS 01 Bovine Pangenome Consortium and generation of better genome assemblies. A reference genome assembly provides the foundation for genomic analysis, but the current cattle reference is derived from a single Hereford cow and is insufficient to describe the full extent of genetic variation in cattle. Led by ARS scientists in Beltsville, Maryland; Madison, Wisconsin; and Clay Center, Nebraska, the Bovine Pangenome Consortium was launched to create and improve genome assemblies for bovine species of economic and biodiversity importance and now includes over 60 members that represent 40 institutions in 20 countries. Using the trio-binning method, which is based on genomes from a family trio of parents and an offspring, the Consortium has released six breed- specific reference assemblies and is developing methods to incorporate those assemblies into a single reference. Genome assemblies were generated from trios from Brahman and Angus cattle, Highland cattle and yak, and bison and Simmental cattle; those assemblies were published in Nature Communications, GigaScience, and the Journal of Heredity, respectively. These six genome assemblies are among the most complete and accurate vertebrate genomes ever produced and have the potential to increase accurate identification and selection for production traits in target populations. 02 Farm Genotype-Tissue Expression (FarmGTEx) Consortium and the Cattle Gene Atlas. Understanding the regulation of livestock gene expression is important for studying the biological mechanisms that underlie economic traits and for improving animal selection. FarmGTEx is an international collaborative to provide a comprehensive atlas of tissue- specific gene expression and genetic regulation in farm animals. Led by ARS scientists in Beltsville, Maryland, and researchers at the University of Edinburgh in Edinburgh, Scotland, the FarmGTEx Consortium includes over 20 universities and institutes around the world. The pilot phase of FarmGTEx built a Cattle Gene Atlas for the research community based on almost 12,000 publicly available RNA-sequence datasets that represent over 100 tissues and cell types among over 40 breeds, and the atlas describes the landscape of transcriptome (the RNA expressed by an organism⿿s genome) across tissues and reports thousands of variants associated with gene expression and alternative splicing (a process that enables RNA to direct synthesis of different protein variants with different cellular functions or properties) for 24 major tissues in cattle. Additionally, this work detected 496 gene-tissue pairs significantly associated with 43 economically important traits in cattle via a large transcriptome-wide association study. A portal was developed to allow researchers to query gene expression, alternative splicing, and DNA regions associated with particular traits in an easy and uniform way across tissues and to serve as a primary reference source for cattle genomics, cattle breeding, adaptive evolution, comparative genomics, and veterinary medicine. 03 IndiGau, a high-density Zebu cattle genotyping platform. Zebu (or indicine) cattle, which originated on the Indian subcontinent, tend to be much more heat tolerant and resilient to parasites and disease, and their genetics are of increasing interest in combating the challenges of climate change. ARS scientists in Beltsville, Maryland, worked with scientists at the National Institute of Animal Biotechnology (NIAB) in India to develop a high-density genotyping array (the IndiGau chip) for Zebu cattle using sequence data from 20 animals for each of five breeds (Sahiwal, Gir, Tharparkar, Red Sindhi, and Kankrej) as well as from 2 animals for each of 38 remaining Indian breeds. Over 6 million high- quality genetic markers were identified, and an additional 1 million markers were available from several commercial genotyping arrays. The Space-Chip software developed by ARS researchers in Beltsville, Maryland, was used to select the best markers for performance of Zebu cattle, and the final IndiGau chip includes almost 800,000 markers. The IndiGau chip will be optimal for marker-enhanced genetic improvement and for understanding the purity and diversity among Zebu breeds. 04 New methods for microbiome screening. The microbiome is the combined genetic material of all microorganisms (bacteria, fungi, protozoa, and viruses) that live in a particular environment. Because those microorganisms exist in large communities that are difficult to assess using old DNA sequencing technologies, ARS scientists in Madison, Wisconsin, led a research project conducted by an international and interdisciplinary team of researchers from four countries (Russia, Netherlands, Israel, and the United States) and two private U.S. companies (Phase Genomics and Pacific Biosciences) in developing new methods for microbiome screening. Using the latest high accuracy, long- read DNA sequencing technologies, microbial strains could be resolved down to single nucleotide variants in the population. Over 44 bacterial genomes were assembled into single, continuous chromosome genomes, which is the highest ever achieved in a single sequenced sample, and using additional DNA sequencing methods, over 400 viral- and 250 plasmid-host associations were identified in this one sample. A manuscript describing the study is in review but also was released as a preprint so that results could be shared with the research community. These discoveries represent the highest resolution image of genomic DNA prevalence and transfer within a single community and will impact the interpretation of future microbiome sequencing results. 05 High-throughput method to assess microbial virus-host associations. Traditionally, researchers had to rely on direct observation via sequencing or through classical microbial isolation to determine virus- host associations. However, a better metagenomics tool could provide therapeutics and prophylactics in agriculture and human medicine. A collaboration between ARS scientists in Madison, Wisconsin, and Clay Center, Nebraska, and industry partner Phase Genomics in Seattle, Washington, has resulted in the development of a new sequence-based method that does not require manual labor and has high throughput. This method, which has been called ⿿proxiPhage⿝ by Phase Genomics, identifies host-virus associations using intracellular DNA-protein interactions and can detect a viral genome within a specific bacterial cell, which is direct evidence of infection. A preprint that details the method is being made available in advance of a more detailed survey on other metagenomics datasets. The beta version of proxiPhage was previously highlighted for a Federal Laboratory Consortium for Technology Transfer award and has already been used in clinical settings to identify gene alleles in the environment that are considered to provide antimicrobial resistance.

Impacts
(N/A)

Publications

Hu, Y., Xia, H., Li, M., Xu, C., Ye, X., Su, R., Zhang, M., Guo, A., Nash, O., Sonstegard, T.S., Yang, L., Liu, G., Zhou, Y. 2020. Comparative analyses of copy number variations between Bos taurus and Bos indicus. BMC Genomics. 21(1):682. https://doi.org/10.1186/s12864-020-07097-6.
Guo, J., Zhong, J., Liu, G., Yang, L., Li, L., Chen, G., Song, T., Zheng, H. 2020. Identification and population genetic analyses of copy number variations in six domestic goat breeds and Bezoar ibexes using next- generation sequencing. BMC Genomics. 21(1):840. https://doi.org/10.1186/ s12864-020-07267-6.
Zhang, W., Qu, Y., Lin, M., Datta, A., Liu, G., Li, B. 2020. Immune cells signaling-pathway and genomic profiles for personalized immunotherapy (Chapter 2). In: Li, B., Larson, A., Li, S. editors. Personalized Immunotherapy for Tumor Diseases and Beyond. Singapore, Singapore: Bentham Science Publishers Pte. Ltd. p. 20-42.
Zhang, W., Liu, G., Devemy, E., Li, B. 2020. Molecular screening and neoantigen cloning - Fundamental of adoptive T-cell immunotherapy (Chapter 6). In: Li, B., Larson, A., Li, S. editors. Personalized Immunotherapy for Tumor Diseases and Beyond. Singapore, Singapore: Bentham Science Publishers Pte. Ltd. p. 80-96.
Liu, G., Zheng, J., Li, B. 2020. Bioinformatics of T-cell and primary tumor cells - Fundamental of adoptive T-cell immunotherapy (Chapter 8). In: Li, B., Larson, A., Li, S. editors. Personalized Immunotherapy for Tumor Diseases and Beyond. Singapore, Singapore: Bentham Science Publishers Pte. Ltd. p. 118-136.
Li, B., Liu, G., Zheng, J. 2020. System modeling of T-cell function - Development of adoptive T-cell immunotherapy (Chapter 12). In: Li, B., Larson, A., Li, S. editors. Personalized Immunotherapy for Tumor Diseases and Beyond. Singapore, Singapore: Bentham Science Publishers Pte. Ltd. p. 197-223.
Yan, Z., Huang, H., Freebern, E., Santos, D.J., Dai, D.D., Si, J., Ma, C., Cao, J., Guo, G., Liu, G., Ma, L., Fang, L., Zhang, Y. 2020. Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle . BMC Genomics. 21(1):489. https://doi.org/ 10.1186/s12864-020-06909-z.
Liang, D., Zhao, P., Si, J., Fang, L., Xu, Q., Hou, Y., Hu, X., Gong, Y., Liang, Z., Tian, B., Mao, H., Yindee, M., Faruque, M.O., Liu, G., Wu, D., Barker, J.S., Han, J., Zhang, Y. 2020. A LINE-1 derived promoter driving over-expression of the ASIP gene is responsible for white color in swamp buffalo. Molecular Biology and Evolution. 38(3):1122-1136. https://doi.org/ 10.1093/molbev/msaa279.
Zhao, G., Zhang, T., Liu, Y., Wang, Z., Xu, L., Zhu, B., Gao, X., Zhang, L. , Gao, H., Liu, G., Li, J., Xu, L. 2020. Genome-wide assessment of runs of homozygosity in Chinese Wagyu beef cattle. Animals. 10(8):E1425. https:// doi.org/10.3390/ani10081425.
Kaumbata, W., Banda, L.J., Meszaros, G., Gondwe, T.N., Woodward Greene, M. J., Rosen, B.D., Van Tassell, C.P., Solkner, J., Wurzinger, M. 2020. Tangible and intangible benefits of local goats rearing in smallholder farms in Malawi. Small Ruminant Research. 87:106095. https://doi.org/10. 1016/j.smallrumres.2020.106095.
Nandolo, W., Meszaros, G., Banda, L.J., Gondwe, T.N., Mulindwa, H.A., Nakimbugwe, H.N., Wurzinger, M., Clark, E., Woodward Greene, M.J., Liu, M., Liu, G., Van Tassell, C.P., Rosen, B.D., Solkner, J. 2021. Detection of copy number variants in African goats using whole genome sequence data. BMC Genomics. 22(1):398. https://doi.org/10.1186/s12864-021-07703-1.
Naji, M.M., Utsunomiya, Y.T., Solkner, J., Rosen, B.D., Meszaros, G. 2021. Investigation of ancestral alleles in the Bovinae subfamily. Gigascience. 22(1):108. https://doi.org/10.1186/s12864-021-07412-9.
Heaton, M.P., Smith, T.P.L., Bickhart, D.M., Vander Ley, B.L., Kuehn, L.A., Oppenheimer, J., Shafer, W.R., Schuetze, F.T., Stroud, B., McClure, J.C., Barfield, J.P., Blackburn, H.D., Kalbfleisch, T.S., Davenport, K.M., Kuhn, K.L., Green, R.E., Shapiro, B., Rosen, B.D. 2021. A reference genome assembly of Simmental cattle, Bos taurus taurus. Journal of Heredity. 112(2):184-191. https://doi.org/10.1093/jhered/esab002.
Oppenheimer, J., Rosen, B.D., Heaton, M.P., Vander Ley, B.L., Shafer, W.R., Schuetze, F.T., Stroud, B., Kuehn, L.A., McClure, J.C., Barfield, J.P., Blackburn, H.D., Kalbfleisch, T.S., Bickhart, D.M., Davenport, K.M., Kuhn, K.L., Green, R.E., Shapiro, B., Smith, T.P.L. 2021. A reference genome assembly of American bison, Bison bison bison. Journal of Heredity. 112(2) :174-183. https://doi.org/10.1093/jhered/esab003.
Gao, Y., Fang, L., Baldwin, R.L., Connor, E.E., Cole, J.B., Van Tassell, C. P., Ma, L., Li, C., Liu, G. 2021. Single-cell transcriptomic analyses of cattle ruminal epithelial cells before and after weaning. Genomics. 113(4) :2045-2055. https://doi.org/10.1016/j.ygeno.2021.04.039.
Edwards, R.J., Field, M.A., Ferguson, J.M., Dudchenko, O., Keilwagen, J., Rosen, B.D., Johnson, G.S., Rice, E., Hillier, L., Hammond, J.M., Towarnicki, S.G., Omer, A., Skvortsova, K., Bogdanovic, O., Zammit, R.A., Aiden, E.L., Warren, W.C., Ballard, J.W. 2021. Chromosome-length genome assembly and structural variations of the primal Basenji dog (Canis lupus familiaris) genome. BMC Genomics. 22(1):188. https://doi.org/10.1186/ s12864-021-07493-6.
Kaumbata, W., Nakimbugwe, H.N., Nandolo, W., Banda, L.J., Meszaros, G., Gondwe, T.N., Woodward Greene, M.J., Rosen, B.D., Van Tassell, C.P., S0lkner, J., Wurzinger, M. 2021. Experiences from the implementation of community-based goat breeding programs in Malawi and Uganda: a potential approach for conservation and improvement of indigenous small ruminants in smallholder farms. Sustainability. 13(3):1494. https://doi.org/10.3390/ su13031494.

Progress 10/01/19 to 09/30/20

Outputs
Progress Report Objectives (from AD-416): 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 (from AD-416): 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. Accomplishments 01 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. 02 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.

Impacts
(N/A)

Publications

Huson, H.J., Sonstegard, T.S., Godfrey, J., Hambrook, D., Wolfe, C., Wiggans, G.R., Blackburn, H.D., Van Tassell, C.P. 2020. A genetic investigation of Island of Jersey cattle, the foundation of the Jersey breed. Frontiers in Genetics. 11:366.
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.
Liu, S., Fang, L., Zhou, Y., Santos, D.J.A., Xiang, R., Daetwyler, H.D., Chamberlain, A.J., Cole, J.B., Li, C., Yu, Y., Ma, L., Zhang, S., Liu, G. 2019. Analyses of inter-individual variations in sperm DNA methylation reveal their regulatory role in gene expression and association with reproduction traits in cattle. BMC Genomics. 20:888.
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):80.
Zhou, Y., Liu, S., Hu, Y., Fang, L., Gao, Y., Xia, H., Schroeder, S.G., Rosen, B.D., Connor, E.E., Li, C., Baldwin, R.L., Cole, J.B., Van Tassell, C.P., Yang, L., Ma, L., Liu, G. 2020. Comparative whole genome DNA methylation profiling of cattle tissues reveals global and tissue-specific methylation patterns. BMC Biology. 18(1):85.
Liu, M., Woodward Greene, M.J., Kang, X., Pan, M.G., Rosen, B.D., Van Tassell, C.P., Chen, H., Liu, G. 2020. Genome-wide CNV analysis revealed variants associated with growth traits in African indigenous goats. Genomics. 112(2):1477-1480.
Freebern, E., Santos, D.J., Fang, L., Jiang, J., Parker-Gaddis, K., Liu, G. , Van Raden, P.M., Maltecca, C., Cole, J.B., Ma, L. 2020. GWAS and fine- mapping of livability and six health traits in Holstein cattle. BMC Genomics. 21:41.
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.
Seroussi, E., Shirak, A., Gershoni, M., Ezra, E., Santos, D.J., Ma, L., Liu, G. 2019. Bos taurus-indicus hybridization correlates with intralocus sexual-conflicting effects of PRDM9 on male and female fertility in Holstein cattle. BMC Genetics. 20:71.
Fang, L., Liu, S., Liu, M., Kang, X., Lin, S., Li, B., Connor, E.E., Baldwin, R.L., Tenesa, A., Ma, L., Liu, G., Li, C. 2019. Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations. BMC Biology. 17(1):68.
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.
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.
Santos, D.J., Cole, J.B., Liu, G., Van Raden, P.M., Ma, L. 2020. Gamevar. f90: A software package for calculating individual gametic diversity. BMC Bioinformatics. 21:100.
Fang, L., Cai, W., Liu, S., Canela-Xandri, O., Gao, Y., Jiang, J., Rawlik, K., Li, B., Schroeder, S.G., Rosen, B.D., Li, C., Sonstegard, T.S., Alexander, L.J., Van Tassell, C.P., Van Raden, P.M., Cole, J.B., Yu, Y., Zhang, S., Tenesa, A., Ma, L., Liu, G. 2019. Comprehensive analyses of 723 transcriptomes enhance biological interpretation and genomic prediction for complex traits in cattle. Genome Research. 30(5):790-801.

Progress 10/01/18 to 09/30/19

Outputs
Progress Report Objectives (from AD-416): 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 (from AD-416): 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. 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 01 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. 02 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. 03 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. 04 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.

Impacts
(N/A)

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.
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.
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.
Amills, M., Rischowsky, B.A., Ajmone-Marsan, P., Boettcher, P., Boyle, O., Bradley, D., Cano Pereira, M.E., Catillo, G., Colli, L., Crepaldi, P., Crisà, A., Del Corvo, M., Daly, K., Droegemuelle, K., Duruz, S., Elbeltagi, A., Esmailizadeh, A., Faco, O., Flury, C., Garcia, J.F., Guldbrandtsen, B. , Haile, A., Hallsteinn Hallsson, J., Heaton, M.P., Hunnicke Nielsen, V., Huson, H., Joost, S., Kijas, J., Lenstra, J.A., Milanesi, M., Minhui, C., Morry O'Donnell, R., Moses Danlami, O., Mwacharo, J., Nicolazzi, E.L., Marras, G., Palhiere, I., Pilla, F., Poli, M., Reecy, J., Rochat, E., Rosen, B.D., Rothschild, M., Rupp, R., Sayre, B., Servin, B., Silva, K., Sonstegard, T.S., Spangler, G.L., Stella, A., Steri, R., Talenti, A., Tortereau, F., Tosser, G., Vajana, E., Van Tassell, C.P., Zhang, W. 2018. AdaptMap: Exploring goat diversity and adaptation. Genetic Selection Evolution. 50:61.
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.
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.
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.
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.
Johnson, T., Keehan, M., Harland, C., Lopdell, T., Spelman, R.J., Davis, S. R., Rosen, B.D., Smith, T.P. 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.
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.
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.
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.
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.
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.
Xu, L., Yang, L., Wang, L., Zhu, B., Chen, Y., Gao, H., 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.
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.
Liu, M., Zhou, Y., Rosen, B.D., Van Tassell, C.P., Stella, A., Tosser, G., Rupp, R., Colli, L., Sayre, B., Crepaldi, P., Meszaros, G., Adaptmap Consortium, Chen, H., Liu, G. 2018. Diversity of copy number variation in the worldwide goat population. Heredity. 122:636⿿646.

Progress 10/01/17 to 09/30/18

Outputs
Progress Report Objectives (from AD-416): 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 (from AD-416): 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. 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. ARS scientists also completed transcript sequencing (RNA-Seq/Iso-Seq) for improved genome annotation, the first whole genome bisulphite sequencing (WGBS) study for sperm DNA methylation. 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 water buffalo, sheep and goats. ARS scientists computed the first genomic predictions that combined CNV and SNP markers. For Objective 2, 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. ARS scientists used genetic data derived from genome sequencing and SNP chips to better understand natural and artificial selection in cattle and goats. In collaborating with IGGC and ADAPTmap, analysis of signatures from selection was completed using SNP data derived from the Illumina Caprine50K assay for more than 3,000 goats identifying several signatures of selection in different chromosomic regions. These regions contain genes that are involved in important biological processes, such as milk, meat or fiber related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences, confirming previous findings in other species about adaptation to extreme environments and human purposes and provide new genes that could explain goat differentiation to geographical distributions and adaptation to different environments. For Objective 3, ARS scientists generated 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, we 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, 67 have been used in custom genotype panels to determine their frequency in a cohort of 1,800 cows. We plan to perform 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. If successful, these marker sites could be used in future association studies to determine their effects on resistance to other common cattle diseases. Accomplishments 01 Improved the reference genome assembly for Hereford L1 Dominette 01449 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 ARS, Clay Center, Nebraska, University of California Davis, Computomics, Dovetail Genomics, University of Maryland, and University of Missouri Columbia. This assembly includes an over 250 times increase of fragment size and near 200 times decreases of gaps representing many fold improvements over the existing cattle assembly. The associated annotation data and statistics for the new cattle reference are now publicly available on the NCBI website. 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. 02 Whole genome sequencing was conducted to study a diverse group of African goats. A total of over 300 goats collected by the African Goat Improvement Network (AGIN) through a collaboration with several groups. The project is part of the AdaptMap consortium that is combining efforts to characterize a global resource population. Sequencing has been done by ARS scientists at Beltsville, Maryland, as well as through two collaborations. A project called VarGoat has been coordinated by scientists at Institut national de la recherche agronomique (INRA) as part of the AdaptMap efforts as well as a collaboration with Roslin Institute, Scottish Agricultural College. These collaborations have resulted in far more animals being sequenced than AGIL staff would have been able to achieve. 03 Completed first genomic prediction study by integrating copy number variation (CNV) and single nucleotide polymorphism (SNP) in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some production traits in cattle. CNV was shown to be associated with disease and complex traits in humans and livestock. However, its impact on genomic selection has never been evaluated. In this study, CNV were included in a SNP based genomic selection framework. A small increase in prediction accuracy for some traits was detected when including CNVs in the models. 04 Completed the first high resolution maps of DNA methylation in bovine sperm using sequencing. DNA methylation plays important functions in individual development and reproduction. ARS scientists at Beltsville, Maryland, profiled the DNA methylation of cattle sperm through comparison with three somatic tissues (mammary gland, brain, and blood). Large differences between cattle sperm and somatic cells were observed in the methylation patterns. This study provides a comprehensive resource for bovine sperm epigenomic research and enables new discoveries about DNA methylation and its role in male fertility. 05 Development of a new method of DNA extraction that enables long-read sequencing of microbial samples. By using a robust, yet gentle, breakup protocol, longer DNA molecules are able to be extracted from complex, reluctant microbial samples. This protocol will enable the use of long-read sequence data to be used in metagenome sequencing and assembly, which is likely to improve the rumen microbial reference genomes. Additionally, this method has applications in the preparation of other metagenomics communities for long-read sequencing, particularly soil-based communities that may be important for assessing agriculturally relevant runoff dynamics.

Impacts
(N/A)

Publications

Hutchison, J.L., Van Raden, P.M., Null, D.J., Cole, J.B., Bickhart, D.M. 2017. Genomic evaluation of age at first calving. Journal of Dairy Science. 100(8):6853-6861.
Ghurye, J., Pop, M., Koren, S., Bickhart, D.M., Chin, C. 2017. Scaffolding of long read assemblies using long range contact information. Biomed Central (BMC) Genomics. 18(1):527.
Yang, L., Xu, L., Zhou, Y., Liu, M., Wang, L., Kijas, J.W., Zhang, H., Li, L., Liu, G. 2017. Diversity of copy number variation in a worldwide population of sheep. Genomics. 110(3):143-148.
Iamartino, D., Nicolazzi, E.L., Van Tassell, C.P., Reecy, J.M., Fritz- Waters, E.R., Koltes, J.E., Biffani, S., Sonstegard, T.S., Schroeder, S.G., Ajmone-Marsan, P., Negrini, R., Pasquariello, R., Ramelli, P., Coletta, A. , Garcia, J.F., Ali, A., Ramunno, L., Cosenza, G., De Oliveira, D., Drummond, M.G., Bastianetto, E., Davassi, A., Pirani, A., Brew, F., Williams, J.L. 2017. Design and validation of a 90K SNP genotyping assay for the Water Buffalo (Bubalus bubalis). PLoS One. 12(10): e0185220.
Bickhart, D.M., Weimer, P.J. 2017. Bovine rumen metagenomics � moving beyond microbial diversity. Journal of Dairy Science. 101:1-10.
Utsunomiya, Y., Milanesi, M., Utsunomiya, A., Torrecilha, R., Kim, E., Silva, M., Do Carmo, A.S., Carvalheiro, R., De Rezende Neves, H.H., Padula, R., Sussai, T., Zavarez, L.B., Cipriano, R.S., Caminhas, M., Hambrecht, G. , Colli, L., Eufemi, E., Ajmone-Marsan, P., Buora, M., Liu, G., Bickhart, D.M., Van Tassell, C.P., Solkner, J., Sonstegard, T.S., Garcia, J.F. 2017. A haplotype spanning PLAG1 contributed to stature recovery in modern cattle. Scientific Reports. 7(1):17140.
Zhou, Y., Shen, B., Jiang, J., Padhi, A., Park, K., Oswalt, A., Sattler, C. , Telugu, B.P., Chen, H., Cole, J.B., Liu, G., Ma, L. 2017. Construction of PRDM9 allele-specific recombination maps in cattle using large-scale pedigree analysis and genome-wide single sperm genomics. DNA Research. 25(2):183�194.
Porto-Neto, L.R., Bickhart, D.M., Landaeta-Hernandez, A.J., Utsunomiya, Y. T., Morales, M.P., Caban-Jimenez, E., Hansen, P.J., Dikmen, S., Schroeder, S.G., Sun, J., Crespo, E., Amati, N., Cole, J.B., Null, D.J., Garcia, J.F., Reverter, A., Barendse, W., Sonstegard, T.S. 2018. Convergent evolution of slick coat in cattle through truncation mutations in the prolactin receptor. Frontiers in Genetics. 9:57.
Connor, E.E., Yang, Z., Liu, G. 2018. The essence of appetite: Does olfactory receptor variation play a role? Journal of Animal Science. 96(4) :1551-1558.
Shen, B., Jiang, J., Seroussi, E., Liu, G., Ma, L. 2018. Characterization of recombination features and the genetic basis in multiple cattle breeds. Biomed Central (BMC) Genomics. 19(1):304.
Zhou, Y., Connor, E.E., Bickhart, D.M., Li, C., Baldwin, R.L., Schroeder, S.G., Rosen, B.D., Yang, L., Van Tassell, C.P., Liu, G. 2018. Comparative whole genome DNA methylation profiling of cattle sperm and somatic tissues reveals striking hypomethylated patterns in sperm. Gigascience. 7(5):1-13.
Zhao, P., Yu, Y., Feng, W., Du, H., Yu, J., Kang, H., Zheng, X., Wang, Z., Liu, G., Ernst, C.W., Ran, X., Wang, J., Liu, J. 2018. Evidence of evolutionary history and selective sweeps in the genome of Meishan pig reveals its genetic and phenotypic characterization. Gigascience. 7(5):1- 12.
Zhou, Y., Connor, E.E., Wiggans, G.R., Lu, Y., Tempelman, R., Schroeder, S. G., Chen, H., Liu, G. 2018. Genome-wide copy number variant analysis reveals variants associated with 10 diverse production traits in Holstein cattle. BMC Genomics. 19(1):314.
Hay, E.A., Utsunomiya, Y.T., Xu, L., Zhou, Y., Neves, H.H., Carvalheiro, R. , Bickhart, D.M., Garcia, J., Liu, G. 2018. Genomic predictions combining SNP markers and copy number variations in Nellore cattle. Biomed Central (BMC) Genomics. 19(1):441.
Lamuno, D., Solkner, J., M�sz�ros, G., Nakimbugwe, H., Mulindwa, H., Nandolo, W., Gondwe, T., Van Tassell, C.P., Gutierrez, G., Mueller, J., Wurzinger, M. 2018. Evaluation framework of community-based livestock breeding programs. Livestock Research for Rural Development. 30(3):47.
Li, W., Bickhart, D.M., Ramunno, L., Iamartino, D., Williams, J., Liu, G. 2018. Comparative sequence alignment reveals River Buffalo genomic structural differences compared with cattle. Genomics.
Schwartz, J.C., Philp, R.L., Bickhart, D.M., Smith, T.P., Hammond, J.A. 2018. The antibody loci of the domestic goat (Capra hircus). Immunogenetics. 70: 317-326. doi:
Li, W., Bickhart, D.M., Ramunno, L., Lamartino, D., Williams, J., Liu, G. 2018. Genomic structural differences between cattle and river buffalo identified through a combination and genomic and transcriptomic analysis. Data in Brief. 19:236-239.