ENHANCING GENETIC MERIT OF RUMINANTS THROUGH GENOME SELECTION AND ANALYSIS

Goals / Objectives
The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants.

Project Methods
Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative.

Progress 10/01/16 to 09/30/17

Outputs
Progress Report Objectives (from AD-416): The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants. Approach (from AD-416): Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative. This is the final report for the Project 8042-31000-104-00D which will end July 23, 2017. New NP101 project, entitled �Enhancing Genetic Merit of Ruminants through Improved Genome Assembly, Annotation and Selection� is being established. During the life of the project, ARS scientists in Beltsville, Maryland, continued as global leaders for production of DNA sequence information by completing the first mammalian genome assembly based solely on caprine sequence data from a third generation sequence platform (PacBio) and contributing all the sequence for international efforts to assemble genomes and single nucleotide polymorphism (SNP) discovery for Bos indicus cattle, extinct Bos primigenius cattle, water buffalo, and other species. In additional, ARS Scientists in Beltsville, Maryland, developed novel genomic tools for selection. These efforts included development of multiple specialized SNP assays for genomic prediction in beef and dairy cattle breeds, Bos indicus cattle, water buffalo, goat, and other species, including turkey. ARS scientists used genetic data derived from genome sequencing and SNP chips to better understand natural and artificial selection in cattle and goats. This effort included searching for genetic variations (SNPs, short insertions and deletions), recessive lethal alleles, runs of homozygosity, regions of the genome under natural selection. This effort also included a comprehensive screen for candidate regions under positive selection across ruminant populations as a result of geographic adaptation and artificial selection. For example, ARS scientists led the effort to characterize the profound impact of genomic selection on population dynamics in dairy cattle. These also included identifying causative mutations affecting SLICK and fertility haplotypes (HH1, BH2, HH3), as well as mapping genomic regions for tropical adaptation, production, and genetic defects (e.g., limber leg and rectovaginal constriction) in cattle. ARS scientists also completed transcript sequencing (RNAseq) for improved genome annotation, the first reduced representation bisulphite sequencing (RRBS) study for DNA methylation, and the first comprehensive prediction of transcription factor binding sites (TFBS) in the cattle genome. Based on SNP array data and high-throughput sequencing data, ARS scientists performed copy number variation (CNV) discovery and CNV-based population genetics studies. ARS scientists also performed genome-wide association studies (GWAS) between CNV and various production and health traits, and designed an integrated tool (RAPTR-SV) to identify CNV using data derived from various discovery platforms. ARS scientists computed the first genomic predictions that combined CNV and SNP markers. This effort demonstrated that combining CNV and SNP marker information can be beneficial for several traits. Furthermore, ARS scientists developed methods to discover microsatellite or short tandem repeats based on high- throughput sequencing. This analysis identified more than 60,000 microsatellites and made it possible to study selection using microsatellites in cattle. Finally, ARS scientists developed two novel photographic methods and a database system for collecting goat phenotypes, and implemented eight community breeding programs in Uganda and Malawi using that technology. In collaborating with IGGC and ADAPTmap, analysis of signatures from natural selection continued using SNP data derived from the Illumina Caprine50K assay for more than 3,000 goats. Accomplishments 01 Completed a reference genome assembly for Capra hircus (goat) using PacBio sequence data and advanced genome scaffolding technologies. Genome assemblies have been produced for numerous species as a result of advances in sequencing technologies; however, many of the assemblies are fragmented, with many gaps, ambiguities, and errors. This was a team effort of ARS scientists in Beltsville, Maryland, working in tandem with members of the National Human Genome Research Institute (NGHRI), USDA MARC, BioNano Genomics, Phase Genomics, and the PirBright Institute (based in the UK). This reference genome represents a 250- fold improvement in continuity over the previously available goat reference assembly that was generated with a sequencing strategy using second-generation short-read sequencing. The annotation data and scaffold statistics for the new goat reference genome are now publicly available on the NCBI genome portal and the quality of the assembly has been publicly praised by NCBI staff in unaffiliated conference presentations. This technique � described in an article published in Nature Genetics - promises to reduce the cost of generating high- quality reference genome assemblies for other animal and plant species. 02 Identification of the West African origins of Caribbean hair sheep. ARS scientists in Beltsville, Maryland, working with scientists from the University of Nottingham, Recombinetics, USDA DBSFRS, Katahdin Hair Sheep International, and Virginia Tech clarified the contributions of African and European sheep breeds to the ancestry of Caribbean hair sheep. Hair sheep of Caribbean origin have become an important part of the U.S. sheep industry. Their lack of wool eliminates a number of health concerns and drastically reduces the cost of production. More importantly, Caribbean hair sheep demonstrate robust production performance even in the presence of drug-resistant gastrointestinal nematodes, a rising concern to the industry. This study used genotypes from 47,750 autosomal SNPs scored in 290 animals to characterize the population structure of the St. Croix, Barbados Blackbelly, Morada Nova, and Santa Ines and established an objective measure indicating Caribbean hair sheep are derived from Iberian and West African origins. This is a major step towards a better understanding of the source of Caribbean hair sheep resilience in the face of high parasite load. 03 Completed the first single-base-resolution maps of bovine DNA methylation in cattle. DNA methylation plays important functions in individual development and various diseases. However, only limited data exist in cattle. This work evaluated over 1.8 million cytosines and detected thousands of differentially methylated cytosines and hundreds of differentially methylated CG islands. Further analyses revealed that many of them were highly correlated with the expression of genes involved in tissue development. This study provided a baseline dataset and essential information for DNA methylation profiles of cattle.

Impacts
(N/A)

Publications

Garcia, A., Cole, J.B., Van Raden, P.M., Wiggans, G.R., Ruiz, F., Van Tassell, C.P. 2016. Changes in genetic selection differentials and generation intervals in US dairy cattle as a result of genomic selection. Proceedings of the National Academy of Sciences. 113:E3995�E4004.
Adams, H.A., Sonstegard, T.S., Van Raden, P.M., Null, D.J., Van Tassell, C. P., Larkin, D.M., Lewin, H.A. 2016. Identification of a nonsense mutation in APAF1 that is likely causal for a decrease in reproductive efficiency in Holstein dairy cattle. Journal of Dairy Science. 99(8):6693-6701.
Van Raden, P.M., Tooker, M.E., O'Connell, J.O., Cole, J.B., Bickhart, D.M. 2017. Selecting sequence variants to improve genomic predictions for dairy cattle. Genetics Selection Evolution. 49:32.
Schwartz, J.C., Gibson, M.S., Heimeier, D., Koren, S., Phillippy, A.M., Bickhart, D.M., Smith, T.P., Medrano, J.F., Hammond, J.A. 2017. The evolution of the natural killer complex; a comparison between mammals using new high-quality genome assemblies and targeted annotation. Immunogenetics. 69(2):255-269.
Zhou, Y., Utsunomiya, Y.T., Xu, L., Hay, E.A., Bickhart, D.M., Carvalheiro, R., Neves, H.H., Van Tassell, C.P., Sonstegard, T.S., Garcia, J., Liu, G. 2016. Comparative analyses across cattle breeds reveal the pitfalls caused by artificial and lineage-differential copy number variations. Scientific Reports. 6:29219.
Zhou, Y., Xu, L., Bickhart, D.M., Hay, E., Schroeder, S.G., Connor, E.E., Leeson, A.J., Sonstegard, T., Van Tassell, C.P., Hong, C., Liu, G. 2016. Reduced representation bisulphite sequencing of the cattle genome reveals DNA methylation patterns. BMC Genomics. 17(1):779.
Hay, E.A., Choi, I., Xu, L., Zhou, Y., Rowland, R., Lunney, J.K., Liu, G. 2017. CNV analysis of host responses to porcine reproductive and respiratory syndrome virus infection. Journal of Genomics. 5:58-63.
Xu, L., Haasl, R.J., Sun, J., Zhou, Y., Bickhart, D.M., Son, J., Van Tassell, C.P., Lwein, H.A., Liu, G. 2016. Systematic profiling of bovine short tandem repeats using whole genome sequencing data. Genome Biology and Evolution. 9(1):20-31.
Xu, L., He, Y., Ding, Y., Sun, G., Carrillo, J., Li, Y., Ghaly, M.M., Ma, L., Zhang, H., Liu, G., Song, J. 2017. Characterization of copy number variation's potential Role in Marek�s disease. International Journal of Molecular Sciences. Available:
Sun, D., Gao, Y., Jiang, S., Yang, S., Hou, Y., Liu, G., Zhang, S., Zhang, Q. 2017. CNV discovery for milk composition traits in dairy cattle using whole genome resequencing. Biomed Central (BMC) Genomics. 18(1):265.
Padhi, A., Shen, B., Jiang, J., Zhou, Y., Liu, G., Ma, L. 2017. Ruminant- specific multiple duplication events of PRDM9 before speciation. BMC Evolutionary Biology. 17:79.
Spangler, G.L., Rosen, B.D., Sonstegard, T.S., Van Tassell, C.P. 2017. Whole genome structural analysis of Caribbean hair sheep reveals quantitative link to west african ancestry. PLoS One. 12(6):e0179021.
Bickhart, D.M., Rosen, B.D., Koren, S., Sayre, B.L., Hastie, A.R., Chan, S. , Lee, J., Lam, E.T., Liachko, I., Sullivan, S.T., Burton, J., Huson, H.J., Kelley, C.M., Hutchison, J.L., Zhou, Y., Sun, J., Crisa, A., Ponce De Leon, F.A., Schwartz, J.C., Hammond, J.A., Waldbieser, G.C., Schroeder, S. G., Liu, G., Dunham, M., Shendure, J., Sonstegard, T.S., Phillippy, A.M., Van Tassell, C.P., Smith, T.P. 2017. Single-molecule sequencing and conformational capture enable de novo mammalian reference genomes. Nature Genetics. 49(4):643-650.

Progress 10/01/15 to 09/30/16

Outputs
Progress Report Objectives (from AD-416): The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants. Approach (from AD-416): Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative. For Objective 1, ARS scientists in Beltsville, Maryland continued as global leaders for production of DNA sequence information by completing the first mammalian genome assembly based solely on caprine sequence data from a third generation sequence platform (PacBio) and contributing sequence for international efforts to assemble genomes and single nucleotide polymorphism (SNP) discovery for catfish, extinct Bos primigenius cattle, and other species. For Objective 2, ARS scientists continued to develop new genomic tools for selection. A turkey genotyping array development was led by Beltsville Agricultural Research Center scientists under a public-private partnership with Hendrix Genetics, Aviagen Ltd and Affymetrix to provide a better understanding of Turkey genetics. The commercial release of that chip occurred in November, 2015. For Objective 3, ARS scientists continued to use genomic tools to better understand natural and artificial selection in cattle and goats. ARS published a paper about identifying causative mutations affecting fertility haplotypes HH1 in Holsteins. ARS scientists developed methods in discovering microsatellite or short tandem repeats based on high throughput sequencing. This analysis identified more than 60,000 microsatellites and made it possible to study selection using microsatellites in Holsteins. ARS contributed to the collaboration to characterize tropical adaptation by characterizing the Nellore cattle genome using genetic data derived from genome sequencing and the BovineHD SNP array. To assist genetic selection, this effort included searching for genetic variations (SNPs, short insertions and deletions), recessive lethal alleles, runs of homozygosity, regions of the genome under natural selection for beef production, tropical adaptation, health and fertility. ARS scientists along with collaborators at INIFAP (National Institute of Forestry, Agricultural, and Livestock Research) in Mexico characterized the profound impact of genomic selection on population dynamics in dairy cattle. ARS scientists developed two novel photo methods and a database system for collecting goat phenotypes, and implemented three community breeding programs in Uganda and Malawi. In collaborating with IGCC and ADAPTmap, analysis of signatures from natural selection continued using more than 2000 goat data derived from the Illumina Caprine50K assay. Additionally, for Objective 2, ARS scientists performed the first genomic predictions combining copy number variation (CNV) and SNP markers in Nellore cattle. This effort demonstrates that combining CNV and SNP marker information can be beneficial for several traits. ARS scientists performed genome-wide association studies (GWAS) between copy number variations (CNV) and mastitis resistance traits in Holstein cattle and host responses to porcine reproductive and respiratory syndrome virus infection in pigs. ARS scientists performed and published an two CNV- based population genetics studies using BovineHD SNP array data and high- throughput sequencing data. Accomplishments 01 Completed a reference genome assembly for Capra hircus (goat) using PacBio sequence data and advanced genome scaffolding technologies. Genome assemblies have been produced for numerous species as a result of advances in sequencing technologies; however, many of the assemblies are fragmented, with many gaps, ambiguities, and errors. This is a team effort of ARS scientists in Beltsville, Maryland working in tandem with members of the National Human Genome Research Institute (NGHRI), USDA MARC, BioNano Genomics, Phase Genomics and the PirBright Institute (based in the UK). This reference genome represents a 250-fold improvement in continuity over the previously available goat reference assembly, which was generated with a sequencing strategy using second- generation short-read sequencing. The annotation data and scaffold statistics for the new goat genome now surpass those of the cattle reference genome assembly, which was deemed as the standard for quality among the sequenced agricultural species. This technique � described in a submitted publication -- promises to reduce the cost of generating high-quality reference genome assemblies for other animal and plant species. 02 Phenotype and genotype collection for African goats in Community Based Breeding Programs (CBBP). ARS scientists in Beltsville, Maryland collected and characterized a broad representation of African goats to develop SNP panels for parentage and to identify selection signatures for optimized selection. Two digital phenotype software methods were developed as an alternative to manual body measurement weight prediction, with electronic phenotype recording. Preliminary results from over 4000 goats have been sampled from over 20 countries, representing over 50 breeds or populations and over 60 locations, show many current breed definitions are inaccurate. A low-density genotyping panel for parentage identification to enable selective breeding from performance history is under development. We plan to genotype a subset of foundation animals from all CBBP sites, with a single site per country for deeper genotyping across a population, to enable association of genetic markers with community selected phenotypes which may enable them to apply genomics to selection. 03 Completed the first genome-wide discovery of cattle microsatellites using high-throughput sequencing. Microsatellites or STRs have become an essential marker for mapping quantitative trait loci (QTL) due to their high variability and easy amplification by PCR, however, there was no existing genome-wide microsatellite data in cattle. ARS scientists in Beltsville, Maryland optimized a human microsatellite detection approach and then performed the first discovery study of cattle microsatellites. This work identified a total of more than 60, 000 microsatellites, generated the first high-resolution microsatellite map and found hundreds of candidate microsatellite loci under selection. This study provided the foundation for future microsatellite-based studies of cattle genome evolution and selection. 04 Performed the first genomic predictions combining copy number variation and SNP markers in cattle. Traditional genomic selection fails in varying degrees for some complex traits, because SNP markers are not sufficient to predict these traits due to the missing heritability caused by additional genetic variations, including copy number variation (CNV). ARS scientists in Beltsville, along with their Brazilian collaborators in St. Paulo State University (UNESP), performed the first CNV-enhanced genetic prediction in cattle. CNVs derived from high density SNP microarray data were included in a SNP- based genomic selection framework and modeled through currently best available models. This result revealed that combining CNV and SNP marker information was beneficial for genomic prediction of some traits in Nellore cattle.

Impacts
(N/A)

Publications

Sun, J., Aswath, K., Schroeder, S.G., Lippolis, J.D., Reinhardt, T.A., Sonstegard, T.S. 2015. MicroRNA expression profiles of bovine milk exosomes in response to Staphylococcus aureus infection. Biomed Central (BMC) Genomics. 16:806.
Bickhart, D.M., Xu, L., Hutchison, J.L., Cole, J.B., Schroeder, S.G., Song, J., Garcia, J., Van Tassell, C.P., Sonstegard, T.S., Schnabel, R.D., Taylor, J.F., Lewin, H.A., Liu, G. 2016. Whole-genome sequencing reveals the diversity of cattle copy number variations and multicopy genes. DNA Research. 23(3):253-62.
Li, Y., Carrillo, J.A., Ding, Y., He, Y., Zhao, C., Lui, J., Liu, G., Zan, L., Song, J. 2015. Transcriptomic profiling of spleen in grass-fed and grain-fed Angus cattle. PLoS One. 10(9):e0135670.
Wiggans, G.R., Cooper, T.A., Van Raden, P.M., Van Tassell, C.P., Bickhart, D.M., Sonstegard, T.S. 2016. Increasing the number of single nucleotide polymorphisms used in genomic evaluation of dairy cattle. Journal of Dairy Science. 99(6):4504-4511.
Utsunomiya, Y.T., Ribeiro, E.S., Quintal, A.P., Sangalli, J.R., Gazola, V. R., Paula, H.B., Trinconi, C.M., Lima, V.M., Perri, S.H., Taylor, J.F., Schnabel, R.D., Sonstegard, T.S., Garcia, J.F., Nunes, C.M. 2015. Genome- wide scan for visceral leishmaniasis in mixed-breed dogs identifies candidate genes involved in T helper cells and macrophage signaling. PLoS One. 10(9):e0136749.
Wang, L., Xu, L., Liu, X., Zhang, T., Li, N., Zhang, Y., Yan, H., Zhao, K., Liu, G., Zhang, L., Wang, L. 2015. CNV-based genome wide association study reveals additional variants contributing to meat quality in swine. Scientific Reports. 5:12535.
Xu, L., Hou, Y., Bickhart, D.M., Zhou, Y., Hay, E.A., Song, J., Sonstegard, T., Van Tassell, C.P., Liu, G. 2016. Population-genetic properties of differentiated copy number variations in cattle. Scientific Reports. 6:23161.
Zhou, Y., Utsunomiya, Y.T., Xu, L., Hay, E.A., Bickhart, D.M., Carvalheiro, R., Neves, H.E., Sonstegard, T., Van Tassell, C.P., Garcia, J., Liu, G. 2016. Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus. Biomed Central (BMC) Genomics. 17(1):419.2016.
Park, S.D., Magee, D.A., Mcgettigan, P.A., Teasdale, M.D., Edwards, C.J., Lohan, A.J., Murphy, A., Braud, M., Donoghue, M.T., Liu, Y., Chamberlain, A.T., Rue-Albrecht, K., Schroeder, S.G., Spillane, C., Tai, S., Bradley, D. G., Sonstegard, T.S., Loftus, B.J., Machugh, D.E. 2015. Genome sequencing of the extinct Eurasian wild aurochs illuminates the phylogeography and evolution of cattle. Genome Biology. 16(1):1-15.
Whitacre, L.K., Tizioto, P.C., Kim, J., Sonstegard, T., Schroeder, S.G., Alexander, L.J., Medrano, J.F., Schnabel, R.D., Taylor, J.F., Decker, J.E. 2015. What's in your next-generation sequence data? An exploration of unmapped DNA and RNA sequence reads from the bovine reference individual. BMC Genomics. 16:1114.
Benavides, M., Sonstegard, T.S., Kemp, S., Mugambi, J.M., Gibson, J., Baker, R., Hanottte, O., Marshall, K., Van Tassell, C.P. 2015. Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC. PLoS One. doi: 10.1371/journal. pone.0122797.eCollection2015.
Song, Q., Jia, G., Hyten, D.L., Jenkins, J., Hwang, E., Schroeder, S.G., Schmutz, J., Jackson, S.A., Mcclean, P., Cregan, P. 2015. SNP marker development for linkage map construction, anchoring of the common bean whole genome sequence and genetic research. G3, Genes/Genomes/Genetics. doi: 10.1534/g3.115.020594.

Progress 10/01/14 to 09/30/15

Outputs
Progress Report Objectives (from AD-416): The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants. Approach (from AD-416): Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative. Under Objective 1, ARS scientists in Beltsville, Maryland continued as global leaders for production of genome sequence information from ruminant species by completing a de novo genome assembly of Bos indicus and the first mammalian (goat) genome assembly based solely on data from a third generation sequence platform (PacBio). Relative to Objective 2, ARS scientists continued to use genomic tools to better understand natural and artificial selection in cattle and goats. ARS scientists developed methods to characterize runs of DNA sequencing homozygosity to detect signatures of artificial selection in contemporary Holsteins compared to an unselected control line. Analysis of sequence signatures from natural selection will continue using more than 1,500 indigenous cattle from Brazil, Venezuela, and Turkey using newly generated data derived from the 700K single nucleotide polymorphism (SNP) beadchip assay (the BovineHD from Illumina) and 600 indigenous goats from Ethiopia, Nigeria, Kenya, Uganda, Turkey, and Egypt using the Illumina Caprine50K assay. To date, regions of the genome under natural selection for thermotolerance (second SLICK mutation), resistance to diseases endemic to Africa, and signatures of selection for carcass traits and fertility have been detected in cattle. This effort also includes a comprehensive screen for candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, Nelore, and N'Dama as a result of geographic adaptation and artificial selection. Other efforts included additional sampling of indigenous goat populations in Mali, Madagascar, Burundi, Tanzania, Egypt, and the Sudan. ARS scientists continued development of a database system for collecting goat phenotypes, and initiated three community breeding programs in Uganda and Malawi. Under Objective 3, ARS scientists performed genome-wide association studies (GWAS) between copy number variations (CNV) and parasite resistance traits in Angus cattle and between CNV and milk traits in Holsteins, and finished an integrated tool/algorithm to merge CNV results derived from various discovery platforms. ARS scientists also generated and analyzed additional whole-genome sequences to identify potential causative mutations affecting fertility haplotype BH2 in Brown Swiss and two different SLICK loci in Senepol and Limonero cattle. Validation genotyping of 900 tropically adapted cattle was completed to confirm the causative variant for thermo-tolerance from the Senepol-derived SLICK allele. Accomplishments 01 Completed a draft reference assembly for Capra hircus (goat) entirely using PacBio sequence data. This is a team effort of ARS scientists in Beltsville, Maryland, working in tandem with members of the National Biodefence and Countermeasures Center (NBACC), USDA MARC, and BioNano Genomics. This reference genome represents a 10-fold improvement in scaffold quality (N50) over the previously available goat reference assembly, which was generated with a sequencing strategy using second- generation short-read sequencing. Additionally, this technique promises to reduce the cost of generating high-quality reference genome assemblies for other animal and plant species by eliminating the need for costly genome finishing experiments to generate chromosome-scale scaffolds. The annotation data and scaffold statistics for the new goat genome now surpass those of the cattle reference genome assembly, which was deemed as the standard for quality among the sequenced agricultural species. It is likely that these methods will be used by computational biologists to generate most future reference genome assemblies and will be used to refine existing resources for agricultural species. 02 Completed one of the first attempts to genotype cattle copy number variation (CNV) within large, diverse populations using sequence data. Taking advantage of the tandem duplication pattern, ARS scientists in Beltsville, Maryland, optimized a new CNV genotyping approach and then performed a population study of cattle CNV. Their findings reveal cattle population structures and uncover lineage-specific or differential CNVs near genes like ASZ1, GAT, GLYAT, and KRTAP9-1. This work provides a new CNV genotyping approach for computational biologists to use for many domesticated animals with genome assemblies currently in the draft status, and where CNV distribution patterns are in tandem. It also provides the foundation for computational biologists to correlate CNV with economically important complex traits. 03 Identified two novel mutations related to thermo-tolerance in cattle. Heat stress is a major problem for efficient production of livestock in tropical and sub-tropical regions. Introduction of adaptive genetic variation for thermo-tolerance is one potential way to increase sustainable production in these regions. Through genome-wide association studies and whole-genome re-sequencing of Criollo breeds of cattle in Venezuela, two novel stop-gain mutations in the prolactin receptor gene were identified that confer the slick hair coat and thermo-tolerance to cattle. These results are convergent adaptive evidence of the importance of heat tolerance in taurine cattle, and provide animal breeders with targets for precision breeding to accelerate genetic improvement of cattle under stress of climate change. 04 Developed tools for precision breeding in dairy production. Traditional selection for dairy production has been focused on polygenic, additive traits of milk production. Due the influence of a few notable historic sires, we hypothesized that signatures of selection encompassing some of the elite Jersey genetics would be evident when comparing animals by birth year. AGIL attempted to identify the genomic locations of traits under selection through analysis of runs of homozygosity using Jersey herdbook genotypes. Our results revealed that genomic inbreeding is not significantly associated with fertility depression; however, many of the recent signatures of selection coincided with genes possibly effecting protein component traits. These results can be used by animal breeders to find variation underlying milk component traits to develop tools for precision breeding.

Impacts
(N/A)

Publications

Mattson, E., Xu, L., Li, L., Liu, G., Xiao, Z. 2014. Transcriptome profilling of CTLs regulated by rapamycin using RNA-Seq. Immunogenetics. 66(11):625-33.
Xu, L., Zhao, F., Ren, H., Li, L., Lu, J., Liu, J., Zhang, S., Liu, G., Song, J., Zhang, L., Wei, C., Du, L. 2014. Co-expression analysis of fetal weight-related genes in ovine skeletal muscle during mid and late fetal development stages. International Journal of Medical Sciences. 10(9):1039- 50.
Xu, L., Bickhart, D.M., Cole, J.B., Schroeder, S.G., Song, J., Van Tassell, C.P., Sonstegard, T.S., Liu, G. 2014. Genomic signatures reveal geographic adaption and human selection in cattle. Molecular Biology and Evolution. 32(3):711-25.
Xu, L., Cole, J.B., Bickhart, D.M., Hou, Y., Song, J., Van Raden, P.M., Sonstegard, T.S., Van Tassell, C.P., Liu, G. 2014. Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins. Biomed Central (BMC) Genomics. 15:683.
Da Silva, M., Dos Santos, D.J., Boison, S.A., Utsunomiya, A.T., Do Carmo, A.S., Sonstegard, T.S., Cole, J.B., Van Tassell, C.P. 2014. The development of genomics applied to dairy breeding. Livestock Science. 166:66-75.
Kim, E., Cole, J.B., Huson, H.J., Wiggans, G.R., Van Tassell, C.P., Crooker, B.A., Liu, G., Da, Y., Sonstegard, T.S. 2013. Effect of artificial selection on runs of Homozygosity in U.S. Holstein cattle. PLoS One. DOI: 10.1371/journal.pone.0080813.
Zavarez, L.B., Utsunomiya, Y.T., Carmo, A.S., Neves, H.H., Carvalheiro, R., Ferencakovic, M., P�rez O�Brien, A.M., Curik, I., Cole, J.B., Van Tassell, C.P., Silva, M.V., Sonstegard, T.S., S�lkner, J., Garcia, J.F. 2015. Assessment of autozygosity in Nellore cows (Bos indicus) through high- density SNP genotypes. Frontiers in Genetics. 6:5.
McClure, M.C., Sonstegard, T.S., Wiggans, G.R., Van Eenennaam, A., Weber, K., Penedo, M., Berry, D.P., Flynn, J., Garcia, J., Santana Do Carmo, A., Regitano, L., Albuquerque, M., Silva, M.V., Machado, M.A., Coffey, M., Moore, K., Boscher, M., Genestout, L., Mazza, R., Taylor, J.F., Schnabel, R., Simpson, B., Marques, E., Mc Ewan, J., Cromie, A., Lehmann Coutinho, L. , Kuehn, L.A., Keele, J.W., Piper, E., Cook, J., Williams, R., Hap Map Consortium, B., Van Tassell, C.P. 2013. Imputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple Bos taurus and Bos indicus breeds. Frontiers in Genetics. 4:176. DOI.10.3389/fgene.2013.00176.
Somavilla, A., Sonstegard, T.S., Higa, R.H., Rosa, A.N., Siqueira, F., Silva, F.L., Silva, L., Torres, R.A., Coutinho, L.L., Alvarenga Mudadu, M., Alencar, M.M., Regitano, L. 2014. A genome-wide scan for selection signatures in Nelore cattle. Animal Genetics. 45(6):771-81.
Kim, E., Sonstegard, T.S., Rothschild, M. 2015. Recent artificial selection in U.S. Jersey cattle impacts autozygosity levels of specific genomic regions. Biomed Central (BMC) Genomics. 16(1):302.
Utsunomiya, Y.T., Perez O'Brien, A.M., Sonstegard, T.S., Solkner, J., Garcia, J. 2015. Genomic data as the 'hitchhiker's guide' to cattle adaptation: Time to track the milestones of past selection in the bovine genome. Frontiers in Genetics. DOI: 10.3389/fgene.2015.00036.
Perez O'Brien, A.M., Meszaros, G., Utsunomiya, Y.T., Sonstegard, T.S., Fernando Garcia, J., Van Tassell, C.P., Carvalheiro, R., Da Silva, M.V., Solkner, J. 2014. Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions. Livestock Science. 166:121-132.
Dikmen, S., Khan, F., Huson, H., Sonstegard, T.S., Moss, J., Dahl, G., Hansen, P. 2014. The SLICK Locus derived from Senepol cattle confers thermotolerance to Intensively-Managed lactating Holstein cows. Journal of Dairy Science. 97(9):5508-20.
Sn De Oliveira, P., Cesar, A., Do Nascimento, M.L., Chaves, A.S., Tullio, R.R., Lanna, D., Rosa, A.N., Sonstegard, T.S., Mourao, G.B., Reecy, J.M., Garrick, D.J., Mudadu, M.A., Coutinho, L.L., Regitano, L.C. 2014. Identification of genomic regions associated with feed efficiency in Nelore cattle. BioMed Central (BMC) Genetics 15:100. DOI:10.1186/s12863- 014-0100-0.
Porto-Neto, L.R., Reverter, A., Prayaga, K.C., Chan, E., Johnston, D.J., Hawken, R.J., Fordyce, G., Fernando Garcia, J., Sonstegard, T.S., Bolormaa, S., Goddard, M., Burrow, H., Henshall, J., Lehnart, S., Barendse, W. 2014. The genetic architecture of climatic adaptation in tropical cattle. PLoS Genetics. 9(11):e113284.
Carvalheiro, R., Boison, A., Neves, H.H., Sargolzaei, M., Schenkel, F., Utsunomiya, Y.T., O'Brien, A., Solkner, J., Mcewan, J., Van Tassell, C.P., Sonstegard, T.S., Garcia, F. 2014. Genotype imputation efficiency in Nelore Cattle. Genetics Selection Evolution. 46(1):69.
Perez O'Brien, A.M., Holler, D., Boison, S.A., Milanesi, M., Utsunomiya, Y. T., Carvalheiro, R., Neves, H.H., Da Silva, M.V., Bomba, L., Van Tassell, C.P., Sonstegard, T.S., Ajmone-Marsan, P., Garcia, F., Solkner, J. 2015. Levels of taurine introgression in the current Brazilian Nelore and Gir indicine cattle populations. Genetics Selection Evolution. 47(1):31.
Tizioto, P.C., Taylor, J.F., Decker, J.E., Gromboni, C.F., Mudadu, M.A., Schnabel, R.D., Coutinho, L.L., Mourao, G.B., Nassu, R.T., Donatoni, F.A., Tholon, P., Sonstegard, T.S., Alencar, M.M., Tullio, R.R., Reecy, J., Nogueira, A.R., Regitano, L.C. 2015. Effects of quantitative trait loci on mineral content 1 of bovine longissimus dorsi muscle. Genetic Selection Evolution. 47(1):15.
Daetwyler, H.D., Capitan, A., Pausch, H., Stothard, P., Van Binsbergen, R., Brandum, R.F., Liao, X., Djari, A., Rodriguez, S., Grohs, C., Jung, S., Esquerre, D., Gollnick, N., Rossignol, M., Klopp, C., Rocha, D., Fritz, S., Eggen, A., Bowman, P., Coote, D., Chamberlin, A., Van Tassell, C.P., Huggsle, I., Goddard, M., Guldbrandsten, B., Lund, M.S., Veerkamp, R., Boichard, D., Fries, R., Hayes, B.J. 2014. The 1000 bull genome project. Nature Genetics. 46(8):858-865.

Progress 10/01/13 to 09/30/14

Outputs
Progress Report Objectives (from AD-416): The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize novel genotypic and environmental data to enhance genetic improvement of food animals across a spectrum of ruminant production systems,including the following: SNP markers or haplotype information to identify signatures of natural and artificial selection; novel marker array panels to generate adapted goat genetic lines for extreme environments that improve animal survival, fertility and growth; and "whole herd" molecular pedigree information to further increase the accuracy and speed of genetic improvement for animal populations. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants. Approach (from AD-416): Completion of the objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in the group. Efforts to characterize genome activity and structural conservation/variation are an extension of the current ARS/BA research program in applied genomics. This project plan completely leverages the resources derived from the Bovine and Caprine Genomes and HapMap and ADAPTmap projects and genotypic data derived from both the official USDA genome enhanced genetic evaluations for North American dairy cattle and African Goat Improvement Network under the Feed the Future Initiative. Under Objective 1, ARS scientists in Beltsville, MD continued as global leaders for production of genome sequence information from ruminant species by completing a de novo genome assembly of Bos indicus and attempting the first mammalian genome assembly based solely on caprine sequence data from a third generation sequence platform (PacBio). Relative to objective 2, ARS scientists continued to use genomic tools to better understand natural and artificial selection in cattle and goats. ARS scientists developed methods in determining runs of homozygosity to detect signatures of artificial selection in contemporary Holsteins compared to an unselected control line. Analysis of signatures from natural selection will continue using more than 1500 indigenous cattle from Brazil, Venezuela, and Turkey using newly generated data derived from the 700K SNP (single nucleotide polymorphism) beadchip assay (Illumina�s BovineHD) and 600 indigenous goats Ethiopia, Nigeria, Kenya, Uganda, Turkey, and Egypt using Illumina�s Caprine50K assay. To date, regions of the genome under natural selection for thermotolerance (second SLICK mutation), resistance to diseases endemic to Africa, and signatures of selection for carcass traits and fertility have been detected in cattle. This effort also includes a comprehensive screen for candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, Nelore, and N'Dama as results of geographic adaptation and human selection. Other efforts included additional sampling of indigenous goat populations in Mali, Madagascar, Burundi, Tanzania, Egypt, and the Sudan. ARS scientists continued development of a digital-based system for collecting goat phenotypes, and initiated three community breeding programs in Uganda and Malawi. Under Objective 3, ARS scientists performed genome-wide association studies (GWAS) between Copy number variations (CNV) and parasite resistance traits in Angus cattle and between copy number variations (CNV) and milk traits in Holsteins, and are finishing an integrated tool/algorithm to merge CNV results derived from various discovery platforms. ARS scientists also generated and analyzed additional whole-genome sequence to identify potential causative mutations affecting fertility haplotype BH2 in Brown Swiss and two different SLICK loci in Senepol and Limonero cattle. Validation genotyping of 900 tropically adapted cattle was completed to confirm the causative variant for thermo-tolerance from the Senepol-derived SLICK allele. Accomplishments 01 Identified mutations affecting thermo-tolerance in cattle. Genotyping and sequencing of Criollo cattle populations revealed that there are at least two different mutations with major effects on skin morphology and hair growth in cattle. One of these mutations derived from Senepol cattle was confirmed as a frameshift mutation in the prolactin receptor (PRLR), which truncates the encoded protein by 120 amino acids. Loss of this encoded domain is associated with maintenance of a cooler body temperature under tropical heat conditions. Results from this study are being used by producers to guide future mating decisions (diagnostic DNA marker for SLICK), and by researchers to better understand the gene pathways involved in adaptation to climate change. 02 Identified signatures of selection for differences in fertility, stature (frame size), carcass quality, milk production, and natural selection among global cattle populations. Within these signatures, identified and validated PLAG1 is a major locus controlling growth potential, while a variety of novel and lesser-known genes like LAP3 and SAR1B affect differences in meat quality and milk production, respectively. Population genetics analyses further revealed that genetic hitchhiking and recombination are two major evolutionary mechanisms involved in natural selection in cattle. These results provided a glimpse into geographic adaptation and human selection during cattle domestication, breed formation, and recent genetic improvement. Deep sequencing of 27 Nelore, 10 Criollo, and 10 West African cattle also was completed, and these data will be used as a resource to identify the actual genetic variants underlying phenotypic differences among temperate and tropically adapted cattle. This information will assist genetic improvement of cattle in nations undergoing rapid economic development and population growth and facing challenges of limited resources and predicted climate change. 03 Completed the first genome-wide association studies using copy number variation (CNV) as the source of genotypic information. For Angus, ARS scientists identified one associated deletion CNV on Chromosome 7 for gastrointestinal parasite resistance near immune-related genes such as ZNF496 and NLRP3. For Holsteins, ARS scientists proved that while 75% of all CNV can be tagged by neighboring single nucleotide polymorphisms (SNP) for association testing, the remaining 25% of CNV provided new trait association information not captured by neighboring SNP. The resultant CNV could be used as additional markers for animal selection for traits like production, parasite resistance, fertility, and feed efficiency. These findings will facilitate genome-assisted breeding to improve animal production and health.

Impacts
(N/A)

Publications

Zhao, C., Zan, L., Wang, Y., Updike, M., Liu, G., Bequette, B.J., Baldwin, R.L., Song, J. 2013. Functional proteomic and interactome analysis of proteins associated with beef tenderness in angus cattle. Livestock Science. 161:201-209.
Xu, L., Hou, Y., Bickhart, D.M., Jiuzhou, S., Liu, G. 2013. Comparative analysis of CNV calling algorithms: literature survey and a case study using bovine high-density SNP data. Microarrays. 2(3):171-185.
Cui, X., Hou, Y., Sun, D., Zhang, S., Lv, X., Liu, G., Zhang, Y., Zhang, Q. 2014. Gene expression profiles of bovine mammary epithelial cells and association with milk composition traits using RNA-seq. Biomed Central (BMC) Genomics 15:226.
Xu, L., Hou, Y., Bickhart, D.M., Song, J., Van Tassell, C.P., Sonstegard, T.S., Liu, G. 2014. A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle. Functional and Integrative Genomics. DOI: 10.1007/s10142-014-0371-6.
Bickhart, D.M., Liu, G. 2014. The challenges and importance of structural variation detection in livestock. Frontiers in Genetics. 5:37.
Perez O'Brien, A.M., Utsunomiya, Y.T., Meszaros, G., Bickhart, D.M., Liu, G., Garcia, J., Van Tassell, C.P., Sonstegard, T.S., Solkner, J. 2014. Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genetics Selection Evolution. 46:19.
Porto-Neto, L.R., Sonstegard, T.S., Liu, G., Bickhart, D.M., Gondro, C., Silva, M., Machado, M., Utsunomiya, Y.T., Garcia, J.F., Van Tassell, C.P. 2013. Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping. Biomed Central (BMC) Genomics. DOI:10.1186/ 1471-2164-14-876.
Liu, G., Xu, L., Huang, K.S. 2014. Recent advances in studying of copy number variation and gene expression. Gene Expression. 7:1-5 DOI:10.4137/ GGG.S14286.
Mbole-Kariuki, M., Sonstegard, T.S., Orth, A., Thumbi, S.M., Bronsvoort, B. S., Kiara, H., Toye, P., Conradie, I., Jennings, A., Coetzer, K., Woolhouse, M.J., Hanotte, O., Tapio, M. 2014. Genome-wide analysis reveals the ancient and recent admixture history of East African Shorthorn Zebu (EASZ). Heredity. DOI:10.1038/hdy.2014.31.
Porto-Neto, L., Lee, S., Sonstegard, T.S., Van Tassell, C.P., Lee, H., Gondro, C. 2014. Genome-wide detection of signatures of selection in Korean Hanwoo cattle. Animal Genetics. 45(2):180-190.
Cesar, A., Regitano, L., Tullio, R.R., Lannal, D., Nassu, R.T., Mudado, M. A., Oliveira, P., Nascimento, M., Chaves, A., Alencar, M.M., Sonstegard, T. S., Garrick, D., Reecy, J.M., Coutinho, L.L. 2014. Genome-wide association study for intramuscular fat deposition and composition in Nellore cattle. BioMed Central (BMC) Genetics. 15(1):39.
Andreote, A., Rosario, M.F., Ledur, M.C., Jorge, E.C., Sonstegard, T.S., Matukumalli, L., Countinho, L.L. 2014. Identification and characterization of MicroRNAs expressed in chicken skeletal muscle. Genetics and Molecular Research. 13(1):1465-1479.
Huson, H., Eui-Soo, K., Godfrey, R.W., Olson, T.A., Mcclure, M., Chase, C. C., Rizzi, R., Perez O'Brien, A., Van Tassell, C.P., Garcia, J., Sonstegard, T.S. 2014. Genome-wide association study and ancestral origins of the slick-hair coat in tropically adapted cattle. Frontiers in Livestock Genomics. 5:101.
Mc Clure, M., Bickhart, D.M., Null, D.J., Van Raden, P.M., Xu, L., Wiggans, G.R., Liu, G., Schroeder, S.G., Glasscock, J., Armstrong, J., Cole, J.B., Sonstegard, T.S., Van Tassell, C.P. 2014. Bovine exome sequence analysis and targeted SNP genotyping of recessive fertility defects HH2, HH3, and BH1 reveals causative mutation in SMC2 for HH3. PLoS One. 9(3):e92769.
Utsunomiya, Y.T., Do Carmo, A.S., Neves, H.H., Carvalheiro, R., Matos, M.C. , Zavarez, L.B., Rauschkolb Katsuda I, P., Perez Obrien, A.M., Solkner, J., Porto Neto, L.R., Schenkel, F.S., Mcewan, J., Cole, J.B., Da Silva, M., Van Tassell, C.P., Sonstegard, T.S., Garcia, J. 2014. Genome-wide mapping of loci explaining variance in scrotal circumference in Nellore cattle. PLoS One. 9(2):e88561.
Murray, G., Woolhouse, M., Tapio, M., Mbole-Kariuki, M.N., Sonstegard, T.S. , Thumbi, S., Jennings, A., Conradie Van Wyk, I., Kiara, H., Toye, P., Coetzer, K., Bronsvoort, B.S., Hanotte, O. 2013. Genetic susceptibility to infectious disease in East African Shorthorn Zebu: a genome-wide analysis of the effect of heterozygosity and exotic introgression. Heredity. 13:246.
Tizioto, P.C., Decker, J.E., Taylor, J.F., Schnabel, R.D., Mudadu, M.A., Silva, F.L., Mourao, G.B., Coutinho, L.L., Tholon, P., Sonstegard, T.S., Rosa, A.N., Alencar, M.M., Tullio, R.R., Medeiros, S.R., Nassu, R.T., Feijo, G., Silva, L., Torres, R.A., Siqueira, F., Higa, R.H., Regitano, L. 2013. A genome scan for meat quality in Nelore beef cattle. Physiological Genomics. 45(21):1012-1020.
Utsunomiya, Y.T., Carmo, A.S., Carvalheiro, R., Neves, H.H., Matos, M.C., Zavarez, L.B., O'Brien, A.M., Solkner, J., Mcewan, J., Cole, J.B., Van Tassell, C.P., Schenkel, F.S., Silva, M.V., Porto Neto, L., Sonstegard, T. S., Garcia, J.F. 2013. Genome-wide association study for birth weight Brazilian Nellore cattle (Bos primigenuis indicus) points to previously described orthologous genes affecting human and bovine height. BioMed Central (BMC) Genetics. 13:14-52.
Lawless, N., Reinhardt, T.A., Bryan, K., Baker, M., Pesch, B.A., Zimmerman, D.R., Zuelke, K.A., Sonstegard, T.S., O'Farrelly, C., Lippolis, J.D., Lynn, D.J. 2014. MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model. Genes, Genomes, Genetics. 4(6):957-971. DOI: 10.1534/g3.113.009936.
Decker, J.E., Mckay, S.D., Rolf, M.M., Kim, J., Alcala, A., Sonstegard, T. S., Hanotte, O., Gotherstrom, A., Seabury, C.M., Praharani, L., Babar, M., Regitano, L. ., Yildiz, M., Heaton, M.P., Lui, W., Lei, C., Reecy, J.M., Saif-Ur-Rehman, M., Schnabel, R.D., Taylor, J.F. 2014. Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genetics. 10(3):e1004254.

Progress 10/01/12 to 09/30/13

Outputs
Progress Report Objectives (from AD-416): The long-term objective of this project is to enhance selection in target ruminant populations by integrating traditional, quantitative-based selection methods with DNA marker-based tools. To successfully meet this objective and better understand the underlying gene networks affecting phenotypic variation, basic research to characterize both genome structure and activity must be done as a complementary effort. Objective 1: Develop biological resources and computational tools to enhance characterization of ruminant genomes. De novo reference genome assemblies will be developed for Zebu cattle (Bos indicus), goat (Capra hircus), and water buffalo (Bos bubalis). In addition, improvements will be made to the existing reference assembly for Bos taurus cattle. These reference genome resources are essential for discovery of single nucleotide polymorphisms (SNP) and copy number variation (CNV) polymorphisms commonly segregating in target populations. Objective 2: Utilize genotypic data to enhance genetic improvement of food animals across a spectrum of ruminant production systems. Objective 3: Characterize functional genetic variation for improved fertility and environmental sustainability of ruminants. Approach (from AD-416): Completion of our objectives is expected, in the short term, to improve methods of genome-wide selection in the U.S. dairy industry as well as initiate new genome-enhanced breeding strategies to bring economic and genetic stability to various ruminant value chains in developing nations. Ultimately, longer term objectives to identify and understand how causative genetic variation affects livestock biology will require a combination of genome resequencing and comparative genome alignment and annotation, quantitative genetics, and gene expression analyses, all of which are components of this project plan and areas of expertise in 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 Genome and HapMap projects and genotypic data derived from the official USDA genome enhanced genetic evaluations for NA dairy cattle. ARS scientists in Beltsville, MD continued as global leaders for production of DNA sequence information from ruminant species by contributing all of the sequence for international efforts to assemble genomes and single nucleotide polymorphism (SNP) discovery for Bos indicus cattle, goat, and water buffalo. ARS scientists generated and analyzed additional whole-genome sequence to identify causative mutations affecting fertility haplotypes HH3 in Holsteins and SLICK in Senepols. ARS scientists continued to develop and use new genomic tools for selection. These efforts included development of: 1) a new 90K SNP assay for breed diversity determination and genetic prediction in water buffalo (Affymetrix 90K), 2) a new 80K SNP assay (Neogen�s GGP BovineHD) for genomic prediction in beef and dairy cattle, and 3) a second new 80K SNP assay (Neogen�s GGP BovineHD for zebu) for genomic prediction in zebu- derived cattle (tropically adapted). ARS scientists continued to characterize tropical adaptation by characterizing the genomes of more than 600 cattle from Africa and SW Asia using genetic data derived from the 700K SNP beadchip assay (Illumina�s BovineHD). This effort included searching for regions of the genome under natural selection for resistance to diseases endemic to Africa. This analysis identified a 1-Mbp region of chromosome 6 containing genes known to be involved in trypanotolerance. Other efforts included sampling indigenous goat populations in Ethiopia, Nigeria, Kenya, and Cameroon. Some of these animals were genotyped along with several North American breeds. The later genotyping results were used to select a San Clemente goat as a genome sequencing animal. Sequence production for a new goat genome assembly model is 95% completed. ARS scientists developed and tested a digital-based system for collecting goat phenotypes in Africa. This project needs further sampling of African goats by collaborative partners to provide the critical information needed to find the best goat to initiate community breeding programs in Sub-Saharan Africa. Other genome characterization, trait mapping, and variant sequencing included completion of projects to determine extent of changes to Holstein and Jersey genomes caused by artificial selection over the past 50 years and imputation of parentage microsatellites from SNP haplotypes for all cattle breeds. Projects also were initiated to elucidate mutations for limber leg and rectovaginal constriction defects in Jersey cattle. ARS scientists also completed transcript sequencing (RNAseq) for improved genome annotation, the first comprehensive prediction of transcription factor binding sites (TFBS) in the cattle genome, and the first comprehensive discovery of copy number variants (CNV) using next- generation sequencing (NGS) data from over 100 cattle individuals. The latter effort continues with an attempt to develop a tool to merge CNV findings across various discovery platforms. Bovine50K SNP data from more than 30,000 dairy cattle samples were collected and processed by PennCNV to find associations with animal production and health traits including fertility, parasite resistance, and feed efficiency. Accomplishments 01 Identified mutations affecting dairy cow fertility. Extensive genotyping of U.S. dairy populations has revealed portions of the genome that appear to contain lethal mutations causing embryonic death during pregnancy. ARS scientists discovered the genetic cause for these recessive lethal mutations known as HH3 in Holsteins using next generation sequencing techniques. Results from this study are being used by producers to guide future mating decisions, thus lowering the rate of infertility caused by embryonic loss or physiological abnormalities, respectively. 02 Developed low-cost genotyping tools for genomic predictions of genetic merit. Better low-cost tools for genotyping were needed encompass parentage and other important DNA tests of economically important traits for the industry. Our continued leadership in DNA tool development for ruminants (three new commercial genotyping tools) provides low cost opportunities for producers to obtain the genetic information needed for genomic selection in the U.S. beef cattle industry and globally for tropically adapted cattle. These tools also should allow DNA service providers to transition from �old technology� to SNP-based technology for parentage determination. The North American dairy industry continues to use products developed in our laboratory at a rate of genotyping more than 15,000 animals per month. Development of a SNP genotyping tool for water buffalo also has the potential to increase the accuracy and efficacy of genomic selection for improved dairy production in the developing world. 03 Developed a computer approach using comparative genomics and identified thousands of gene expression regulatory elements (i.e. transcription factor binding sites - TFBS) in the cattle genome, which serves as a resource for functional genomics studies. 04 Developed a computer approach to detect copy number variation (CNV) based on population scale next-generation sequencing. Generated thousands of new CNV regions, which enable future studies of highly variable regions in the cattle genome. 05 Led �big data� support within the Agricultural Research Service. Next generation sequencing instruments and associated molecular and bioinformatic methods are important experimental tools for genetics and biological discovery in agricultural research. ARS scientists in Beltsville, MD supported genomics research within the Agency and with national and international collaborators in a multitude of species and applications by providing scientific computing, labor, and bioinformatic support for projects at various locations that wanted to use next-generation sequencing methods. These efforts included genomics research in water buffalo, cattle, goat, wood rot fungus, and other agriculturally relevant species.

Impacts
(N/A)

Publications

Zhao, C., Fei, T., Yu, Y., Luo, J., Mitra, A., Zhan, F., Hou, Y., Liu, G., Zan, L., Updike, M., Song, J. 2012. Functional Genomic Analysis of Variation on Beef Tenderness Induced by Acute Stress in Angus Cattle. Comparative and Functional Genomics. DOI: 10.1155/2012/756284.
Bickhart, D.M., Liu, G. 2013. Identification of candidate transcription factor binding sites in the cattle genome. Genomics, Proteomics and Bioinformatics. 11(3):195-198.
Utsunomiya, Y.T., O'Brien, A.P., Sonstegard, T.S., Van Tassell, C.P., Santana Do Carmo, A.D., Meszaros, G., Solkner, J., Garcia, J.F. 2013. Detecting Loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods. PLoS One. 8(5):e64280.
Tang, J.D., Perkins, A.D., Sonstegard, T.S., Schroeder, S.G., Nicholas, D. D., Diehl, S.V. 2012. Gene expression analysis of copper tolerance and wood decay in the brown rot fungus Fibroporia radiculosa. Applied and Environmental Microbiology. 79(5):1523-33.
Zhao, C., Tian, F., Yu, Y., Liu, G., Zan, L., Updike, M., Song, J. 2012. miRNA-dysregulation associated with tenderness variation induced by acute stress in angus cattle. Animal Science Biotechnol. 3(1):12.
Liu, G., Bickhart, D.M. 2013. The trappin gene famliy: structue, function and evolution. Cattle: Domestication, Disease and Environment. 1st edition. Hauppauge, NY: Nova Science Publishers, Inc. 25-38 p.
Hou, Y., Bickhart, D.M., Hvinden, M.L., Li, C., Song, J., Boichard, D.A., Fritz, S., Eggen, A., Denise, S., Wiggans, G.R., Sonstegard, T.S., Van Tassell, C.P., Liu, G. 2012. Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array. Biomed Central (BMC) Genomics. 13:376.
Aslam, M.L., Bastiaansen, J.W., Elferink, M., Megens, H., Crooijmas, R.P., Blomberg, L., Fleischer, R.C., Van Tassell, C.P., Sonstegard, T.S., Schroeder, S.G., Groenen, M.A., Long, J.A. 2012. Whole genome snp discovery and analysis of genetic diversity in turkey (meleagris gallopavo) . Biomed Central (BMC) Genomics. 13:391.
Mcclure, M.C., Sonstegard, T.S., Van Tassell, C.P., Wiggans, G.R. 2012. Imputation of Microsatellite Allele from Dense SNP Genotypes for Parentage Verification. Frontiers in Livestock Genomics. 3:140.
Ma, L., Wiggans, G.R., Wang, S., Sonstegard, T.S., Yang, J., Crooker, B.A., Cole, J.B., Van Tassell, C.P., Da, Y. 2012. Effect of sample stratification on dairy GWAS results. Biomed Central (BMC) Genomics. 13:536.
Van Raden, P.M., Null, D.J., Sargolzaei, M., Wiggans, G.R., Tooker, M.E., Cole, J.B., Sonstegard, T.S., Connor, E.E., Winters, M., Van Kaam, J., Van Doormaal, B.J., Faust, M.A., Doak, G.A. 2013. Genomic imputation and evaluation using high density Holstein genotypes. Journal of Dairy Science. 96(1):668-678.
Wiggans, G.R., Cooper, T.A., Van Tassell, C.P., Sonstegard, T.S., Simpson, E.B. 2013. Technical note: Characteristics and use of the Illumina BovineLD and GeneSeek Genomic Profiler low-density bead chips for genomic evaluation. Journal of Dairy Science. 96(2):1258-1263.
Sonstegard, T.S., Cole, J.B., Van Raden, P.M., Van Tassell, C.P., Null, D. J., Schroeder, S.G., Bickhart, D.M., Mcclure, M.C. 2013. Identification of a nonsense mutation in CWC15 associated with decreased reproductive efficiency in Jersey cattle. PLoS One. 8(1):e54872.
Mcclure, M.C., Kim, E., Bickhart, D.M., Null, D.J., Cooper, T.A., Cole, J. B., Wiggans, G.R., Marsan, P.A., Colli, L., Santus, E., Liu, G., Schroeder, S.G., Matukumalli, L., Van Tassell, C.P., Sonstegard, T.S. 2013. Fine mapping for Weaver Syndrome in the Brown Swiss breed with the identification of possible casual mutations across NRCAM, PNPLA8, and CTTNBP2 and Developement of a diagnostic SNP haplotype. PLoS One. 8(3) :e59251.
Liu, G., Bickhart, D.M. 2012. Copy Number Variation in the Cattle Genome. Functional and Integrative Genomics. DOI: 10.1007/S10142-012-0289-9.