Progress 08/15/17 to 08/14/20
Outputs
Target Audience: geneticists (human and livestock) animal breeders animal scientists progressive livestock producers livestock genetics industry Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Graduate students and post-doctoral fellows were involved in the development of the workshop programs, as well as, hosting of the meeting. These students and fellow were instrumental in collection of meeting notes and in drafting of the meeting manuscript. How have the results been disseminated to communities of interest?The presentations and accompanying letters presented at the workshops are publicly available at: https://www.animalgenome.org/share/meetings/LivestockHTP https://www.animalgenome.org/share/meetings/Genome2Phenome What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Overall impact statement:The animal science community needs to continue to synergize efforts to gain the most from the wealth of data available. Animal sciences hold an advantage in seeking knowledge in that many sub disciplines can share information and experience to use "big data." Behaviorists, geneticists, informaticians, meat scientists, microbiologists and immunologists nutritionists, physiologists and reproductive specialists and statisticians are accustomed to working together. To handle the large and diverse types of data being generated across animal science sub disciplines, there is a need for more interaction with engineers, computer scientists, imaging specialists, and other personal working with "big data". Animal Sciences could learn a great deal from plant science, meteorologists, national security officials as well as business and social scientists dealing with large consumer behavior and purchasing data. These interactions are needed to educate our field on data management, analytics and high-throughput phenotyping technologies to learn how to best make use of the data and overcome challenges inherit in high-throughput measurement systems. Objective 2... Key outcomes achieved at the Livestock Genomics BluePrint Conference were: (1) exchange the latest scientific developments in the field of livestock genetics and genomics; (2) articulation of a vision for future impacts and applications of such technologies on animal breeding systems; and (3) discussion of strategies on how to implement these new technologies and methodologies in commercial breeding programs. This last year, a vision for high-throughput phenotyping and big data in livestock was published. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934059/ This publication as a direct result of the original high-throughput workshop held in Beltsville, MD at the National Ag Library. In addition, a follow-on workshop was held prior to the Plant and Animal Genome meeting on January 10, 2020. The desired outcome from this workshop were to identify high-priority areas for implementation of the Livestock Genomics BluePrint from the 1) industry perspective and 2) from the academic perspective. The Agenda for the workshop can be found at: https://www.animalgenome.org/share/meetings/Genome2Phenome.2020 Industry speakers were from the sheep, beef, dairy, swine, poultry, and aquaculture sectors. In addition, a speaker also represented the gene editing industry. While the academic speakers represented a historical view point, as well as from the quantitative, molecular and bioinformatic view points. As a result of this meeting the academic community developed a list of high priority research areas... Goal: Understanding genome biology to accelerate genetic improvement of economically important traits Link genes to function Link non-promoter regulatory elements to the target genes and create links between genetic variants and gene expression levels Current methods (Hi-ChIP, RNAseq+ATAC-seq) are expensive and there is limited experience with them in livestock community Methods such as eQTL mapping not heavily used due to cost New methods such as 3'RNAseq may decrease cost Link well-defined phenotypes with their genomics, transcriptomics, epigenomics, proteomics, and microbiomics/metagenomics Translate genome assembly and annotation to define biological mechanisms and networks at the cellular, organ, and/or whole-animal levels Goal: Reducing the effects of animal diseases Reduce animal health issues regarding common ailments, disease, and parasitic infection while concurrently limiting dependence on antibiotic and anthelmintic treatments Goal: Applying precision agriculture technologies to animal phenotyping Develop precision phenotyping Identify and clearly define new traits of interest and simplify/reduce cost of phenotyping without sacrificing integrity Goal: Training the next generation of animal scientists Different modes of training required for scientists at different career levels (degree courses, workshops) Must support educational resources and extension representatives so producers, veterinarians, and other stakeholders are aware of available technology and findings/resources of genetics/genomics community Goal: Developing advanced genomic tools, technologies, and resources for agricultural animals Geneticists will need to store, analyze, and display very large datasets composed of sequence data Necessary infrastructure includes annotated reference genome(s), curated collection of genetics and genomics analysis tools, data repositories, cell/tissue biobanks, and resources for conveying value and utility of scientific findings to stakeholders Genetics and genomics tools must be maintained with appropriate documentation, so scientists and stakeholders can use the tools to advance and apply findings within their hers, and/or to further explore other phenotypes or conditions Data must be properly stored within data repositories with appropriate metadata Shared data analysis tools will allow for efficient comparative genomics within and across species Shared biobanks allow for comparative research to be done across populations to better understand performance traits, production phenotypes, and disease states Genome sequence and assembly resources require further development and expansion Imputation pipelines are required to enable imputation of low-density genotypes to sequence level to narrow QTL regions and uncover putative QTN Streamline production systems to require less human labor and favor database management and the ability to capture, preserve, and implement accurate phenotypic and genotypic information to develop the most effective breeding schemes Develop pan-genomes including all genomic segments that can be identified in representatives within the species New visualization and analysis tools will be required, e.g. for new pan-genomes Goal: Advancing biotechnology to improve the sustainability and efficiency of animal production Develop genome editing tools and resources to validate functional element predictions as well as to accelerate genetic improvement Increase efficiency of animal production and performance, including reproductive competency, out-of-season breeding, and feed efficiency, while still prioritizing animal welfare standards and providing transparency on production practices and product traceability from the grower to the end consumer Molecular genetic technologies should be combined with the existing selection techniques, providing a whole-systems approach to improve productivity Utilizing selective breeding to propagate genetics for improved animal health will improve animal welfare Improving production efficiency can reduce negative environmental effects of animal production and may even benefit the environment Genomics tools for genetic improvement must be presented to the industry and individual consumers/stakeholders in relevant and producer-assistive ways Discoveries must be translated into measurements that are commercially accessible and easily interpreted
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
James E. Koltes, John B. Cole, Roxanne Clemmens, Ryan N. Dilger, Luke M. Kramer, Joan K. Lunney, Molly E. McCue, Stephanie D. McKay, Raluca G. Mateescu, Brenda M. Murdoch, Ryan Reuter, Caird E. Rexroad, Guilherme J. M. Rosa, Nick V. L. Ser�o, Stephen N. White, M. Jennifer Woodward-Greene, Millie Worku, Hongwei Zhang, James M. Reecy
Front Genet. 2019; 10: 1197. Published online 2019 Dec 17. doi: 10.3389/fgene.2019.01197
PMCID: PMC6934059
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Rexroad C, Vallet J, Matukumalli LK, Reecy J, Bickhart D, Blackburn H, Boggess M, Cheng H, Clutter A, Cockett N, Ernst C, Fulton JE, Liu J, Lunney J, Neibergs H, Purcell C, Smith TPL, Sonstegard T, Taylor J, Telugu B, Eenennaam AV, Tassell CPV, Wells K. Genome to Phenome: Improving Animal Health, Production, and Well-Being - A New USDA Blueprint for Animal Genome Research 2018-2027. Front Genet. 2019 May 16;10:327. doi: 10.3389/fgene.2019.00327. eCollection 2019.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
James E Koltes, John B. Cole, Roxanne Clemmens, Ryan N Dilger, Luke M Kramer, Joan K Lunney, Molly Elizabeth McCue, Stephanie McKay, Raluca Mateescu, Brenda M Murdoch, Ryan Reuter, Caird Rexroad, Guilherme J M Rosa, Nick V. L. Ser�o, Stephen N White, Mary Jennifer Woodward-Greene, Millie Worku, Hongwei Zhang, James Reecy. 2019. A vision for development and utilization of high-throughput phenotyping and big data analytics in livestock. Front. Genet., 17 December 2019. https://doi.org/10.3389/fgene.2019.01197
|
Progress 08/15/18 to 08/14/19
Outputs
Target Audience:The results of this workshop, and the related journal articles, are of interest to geneticists (human and livestock), animal breeders, animal scientists, progressive livestock producers and livestock genetics industry. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?The published manuscript was added to the presentations and accompanying letters presented at the workshops are publicly available at: https://www.animalgenome.org/share/meetings/LivestockHTP https://www.animalgenome.org/share/meetings/Genome2Phenome What do you plan to do during the next reporting period to accomplish the goals?This coming year, the team will develop an implementation plan for the Blueprint. It is expected that a workshop will be held in conjunction with the 2020 Plant and Animal Genome meeting. In addition, a workshop on will help providing participants withUnix 101 training followed by instructions from start to finish on how to do RNAseq analysis and ATACseq, maybe ChIPseq workflowin support of the Functional Annotation of Animal Genomes consortium project.
Impacts
What was accomplished under these goals?
Animal sciences has entered a golden age of opportunities thanks to the wealth of diverse data now available. Automated technologies are collecting unprecedented amounts of data on a daily basis in the livestock industry.For instance, in the dairy cattle world, sensors are collecting milk quality data and in some cases body condition scores, and activity information on a routine basis.Video data is also being produced at high rates to evaluate animal welfare, health, and management strategies.Millions of dairy cattle have been genotyped as well as hundreds of thousands of pigs, chickens and beef cattle for use in genomic evaluations.All of these data can be used to predict animal health, improve animal efficiency and for breeding purposes, thus improving animal management.Unfortunately, this wealth of information is largely underutilized. Genomic information on most livestock species is also now more detailed than ever, with recent improvements in the cattle, chicken, pig and sheep genomes. In addition, the FAANG project is delivering the first global map of non-coding regulatory regions, similar to that produced by ENCODE and modENCODE projects in humans and model organisms.Since it has been estimated that more than 70% of the quantitative trait loci (QTL) in the genome are in non-coding regions, these resources are particularly invaluable in making the link from genotype to phenotype.As new sequencing technologies continue to develop, the price of high-throughput molecular data continues to decline rapidly. This has resulted in a large amount of sequence data generated in livestock species. In addition, improved high-throughput mass spectrometry equipment has greatly increased the amount of metabolomics data being generated. There is currently a need for more training in bioinformatics, data management, high-performance computing, statistical genomics and related fields to determine how best to use this data. New methods are also needed to better integrate these data types.In addition, given the substantial investments by funding agencies, there is a need to develop new high-capacity methodology for meta-analyses to better re-use and integrate the existing functional genomics data. The animal science community needs to continue to synergize to gain the most from the wealth of data available. Animal sciences hold an advantage in seeking knowledge in that many sub disciplines can share information and experience to use "big data."Behaviorists, geneticists, informaticians, meat scientists, microbiologists and immunologists nutritionists, physiologists and reproductive specialists and statisticians are accustomed to working together. To handle the large and diverse types of data being generated across animal science sub disciplines, there is a need for more interaction with engineers, computer scientists, imaging specialists, and other personal working with "big data".Animal Sciences could learn a great deal from plant science, meteorologists, national security officials as well as business and social scientists dealing with large consumer behavior and purchasing data.These interactions are needed to educate our field on data management, analytics and high-throughput phenotyping technologies to learn how to best make use of the data and overcome challenges inherit in high-throughput measurement systems. Objective 2... Key outcomes expected for Livestock Genomics BluePrint Conference are: (1) exchange of the latest scientific developments in the field of livestock genetics and genomics; (2) articulation of a vision for future impacts and applications of such technologies on animal breeding systems; and (3) discussion of strategies on how to implement these new technologies and methodologies in commercial breeding programs. Thisproject year, the blueprint was published in Frontiers in Genetics (Rexroad et al., Frontiers in Genetics 16:327; doi:10.3389/fgene.2019.00327). In addition, an executive summary was written and disseminated by the meeting website - https://www.animalgenome.org/share/meetings/Genome2Phenome.doc/AGBlueprint2018-2027_ExecSummary.pdf
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Rexroad C, Vallet J, Matukumalli LK, Reecy J, Bickhart D, Blackburn H, Boggess M, Cheng H, Clutter A, Cockett N, Ernst C, Fulton JE, Liu J, Lunney J, Neibergs H, Purcell C, Smith TPL, Sonstegard T, Taylor J, Telugu B, Eenennaam AV, Tassell CPV, Wells K. Genome to Phenome: Improving Animal Health, Production, and Well-Being - A New USDA Blueprint for Animal Genome Research 2018-2027. Front Genet. 2019 May 16;10:327. doi: 10.3389/fgene.2019.00327. eCollection 2019.
- Type:
Journal Articles
Status:
Submitted
Year Published:
2019
Citation:
Koltes J; Cole J, Clemmens R, Dilger R, Kramer L, Lunney J, McCue ME, McKay S, Mateescu R, Murdoch B, Reuter R, Rexroad C, Rosa G, Serao N, White S, Woodward-Green MJ, Worku M, Zhang H, Reecy J., 2019, A vision for development and utilization of high-throughput phenotyping and big data analytics in livestock. Front Genet. Submitted.
|
Progress 08/15/17 to 08/14/18
Outputs
Target Audience:Geneticists (human and livestock), animal breeders, animal scientists, and progressive livestock producers. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Graduate students and post-doctoral fellows were involved in the development of the workshop programs, as well as, hosting of the meeting. These students and fellow were instrumental in collection of meeting notes and in drafting of the meeting manuscript. How have the results been disseminated to communities of interest?In addition to workshop participants, the presentations and accompanying letters presented at the workshops are publicly available at: https://www.animalgenome.org/share/meetings/LivestockHTP https://www.animalgenome.org/share/meetings/Genome2Phenome What do you plan to do during the next reporting period to accomplish the goals?It is expected that the manuscript for the Livestock High-Throughput Phenotyping and Data Analytics meeting will be submitted for publication in September 2018. Furthermore, it is expected that the Genome2Phenome BluePrint will be posted for public comment in the fall of 2018.
Impacts
What was accomplished under these goals?
Overall impact statement: Animal sciences has entered a golden age of opportunities thanks to the wealth of diverse data now available. Automated technologies are collecting unprecedented amounts of data on a daily basis in the livestock industry. For instance, in the dairy cattle world, sensors are collecting milk quality data and in some cases body condition scores, and activity information on a routine basis. Video data is also being produced at high rates to evaluate animal welfare, health, and management strategies. Millions of dairy cattle have been genotyped as well as hundreds of thousands of pigs, chickens and beef cattle for use in genomic evaluations. All of these data can be used to predict animal health, improve animal efficiency and for breeding purposes, thus improving animal management. Unfortunately, this wealth of information is largely underutilized. Genomic information on most livestock species is also now more detailed than ever, with recent improvements in the cattle, chicken, pig and sheep genomes. In addition, the FAANG project is delivering the first global map of non-coding regulatory regions, similar to that produced by ENCODE and modENCODE projects in humans and model organisms. Since it has been estimated that more than 70% of the quantitative trait loci (QTL) in the genome are in non-coding regions, these resources are particularly invaluable in making the link from genotype to phenotype. As new sequencing technologies continue to develop, the price of high-throughput molecular data continues to decline rapidly. This has resulted in a large amount of sequence data generated in livestock species. In addition, improved high-throughput mass spectrometry equipment has greatly increased the amount of metabolomics data being generated. There is currently a need for more training in bioinformatics, data management, high-performance computing, statistical genomics and related fields to determine how best to use this data. New methods are also needed to better integrate these data types. In addition, given the substantial investments by funding agencies, there is a need to develop new high-capacity methodology for meta-analyses to better re-use and integrate the existing functional genomics data. The animal science community needs to continue to synergize to gain the most from the wealth of data available. Animal sciences hold an advantage in seeking knowledge in that many sub disciplines can share information and experience to use "big data." Behaviorists, geneticists, informaticians, meat scientists, microbiologists and immunologists nutritionists, physiologists and reproductive specialists and statisticians are accustomed to working together. To handle the large and diverse types of data being generated across animal science sub disciplines, there is a need for more interaction with engineers, computer scientists, imaging specialists, and other personal working with "big data". Animal Sciences could learn a great deal from plant science, meteorologists, national security officials as well as business and social scientists dealing with large consumer behavior and purchasing data. These interactions are needed to educate our field on data management, analytics and high-throughput phenotyping technologies to learn how to best make use of the data and overcome challenges inherit in high-throughput measurement systems. A decade ago, the animal genomics community, under the leadership of Dr. Ronnie Green (USDA-ARS) and Dr. Muquarrab Qureshi (USDA-NIFA), developed a report titled "Blueprint for USDA Efforts in Agricultural Animal Genomics 2008 - 2017." Over the last decade the vision outlined in this document has served to guide intra- and extramural research programs at USDA and in the broader international community.This project period, we provided a workshop for researchers that explored the progress made and developed meaningful and tangible goals for the next decade. Also, we provide a meeting for researchers entitled "Livestock High-Throughput Phenotyping and Big Data Analytics (Livestock HTP and Big Data)." At the meeting, we encouraged the expansion of the use of high-throughput data and developed a vision and strategy to apply these data to production agriculture. We also identified research priorities for the coming years. 200 stakeholders participated in the meetings. Objective 1... Develop the conference: Livestock High-Throughput Phenotyping and Big Data Analytics (Livestock HTP and Big Data) meeting. The Livestock High-throughput Phenotyping and Big Data Analytics meeting was held November 13-14, 2017 at the USDA National Agricultural Library. This meeting provided an opportunity to discuss how cutting-edge methodologies to manage and analyze large diverse livestock data can be applied to the animal sciences. The goal of this meeting was to gather a diverse group of animal scientists in across disciplines to stimulate the livestock research community to expand the use of high-throughput data and develop a vision and strategy to apply these data to production agriculture. A draft manuscript is under development by workshop participants and will be shortly submitted to a journal for publication in 2018. Objective 2... Develop the meeting: Genome to Phenome: An USDA Blueprint for Improving Animal Production (Livestock GtoP blueprint) meeting. In November 15-17, 2017, USDA and Iowa State University hosted federal and university scientists, funding agencies, and industry stakeholders at a workshop having the aim of developing a collective vision for the next decade of animal genomics research. The workshop included priorities communicated by the animal agriculture industries, perspectives of Federal and International funding agencies, and presentations from leaders in various fields of genome biology. Participants discussed a vision for how the next decade of genome research will be used to improve animal production, and the steps necessary to make those improvements a reality.The effort built on the successes of the previous Blueprint report by identifying research priorities within the framework of: 1) Science to Practice; 2) Discovery Science, and 3) Infrastructure. A draft of the updated Blueprint has been revised by workshop participants and will be posted online for community review prior to journal submission in 2018.
Publications
|
|