Source: UNIVERSITY OF CALIFORNIA, DAVIS submitted to NRP
GENOMIC EVALUATION USING FUNCTIONAL GENOMICS DATA AT INDIVIDUAL- AND SNP-LEVELS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1030498
Grant No.
2023-67015-39564
Cumulative Award Amt.
$650,000.00
Proposal No.
2022-08300
Multistate No.
(N/A)
Project Start Date
Jul 1, 2023
Project End Date
Jun 30, 2026
Grant Year
2023
Program Code
[A1201]- Animal Health and Production and Animal Products: Animal Breeding, Genetics, and Genomics
Recipient Organization
UNIVERSITY OF CALIFORNIA, DAVIS
410 MRAK HALL
DAVIS,CA 95616-8671
Performing Department
(N/A)
Non Technical Summary
In animal genomics, two types of functional genomics data, at least, are being generated by public research consortia or private industry: (1) SNP-level functional annotations, and (2) individual-level intermediate omics data. At the SNP level, highly annotated genomes are now available for multiple species. At the individual level, intermediate omics data (e.g., metabolomics, transcriptomics, and other omics data) are becoming increasingly available, and generating omics data is now possible for large populations of individuals in commercial breeding programs. We will develop statistical methods and computational algorithms to incorporate functional genomic data generated by public research consortia or private industry into genomic evaluations.We wil develop statistical methods and computational algorithms to incorporate functional genomic data generated by public research consortia or private industry into genomic evaluations. For that, the generated methods and algorithms will be implemented in routinely used software.
Animal Health Component
30%
Research Effort Categories
Basic
50%
Applied
30%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
3033910108060%
3033910208020%
3033910209020%
Knowledge Area
303 - Genetic Improvement of Animals;

Subject Of Investigation
3910 - Cross-commodity research--multiple animal species;

Field Of Science
2090 - Statistics, econometrics, and biometrics; 2080 - Mathematics and computer sciences; 1080 - Genetics;
Goals / Objectives
Developstatistical methods to incorporate SNP-level (i.e., highly-annotated genomes information) and individual-level (intermediate omics data for a large population of animals) functional genomics data for farmed animals.
Project Methods
1. Develop statistical models and tools to include individual-level (incomplete) intermediate omics data for FAANG-enabled genomic prediction.2. Develop statistical models and tools to incorporate SNP-level continuous-valued and categorical functional annotations for FAANG-enabled genomic prediction.3. Implement and evaluate the use of individual-level intermediate omics data and SNP-level functional annotations (multiple tissues) in commercial breeding programs for genomic prediction, in addition to phenotypic, pedigree, and genotypic data.

Progress 07/01/24 to 06/30/25

Outputs
Target Audience:Our audiences are 1)research scientists that are either engaged directly in animal genome research or utilize genomic data in complementary areas of animal science, 2) commercial animal breeders and producers who apply genomic data and related technologies to enhance aspects of animal health, welfare, productivity, and management. 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?We have published peer-reviewed articles, creating extensive opportunities for engagement with stakeholders, including animal breeders and geneticists from both academia and industry. Our work has also been shared through talks at conferences, and the resulting methods and tools are already being applied in collaborations with companies. What do you plan to do during the next reporting period to accomplish the goals?We will continue to advance statistical models and tools to handle large-scale datasets. Our next steps include implementing and evaluating the use of individual-level intermediate omics data (blood metabolome) and SNP-level functional annotations (across multiple tissues) in commercial swine breeding programs, applying these methods to more complex genomic prediction scenarios.

Impacts
What was accomplished under these goals? We have improved several statistical models and tools to incorporate individual-level (including incomplete) intermediate omics data and functional annotations for FAANG-enabled genomic prediction. These advances have been successfully applied to real swine data using blood metabolite samples, demonstrating their practical value.

Publications

  • Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Bridging Genome to Phenome (G2P): Innovations in Statistical, Machine Learning, and Computational Methods. The Roslin Institute, University of Edinburgh, December 13, 2024
  • Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Bayesian variable selection for multi-layer biological data, 18th International Conference on Computational and Methodological Statistics, King's College London, UK, December 15, 2024


Progress 07/01/23 to 06/30/24

Outputs
Target Audience:Our audiences are 1) research scientists that are either engaged directly in animal genome research or utilize genomic data in complementary areas of animal science, 2) commercial animal breeders and producers who apply genomic data and related technologies to enhance aspects of animal health, welfare, productivity, and management. 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?Peer-reviewed articles have been published, proving extensive opportunities for interaction with stakeholders (animal breeders and other geneticists from both academia and industry). Talks and posters were presented at conferences. Results (methods and tools) are used through collaborations with companies. What do you plan to do during the next reporting period to accomplish the goals?We will further develop statistical models and tools. We will implement and evaluate the use of individual-level intermediate omics data (blood metabolome) and SNP-level functional annotations (multiple tissues) in commercial swine breeding programs for genomic prediction, in addition to phenotypic, pedigree, and genotypic data.

Impacts
What was accomplished under these goals? We have developed several statistical models and tools to include individual-level (incomplete) intermediate omics data and functional annotations for FAANG-enabled genomic prediction.

Publications

  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Yang, Z., Zhao, T., Cheng, H, Yang, J., Microbiome-enabled genomic selection improves
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Zhao, T., Cheng, H, 2023, Interpreting single-step genomic evaluation as a neural network of three layers: pedigree, genotypes, and phenotypes. Genet Sel Evol 55, 68 . https://doi.org/10.1186/s12711-023-00838-7
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Li, J., Zhao, T., Guan, D., Pan, Z., Bai, Z., Teng, J., Zhang, Z., Zheng, Z., Zeng, J., Zhou, H., Fang, L., Cheng, H., 2023, Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex trait, Cell Genomics (2023)
  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Zhao, T., Wang, F., Mott, R., Dekkers., J., Cheng, H, 2024, Using encrypted genotypes and phenotypes for collaborative genomic analyses to maintain data confidentiality, Genetics, iyad210, https://doi.org/10.1093/genetics/iyad210