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Translational Omics Working Group

We are excited to introduce the SCINet Translational Omics Working Group, an interdisciplinary team of researchers and experts dedicated to advancing the field of translational omics and its applications in agriculture. Omics technologies will play a pivotal role in the new agricultural revolution by unraveling the complex molecular underpinnings of complex traits and helping guide future farming practices.

The concept of “omics” refers to the comprehensive study of various biological molecules, including genomics (structural genomics - sequence assembly and variation and functional genomics - gene function and annotation), epigenomics (changes in gene expression regulation without change in DNA sequence), transcriptomics (gene expression analysis), proteomics (proteins and their interactions), metabolomics (small molecule metabolites), and metagenomics (microbiota - a community of microorganisms). These approaches have already demonstrated immense potential in understanding molecular mechanisms, finding biomarkers, and developing effective selections and treatments. The primary goal of the Translational Omics Working Group is to foster collaboration, knowledge-sharing, and innovation among researchers and experts in diverse fields, including but not limited to genomics, bioinformatics, computational biology, and artificial intelligence (AI). Together, we aim to overcome research and technical challenges, explore novel techniques, and promote omics data integration in agriculture and food research.

Key objectives of the Translational Omics Working Group are:

  • Education and Outreach: Organize seminars, workshops, and conferences to disseminate knowledge (tools and resources) and raise awareness about the potential of omics technologies in transforming agricultural research.
  • Data Integration: Facilitate discussions and methodologies for integrating multi-omics data to comprehensively understand biological processes and molecular mechanisms.

Other potential applied topics include:

  • Biomarker and Treatment Development: Promote research and validation of omics-based biomarkers for crop and animal selection. Explore the utility of omics technologies in identifying potential targets and improving the efficiency of disease management.
  • Ethical and Legal Considerations: Address the ethical, legal, and privacy challenges associated with omics data while ensuring that our research adheres to the highest standards of data security and animal welfare. Collaborate with veterinarians and animal caretakers to effectively translate omics research into animal husbandry practice, ensuring the benefits reach animals promptly and responsibly.

By fostering a dynamic environment for interaction and cooperation, we believe the Translational Omics Working Group will play a significant role in advancing AI applications to omics research and bringing us closer to the new agricultural revolution. We invite all ARS researchers and supporting professionals interested in omics and AI and their translational potentials to join us on this exciting journey. Together, we can make a tangible impact on ARS’s research mission and revolutionize the future of farming.

If you are interested in and would like to join the group, please fill out the following survey: Translational Omics Working Group Survey.

For more information, please contact George Liu (George.Liu@usda.gov) or Zhenbin Hu (Zhenbin.Hu@usda.gov).

Meeting Materials

Presentation materials from previous meetings are available to USDA employees in the list below.


  • Harnessing Transposons for Precise and Efficient Genome Editing in Plants

  • The genomic and metabolic making of yeast ecological diversity

    • Thursday, October 10, 2024, 11am-12pm ET
  • Exploiting microbiota-derived bioactive compounds to enhance animal health and production

    • Thursday, September 12, 2024, 11am-12pm ET
  • Untangling False Positives, Statistical Power, Populations Structure, and Kinship in GWAS

  • Livestock, Companion Animals, and Wildlife; Working Across Industries in Genomics Research

  • Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes

  • Advancing omics measurement science to support agricultural research

  • Statistical and computational methods for spatial transcriptomics data analysis

  • Evolutionary dynamics of transposable elements in plant genomes

  • Using multiomics to explore the impact of drought on the root microbiome

  • Farm Animal Genotype-Tissue Expression (FarmGTEx)

  • Initial Organization Meeting