“Integrating Omics Databases for Enhanced Crop Breeding”

UNIVERSITY OF AGRICULTURAL SCIENCES, GKVK, BANGALORE

DEPARTMENT OF GENETICS AND PLANT BREEDING

SEMINAR ON

“Integrating Omics Databases for Enhanced Crop Breeding”

In the post-genomic era, numerous novel high-throughput technologies have emerged, capable of measuring thousands of biological molecules simultaneously. This advancement has led to the development of various “omics” platforms, offering a unique opportunity to study how different components of a biological system interact to produce emerging phenotypes. Integration of diverse omics databases offers significant advantages for crop plant breeding by enhancing our ability to understand biological systems and to develop improved plant varieties. By combining genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, researchers can identify novel gene targets associated with desirable traits, including those involved in key metabolic pathways or exhibiting differential expression. Additionally, integrating omics data with environmental factors facilitates the creation of predictive models for crop performance, allowing for the evaluation of new plant varieties under various conditions and aiding in the selection of the most promising ones¹.

SoyMD is a user-friendly multi-omics database for the soybean crop that offers efficient query options and analysis tools, enabling researchers to quickly access relevant omics information and perform in-depth multi-omics analyses. The database integrates extensive datasets, including 38 genomes, 435 transcriptome samples, 125 phenotypes from 6,686 accessions, along with comprehensive epigenomic and genetic variation data⁴.

Ppomics database (db) offers up-to-date multi-omics information on pigeonpea. It provides an integrated platform for discovering key regulators of various traits, thereby facilitating superior breed development. Researchers can utilize it to access comprehensive omics information and conduct multi-omics data analyses².

The integrative omics approach accelerates breeding cycles by deepening our understanding of the molecular mechanisms underlying crop traits and also reduces the time and costs associated with developing new varieties. Ultimately, these advancements contribute to global food security by equipping breeders with the tools to create crops that are more resilient to environmental stresses and capable of higher yields³.

REFERENCES

1. Chao, H., Zhang, S., Hu, Y., Ni, Q., Xin, S., Zhao, L., Ivanisenko, V.A., Orlov, Y.L. and Chen, M., 2024. Integrating omics databases for enhanced crop breeding. J. Integr. Bioinform., 20(4): 20230012.

2. Singh, N., Ujinwal, M. and Singh, N.K., 2024. Ppomicsdb: A multi-omics database for genetic and molecular breeding applications in pigeonpea. Legum. Sci., 6(2): 220.

3. Scossa, F., Alseekh, S. and Fernie, A.R., 2021. Integrating multi-omics data for crop improvement. J. Plant Physiol., 257: 153352.

4. Yang, Z., Luo, C., Pei, X., Wang, S., Huang, Y., Li, J., Liu, B., Kong, F., Yang, Q.Y. and Fang, C., 2024. SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding. Nucleic Acids Res., 52: 1639-1650.