If someone asked you which data sets are most important for plant breeding – genome or transcriptome data – how would you respond? It used to be that the obvious choice would have been the genome. However, the omics landscape has evolved, and the answer is far from straightforward.
Both genome and transcriptome data play pivotal roles in the field of plant breeding. Genome data shows a plant’s chemical and metabolic potential. It proves invaluable for uncovering new genes, genetic mapping, and identifying metabolic pathways. The increasing amount of plant genomic data available enables us to identify common genes and genetic pathways that hold significance for agronomic traits across various plant species (1).
On the other hand, transcriptome data provides us with insight into which genes and metabolic pathways are potentially active under specific environmental conditions and across diverse plant tissues. In essence, it offers a comprehensive snapshot of transcribed genes and metabolic pathways at a particular moment or under specific circumstances, by measuring messenger RNA (mRNA) incidence in specific tissues. This information aids in comprehending how plants react to distinct environmental factors like drought, heat stress, or salinity (2).
Nevertheless, is not the complete story. What about the regulation of mRNA translation into proteins? Do those fragments of mRNA within the cell genuinely represent active pathways, or are they merely phantom signals? What are the mechanisms that control translation at the post-translational level (3)? Our understanding of protein expression modulation in plant tissues is still in its infancy. We are only just beginning to scratch the surface of this fascinating realm.
In the end, both genome and transcriptome data hold immense value for plant breeding. The genome provides us with a comprehensive understanding of a plant’s potential, while transcriptome data offers insights into gene regulation under various conditions. However, there is still much to learn about other regulation mechanisms of crop plants stress response. As we continue to increase the number and types of omics datasets, we will develop better strategies to selectively evolve crop plants that can adapt to rapidly changing environmental conditions (4).
- l-Salihi, S.A.A., Ford, K.L. Comparative bioinformatics analysis of the biosynthetic pathways and key candidate genes of three species, Vitis vinifera, Fragaria vesca and Olea europaea, furnish enzyme sets for the production of pharmaceutically valuable terpenes in heterologous hosts. J. Plant Biochem. Biotechnol. (2023). s13562-022-00823-z
- Booth, Mitchell W., et al. “Tissue-specific transcriptome profiles identify functional differences key to understanding whole plant response to life in variable salinity.” Biology Open11.8 (2022): bio059147.
- Son S and Park SR (2023) Plant translational reprogramming for stress resilience. Front. Plant Sci. 14:1151587. fpls.2023.1151587
- Zhou R, Jiang F, Niu L, Song X, Yu L, Yang Y and Wu Z (2022) Increase Crop Resilience to Heat Stress Using Omic Strategies. Front. Plant Sci. 13:891861. doi: fpls.2022.891861
