Transcriptome architecture of the three main lineages of agrobacteria
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- Department of Bioengineering, University of California , Berkeley, California, USA, Joint BioEnergy Institute , Emeryville, California, USA, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA
- Joint BioEnergy Institute , Emeryville, California, USA, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA
- Department of Botany and Plant Pathology, Oregon State University , Corvallis, Oregon, USA
- Joint BioEnergy Institute , Emeryville, California, USA, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA, Department of Chemical and Biomolecular Engineering, University of California , Berkeley, California, USA
- Joint BioEnergy Institute , Emeryville, California, USA, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA, Department of Chemical and Biomolecular Engineering, University of California , Berkeley, California, USA, Institute for Quantitative Biosciences, University of California , Berkeley, California, USA, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark
- Joint BioEnergy Institute , Emeryville, California, USA, Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California, USA, Department of Plant and Microbial Biology, University of California , Berkeley, California, USA
ABSTRACT Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. IMPORTANCE Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- US Department of Agriculture (USDA); USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO); USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1992011
- Journal Information:
- mSystems, Journal Name: mSystems; ISSN 2379-5077
- Publisher:
- American Society for MicrobiologyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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