Comparison of DNA-seq and RNA-seq in plant microbiome identification on rye – a case study

All samples provided similar information about detected microorganisms, and difference in abundance might be related to the gene expression activity of the organisms. •Taxonomic profiling of DNA and RNA samples provides very similar results for the same plant material •Main bacterial families in the symptomatic samples are Oxalobacteraceae (Duganella, Massilia, Pseudoduganella) in both RNA and DNA samples This work was funded by the European Union's Horizon Europe research and innovation program under the Marie Skłodowska-Curie grant agreement No. 101106728 Other logos here Comparison of DNA-seq and RNA-seq in plant microbiome identification on rye – a case study Marta Niedzicka*, Stephen Kildea, Stephen Byrne Crop Science Department, Teagasc, Oak Park, Carlow, R93 XE12, Ireland. *[email protected] High-throughput sequencing of RNA is an indispensable tool in plant virology for virus detection and identification. However, the acquired dataset consists of more than just viral reads and traces of other pathogens can be detected in the data, like bacteria and fungi. Using RNAseq for detection of more than just viral pathogens have been discussed in literature1,2. To test the reliability in detection of various microbes using only RNA-seq, this study presents the comparison of microorganisms detected in DNA-seq and RNA-seq analysis of the same samples I. Five symptomatic and one asymptomatic (no visible symptoms) rye samples were collected from the field. DNA and RNA were extracted from the same plant material. Symptomatic samples showed likely bacterial infection. All plants were collected on the same field on 24/04/2024, co. Carlow, Ireland. I. Extracted DNA was sequenced on Illumina (2x150 bp PE). II. Extracted RNA was sequenced after rRNA depletion on Illumina (2x150 bp PE). III. After QC and trimming, the reads were mapped to the host plant (rye genome) and unmapped reads were collected. Reference sequence of rye: GCA_902687465.1 IV. Taxonomic profiling with KRAKEN23 was performed on unmapped reads. V. Abundances calculated on KRAKEN2 reports using R/phyloseq5 and KRONA6, with an exclusion of Streptophyta. Images created with Biorender.com Absolute and relative abundances on the kingdom level References: 1. Haegeman, A. et al. Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests. Plants 12, 2139 (2023). 2. Hu, X. et al. PhytoPipe: a phytosanitary pipeline for plant pathogen detection and diagnosis using RNA-seq data. BMC Bioinformatics 24, 470 (2023). 3. Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol 20, 257 (2019). 4. Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017). 5. McMurdie, P. J. & Holmes, S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 8, e61217 (2013). 6. Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics 12, 385 (2011). Methodology RNA DNA RYE CAS1 – an asymptomatic sample; RYE CS1-5 – symptomatic samples Comparison of taxonomic profiling on the family level (4 symptomatic samples presented) CS1 CS1 CS5 CAS1 CAS1 DNA DNA RNARNA CS2 CS2 CS5 CS4 CS4 RYE CS4 subset Showing Oxalobacteraceae only Limitations: •KRAKEN2 taxonomic assignment has limited capabilities and requires further confirmation of exact detected species •De novo assembled contigs should be verified with megaBLAST and/or BLASTx Dataset availability: non-host reads deposited at NCBI SAMN53388573-SAMN53388578 (DNA) and SAMN53408708SAMN53408713 (RNA); BioProject PRJNA1114626