Transcriptional profiling during infection of potato NLRs and Phytophthora infestans effectors using cDNA enrichment sequencing
Year: 2024
Type: article
Abstract: An accurate assessment of host and pathogen gene expression during infection is critical for understanding the molecular aspects of host-pathogen interactions. Often, pathogen-derived transcripts are difficult to ascertain at early infection stages owing to the unfavourable transcript representation compared to the host genes. In this study, we compare two sequencing techniques, RNAseq and enrichment sequencing (RenSeq and PenSeq) of cDNA, to investigate gene expression patterns in the doubled monoploid potato (DM) infected with the late blight pathogen Phytophthora infestans. Our results reveal distinct advantages of cDNA RenSeq and PenSeq over traditional RNAseq in terms of target gene representation and transcriptional quantification at early infection stages. Throughout the infection time course, cDNA enrichment sequencing enables transcriptomic analyses for more targeted host and pathogen genes. For highly expressed genes that were sampled in parallel by both cDNA enrichment and RNAseq, a high level of concordance in expression profiles is observed, indicative of at least semi-quantitative gene expression representation following enrichment.
Source: The Crop Journal
Authors: Amanpreet Kaur, Vikrant Singh, Stephen Byrne, Miles Armstrong, Thomas M. Adams, Brian Harrower, Eleanor Gilroy, Ewen Mullins, Ingo Hein
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $1,890
Awards: G1505612651, G2375274558, G2833454030, UK Crop Diversity Bioinformatics Resource, G3957548433, G434337789, Studying Co-evolution in agriculture to inform NLR deployment, G5052871238, Research Leaders 2025 - A Fellowship Programme developing the Next Generation of Agri-Food Research Leaders, G6366470468, G6669963059, G7917327042, Potato PCN Resistance: Cloning effective resistances against potato cyst nematodes
OpenAlex ID: W4403500682
