E-GEOD-48071 - Identification of novel potato candidate genes for quantitative resistance to Phytophthora infestans by SuperSAGE transcriptome analysis
Released on 10 October 2013, last updated on 25 November 2013
To gain novel molecular insights into quantitative late blight resistance, we performed a high-resolution quantitative analysis of gene expression using potato cultivars with contrasting SNP alleles at the StAOS2 locus associated with maturity corrected resistance (MCR). SuperSAGE samples were generated from uninfected and infected plants of the selected genotypes under controlled environmental conditions. Genotypes were pooled to reduce the influence of the genetic background on the transcriptome. Nine SuperSAGE samples were prepared from artificially inoculated plants in a growth chamber using total RNA of the pooled 14, 6 and 9 genotypes in groups A1, A2 and B2, respectively, at three infection time points T0, T1 and T2. Combining the tag counts of both NlaIII and DpnII libraries resulted in 1.1 to 6.2 million tags per sample. Of total 266361 unique tags (unitags), 52.6% matched to the potato genome sequence when up to three mismatches per 26 base pairs were allowed, and 23.3% matched without mismatch. Fifteen pair wise comparisons were performed between the nine SuperSAGE samples to identify transcripts that were differentially expressed in response to infection (six comparisons) or between three genotype pools at the infection time points T0, T1 and T2 (nine comparisons). The number of unitags per comparison ranged from 127 000 to 182 000 (average 158 000). Between 2100 and 11800 tags were differentially expressed in pair wise comparisons, depending on arbitrary cut-off p-values for a significant difference. The highest number of differences was observed for the comparison between genotype pools A1 and A2 one day after infection (A1-T1 vs A2-T1), and the lowest between genotype pools A2 and B2 two days after infection (B2-T2 vs A2-T2). The number of differences in response to infection and between genotype pools even before infection (T0) was in the same order of magnitude. Based on the annotations in the DFCI potato gene index, in the potato genome and in few cases by BLASTX searches against the protein database at NCBI, transcripts that showed reproducible differential expression over the infection time course or between genotype pools A1, A2 and B2 were grouped in 16 functional categories, with overlaps between categories. Genes with genotype dependent, constitutive differential expression provide excellent targets for developing novel diagnostic markers for breeding cultivars with improved quantitative resistance to late blight and possibly other biotic and abiotic stresses. Relevant in this respect appear, besides numerous genes of unknown or ill-defined function, genes with known function involved in stress responses, photosynthesis, protein biosynthesis, protein degradation via the 26S proteasome, transport of proteins, lipids, ions and other small molecules, cell wall structure and many others. Eighteen SuperSAGE libraries were constructed based on nine leaf samples from one infection experiment. For each time point (T0, T1 and T2) one leaflet each of 14, 6 and 9 SL genotypes in genotypic groups A1, A2 and B2, respectively, were pooled. Frozen pooled leaf tissue was powdered in a CryoMill. SuperSAGE libraries were generated at GenXPro GmbH (Frankfurt, Germany) essentially as described (Matsumura et al. 2010). To prevent amplification biases the TrueQuant technology was applied as described by B. Rotter (Patent application Nr. WO2009152928). Besides NlaIII (recognition site: 5’-CATG-3’), DpnII (recognition site: 5’-GATC-3’) was used as second anchoring enzyme, to capture transcripts without a NlaIII site. Therefore, the 26 bp tags carry either CATG or GATC at their 5’ end. The libraries were pooled and sequenced by Solexa/Illumina technology (Illumina, Inc., USA).
RNA-seq of coding RNA
Astrid M Draffehn, Birgit Walkemeier, Björn Rotter, Christiane Gebhardt, Jens Lübeck, Jia Ding, Josef Strahwald, Li Li, Meki S Muktar, Nicolas Krezdorn