A Bioinformatic Hunt for the Root Cause of Nematode Resistance in Solanum Sisymbriifolium
Abstract
Solanum sisymbriifolium is resistant to potato cyst nematode, a major potato parasite. To understand the basis for this, we sequenced the transcriptome of the plant and developed transformation protocols with the intention of isolating R-genes (genes that encode proteins able to recognize the pathogen) that could be incorporated into potatoes. We performed de novo analyses of the transcriptome, starting with a data set of about 102,000 “potential genes,” a number far higher than any related plant, thus many of these may be artifacts of data assembly. To trim these data, we developed quality control programs, relying on highly conserved genes within the Solanum family. By comparing these genes to reference genomes, we concluded that some of the variation comes from read or assembly errors and not from actual gene variation. Analysis of this trimmed data set has allowed us to establish which filtering procedures most reliably returned only quality reads. Our goal is to filter potential R-genes from this refined data, and then use RNA-seq analysis to establish which genes could be responsible for the unique resistances of S. sisymbriifolium.
A Bioinformatic Hunt for the Root Cause of Nematode Resistance in Solanum Sisymbriifolium
Solanum sisymbriifolium is resistant to potato cyst nematode, a major potato parasite. To understand the basis for this, we sequenced the transcriptome of the plant and developed transformation protocols with the intention of isolating R-genes (genes that encode proteins able to recognize the pathogen) that could be incorporated into potatoes. We performed de novo analyses of the transcriptome, starting with a data set of about 102,000 “potential genes,” a number far higher than any related plant, thus many of these may be artifacts of data assembly. To trim these data, we developed quality control programs, relying on highly conserved genes within the Solanum family. By comparing these genes to reference genomes, we concluded that some of the variation comes from read or assembly errors and not from actual gene variation. Analysis of this trimmed data set has allowed us to establish which filtering procedures most reliably returned only quality reads. Our goal is to filter potential R-genes from this refined data, and then use RNA-seq analysis to establish which genes could be responsible for the unique resistances of S. sisymbriifolium.