Next generation sequencing (NGS) technologies for mapping-based cloning and gene expression analysis offer biologists the ability to rapidly and efficiently identify ethyl methanesulfonate (EMS)-induced point mutations responsible for a given phenotype and to examine expression levels across an organism’s transcriptome. The volume of data generated by NGS technologies necessitates the use of bioinformatic methods for data analysis. To allow biologist-friendly access to such bioinformatic methods, we have developed two web-based  applications that can be used without local setup.

The first application is a web-based implementation of the NGS-based identification of EMS-induced point mutations as described in the eMAP poster by Austin et al. The application guides users through the different steps of the eMAP process starting with the upload of single nucleotide polymorphism (SNP) data, which can be generated by widely available mapping tools such as maq. For the eMAP chastity statistics (see Austin et al. poster) additional information may be extracted from pileup data with an easy-to-use java applet. For each step the user can adjust several parameters to improve the identification of SNPs that putatively cause an observed phenotype.

The second application is an alfalfa (Medicago sativa) 'electronic fluorescent pictographic' (eFP) browser for exploring the expression patterns of a gene of interest, based on transcriptome data generated by the NGS-based mRNA-seq method. This application is based on the open source eFP Browser framework at http://bar.utoronto.ca [Winter et al., PLoS ONE 2(8):e718]. The application displays gene expression signals in different parts of the plant as a biologist-friendly pictogram.