WP9 Improvement of Existing Methods
- DNA variations cause perturbations to extended networks of RNA expression. Variation in RNA transcription is a major mechanism mediating disease susceptibility. In a pilot experiment we aim to exemplarily integrate expression quantitative trait loci (eQTLs), gene expression, and phenotype (clinical) data to infer causal relationships underlying clinical traits. In WP11 we will further develop computational tools for the analysis of AE. The rationale of this approach shall finally be applied in transnational access projects dealing with the in-depth analysis of eQTLs.
- For efficient analysis of genetic variation, we aim to provide improved experimental protocols for subgenome fractionation for mammalian genomes for in-depth analysis of sequence variation. Currently available approaches will be reviewed and further developed. Protocols being optimised particularly use targeted selection of subgenomes by hybridisation capture procedures. Furthermore we will focus on library preparation for specific sequencing applications such as detection DNase I sensitive sites.
- We aim to further develop and implement pair-end mapping technology for identification and characterisation of structural variants and develop specific genotyping arrays for CNV identification using the i-select and e-array technologies. Currently, SNP content in commercial platforms is skewed towards “genotypable” SNPs present in the HapMap. Since SNPs located in CNVs are more likely to cause genotyping difficulties, common CNVs are not likely to be covered by standard genotyping arrays. Some of these SNPs are paralogous sequence variants (PSVs), which have to be specifically targeted. Thus, generation and testing of custom arrays built specifically for CNV identification is a necessary step for efficient CNV analysis.
The tools that will be developed in this WP, will be disseminated through ESGI in the frame of the networking activities of WP2 to strengthen the infrastructure and steadily improve its service capabilities.
Dr. Ivo Gut, PCB/Centro Nacional de Analisis Genómico (ES)