Systems genetics, bioinformatics and eQTL mapping

Abstract

Jansen and Nap (Trends Genet 17(7):388-391, 2001) and Jansen (Nat Rev Genet 4:145-151, 2003) first proposed the concept of genetical genomics, or genome-wide genetic analysis of gene expression data, which is also called transcriptome mapping. In this approach, microarrays are used for measuring gene expression levels across genetic mapping populations. These gene expression patterns have been used for genome-wide association analysis, an analysis referred to as expression QTL (eQTL) mapping. Recent progress in genomics and experimental biology has brought exponential growth of the biological information available for computational analysis in public genomics databases. Bioinformatics is essential to genome-wide analysis of gene expression data and used as an effective tool for eQTL mapping. The use of Plabsoft database, EcoTILLING, GNARE and FastMap allowed for dramatic reduction of time in genome analysis. Some web-based tools (e.g., Lirnet, eQTL Viewer) provide efficient and intuitive ways for biologists to explore transcriptional regulation patterns, and to generate hypotheses on the genetic basis of transcriptional regulations. Expression quantitative trait loci (eQTL) mapping concerns finding genomic variation to elucidate variation of expression traits. This problem poses significant challenges due to high dimensionality of both the gene expression and the genomic marker data. The core challenges in understanding and explaining eQTL associations are the fine mapping and the lack of mechanistic explanation. But with the development of genetical genomics and computer technology, many new approaches for eQTL mapping will emerge. The statistical methods used for the analysis of expression QTL will become mature in the future.