GridQTL offers a web based user-friendly analysis portal for QTL analyses in outbred pedigrees using flexible computer resources to enable computationally demanding applications. Click here for the GridQTL homepage and to sign up for a user account.

QTL mapping is an essential tool for understanding the genetic basis of complex traits, including product yield and quality in agricultural species and risk factors for disease in animal and human populations. While we cannot yet fully describe the path from 'sequence to consequence' there is increasing literature on genome regions affecting traits of interest (quantitative trait loci or QTL).  The last 10 years has seen a tremendous increase in the populations used for genome analysis, the numbers of molecular markers used (from a few hundred microsatellites to a million SNP markers), and the type and number of phenotypes and pseudo phenotypes (gene expression using microarrays, protein yields and metabolomics).  Supported by the BBSRC, we have developed user friendly tools for genome analyses over the last decade. Initially this was via QTL Express and now through GridQTL. 

This project is a collaboration with colleagues from The Roslin Institute, The University of Edinburgh.


Locating the Missing Heritability of Complex Traits using Regional Haplotype Mapping

In this project we are exploring the use of haplotypes to identify genomic regions that harbour loci responsible for trait variation. This may enable the detection of regions undiscovered using traditional (‘individual SNP’) GWAS, such as these harbouring multiple rare variants or common variants with small effects. The identification of such genomic regions would generally increase our understanding of the genetic architecture underlying complex traits, but also, more particularly, and by the identification of specific loci or genomic regions, allow targeting regions for functional studies or to be used in genetic (genomic) evaluation (prediction or profiling).

This project is supported by the BBSRC and is a collaboration with Chris Haley, Pau Navarro and Masoud Shirali at the IGMM and Ricardo Pong-Wong at The Roslin Institute.