SUMMARYIncreased phenotyping accuracy and throughput are necessary to improve our understanding of quantitative variation and to be able to deconstruct complex traits such as those involved in growth responses to the environment. Still, only a few facilities are known to handle individual plants of small stature for non-destructive, real-time phenotype acquisition from plants grown in precisely adjusted and variable experimental conditions. Here, we describe Phenoscope, a high-throughput phenotyping platform that has the unique feature of continuously rotating 735 individual pots over a table. It automatically adjusts watering and is equipped with a zenithal imaging system to monitor rosette size and expansion rate during the vegetative stage, with automatic image analysis allowing manual correction. When applied to Arabidopsis thaliana, we show that rotating the pots strongly reduced micro-environmental disparity: heterogeneity in evaporation was cut by a factor of 2.5 and the number of replicates needed to detect a specific mild genotypic effect was reduced by a factor of 3. In addition, by controlling a large proportion of the micro-environmental variance, other tangible sources of variance become noticeable. Overall, Phenoscope makes it possible to perform large-scale experiments that would not be possible or reproducible by hand. When applied to a typical quantitative trait loci (QTL) mapping experiment, we show that mapping power is more limited by genetic complexity than phenotyping accuracy. This will help to draw a more general picture as to how genetic diversity shapes phenotypic variation.

BackgroundExpression traits can vary quantitatively between individuals and have a complex inheritance. Identification of the genetics underlying transcript variation can help in the understanding of phenotypic variation due to genetic factors regulating transcript abundance and shed light into divergence patterns. So far, only a limited number of studies have addressed this subject in Arabidopsis, with contrasting results due to dissimilar statistical power. Here, we present the transcriptome architecture in leaf tissue of two RIL sets obtained from a connected-cross design involving 3 commonly used accessions. We also present the transcriptome architecture observed in developing seeds of a third independent cross.ResultsThe utilisation of the novel R/eqtl package (which goal is to automatize and extend functions from the R/qtl package) allowed us to map 4,290 and 6,534 eQTLs in the Cvi-0 × Col-0 and Bur-0 × Col-0 recombinant populations respectively. In agreement with previous studies, we observed a larger phenotypic variance explained by eQTLs in linkage with the controlled gene (potentially cis-acting), compared to distant loci (acting necessarily indirectly or in trans). Distant eQTLs hotspots were essentially not conserved between crosses, but instead, cross-specific. Accounting for confounding factors using a probabilistic approach (VBQTL) increased the mapping resolution and the number of significant associations. Moreover, using local eQTLs obtained from this approach, we detected evidence for a directional allelic effect in genes with related function, where significantly more eQTLs than expected by chance were up-regulated from one of the accessions. Primary experimental data, analysis parameters, eQTL results and visualisation of LOD score curves presented here are stored and accessible through the QTLstore service database http://qtlstore.versailles.inra.fr/.ConclusionsOur results demonstrate the extensive diversity and moderately conserved eQTL landscape between crosses and validate the utilisation of expression traits to explore for candidates behind phenotypic variation among accessions. Furthermore, this stresses the need for a wider spectrum of diversity to fully understand expression trait variation within a species.