Temperature fine-tunes Mediterranean Arabidopsis thaliana life-cycle phenology geographically.

To understand how adaptive evolution in life-cycle phenology operates in plants, we need to unravel the effects of geographic variation in putative agents of natural selection on life-cycle phenology by considering all key developmental transitions and their co-variation patterns. We address this goal by quantifying the temperature-driven and geographically varying relationship between seed dormancy and flowering time in the annual Arabidopsis thaliana across the Iberian Peninsula. We used data on genetic variation in two major life-cycle traits, seed dormancy (DSDS50) and flowering time (FT), in a collection of 300 A. thaliana accessions from the Iberian Peninsula. The geographically varying relationship between life-cycle traits and minimum temperature, a major driver of variation in DSDS50 and FT, was explored with geographically weighted regressions (GWR). The environmentally varying correlation between DSDS50 and FT was analysed by means of sliding window analysis across a minimum temperature gradient. Maximum local adjustments between minimum temperature and life-cycle traits were obtained in the southwest Iberian Peninsula, an area with the highest minimum temperatures. In contrast, in off-southwest locations, the effects of minimum temperature on DSDS50 were rather constant across the region, whereas those of minimum temperature on FT were more variable, with peaks of strong local adjustments of GWR models in central and northwest Spain. Sliding window analysis identified a minimum temperature turning point in the relationship between DSDS50 and FT around a minimum temperature of 7.2 °C. Above this minimum temperature turning point, the variation in the FT/DSDS50 ratio became rapidly constrained and the negative correlation between FT and DSDS50 did not increase any further with increasing minimum temperatures. The southwest Iberian Peninsula emerges as an area where variation in life-cycle phenology appears to be restricted by the duration and severity of the hot summer drought. The temperature-driven varying relationship between DSDS50 and FT detected environmental boundaries for the co-evolution between FT and DSDS50 in A. thaliana. In the context of global warming, we conclude that A. thaliana phenology from the southwest Iberian Peninsula, determined by early flowering and deep seed dormancy, might become the most common life-cycle phenotype for this annual plant in the region.

Advances in genetical genomics of plants.

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other 'omics' technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the 'omics' area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research.