Integrating cereal genomics to support innovation in the Triticeae.

The genomic resources of small grain cereals that include some of the most important crop species such as wheat, barley, and rye are attaining a level of completion that now is contributing to new structural and functional studies as well as refining molecular marker development and mapping strategies for increasing the efficiency of breeding processes. The integration of new efforts to obtain reference sequences in bread wheat and barley, in particular, is accelerating the acquisition and interpretation of genome-level analyses in both of these major crops.

Genome-wide association analysis to identify chromosomal regions determining components of earliness in wheat.

The modification of flowering date is considered an important way to escape the current or future climatic constraints that affect wheat crops. A better understanding of its genetic bases would enable a more efficient and rapid modification through breeding. The objective of this study was to identify chromosomal regions associated with earliness in wheat. A 227-wheat core collection chosen to be highly contrasted for earliness was characterized for heading date. Experiments were conducted in controlled conditions and in the field for 3 years to break down earliness in the component traits: photoperiod sensitivity, vernalization requirement and narrow-sense earliness. Whole-genome association mapping was carried out using 760 molecular markers and taking into account the five ancestral group structure. We identified 62 markers individually associated to earliness components corresponding to 33 chromosomal regions. In addition, we identified 15 other significant markers and seven more regions by testing marker pair interactions. Co-localizations were observed with the Ppd-1, Vrn-1 and Rht-1 candidate genes. Using an independent set of lines to validate the model built for heading date, we were able to explain 34% of the variation using the structure and the significant markers. Results were compared with already published data using bi-parental populations giving an insight into the genetic architecture of flowering time in wheat.