Plant & Animal Genomes XVI Conference

January 12-16, 2008
Town & Country Convention Center
San Diego, CA

Integrating Molecular And Genetic Data For A Better Understanding Of Bud Set In Poplar

Antje Rohde^1,2 , Tom Ruttink^1,2 , Veronique Storme² , Veronique Jorge³ , Isabella Paolucci⁴ , Muriel Gaudet⁴ , Maurizio Sabatti⁴ , Wout Boerjan² , Catherine Bastien³

¹  Institute for Agricultural and Fisheries Research, Caritasstraat 21, 9090 Melle, Belgium.

²  Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Gent, Belgium.

³  INRA Forest Tree Improvement, Genetics and Physiology Unit, BP 20619 Ardon, 45166 Olivet, France.

⁴  Department of Forest Resources and Environment (DISAFRI), University of Tuscia, via San Camillo de Lellis snc, 01100 Viterbo, Italy.

The seasonal cycle of growth and dormancy distinguishes perennial plants and represents one of the most basic adaptations of trees to their environment. Because bud set is of prime importance for season length in a changing environment, we dissected this developmental program at the phenotypic, genetic and molecular levels.
Combined metabolite and gene expression studies were used to reconstruct the molecular events during apical bud development in poplar. Bud development could be dissected into bud formation, acclimation to dehydration and cold, and dormancy. To each of these processes, specific sets of regulatory and marker genes and metabolites are associated and provide a reference frame for functional studies. A large set of differentially expressed genes was also expressed during the growth-to-dormancy transitions in poplar cambium and Arabidopsis seeds, suggesting parallels for dormancy regulation in different plant organs.
Bud set in field conditions was evaluated with a new high-resolution scoring system in five breeding pedigrees and a collection of P. nigra. QTLs identified in the different genetic maps are investigated for co-localization on the poplar genome sequence. Genomic regions of relevance for bud set are being tested for their adaptive value through association genetics approaches.