hybrid: populus deltoides x populus nigra harvest date: 06-06-07 clone: Soligo tissue: leaf
Treatment protocol
no treatment
Growth protocol
leaf - Plants were grown in 10-liter pots filled with peat/sand mix (50/50 v/v amended with 1g/l CaMg(CO2)3 and fertilised with Nutricote T100 (13-13-13-2, N-P-K-Mg + trace elements)). In the greenhouse, temperature oscillated with outside irradiance but kept in the range 15-26 °C, and air humidity during day oscillated in the range 50-75%. Irradiance depended on outside and varied in the range 300-850 µmol m-1 s-1 (cloudy-sunny), and was over750 µmol m-1 s-1 most of the experience. During the 3 days preceding harvest, mean day temperature was 25°C, humidity was 65% and light was 850 µmol m-1 s-1.
Extracted molecule
total RNA
Extraction protocol
Pool of extract, 103-SCTL-L:1ug, 104-SCTL-L:1ug, 107-SCTL-L:1ug.
Label
Biotin
Label protocol
labelling Biotin direct, amplification=yes, cRNA 20 ug.
Hybridization protocol
labelled extract quantity: 15ug
Scan protocol
GCOS, Biotin:pmt voltage 570nm,650V,laser power 1
Description
This project aims to identify genes of interest for water deficit acclimation and/or adaptation in a tree species: poplar. We look for genes and gene expression networks related to drought stress. We intend to analyse the transcriptome in mature leaves, in two genotypes, Carpaccio and Soligo, at various stages and intensities of stress. During water deficit, leaves underwent many processes aiming to maintain cells integrity such as water status adjustment through osmoregulation or cell detoxication. These analyses intend to identify genes of interest involved in homeostasis maintenance. The comparison between medium and severe stress intensities and between early and long term stresses will power the selection of genes of interest. The co-analysis of two genotypes of contrasted tolerance to water deficit should help to discriminate genes presenting a potential adaptative character from genes responding passively to the constraint
Data processing
The data were normalized with the gcrma algorithm (Irizarry et al., 2003), available in the Bioconductor package (Gentleman and Carey, 2002).
