Proceedings of the XLVII Italian Society of Agricultural Genetics - SIGA Annual Congress

Verona, Italy - 24/27 September, 2003

ISBN 88-900622-4-X

Poster Abstract - 1.44

PROFILING GRAPE GENE EXPRESSION DURING LEAF DEVELOPMENT AND SENESCENCE BY cDNA ARRAYS

M. PINDO*, C. MOSER*, P. GATTO*, C. SEGALA*, P. FONTANA*, H.A. BECKER***, E. BLANZIERI**, R. VELASCO*

*) Area Biologia Avanzata, Istituto Agrario S. Michele a/Adige, S. Michele a/Adige, Trento

**) Dip. di Informatica e Telecomunicazioni, Università di Trento

***) Max Plank Institut für Züchtungsforschung, Koeln, Germany

grape, gene expression, ESTs, arrays, leaf development

High-throughput sequencing of ESTs and array technologies are important tools for genome-wide studies of essential biological processes like leaf development and senescence. At our institute, we are interested in understanding the process of grape leaf senescence from a physiological and molecular point of view. Early symptoms of senescence in grapevines leaves can indeed severely affect the quality of the grape harvest.

In order to obtain a collection of grape expressed sequences we constructed several standard cDNA libraries from bud, leaf, berry, root (cultivar 'Pinot noir'), sprout and inflorescence (cultivar 'Regent', in collaboration with the Institut fuer Rebenzuechtung, Geiweilerhof, Germany). In addition three subtracted cDNA libraries were constructed by coupled subtractive hybridizations of leaf, berry and root ('Pinot noir'). A subset of these cDNA clones (from leaf, bud, sprout and inflorescence tissues) were sequenced and amplified by PCR and then orderly arrayed on nylon membranes for gene expression studies. The high-density nylon filters contain 4010 amplified cDNAs double spotted corresponding to about 2300 clusters (unigenes). Positive and negative controls were also included. Radioactively-labeled RNAs from 'Pinot noir' leaves at 5 different development stages were used to hybridize the high-density filters to profile gene-expression during development and senescence of grape leaves. 6 independent measurements for each condition were collected and the data were then normalized making the assumption that global expression does not change among filters and conditions. Analysis of gene expression data has been carried out by looking at genes involved in specific metabolic functions and by clustering methods. Gene clusters will contain those transcripts whose expression is similar in the 5 tested conditions. Preliminary results, to be further validated by RT-PCR, high-lighted genes that are up-regulated during the senescent phase.

This work was supported by the project "Advanced Biology" funded by the Fondazione delle Casse di Risparmio di Trento e Rovereto (Trento-Italy).