A Strategy for the Identification of New Abiotic Stress Determinants in Arabidopsis Using Web-Based Data Mining and Reverse Genetics

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Azevedo, H (Author) Other; Silva Correia, J (Author) Other; Oliveira, J (Author) Other; Laranjeira, S (Author) Other; Barbeta, C (Author) Other; Amorim Silva, V (Author) Other; Botella, MA (Author) Other; Lino Neto, T (Author) Other; Tavares, RM (Author) Other

Journal

Title: OMICS A Journal of Integrative Biology

Vol. 15

Pages: 935-947

ISSN: 1536-2310

Publisher: Mary Ann Liebert

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-002-J2N

DOI: 10.1089/omi.2011.0083

Abstract (EN): Since the sequencing of the Arabidopsis thaliana genome in 2000, plant researchers have faced the complex challenge of assigning function to thousands of genes. Functional discovery by in silico prediction or homology search resolved a significant number of genes, but only a minor part has been experimentally validated. Arabidopsis entry into the post-genomic era signified a massive increase in high-throughput approaches to functional discovery, which have since become available through publicly-available web-based resources. The present work focuses on an easy and straightforward strategy that couples data-mining to reverse genetics principles, to allow for the identification of new abiotic stress determinant genes. The strategy explores systematic microarray-based transcriptomics experiments, involving Arabidopsis abiotic stress responses. An overview of the most significant resources and databases for functional discovery in Arabidopsis is presented. The successful application of the outlined strategy is illustrated by the identification of a new abiotic stress determinant gene, HRR, which displays a heat-stress-related phenotype after a loss-of-function reverse genetics approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13