Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Comparative analysis of ESTs involved in grape responses to Xylella fastidiosa infection | BMC Plant Biology BioMed Central Research article Comparative analysis of ESTs involved in grape responses to Xylella fastidiosa infection Hong Lin t1 Harshavardhan Doddapanenh1 2 Yuri Takahashi2 3 and M Andrew Walker2 Open Access Address 1USDA-ARS 9611 S. Riverbend Avenue Parlier California 93648 USA 2Department of Viticulture Enology University of California Davis California 95616 USA and 3Department of Food sciences Ehime Women s College Uwajima 798-0025 Japan Email Hong Lin - hlin@ Harshavardhan Doddapaneni - harsha@ Yuri Takahashi - takahashi@ M Andrew Walker - walker@ Corresponding author tEqual contributors Published 22 February 2007 Received 23 August 2006 BMC Plant Biology 2007 7 8 doi 1471 -2229-7-8 Accepted 22 February 2007 This article is available from http 1471-2229 7 8 2007 Lin et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background The gram-negative bacterium Xylella fastidiosa Xf is the causal agent of Pierce s disease PD in grape as well as diseases of many fruit and ornamental plants. The current molecular breeding efforts have identified genetic basis of PD resistance in grapes. However the transcriptome level characterization of the host response to this pathogen is lacking. Results Twelve tissue specific subtractive suppression hybridization SSH cDNA libraries derived from a time course sampling scheme were constructed from stems leaves and shoots of PD resistant and susceptible sibling genotypes V. rupestris X V. arizonica in response to Xf infection. A total of 5 794 sequences were obtained from these cDNA libraries from which 993 contigs and 949 singletons were derived. Using Gene Ontology GO
