SummaryThe signal transduction network controlling plant responses to pathogens includes pathways requiring the signal molecules salicylic acid (SA), jasmonic acid (JA), and ethylene (ET). The network topology was explored using global expression phenotyping of wild-type and signaling-defective mutant plants, including eds3, eds4, eds5, eds8, pad1, pad2, pad4, NahG, npr1, sid2, ein2, and coi1. Hierarchical clustering was used to de®ne groups of mutations with similar effects on gene expression and groups of similarly regulated genes. Mutations affecting SA signaling formed two groups: one comprised of eds4, eds5, sid2, and npr1-3 affecting only SA signaling; and the other comprised of pad2, eds3, npr1-1, pad4, and NahG affecting SA signaling as well as another unknown process. Major differences between the expression patterns in NahG and the SA biosynthetic mutant sid2 suggest that NahG has pleiotropic effects beyond elimination of SA. A third group of mutants comprised of eds8, pad1, ein2, and coi1 affected ethylene and jasmonate signaling. Expression patterns of some genes revealed mutual inhibition between SA-and JA-dependent signaling, while other genes required JA and ET signaling as well as the unknown signaling process for full expression. Global expression phenotype similarities among mutants suggested, and experiments con®rmed, that EDS3 affects SA signaling while EDS8 and PAD1 affect JA signaling. This work allowed modeling of network topology, de®nition of co-regulated genes, and placement of previously uncharacterized regulatory genes in the network.

SummarySystemic infections of plants by viruses require that viruses modify host cells in order to facilitate infections. These modifications include induction of host factors required for replication, propagation and movement, and suppression of host defense responses, which are likely to be associated with changes in host gene expression. Past studies of the effects of viral infection on gene expression in susceptible hosts have been limited to only a handful of genes. To gain broader insight into the responses elicited by viruses in susceptible hosts, high-density oligonucleotide probe microarray technology was used. Arabidopsis leaves were either mock inoculated or inoculated with cucumber mosaic cucumovirus, oil seed rape tobamovirus, turnip vein clearing tobamovirus, potato virus X potexvirus, or turnip mosaic potyvirus. Inoculated leaves were collected at 1, 2, 4, and 5 days after inoculation, total RNA was isolated, and samples were hybridized to Arabidopsis GeneChip microarrays (Affymetrix). Microarray hybridization revealed co-ordinated changes in gene expression in response to infection by diverse viruses. These changes include virus-general and virusspecific alterations in the expression of genes associated with distinct defense or stress responses. Analyses of the promoters of these genes further suggest that diverse RNA viruses elicit common responses in susceptible plant hosts through signaling pathways that have not been previously characterized.

SummaryCereal grains accumulate carbohydrates, storage proteins and fatty acids via different pathways during their development. Many genes that participate in nutrient partitioning during grain filling and that affect starch quality have been identified. To understand how the expression of these genes is coordinated during grain development, a genomic approach to surveying the participation and interactions of all the pathways is necessary.Using recently published rice genome information, we designed a rice GeneChip microarray that covers half the rice genome. By monitoring the expression of 21 000 genes in parallel, we identified genes involved in the grain filling process and found that the expression of genes involved in different pathways is coordinately controlled in a synchronized fashion during grain filling. Interestingly, a known promoter element in genes encoding seed storage proteins, AACA, is statistically over-represented among the 269 genes in different pathways with diverse functions that are significantly up-regulated during grain filling. By expression pattern matching, a group of transcription factors that have the potential to interact with this element was identified. We also found that most genes in the starch biosynthetic pathway show multiple distinct spatial and temporal expression patterns, suggesting that different isoforms of a given enzyme are expressed in different tissues and at different developmental stages. Our results reveal key regulatory machinery and provide an opportunity for modifying multiple pathways by manipulating key regulatory elements for improving grain quality and quantity.

Plants alter their gene expression patterns in response to drought. Sometimes these transcriptional changes are successful adaptations leading to tolerance, while in other instances the plant ultimately fails to adapt to the stress and is labeled as sensitive to that condition. We measured the expression of approximately half of the genes in rice ( approximately 21,000) in phenotypically divergent accessions and their transgressive segregants to associate stress-regulated gene expression changes with quantitative trait loci (QTLs) for osmotic adjustment (OA, a trait associated with drought tolerance). Among the parental lines, a total of 662 transcripts were differentially expressed. Only 12 genes were induced in the low OA parent, CT9993, at moderate dehydration stress levels while over 200 genes were induced in the high OA parent, IR62266. The high and low OA parents had almost entirely different transcriptional responses to dehydration stress suggesting a complete absence of an appropriate response rather than a slower response in CT9993. Sixty-nine genes were up-regulated in all the high OA lines and nine of those genes were not induced in any of the low OA lines. The annotation of four of those genes, sucrose synthase, a pore protein, a heat shock and an LEA protein, suggests a role in maintaining high OA and membrane stability. Of the 3,954-probe sets that correspond to the QTL intervals, very few had a differential expression pattern between the high OA and low OA lines that suggest a role leading to the phenotypic variation. However, several promising candidates were identified for each of the five QTL including a snRNP auxiliary factor, a LEA protein, a protein phosphatase 2C and a Sar1 homolog.