Expression-based discovery of candidate ovule development regulators through transcriptional profiling of ovule mutants

<p>Abstract</p> <p>Background</p> <p><it>Arabidopsis </it>ovules comprise four morphologically distinct parts: the nucellus, which contains the embryo sac, two integuments that become the seed coat, and the funiculus that anchors the ovule within the carpel. Analysis of developmental mutants has shown that ovule morphogenesis relies on tightly regulated genetic interactions that can serve as a model for developmental regulation. Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes. Expression-based gene discovery can be used access such obscured genes.</p> <p>Results</p> <p>Affymetrix microarrays were used for expression-based gene discovery to identify sets of genes expressed in either or both integuments. The genes were identified by comparison of pistil mRNA from wild type with mRNA from two mutants; <it>inner no outer </it>(<it>ino</it>, which lacks the outer integument), and <it>aintegumenta </it>(<it>ant</it>, which lacks both integuments). Pools of pistils representing early and late stages of ovule development were evaluated and data from the three genotypes were used to designate genes that were predominantly expressed in the integuments using pair-wise and cluster analyses. Approximately two hundred genes were found to have a high probability of preferential expression in these structures, and the predictive nature of the expression classes was confirmed with reverse transcriptase polymerase chain reaction and <it>in situ </it>hybridization.</p> <p>Conclusion</p> <p>The results showed that it was possible to use a mutant, <it>ant</it>, with broad effects on plant phenotype to identify genes expressed specifically in ovules, when coupled with predictions from known gene expression patterns, or in combination with a more specific mutant, <it>ino</it>. Robust microarray averaging (RMA) analysis of array data provided the most reliable comparisons, especially for weakly expressed genes. The studies yielded an over-abundance of transcriptional regulators in the identified genes, and these form a set of candidate genes for evaluation of roles in ovule development using reverse genetics.</p>