Biomedical subjects

Susana Perelman

Publications and source records attributed to Susana Perelman.

2 recordsLinked to original sources

PubMed2005

Phytochrome control of the Arabidopsis transcriptome anticipates seedling exposure to light.

Phytochromes mediate a profound developmental shift when dark-grown seedlings are exposed to light. Here, we show that a subset of genes is upregulated in phytochrome B (phyB) mutants even before dark-grown Arabidopsis thaliana seedlings are exposed to light. Most of these genes bear the RY cis motif, which is a binding site of the transcription factor ABSCISIC ACID INSENSITIVE3 (ABI3), and the phyB mutation also enhances ABI3 expression. These changes in transcriptome have physiological consequences, because seedlings of the abi3 mutant showed enhanced responses to pulses of far-red light, whereas ABI3 overexpressers exhibited the opposite pattern. Seedlings of the wild type derived from seeds germinated in full darkness showed enhanced expression of genes bearing the RY cis motif and reduced responses to far-red light. We propose that, via changes in ABI3 expression, light, perceived mainly by phyB in the seed, generates a downstream transdevelopmental phase signal that preconditions the seedling to its most likely environment.

Arabidopsis↗

PubMed2003

Finding unexpected patterns in microarray data.

We describe the performance of a protocol based on the sequential application of unsupervised and supervised methods to analyze microarray samples defined by a combination of factors. Correspondence analysis is used to visualize the emerging patterns of three set of novel or previously published data: photoreceptor mutants of Arabidopsis grown under different light/dark conditions, Arabidopsis exposed to different types of biotic and abiotic stress, and human acute leukemia. We find, for instance, that light has a dramatic effect on plants despite the absence of the four major photoreceptors, that bacterial-, fungal-, and viral-induced responses converge at later stages of attack, and that sample preparation procedures used in different hospitals have large effects on transcriptome patterns. We use canonical discriminant analysis to identify the genes associated with these patters and hierarchical clustering to find groups of coregulated genes that are easily visualized in a second round of correspondence analysis and ordered tables. The unconventional combination of standard descriptive multivariate methods offers a previously unrecognized tool to uncover unexpected information.

Arabidopsis↗