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William Dirks

Publications and source records attributed to William Dirks.

2 recordsLinked to original sources

Early evolution of animal cell signaling and adhesion genes.

In stark contrast to the rapid morphological radiation of eumetazoans during the Cambrian explosion, the simple body plan of sponges (Phylum Porifera) emerged from the Cambrian relatively unchanged. Although the genetic and developmental underpinnings of these disparate evolutionary outcomes are unknown, comparisons between modern sponges and eumetazoans promise to reveal the extent to which critical genetic factors were present in their common ancestors. Two particularly interesting classes of genes in this respect are those involved in cell signaling and adhesion. These genes help guide development and morphogenesis in modern eumetazoans, but the timing and sequence of their origins is unknown. Here, we demonstrate that the sponge Oscarella carmela, one of the earliest branching animals, expresses core components of the Wnt, transforming growth factor beta, receptor tyrosine kinase, Notch, Hedgehog, and Jak/Stat signaling pathways. Furthermore, we identify sponge homologs of nearly every major eumetazoan cell-adhesion gene family, including those that encode cell-surface receptors, cytoplasmic linkers, and extracellular-matrix proteins. From these data, we infer that key signaling and adhesion genes were in place early in animal evolution, before the divergence of sponge and eumetazoan lineages.

Animals↗

Effective similarity measures for expression profiles.

It is commonly accepted that genes with similar expression profiles are functionally related. However, there are many ways one can measure the similarity of expression profiles, and it is not clear a priori what is the most effective one. Moreover, so far no clear distinction has been made as for the type of the functional link between genes as suggested by microarray data. Similarly expressed genes can be part of the same complex as interacting partners; they can participate in the same pathway without interacting directly; they can perform similar functions; or they can simply have similar regulatory sequences. Here we conduct a study of the notion of functional link as implied from expression data. We analyze different similarity measures of gene expression profiles and assess their usefulness and robustness in detecting biological relationships by comparing the similarity scores with results obtained from databases of interacting proteins, promoter signals and cellular pathways, as well as through sequence comparisons. We also introduce variations on similarity measures that are based on statistical analysis and better discriminate genes which are functionally nearby and faraway. Our tools can be used to assess other similarity measures for expression profiles, and are accessible at biozon.org/tools/expression/

Algorithms↗