Aspergillus comparative transcriptional profiling

ResearchBlogging.org

Researchers from Technical University of Denmark published some interesting results from comparing expression across the very distinct Aspergillus species.

Kudos also goes to making it Open Access. I am posting a few key figures below the fold because I can! They grew the fungi in bioreactors fermenting glucose or xylose. After calibrating the growth curves they were able to sample the appropriate time points for comparison of gene expression across these three species. They found a set of genes commonly expressed.

Andersen Fig3 Figure 3 venn diagram summarizes that there is a core of genes which are significantly differentially expressed during glucose/xylose fermentation. They find a common set of genes significantly expressed in the same conditions in the gray parts of the graph.

They use this grouping of genes to look for conserved upstream motif that they identify among the orthologous and similarly expressed genes discovering a novel xylose cis-regulating element.

What this tells us, is that at least for xylose fermentation is probably older than the divergence of these species. The xylose cis-regulatory motif is also found upstream of orthologous genes in Aspergillus fumigatus further supporting this hypothesis.

The array platform is also now available from Affymetrix so you can try this at home if you have a few bucks.

Work dissecting the degree to which the transcriptional programs overlap in related species and ultimately how they evolve is ongoing in several fungal systems including some neat published and ongoing work from the Regev lab looking at yeast and work from the Johnson lab on mating pathway evolution in Candida albicans and Saccharomyces cerevisiae (1,2,3). However, this paper is one of the first looking at filamentous Pezizomycota fungi that I can think of.

A little snark about the title “A trispecies Aspergillus microarray: Comparative transcriptomics of three Aspergillus species.” (seems I am daring to channel some of my blogging friends)

  1. Isn’t the title a little redundant? Trispecies and three; Aspergillus twice in the same title.
  2. I also can’t wait till we champion the technique (microarray) less and the results more (surprising overlap in gene expression profiles across multiple species). I realize it has been a big deal (and $$) to get a chip created (Affymetrix) that will work well across the species, but Solexa/454/another sequencing technology will make chip development less of a big deal.
  3. In the results: a microarray paper without a cluster-o-gram, yah! (Snark directed at other papers!)

These results really are a quite nice starting point for more comparative transcriptional profiling. A bit more comparative analyses should be done with the genomes from the twelve or so Eurotioales fungal genomes to also assess the patterns of evolution across these species. By assaying how gene expression patterns and complement of genes behave under similar biological conditions we can hope to dissect the pathways and feedback loops and understand how labile these connections are. There are of course a whole host of other interesting conditions to try out now that this is possible among these species and whether different induction of secondary metabolites are controlled by same input conditions, how stress response pathways are different for different conditions and understand how strains that are highly adapted to fermentation in industrial cultures have changed from more wild-strains.

Andersen, M.R., Vongsangnak, W., Panagiotou, G., Salazar, M.P., Lehmann, L., Nielsen, J. (2008). A trispecies Aspergillus microarray: Comparative transcriptomics of three Aspergillus species. Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0709964105

One thought on “Aspergillus comparative transcriptional profiling”

  1. The nice thing about expression data is that the coverage is close to complete and the accuracy on the measurements is high. It is much harder to look at low coverage or low accuracy data sources and try to estimate divergence. I think this issue should have been better discussed for the ChIP-Chip data on cis- regulatory evolution papers.
    I am having a go at phosphorylation evolution in Ascomycota right now and it is a pity that with current data it is very hard to put a number on absolute rates of change or pinpoint specific cases of divergence.

Leave a Reply