Studies in mushrooms can have important impact on other research areas.  They can be useful in biotechnology as protein biosynthesis factories for producing compounds or even as an edible delivery mechanism for new drugs.  What we found in the analysis of this genome include clues to mechanisms of how white rotting fungi degrade lignin through analysis of enzyme families.  We also saw evidence for extensive antisense transcription during different developmental stages suggesting some important clues as to how some gene regulation could impact or control developmental progression.  Through gene expression comparison (by MPSS) a large number of transcription factors were shown to be differentially regulated during sexual development.  A knockout out two of these (fst3 and fst4) resulting in changes in ability to form mushrooms (fst4) or smaller mushrooms (fst3).

Several more interesting findings in this work that I hope to add back to this post when there is a little more time -

Ohm, R., de Jong, J., Lugones, L., Aerts, A., Kothe, E., Stajich, J., de Vries, R., Record, E., Levasseur, A., Baker, S., Bartholomew, K., Coutinho, P., Erdmann, S., Fowler, T., Gathman, A., Lombard, V., Henrissat, B., Knabe, N., Kües, U., Lilly, W., Lindquist, E., Lucas, S., Magnuson, J., Piumi, F., Raudaskoski, M., Salamov, A., Schmutz, J., Schwarze, F., vanKuyk, P., Horton, J., Grigoriev, I., & Wösten, H. (2010). Genome sequence of the model mushroom Schizophyllum commune Nature Biotechnology DOI: 10.1038/nbt.1643

Stajich, J., Wilke, S., Ahren, D., Au, C., Birren, B., Borodovsky, M., Burns, C., Canback, B., Casselton, L., Cheng, C., Deng, J., Dietrich, F., Fargo, D., Farman, M., Gathman, A., Goldberg, J., Guigo, R., Hoegger, P., Hooker, J., Huggins, A., James, T., Kamada, T., Kilaru, S., Kodira, C., Kues, U., Kupfer, D., Kwan, H., Lomsadze, A., Li, W., Lilly, W., Ma, L., Mackey, A., Manning, G., Martin, F., Muraguchi, H., Natvig, D., Palmerini, H., Ramesh, M., Rehmeyer, C., Roe, B., Shenoy, N., Stanke, M., Ter-Hovhannisyan, V., Tunlid, A., Velagapudi, R., Vision, T., Zeng, Q., Zolan, M., & Pukkila, P. (2010). Insights into evolution of multicellular fungi from the assembled chromosomes of the mushroom Coprinopsis cinerea (Coprinus cinereus) Proceedings of the National Academy of Sciences, 107 (26), 11889-11894 DOI: 10.1073/pnas.1003391107

• A phylogenetic approach from a Saccharomyces perspective is at PhylomeDB.
• Fungal Orthogroups is based on Synergy algorithm from I. Wapinski formerly of the Regev group at the Broad Institutue.
• Yeast gene order browser (YGOB) for Saccharomyces spp and CGOB for Candida spp.
• OrthoMCL database based on whole genomes, not a ton of fungi but useful starting set.
• Ensembl Genomes provides ortholog prediction as part of the Compara pipeline though there is a limited phylogenetic diversity in the current Ensembl Fungal genomes.
• TreeFam has Saccharomyces cerevisiae and Schizosaccharomyces pombe as the two fungi included in the curated ortholog assignments and phylogenies.
• SIMAP provides pre-computed similarities among all proteins in UniProt.
• InParanoid provides a pretty comprehensive of available 100 whole genomes and many fungal genomes which I tried to help select.
• JGI’s Mycocosm attempts to provide a fungal focused paralog/gene family look at clusters of genes based on whole genomes
• E-Fungi is also an attempt at automated clustering with some fancy webservices logic.
• Fungal Transcription Factor database focused just on families of transcription factors.

Some of these tools are better than others in terms of providing downloadable tables.  Another problem is what Identifiers are used. Many biologists are using gene names or Locus identifiers not UniProt/GenPept IDs to identify genes or proteins of interest.  So tools that just cluster UniProt data aren’t as useful as those which refer to the gene or locus names. Also, providing a way to download all the data from a comparison is important for further mining and grouping of the data or cross-referencing local datasets.  One-by-one plugging in geneids is not really a tool that respects the idea that your user wants to ask sophisticated queries.

Also – beware that some approaches are very much pairwise comparisons lists whereas others are finding orthologous groupings.  So if you want to fine the Rad59 ortholog from all fungi it may be easier or harder depending on the source.

[I may make this a static page in the future to allow for more detailed updating since I know the available resources wax and wane]

• Exploration of snoRNAs finding that a large fraction are clustered in the genome and located in introns.
• Description of transcription factors and their evolutionary conservation and potential link to multicellularity.
• Duplication and diversification of the RNA processing machinery for small RNA mediated silencing.
• Gleaning additional information from Chlamy ESTs that have been over-trimmed.
• Integrating metabolomics and proteomics into better genome annotation.
• Evolution of signaling proteins found in multicellular animals and now Chlamydomonas.

The most surprising findings from the paper include the fact that there are so few members of some of the enzyme families even though this fungus is able to generate enzymes with so much cellulase activity. The authors found that there is not a significantly larger number of glucoside hydrolases which is a collection of carbohydrate degrading enzymes great for making simple sugars out of complex ones. In fact, several plant pathogens compared (Fusarium graminearum and Magnaporthe grisea) and the sake fermenting Aspergillus oryzae all have more members of this family than does.  T. reesei has almost the least (36) copies of a cellulose binding domain (CBM) of any of the filamentous ascomycete fungi.  They used the CAZyme database (carbohydrate active enzymes) database which has done a fantastic job building up profiles of different enzymes involved in carhohydrate degradation binding, and modifications.

Whether T. reesei is really the best cellulose degrading fungus is definitely an open question.  That it works well in the industrial culture that it has been utilized in is important, but there may be other species of fungi with improved cellulase activity and who may in fact have many more copies of cellulases.  So it will be good to add other fungi to the mix with quantitative information about degradation to try and glean what are the most important combination of enzymes and activities.

One technical note.  The comparison of copy number differences employed in the paper is a simple enough Chi-Squared, work that I’ve done with Matt Hahn and others include a gene family size comparison approach that also taked into account phylogenetic distances and assumes a birth-death process of gene family size change.  It would be great to apply the copy number differences through this or other approaches that just evaluate gene trees for these domains to see where the differences are significant and if they can be polarized to a particular branch of the tree.

So will this genome sequence lead to cheaper, better biofuel production? Certainly it provides an important toolkit to start systematically testing individual cellulase enzymes. It’s hard to say how fast this will make an impact, but the work of JBEI and a host of other research groups and biotech companies are going to be able to systematically test out the utility of these individual enzymes.

There is also evolutionary work by other groups on the evolution of these Hypocreales fungi trying to better define when biotrophic and heterotrophic transitions occurred to sample fungi with different lifestyles that might have different cellulase enyzmes that may not have been observed. Defining the relationships of these fungi and when and how many times transitions to lifestyles occurred to choose the most diverse fungi may be an important part of discovering novel enzymes.

Also see

• Discovery Channel Blog
  
• JGI press release

Martinez, D., Berka, R.M., Henrissat, B., Saloheimo, M., Arvas, M., Baker, S.E., Chapman, J., Chertkov, O., Coutinho, P.M., Cullen, D., Danchin, E.G., Grigoriev, I.V., Harris, P., Jackson, M., Kubicek, C.P., Han, C.S., Ho, I., Larrondo, L.F., de Leon, A.L., Magnuson, J.K., Merino, S., Misra, M., Nelson, B., Putnam, N., Robbertse, B., Salamov, A.A., Schmoll, M., Terry, A., Thayer, N., Westerholm-Parvinen, A., Schoch, C.L., Yao, J., Barbote, R., Nelson, M.A., Detter, C., Bruce, D., Kuske, C.R., Xie, G., Richardson, P., Rokhsar, D.S., Lucas, S.M., Rubin, E.M., Dunn-Coleman, N., Ward, M., Brettin, T.S. (2008). Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina). Nature Biotechnology DOI: 10.1038/nbt1403