Tag Archives: basidiomycete

Presents for the holidays – Plant pathogen genomes

Though a bit cliche, I think the metaphor of “presents under the tree” of some new plant pathogen genomes summarized in 4 recent publications is still too good to resist.  There are 4 papers in this week’s Science that will certainly make a collection of plant pathogen biologists very happy. There are also treats for the general purpose genome biologists with descriptions of next generation/2nd generation sequencing technologies, assembly methods, and comparative genomics. Much more inside these papers than I am summarizing so I urge you to take look if you have access to these pay-for-view articles or contact the authors for reprints to get a copy.

Hyaloperonospora

These include the genome of biotrophic oomycete and Arabidopsis pathogen Hyaloperonospora arabidopsidis (Baxter et al). While preserving the health of Arabidopsis is not a major concern of most researchers, this is an excellent model system for studying plant-microbe interaction.  The genome sequence of Hpa provides a look at specialization as a biotroph. The authors found a reduction (relative to other oomycete species) in factors related to host-targeted degrading enzymes and also reduction in necrosis factors suggesting the specialization in biotrophic lifestyle from a necrotrophic ancestor. Hpa also does not make zoospores with flagella like its relatives and sequence searches for 90 flagella-related genes turned up no identifiable homologs.

While the technical aspects of sequencing are less glamourous now the authors used Sanger and Illumina sequencing to complete this genome at 45X sequencing coverage and an estimated genome size fo 80 Mb. To produce the assembly they used Velvet on the paired end Illumina data to produce a 56Mb assembly and PCAP (8X coverage to produce a 70Mb genome) on the Sanger reads to produce two assemblies that were merged with an ad hoc procedure that relied on BLAT to scaffold and link contigs through the two assembled datasets. They used CEGMA and several in-house pipelines to annotate the genes in this assembly. SYNTENY analysis was completed with PHRINGE. A relatively large percentage (17%) of the genome fell into ‘Unknown repetitive sequence’ that is unclassified – larger than P.sojae (12%) but there remain a lot of mystery elements of unknown function in these genomes.  If you jump ahead to the Blumeria genome article you’ll see this is still peanuts compared to that Blumeria’s genome (64%). The largest known transposable element family in Hpa was the LTR/Gypsy element. Of interest to some following oomycete literature is the relative abundance of the RLXR containing proteins which are typically effectors – there were still quite a few (~150 instead of ~500 see in some Phytophora genomes).

Blumeria

 

A second paper on the genome of the barley powdery mildew Blumeria graminis f.sp. hordei and two close relatives Erysiphe pisi, a pea pathogen, and Golovinomyces orontii, an Arabidopsis thaliana pathogen (Spanu et al).  These are Ascomycetes in the Leotiomycete class where there are only a handful of genomes Overall this paper tells a story told about how obligate biotrophy has shaped the genome. I found most striking was depicted in Figure 1. It shows that typical genome size for (so far sampled) Pezizomycotina Ascomycetes in the ~40-50Mb range whereas these powdery mildew genomes here significantly large genomes in ~120-160 Mb range. These large genomes were primarily comprised of Transposable Elements (TE) with ~65% of the genome containing TE. However the protein coding gene content is still only on the order of ~6000 genes, which is actually quite low for a filamentous Ascomycete, suggesting that despite genome expansion the functional potential shows signs of reduction.  The obligate lifestyle of the powdery mildews suggested that the species had lost some autotrophic genes and the authors further cataloged a set of ~100 genes which are missing in the mildews but are found in the core ascomycete genomes. They also document other genome cataloging results like only a few secondary metabolite genes although these are typically in much higher copy numbers in other filamentous ascomycetes (e.g. Aspergillus).  I still don’t have a clear picture of how this gene content differs from their closest sequenced neighbors, the other Leotiomycetes Botrytis cinerea and Sclerotinia sclerotium, are on the order of 12-14k genes. Since the E. pisi and G. orontii data is not yet available in GenBank or the MPI site it is hard to figure this out just yet – I presume it will be available soon.

More techie details — The authors used Sanger and second generation technologies and utilized the Celera assembler to build the assemblies from 120X coverage sequence from a hybrid of sequencing technologies.  Interestingly, for the E. pisi and G. orontii assemblies the MPI site lists the genome sizes closer to 65Mb in the first drafts of the assembly with 454 data so I guess you can see what happens when the Newbler assembler which overcollapses repeats. They also used a customized automated annotation with some ab intio gene finders (not sure if there was custom training or not for the various gene finders) and estimated the coverage with the CEGMA genes. I do think a Fungal-Specific set of core-conserved genes would be in order here as a better comparison set – some nice data like this already exist in a few databases but would be interesting to see if CEGMA represents a broad enough core-set to estimate genome coverage vs a Fungal-derived CEGMA-like set.

 

A third paper in this issue covers the genome evolution in the massively successful pathogen Phytophora infestans through resequencing of six genomes of related species to track recent evolutionary history of the pathogen (Raffaele et al). The authors used high throughput Illumina sequencing to sequence genomes of closely related species. They found a variety differences among genes in the pathogen among the findings “genes in repeat-rich regions show[ed] higher rates of structural polymorphisms and positive selection”. They found 14% of the genes experienced positive selection and these included many (300 out of ~800) of the annotated effector genes. P. infestans also showed high rates of change in the repeat rich regions which is also where a lot of the disease implicated genes are locating supporting the hypothesis that the repeat driven expansion of the genome (as described in the 2009 genome paper). The paper generates a lot of very nice data for followup by helping to prioritize the genes with fast rates of evolution or profiles that suggest they have been shaped by recent adaptive evolutionary forces and are candidates for the mechanisms of pathogenecity in this devastating plant pathogen.

 

A fourth paper describes the genome sequencing of Sporisorium reilianum, a biotrophic pathogen that is closely related species to corn smut Ustilago maydis (Schirawski et al). Both these species both infect maize hosts but while U. maydis induces tumors in the ears, leaves, tassels of corn the S. reilianum infection is limited to tassels and . The authors used comparative biology and genome sequencing to try and tease out what genetic components may be responsible for the phenotypic differences. The comparison revealed a relative syntentic genome but also found 43 regions in U. maydis that represent highly divergent sequence between the species. These regions contained disproportionate number of secreted proteins indicating that these secreted proteins have been evolving at a much faster rate and that they may be important for the distinct differences in the biology. The chromosome ends of U. maydis were also found to contain up to 20 additional genes in the sub-telomeric regions that were unique to U. maydis. Another fantastic finding that this sequencing and comparison revealed is more about the history of the lack of RNAi genes in U. maydis. It was a striking feature from the 2006 genome sequence that the genome lacked a functioning copy of Dicer. However knocking out this gene in S. reilianum failed to show a developmental or virulence phenotype suggesting it is dispensible for those functions so I think there will be some followups to explore (like do either of these species make small RNAs, do they produce any that are translocated to the host, etc).  The rest of the analyses covered in the manuscript identify the specific loci that are different between the two species — interestingly a lot of the identified loci were the same ones found as islands of secreted proteins in the first genome analysis paper so the comparative approach was another way to get to the genes which may be important for the virulence if the two organisms have different phenotypes. This is certainly the approach that has also been take in other plant pathogens (e.g. Mycosphaerella, Fusarium) and animal pathogens (Candida, Cryptococcus, Coccidioides) but requires a sampling species or appropriate distance that that the number of changes haven’t saturated our ability to reconstruct the history either at the gene order/content or codon level.

Without the comparison of an outgroup species it is impossible to determine if U. maydis gained function that relates to the phenotypes observed here through these speculated evolutionary changes involving new genes and newly evolved functions or if S. reilianum lost functionality that was present in their common ancestor. However, this paper is an example of how using a comparative approach can identify testable hypotheses for origins of pathogenecity genes.

 

Hope everyone has a chance to enjoy holidays and unwrap and spend some time looking at these and other science gems over the coming weeks.

 

Baxter, L., Tripathy, S., Ishaque, N., Boot, N., Cabral, A., Kemen, E., Thines, M., Ah-Fong, A., Anderson, R., Badejoko, W., Bittner-Eddy, P., Boore, J., Chibucos, M., Coates, M., Dehal, P., Delehaunty, K., Dong, S., Downton, P., Dumas, B., Fabro, G., Fronick, C., Fuerstenberg, S., Fulton, L., Gaulin, E., Govers, F., Hughes, L., Humphray, S., Jiang, R., Judelson, H., Kamoun, S., Kyung, K., Meijer, H., Minx, P., Morris, P., Nelson, J., Phuntumart, V., Qutob, D., Rehmany, A., Rougon-Cardoso, A., Ryden, P., Torto-Alalibo, T., Studholme, D., Wang, Y., Win, J., Wood, J., Clifton, S., Rogers, J., Van den Ackerveken, G., Jones, J., McDowell, J., Beynon, J., & Tyler, B. (2010). Signatures of Adaptation to Obligate Biotrophy in the Hyaloperonospora arabidopsidis Genome Science, 330 (6010), 1549-1551 DOI: 10.1126/science.1195203

Spanu, P., Abbott, J., Amselem, J., Burgis, T., Soanes, D., Stuber, K., Loren van Themaat, E., Brown, J., Butcher, S., Gurr, S., Lebrun, M., Ridout, C., Schulze-Lefert, P., Talbot, N., Ahmadinejad, N., Ametz, C., Barton, G., Benjdia, M., Bidzinski, P., Bindschedler, L., Both, M., Brewer, M., Cadle-Davidson, L., Cadle-Davidson, M., Collemare, J., Cramer, R., Frenkel, O., Godfrey, D., Harriman, J., Hoede, C., King, B., Klages, S., Kleemann, J., Knoll, D., Koti, P., Kreplak, J., Lopez-Ruiz, F., Lu, X., Maekawa, T., Mahanil, S., Micali, C., Milgroom, M., Montana, G., Noir, S., O’Connell, R., Oberhaensli, S., Parlange, F., Pedersen, C., Quesneville, H., Reinhardt, R., Rott, M., Sacristan, S., Schmidt, S., Schon, M., Skamnioti, P., Sommer, H., Stephens, A., Takahara, H., Thordal-Christensen, H., Vigouroux, M., Wessling, R., Wicker, T., & Panstruga, R. (2010). Genome Expansion and Gene Loss in Powdery Mildew Fungi Reveal Tradeoffs in Extreme Parasitism Science, 330 (6010), 1543-1546 DOI: 10.1126/science.1194573

Raffaele, S., Farrer, R., Cano, L., Studholme, D., MacLean, D., Thines, M., Jiang, R., Zody, M., Kunjeti, S., Donofrio, N., Meyers, B., Nusbaum, C., & Kamoun, S. (2010). Genome Evolution Following Host Jumps in the Irish Potato Famine Pathogen Lineage Science, 330 (6010), 1540-1543 DOI: 10.1126/science.1193070

Schirawski, J., Mannhaupt, G., Munch, K., Brefort, T., Schipper, K., Doehlemann, G., Di Stasio, M., Rossel, N., Mendoza-Mendoza, A., Pester, D., Muller, O., Winterberg, B., Meyer, E., Ghareeb, H., Wollenberg, T., Munsterkotter, M., Wong, P., Walter, M., Stukenbrock, E., Guldener, U., & Kahmann, R. (2010). Pathogenicity Determinants in Smut Fungi Revealed by Genome Comparison Science, 330 (6010), 1546-1548 DOI: 10.1126/science.1195330

Schizophyllum genome portal live at JGI

In preparation for Asilomar, JGI is releasing lots of the genome sequencing project portals. The Schizophyllum commune Genome Portal is now publicly available. Go get your white-rot gene investigation on! (Though please respect the community rules for 1st rights to publication of the genome-wide analyses).

On the content of (petri plate) Media

ResearchBlogging.orgAn avid reader pointed out that I was not entirely thorough in describing that we don’t enough about the V8 agar media that is used to induce mating in Cryptococcus. In fact a great deal of work on mating in this fungus had focused on identifying what pathways are induced by V8 agar that induce mating.  It was shown that inositol stimulates mating through use of defined media containing inositol (Xue et al, 2007).  This paper interestingly explores plant-fungal interactions and Cryptococcus suggesting that mating may occur preferentially on plants in cases where inositol is abundant.

It is also worth noting that V8 media contains a high level of copper ions and it was also pointed out to me that Jef Edman’s lab showed that melanin mutants have mating defects, and both phenotypes are suppressed by copper. And more recently (Lin et al, PLOS Genetics 2006) found that alleles of the Mac1 copper regulated transcription factor are a QTL influencing hyphal growth and melanin production, and showed that copper can enhance hyphal growth.

So the role of copper and interplay with V8 agar media and how this induces mating is actually quite known.

C XUE, Y TADA, X DONG, J HEITMAN (2007). The Human Fungal Pathogen Cryptococcus Can Complete Its Sexual Cycle during a Pathogenic Association with Plants Cell Host & Microbe, 1 (4), 263-273 DOI: 10.1016/j.chom.2007.05.005

Fungal P450s

A paper (Park et al, BMC Genomics) from Fungal Bioinformatics Lab at Seoul University in South Korea describes their new “Fungal P450 Database”. The database contains sequence, names, and genome links for P450’s (or Cytochrome P450s) identified by similarity and phylogenetic classification from genome annotations.  The group is using most of annotated genomes in GenBank (and I think some from elsewhere) of bacterial, fungi, animals, and plants.

I find the current nomenclature for this family of genes confusing but it has been I am sure a difficult job and wrangled to a large part by David Nelson (who also has a new paper on the CYPome of Aspergillus nidulans). I have found it difficult to follow the logic for naming these members, as it didn’t seem to be particularly phylogenetic at first, although I think that has improved. However, a stable and solid reference database is needed to for naming these gene members and for mapping new members in through straightforward analyses is an essential resource. Park et al have made great inroads to that end and it may indeed meet needs (I am cautious to say it is solved without more exploration or some sense of whether it is intended or will be taken up as just that sort of reference by the P450 community).  It has seemed to me that a proper phylogenetic (or really, a phylogenomic) approach is essential for naming the P450 member genes as orthologous or paralogous members across multiple species. The group has defined their classes as clusters of homologs (e.g. Mg004 is Magnaporthe grisea gene in Cluster 9.1) and linked these also to the Nelson nomeclature (CYP68E1).  By defining orthologous family members we can make more interpretations about how to transfer functional annotation in a truly phylogenomic context. 

The overall family is so large and diverse (they report 4538 fungal P450s into 141 clusters/sub-families from 68 species) across many different species. The fungi tend to have very large families in some clades (e.g. some filamentous fungi) so I think this type of systematic and searchable system that will have stable identities for clusters is an essential resource. I know I’m going to try and give it a whirl. We have a couple of cool findings about changes in the P450 families in Basidiomycete Coprinopsis and related species comparisons that I hope we’ll be able to better interpret with this additional phylogenomic naming of gene family members.

Jongsun Park, Seungmin Lee, Jaeyoung Choi, Kyohun Ahn, Bongsoo Park, Jaejin Park, Seogchan Kang, Yong-Hwan Lee (2008). Fungal cytochrome P450 database BMC Genomics, 9 (1) DOI: 10.1186/1471-2164-9-402

Basidiomycete Research Networks

Mike Challen has summarized discussion at two recent conferences regarding a Basidiomycete Research Network at his blog in a post on BRN – Summary of Discussions, 14/07/08.

In particular it is important to establish a community network that will help basidiomycete labs. There is also a strong need for shared approaches for effective use the genomic data from the more than a dozen basidiomycete genomes currently being sequenced.

Mike’s blog is open for discussion on the topic and I hope you’ll weigh in on suggestions for how the community can better communicate and share ideas.

Basidiomycete genomes galore


Just finished attending Genetics and Cell Biology of Basidiomycetes in Cape Girardeau, MO which was an intimate gathering of basidiomycetaphiles.  I learned about systems that are used for studying fruiting body development, genetic mapping, pheromone and mating genes, kinesin dynamics, meoitic gene regulation, and a host of topics.  I’m happy I got a chance to meet more folks in the community and learned about where informatics and computational approaches are really needed to push along some of the interpretation of the more than a dozen basidiomycete genomes.  In particular it sounds like the PleurotusSchizophyllum, Agaricus bisporus, and Serpula genomes are all marching along to completion with some already in 4X assembly or further.  

GCBBVI Group Picture

So we’ll further have more samples from of key model and some less-model species to assist researchers working on many different mushroom-forming fungi that range from brown and white-rotting saprophyte fungi to mycorrhizal fungi that associate with plants.    I’m excited about the work to make transformation and knockouts more readily in these systems too to push the genetics and cellular biology of these systems even further.  The genome sequences will be another tool in these endeavors.

The last day ended with a discussion about genome annotation and future support for curating gene models.  Basically everyone is unhappy with computational predictions and want to be able to go in and fix things. (I think people remember the ones that are gotten wrong more readily than the ones that were right, but computational prediction definitely performs poorly in some situations).   In this Web 2.0-land we live in, this is still not something easily done with any of the freely available genome browsing tools. The JGI’s browser was lauded for its ability to handle these kinds of requests, but how do we proceed when genomes are not sequenced by that center or when (not too distant future) communities are able to sequence a genome themselves using 454/Illumina-Solexa/Helicos/Pacific Biosystems approaches in their own lab?  There is still a huge lag in what kinds of tools researchers can use to annotate genomes to fix gene models and add functions.  Hopefully projects like GMOD will continue to develop useful tools for solving these needs, but there is certainly a need for better support of distributed community annotation of genomes where this little direct money for supporting curators from a single place.

Fungal Genetics 2007 details

I’m including a recapping as many of the talks as I remember. There were 6 concurrent sessions each afternoon so you have to miss a lot of talks. The conference was bursting at the seams as it was- at least 140 people had to be turned away beyond the 750 who attended.

If there was any theme in the conference it was “Hey we are all using these genome sequences we’ve been talking about getting”. I only found the overview talks that solely describe the genome solely a little dry as compared to those more focused on particular questions. I guess my genome palate is becoming refined.

Continue reading Fungal Genetics 2007 details