Category Archives: genome annotation

Neurospora annotation update (v5)

Here is a message from the Broad Institute about a gene annotation update that was made recently in response to an issue that was revealed in the June 2010 release.  This new version is called V5 and should be on its way to GenBank.

Dear Neurospora scientists,

Recently we discovered an issue with the way locus tags were assigned
to our most recent Neurospora gene set, released publicly on the Broad
website in June of 2010. Many genes in this gene set have mismatched
locus numbers compared to the same genes released in February 2010.
Adding to the confusion, both releases were labeled version 4.

To remedy this we have recalled the June locus numbers and released a
new, version 5 gene set. Genes in this set have been numbered to
preserve historical locus numbers (back to the original genbank
release) as much as possible.

Folks who call their favorite genes by their v1, v2 or v3 numbers can
search for them on our web page, which will map them to v5
automatically and accurately. The same will work for most v4 numbers.
Unfortunately, 863 genes have different locus tags in the two v4
releases. If you search for one of them, you will get two hits - the
v5 gene that the February edition mapped to, and the v5 gene that the
June edition mapped to.

Two examples to clarify:

A. Suppose you search for NCU11713.4 on our web page. This query will
retrieve two genes, NCU11688.5 and NCU11713.5. The gene which in the
February release was called NCU11713.4 is the same as NCU11688.5,
while the gene labeled NCU11713.4 in June is the same as NCU11713.5.

B. Searching for NCU11324.4 yields but one hit because that gene, like
most genes, was consistently numbered between the two releases labeled
4.

If you are not sure when you downloaded your genes, the following may
help. If you see any of these locus numbers in your gene set:

NCU00129.4, NCU00457.4, NCU00499.4, NCU00556.4, NCU00627.4,
NCU00685.4, NCU00768.4, NCU00856.4, NCU00986.4, NCU01064.4,
NCU01065.4, NCU01282.4, NCU01299.4, NCU01300.4, NCU01483.4,
NCU01559.4, NCU01560.4, NCU01610.4, NCU01611.4, NCU01664.4,
NCU01665.4, NCU01871.4, NCU01903.4, NCU02200.4, NCU02259.4,
NCU02666.4, NCU02758.4, NCU02837.4, NCU02998.4, NCU03047.4,
NCU03206.4, NCU03773.4, NCU04239.4, NCU04240.4, NCU04518.4,
NCU04519.4, NCU04710.4, NCU04711.4, NCU05275.4, NCU05512.4,
NCU05776.4, NCU06013.4, NCU06370.4, NCU06732.4, NCU07107.4,
NCU07259.4, NCU07260.4, NCU07301.4, NCU07405.4, NCU07856.4,
NCU07857.4, NCU08090.4, NCU08182.4, NCU08323.4, NCU08332.4,
NCU09085.4, NCU09256.4, NCU09257.4, NCU09998.4, NCU10166.4,
NCU10574.4, NCU11040.4, NCU11240.4, NCU11253.4, NCU11376.4,
NCU11390.4, NCU11393.4

then your genes are from the February 2010 gene set. However, if you see

NCU00082.4, NCU00083.4, NCU00084.4, NCU00085.4, NCU00516.4,
NCU01819.4, NCU04299.4, NCU04300.4, NCU04301.4, NCU04302.4,
NCU04303.4, NCU04304.4, NCU04305.4, NCU05000.4, NCU05111.4,
NCU05112.4, NCU05113.4, NCU05114.4, NCU05115.4, NCU05116.4,
NCU05448.4, NCU05452.4, NCU06667.4, NCU07323.4, NCU09066.4,
NCU10179.4, NCU10301.4, NCU10379.4, NCU10383.4, NCU10753.4,
NCU10866.4, NCU10914.4, NCU11068.4, NCU11182.4, NCU12157.4,
NCU12158.4, NCU12159.4, NCU12160.4, NCU12161.4, NCU12162.4,
NCU12163.4, NCU12164.4, NCU12165.4, NCU12166.4, NCU12167.4,
NCU12168.4, NCU12169.4, NCU12170.4, NCU12171.4, NCU12172.4,
NCU12173.4, NCU12174.4, NCU12175.4, NCU12176.4, NCU12177.4,
NCU12178.4, NCU12179.4, NCU12180.4, NCU12181.4, NCU12182.4,
NCU12183.4, NCU12184.4, NCU12185.4, NCU12186.4, NCU12187.4, NCU12188.4

then your genes are from the June 2010 release.

Attached please find five mapping tables which can be used to migrate
locus numbers from any of the previous releases to the latest version
5 locus tags (linked below).

We apologize for any confusion this may cause.
Love,
The Broad Institute

I’ve also uploaded the locus update files which maps between versions of the annotation.

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

A mushroom on the cover

I’ll indulge a bit here to happily to point to the cover of this week’s PNAS with an image of Coprinopsis cinerea mushrooms fruiting referring to our article on the genome sequence of this important model fungus.  You should also enjoy the commentary article from John Taylor and Chris Ellison that provides a summary of some of the high points in the paper.

Coprinopsis cover

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

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).

Yeast population genomics

ResearchBlogging.org
I have cheered the Sanger-Wellcome SGRP group work to generate multiple Saccharomyces cerevisiae and S. paradoxus strain genome sequences.   The group had previously submitted a version of the manuscript to Nature precedings and it is now published in Nature AOP showing that submitting to a preprint server doesn’t necessarily hurt your manuscript getting published…  The research groups explored the impact of domestication (as was also recently done for the sake and soy sauce worker fungus, Aspergillus oryzae) on the Saccharomyces genome by comparing individuals from wild strains of S. paradoxus.

This paper addressed several challenges including methodology for light genome sequencing for population genomics. This data represents in a way, a pilot project on for genome resequencing projects and using draft genome sequencing with next generation sequencing tools. Of course with the pace of sequencing technology development, any project more than a couple months old will be using outdated technology it seems, but this work represents some important progress.  Tools like MAQ were also developed and tuned as part of the project.  In addition to the methods development it also provided a new look at evolutionary dynamics of a well-studied fungus.

Genome assembly
The authors apply several different quality controls and utilize a new tool called PALAS (Parallel ALignment and ASsembly)  to assemble all the strains at the same time using a graph-based approach that utilized the reference genome sequences for each species. This is different than a full-blown WGA approach like PCAP, Phusion or Arachne because this is deliberately low-coverage sequencing pass.  The authors are trying impute missing sequence via Ancestral Recombination Graphs as implemented in the Margarita system.   They also use MAQ to align sequence from Illumina/Solexa sequencing to these assemblies made by PALAS.

Since this project was on two species of SaccharomycesS. cerevisiae and S. paradoxus they needed good reference assemblies for each of these species. The previously availably S.paradoxus assembly wasn’t complete enough for this study so they did an addition 4.3 X coverage with sanger/ABI sequencing and 80X coverage with Illumina.

Population genomics and domestication

The sequencing data also provided a framework for population genetic investigations. Some simple findings showed that geographic isolates within each species were more genetically similar to each other.  The main geographic regions of samples for S.paradoxus data included the UK, American, and Far East samples, some of which had been analyzed in a very nice study on Chromosome III.  For the S. cerevisiae samples there were individuals from around Europe, at least 10 European wine strains, Malaysian, Sake brewing strains, West Africa, and North America. From these data it was possible to discover that there are several of strains with mosiac genomes meaning that pieces of the genome match best with the sake fermentation strains and other parts from the wine/European samples.

Efforts to detect the effects of natural selection that may be linked to domestication of these strains explored two different approaches. The McDonald-Kreitman test did not identify any loci under positive selection while Tajima’s D was negative in the S.cerevisiae global and wine strain populations indicating an excess of singleton polymorphisms – though they draw little conclusions from that.  The authors also observed a sharper decay of linkage disequilibrium in S.cerevisiae (half maximum of 3kb) than S.paradoxus (half maximum 9kb) suggesting that S.cerevisiae is recombining more, either due to increased opportunities or a great frequency of recombination events when it does.

In context of the paper title and the idea of exploring the effects of domestication on the genome, the authors observe that the standard paradigm that ‘domesticated’ species have lower diversity levels is simply not the case in these samples.  This isn’t to say there isn’t evidence of the selection for fermentation production from these strains based on the stress response conditions they were tested on, but that there is still ample evidence of maintaining diversity within the populations presumably through various amounts of outcrossing.

We are also interested in these results as we apply similar questions to population genomics of the human pathogenic fungus Coccidioides where 14 strains have been sequenced with sanger sequencing technology.  Hopefully some of these lessons will resonate in our analyses and also that this era of population genomics will see ever more extensive collections to address aspects of migration, phylogeography, and local adaptations within populations of fungi and other microbes.

Gianni Liti, David M. Carter, Alan M. Moses, Jonas Warringer, Leopold Parts, Stephen A. James, Robert P. Davey, Ian N. Roberts, Austin Burt, Vassiliki Koufopanou, Isheng J. Tsai, Casey M. Bergman, Douda Bensasson, Michael J. T. O’Kelly, Alexander van Oudenaarden, David B. H. Barton, Elizabeth Bailes, Alex N. Nguyen, Matthew Jones, Michael A. Quail, Ian Goodhead, Sarah Sims, Frances Smith, Anders Blomberg, Richard Durbin, Edward J. Louis (2009). Population genomics of domestic and wild yeasts Nature DOI: 10.1038/nature07743

First release of N.tetrasperma and N.discreta

The JGI in collaboration with our lab at Berkeley have released the Neurospora tetrasperma (mat A) and N. discreta (mat A) genome sequences and annotation after about two years of work.  These are two closely related species to the well studied laboratory workhorse Neurospora crassa.

The N.tetrasperma assembly (8X) has an N50 of 976kb and is highly colinear with the N.crassa genome.  With the JGI, we’ve also done some additional 454 sequencing which will represent an improved assembly and 23X coverage in the next release.  We also did some comparative scaffolding and can basically double that N50 – most of which looks good when compared to the improved V2 assembly.

The N.discreta assembly (8X) is also quite good with an N50 of 2.3 Mb. For comparison, the V7 of N.crassa has an N50 of 664 kb. although with genetic map information the 250+ contigs can be scaffolded into 7 chromosomes with 146 unmapped contigs.

Both N.discreta and N.tetrasperma genomes contain about 10k predicted genes similar to counts in other related species like N.crassa and Podospora anserina.

We’re finalizing several analyses to present at the Asilomar meeting to describe these Neurospora genomes and comparisons with other Sordariomycete species.

Brown rotting fungal genome published

ResearchBlogging.orgPostia placenta genome is now published in early edition of PNAS.   Brown rotting fungi are import part of the cellulose degrading ecology of the forest as well (hopefully) providing some enzymes that will help in the ligin to biofuels process. Brown rotters break down cellulose but cannot break down lignin or lignocellulose while white rotters (like the previously sequenced Phanerochaete chrysosporium) are able to break down the lignin.  This fungus was chosen for sequencing as it is another potentially helpful fungus in the war on sugars (turning them into fuels) including recently published Trichoderma reesei and 1st basidiomycete genome Phanerochaete (all incidentally with the Diego Martinez as first author – go Diego!). It is also helpful to contrast the white and brown rotters to understand how their enzyme capabilities have changed and how these different lifestyles evolved.  There had been some issues with the initial assembly of this genome which is basically twice as big as one would expect because the dikaryon genome was sequenced – this is where two nuclei with different genomes are present as the result of fusion between two parents of opposite mating types.  When genome sequenced is performed it is hard to assemble these into a single assembly since there are really two haplotypes present.  So these haplotypes have to be sorted out to obtain the gene ‘count’ for the organism for those who like simple numbers. This is a similar situation to the Candida albicans genome, although those haplotypes are much more similar.  The main problem is that one has to generate twice as much sequence to get the same coverage of each haplotype without playing some tricks to collapse them into a consensus and them afterwards separate the haplotypes back out.  At any rate, this sequenced provided a good summary of the gene content and thus metabolic and enzymatic capabilities to match up functional data collected from LC/MS and transcriptional profiling. 

There are several other rotting fungi that are nearly done at JGI (but the task of writing and coordinating the analyses for the papers are ongoing!) include Schizophyllum commune and Pleurotus ostreatus. There are also several more mycorrhizal and plant pathogenic basidiomycete fungi as well as some classic model systems that have finished genomes and are in the process of finalizing papers.  It is an exciting time that is just beginning as these genome and transcriptional data are integrated and compared for their different ecological, morphological, and metabolic capabilities.

The article is unfortunately not Open Access so I haven’t even read it from home yet, but pass along this news to you, dear reader. Will get a chance to read through more than the abstract to see what glistening gems have been extracted from this genomic endeavor.
D. Martinez, J. Challacombe, I. Morgenstern, D. Hibbett, M. Schmoll, C. P. Kubicek, P. Ferreira, F. J. Ruiz-Duenas, A. T. Martinez, P. Kersten, K. E. Hammel, A. V. Wymelenberg, J. Gaskell, E. Lindquist, G. Sabat, S. S. BonDurant, L. F. Larrondo, P. Canessa, R. Vicuna, J. Yadav, H. Doddapaneni, V. Subramanian, A. G. Pisabarro, J. L. Lavin, J. A. Oguiza, E. Master, B. Henrissat, P. M. Coutinho, P. Harris, J. K. Magnuson, S. E. Baker, K. Bruno, W. Kenealy, P. J. Hoegger, U. Kues, P. Ramaiya, S. Lucas, A. Salamov, H. Shapiro, H. Tu, C. L. Chee, M. Misra, G. Xie, S. Teter, D. Yaver, T. James, M. Mokrejs, M. Pospisek, I. V. Grigoriev, T. Brettin, D. Rokhsar, R. Berka, D. Cullen (2009). Genome, transcriptome, and secretome analysis of wood decay fungus Postia placenta supports unique mechanisms of lignocellulose conversion Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0809575106

A few tool updates

I’m working to make more data available in the genome browsers for fungi. One is adding in the Primer information from the Neurospora KO project to the Neurospora browser to indicate the position and primer sequences for all the gene knockouts being (or already) constructed.  At least 60% of the genes have been knocked out and are available from the FGSC.

We’re also integrating SNP data using the HapMap glyphs in which you can see one way to view this information in the Genome Browser for Coccidioides.  Working on other information including PhastCons conservation profiles and other information in our development server and hope to make this public soon.

Coprinopsis cinereus genome annotation updated

Coprinus cinereus genome projectThe Broad Institute in collaboration with many of the Coprinopsis cinereus (Coprinus cinerea) community of researchers have updated the genome annotation for C. cinereus with additional gene calls based on ESTs and improved gene callers. The annotation was made on the 13 chromosome assembly produced by work by SEMO fungal biology group and collaborators across the globe including a BAC map from H. Muraguchi.  Thanks to Jonathan Goldberg and colleagues at the Broad Institute for getting this updated annotation out the door.

 

This updated annotation is able to join and split several sets of genes and the gene count sits at just under 14k genes in this 36Mb genome. There are a couple of hiccups in the GTF and Genome contig/supercontig file naming that I am told will be fixed by early next week.  Additional work to annotate the “Kinome” by the Broad team provides some promising new insight to this genome annotation as well.

We’re using this updated genome assembly address questions about evolution of genome structure by studying syntenic conservation and aspects of crossing over points during meiosis.  The C. cinereus system has long been used as model for fungal development and morphogensis of mushrooms as it is straightforward to induce mushroom fruiting in the laboratory.  It also a model for studying meiosis due to the synchronized meiosis occurring in the cells in the cap of the mushroom.

Happy genome shrooming.