What's New
Recent publications:
Wilkerson, M.D., Ru, Y., and Brendel, V.P. (2009)
Common introns within orthologous genes: software and application to plants
Briefings in Bioinformatics, 10(6), 631-644.
[abstract]
[PDF]
PlantGDB News:
Community-annotated maize gene models (see an example at ZmGDB) are now displayed at both MaizeGDB and maizesequence.org, by means of Distributed Annotation Service (DAS) (November 21, 2009).
Brachypodium distachyon browser:
BdGDB, a genome browser for the model grass species Brachypodium distachyon, is now available, based on the JGI v1.0 8x genome assembly. The assembly displayed comprises 271.15 Mb arranged in 5 pseudochromosomes. Display includes gene models, splice-aligned EST, cDNA, PUT assembly and Arabidopsis and rice predicted proteins (October 30, 2009).
Group Meetings
Meeting Information:
Brendel Group meetings this term will be held every Friday afternoon at 2:00 PM in Room 2034 Molecular Biology. The first half hour will be devoted to literature/resource review. You may select papers yourself or pick from the list below. In either case, please post your selection several days before the meeting to give other group members adequate time to read the papers. In your discussion, please briefly review the background, goals, and achievements of the paper, then suggest applications to your or our group's work as well as extensions or improvements. It is not expected that you necessarily understand all aspects of the paper you present. If thoughtful questions arise, pose them, and the group will be challenged to help.
The second half hour of the group meeting will be devoted to research presentations. Use these times to practice giving short talks, get others excited about what you are doing, and outline what you have accomplished and where you are headed in your research.
Meeting Topics (reverse chronological order)
December 12, 2008
Literature Review:
by Michael Sparks
Genome Research 18, 1979-1990
Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training
Vardges Ter-Hovhannisyan, Alexandre Lomsadze, Yury O. Chernoff, and Mark Borodovsky
Abstract:
We describe a new ab initio algorithm, GeneMark-ES version 2, that identifies protein-coding genes in fungal genomes. The algorithm does not require a predetermined training set to estimate parameters of the underlying hidden Markov model (HMM). Instead, the anonymous genomic sequence in question is used as an input for iterative unsupervised training. The algorithm extends our previously developed method tested on genomes of Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. To better reflect features of fungal gene organization, we enhanced the intron submodel to accommodate sequences with and without branch point sites. This design enables the algorithm to work equally well for species with the kinds of variations in splicing mechanisms seen in the fungal phyla Ascomycota, Basidiomycota, and Zygomycota. Upon self-training, the intron submodel switches on in several steps to reach its full complexity. We demonstrate that the algorithm accuracy, both at the exon and the whole gene level, is favorably compared to the accuracy of gene finders that employ supervised training. Application of the new method to known fungal genomes indicates substantial improvement over existing annotations. By eliminating the effort necessary to build comprehensive training sets, the new algorithm can streamline and accelerate the process of annotation in a large number of fungal genome sequencing projects.
