The DOE Joint Genome Institute has sequenced over 50 eukaryotic genomes, ranging in size from 15 MB to 1.6 GB, over a wide range of organism types. In the course of doing so, it has become clear that a substantial fraction of these data sets contains bonus organisms, usually prokaryotes, in addition to the desired genome. While some of these additional organisms are extraneous contamination, they are sometimes symbionts, and so can be of biological interest.Therefore, it is desirable to assemble the bonus organisms along with the main genome. This transforms the problem into one of metagenomic assembly, which is considerably more challenging than traditional whole-genome shotgun (WGS) assembly. The different organisms will usually be present at different sequence depths, which is difficult to handle in most WGS assemblers. In addition, with multiple distinct genomes present, chimerism can produce cross-organism combinations. Finally, there is no guarantee that only a single bonus organism will be present. For example, one JGI project contained at least two different prokaryotic contaminants, plus a 145 KB plasmid of unknown origin.We have developed techniques to routinely identify and handle such bonus organisms in a high-throughput sequencing environment. Approaches include screening and partitioning the unassembled data, and iterative subassemblies. These methods are applicable not only to bonus organisms, but also to desired components such as organelles. These procedures have the additional benefit of identifying, and allowing for the removal of, cloning artifacts such as E.coli and spurious vector inclusions.

High-throughput Sanger sequencing requires DNA to be inserted into bacterial vectors for biological amplification. Adapter or linker oligonucleotides may also be attached to target DNA fragments to facilitate insertion into the vector. These vector and adapter sequences are sequenced concomitantly with the target, or insert, sequence and represent contamination which must be removed from the dataset prior to analysis. Removal of such contamination can be accomplished by screening the dataset against the known sequence of the vector and adapter used to generate the data. However, often in the case of public or collaborator datasets, information regarding these contaminant sequences may be incorrect or absent, resulting in an incomplete screening.We've created a piece of software, VecFinder, which is able to identify the sequence of the vector and adapter from the read sequences alone and subsequently remove it. This alleviates the dependence on the library creators to provide the vector and adapter sequences used for the library. It also automates the previously manual task of identifying and screening the adapter or linker sequence, which can be tedious and time-consuming

It is a challenging job for genome analysts to accurately debug, troubleshoot, and validate genome assembly results. Genome analysts rely on visualization tools to help validate and troubleshoot assembly results, including such problems as mis-assemblies, low-quality regions, and repeats. Short read data adds further complexity and makes it extremely challenging for the visualization tools to scale and to view all needed assembly information. As a result, there is a need for a visualization tool that can scale to display assembly data from the new sequencing technologies. We present Genome Assembly Visualization Tool (GAViT), a highly scalable and interactive assembly visualization tool developed at the DOE Joint Genome Institute (JGI).

Paired-end library sequencing has been proven useful in scaffold construction during de novo assembly of genomic sequences. The ability of generating mate pairs with 8 Kb or greater insert sizes is especially important for genomes containing long repeats. While the current 454 GS LT Paired-end library preparation protocol can successfully construct libraries with 3 Kb insert size, it fails to generate longer insert sizes because the protocol is optimized to purify shorter fragments. We have made several changes in the protocol in order to increase the fragment length. These changes include the use of Promega column to increase the yield of large size DNA fragments, two gel purification steps to remove contaminated short fragments, and a large reaction volume in the circularization step to decrease the formation of chimeras. We have also made additional changes in the protocol to increase the overall quality of the libraries. The quality of the libraries are measured by a set of metrics, which include levels of redundant reads, linker positive, linker negative, half linker reads, and driver DNA contamination, and read length distribution, were used to measure the primary quality of these libraries. We have also assessed the quality of the resulted mate pairs including levels of chimera, distribution of insert sizes, and genome coverage after the assemblies are completed. Our data indicated that all these changes have improved the quality of the longer insert size libraries.

We have constructed and sequenced several 454 paired end LT libraries with 3 Kb insert size to assess the quality and effectiveness of the technology in the whole genome assembly. A set of quality metrics, which include levels of redundant reads, linker positive, linker negative, half linker reads, and driver DNA contamination, and read length distribution, were used to measure the primary quality of these libraries. We have also assessed the quality of the resulted mate pairs including levels of chimera, distribution of insert sizes, and genome coverages after the assemblies are completed. In general, the technology is performing as expected with 3 Kb fragments. We have made several modifications in the procedure to improve the quality of the libraries, especially in the areas of reducing redundant reads and eliminating pUC driver DNA contamination. We have also compared two assembly tools for their performance in the assembly of mixed Sanger and 454 shotgun or paired-end data. We will report the quality of these libraries and the comparison of the assemblies with shotgun and paired-end reads. The current GS paired end LT library construction protocol would not work for fragment sizes larger than 3 Kb. The major obstacles are the low recovery of large DNA fragments after multiple purification steps and the lack of an efficient way to circularize large DNA fragments. We are in the process of modifying some steps to overcome these obstacles. We will present results of the improvements.

We report the draft genome sequence of the model moss Physcomitrella patens and compare its features with those of flowering plants, from which it is separated by more than 400 million years, and unicellular aquatic algae. This comparison reveals genomic changes concomitant with the evolutionary movement to land, including a general increase in gene family complexity; loss of genes associated with aquatic environments (e.g., flagellar arms); acquisition of genes for tolerating terrestrial stresses (e.g., variation in temperature and water availability); and the development of the auxin and abscisic acid signaling pathways for coordinating multicellular growth and dehydration response. The Physcomitrella genome provides a resource for phylogenetic inferences about gene function and for experimental analysis of plant processes through this plant's unique facility for reverse genetics.

The plant-pathogenic fungus Mycosphaerella graminicola (asexual stage: Septoria tritici) causes septoria tritici blotch, a disease that greatly reduces the yield and quality of wheat. This disease is economically important in most wheat-growing areas worldwide and threatens global food production. Control of the disease has been hampered by a limited understanding of the genetic and biochemical bases of pathogenicity, including mechanisms of infection and of resistance in the host. Unlike most other plant pathogens, M. graminicola has a long latent period during which it evades host defenses. Although this type of stealth pathogenicity occurs commonly in Mycosphaerella and other Dothideomycetes, the largest class of plant-pathogenic fungi, its genetic basis is not known. To address this problem, the genome of M. graminicola was sequenced completely. The finished genome contains 21 chromosomes, eight of which could be lost with no visible effect on the fungus and thus are dispensable. This eight-chromosome dispensome is dynamic in field and progeny isolates, is different from the core genome in gene and repeat content, and appears to have originated by ancient horizontal transfer from an unknown donor. Synteny plots of the M. graminicola chromosomes versus those of the only other sequenced Dothideomycete, Stagonospora nodorum, revealed conservation of gene content but not order or orientation, suggesting a high rate of intra-chromosomal rearrangement in one or both species. This observed "mesosynteny" is very different from synteny seen between other organisms. A surprising feature of the M. graminicola genome compared to other sequenced plant pathogens was that it contained very few genes for enzymes that break down plant cell walls, which was more similar to endophytes than to pathogens. The stealth pathogenesis of M. graminicola probably involves degradation of proteins rather than carbohydrates to evade host defenses during the biotrophic stage of infection and may have evolved from endophytic ancestors.