Shotgun sequencing and finishing of an isolate of the Spirochaeta aurantia M1 genome, a free-living nonpathogenic Spirochete, is in process at the Joint Genome Institute. S. aurantia M1 is being sequenced due to its proximity on the phylogenetic tree to bacteria present in the termite hindgut that were partially sequenced during a metagenomic project at the JGI ,and, for improving the understanding of pathogenic Spirocheates through comparative genomic studies. The assembly is currently in 3 contigs and most of the finishing has been done using fosmid templates to close gaps. The shotgun assembly is a combination of fosmid sequencing, a novel Sanger approach, 454 sequencing, and Solexa data. The novel Sanger approach takes advantage of a bulk cloneless library preparation method involving the amplification of long DNA fragments onto beads, by emulsion PCR, and the subsequent sorting of individual beads by flow cytometry for seeding the Sanger chemistry process.

BACKGROUND: The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step. RESULTS: Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools. CONCLUSIONS: BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

Background

The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step.

Results

Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools.

Conclusions

BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

As the vast majority of microorganisms have yet to be cultivated in a laboratory setting, access to their genetic makeup has largely been limited to cultivation-independent methods. These methods, namely metagenomics and more recently single-cell genomics, have become cornerstones for microbial ecology and environmental microbiology. One ultimate goal is the recovery of genome sequences from each cell within an environment to move toward a better understanding of community metabolic potential and to provide substrate for experimental work. As single-cell sequencing has the ability to decipher all sequence information contained in an individual cell, this method holds great promise in tackling such challenge. Methodological limitations and inherent biases however do exist, which will be discussed here based on environmental and benchmark data, to assess how far we are from reaching this goal.

With the onset of new technology JGI has shifted its scope of work for microbes to 454 standard titanium, 454 paired end titanium, and illumina data for gap closer and quality improvement (polishing). Raw reads are assembled by Newbler to create a draft assembly that will be passed to finishers. An in-house developed software tool creates subprojects for each gap. In-silico attempts are made to close gaps using existing unassembled pyrosequence and Illumina data. Any remaining gaps are tackled by PCR based methods. These include standard PCR, bubble PCR, multiplex PCR, combinatorial PCR, and long range PCR. Once products are generated they can be sequenced, cloned or shattered as needed. Currently gap closing data is still generated using sanger. Eventually these gaps may be pooled and sequenced using illumina or 454. Once a genome is closed, illumina data is used to polish the genome. Any areas that are still substandard are subjects for resequencing. We extend this approach to fungal genomes