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Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

ABSTRACT: Sequencing data analysis remains limiting and problematic, especially for low complexity repeat sequences and transposon elements due to inherent sequencing errors and short sequence read lengths. We have developed a program, ReviSeq, which uses a hybrid method composed of iterative remapping and local assembly upon a bacterial sequence backbone. Application of this method to six Brucella suis field isolates compared to the newly revised B. suis 1330 reference genome identified on average 13, 15, 19 and 9 more variants per sample than STAMPY/SAMtools, BWA/SAMtools, iCORN and BWA/PINDEL pipelines, and excluded on average 4, 2, 3 and 19 variants per sample, respectively. In total, using this iterative approach, we identified on average 87 variants including SNVs, short INDELs and long INDELs per strain when compared to the reference. Our program outperforms other methods especially for long INDEL calling. The program is available at http://reviseq.sourceforge.net.

SUBMITTER: Tae H

PROVIDER: S-EPMC3483379 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

Tae Hongseok H Settlage Robert E RE Shallom Shamira S Bavarva Jasmin H JH Preston Dale D Hawkins Gregory N GN Adams L Garry LG Garner Harold R HR

Genomics 20120810 5

Sequencing data analysis remains limiting and problematic, especially for low complexity repeat sequences and transposon elements due to inherent sequencing errors and short sequence read lengths. We have developed a program, ReviSeq, which uses a hybrid method composed of iterative remapping and local assembly upon a bacterial sequence backbone. Application of this method to six Brucella suis field isolates compared to the newly revised B. suis 1330 reference genome identified on average 13, 15 ...[more]

PMID: 22967795

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Project description:BackgroundGenome-centric approaches are widely used to investigate microbial compositions, dynamics, ecology, and interactions within various environmental systems. Hundreds or even thousands of genomes could be retrieved in a single study contributed by the cost-effective short-read sequencing and developed assembly/binning pipelines. However, conventional binning methods usually yield highly fragmented draft genomes that limit our ability to comprehensively understand these microbial communities. Thus, to leverage advantage of both the long and short reads to retrieve more complete genomes from environmental samples is a must-do task to move this direction forward.ResultsHere, we used an iterative hybrid assembly (IHA) approach to reconstruct 49 metagenome-assembled genomes (MAGs), including 27 high-quality (HQ) and high-contiguity (HC) genomes with contig number ≤ 5, eight of which were circular finished genomes from a partial-nitritation anammox (PNA) reactor. These 49 recovered MAGs (43 MAGs encoding full-length rRNA, average N50 of 2.2 Mbp), represented the majority (92.3%) of the bacterial community. Moreover, the workflow retrieved HQ and HC MAGs even with an extremely low coverage (relative abundance < 0.1%). Among them, 34 MAGs could not be assigned to the genus level, indicating the novelty of the genomes retrieved using the IHA method proposed in this study. Comparative analysis of HQ MAG pairs reconstructed using two methods, i.e., hybrid and short reads only, revealed that identical genes in the MAG pairs represented 87.5% and 95.5% of the total gene inventory of hybrid and short reads only assembled MAGs, respectively. In addition, the first finished anammox genome of the genus Ca. Brocadia reconstructed revealed that there were two identical hydrazine synthase (hzs) genes, providing the exact gene copy number of this crucial phylomarker of anammox at the genome level.ConclusionsOur results showcased the high-quality and high-contiguity genome retrieval performance and demonstrated the feasibility of complete genome reconstruction using the IHA workflow from the enrichment system. These (near-) complete genomes provided a high resolution of the microbial community, which might help to understand the bacterial repertoire of anammox-associated systems. Combined with other validation experiments, the workflow can enable a detailed view of the anammox or other similar enrichment systems. Video Abstract.

Project description:Archival tumor samples represent a rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and individual-specific germline variants. Archival sections often contain adjacent normal tissue, but this tissue can include infiltrating tumor cells. As existing comparative somatic variant callers are designed to exclude variants present in the normal sample, a novel approach is required to leverage adjacent normal tissue with infiltrating tumor cells for somatic variant calling. Here we present lumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient, built upon our previous single sample tumor only variant caller lumosVar 1.0. The approach assumes that the allelic fraction of somatic variants and germline variants follow different patterns as tumor content and copy number state change. lumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses a to model to determine expected allelic fractions for somatic and germline variants and to classify variants accordingly. To evaluate the utility of lumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high and low tumor content and germline whole exome sequencing data (for true somatic variants) available for each patient. Both sensitivity and positive predictive value were improved when analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using lumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent tissue as presumed normal reference. Together, these results demonstrate the utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional sample is not available.

Dataset Information

Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

Publications

Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

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