Dataset Information

SVM²: an improved paired-end-based tool for the detection of small genomic structural variations using high-throughput single-genome resequencing data.

ABSTRACT: Several bioinformatics methods have been proposed for the detection and characterization of genomic structural variation (SV) from ultra high-throughput genome resequencing data. Recent surveys show that comprehensive detection of SV events of different types between an individual resequenced genome and a reference sequence is best achieved through the combination of methods based on different principles (split mapping, reassembly, read depth, insert size, etc.). The improvement of individual predictors is thus an important objective. In this study, we propose a new method that combines deviations from expected library insert sizes and additional information from local patterns of read mapping and uses supervised learning to predict the position and nature of structural variants. We show that our approach provides greatly increased sensitivity with respect to other tools based on paired end read mapping at no cost in specificity, and it makes reliable predictions of very short insertions and deletions in repetitive and low-complexity genomic contexts that can confound tools based on split mapping of reads.

SUBMITTER: Chiara M

PROVIDER: S-EPMC3467043 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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SVM²: an improved paired-end-based tool for the detection of small genomic structural variations using high-throughput single-genome resequencing data.

Chiara Matteo M Pesole Graziano G Horner David S DS

Nucleic acids research 20120625 18

Several bioinformatics methods have been proposed for the detection and characterization of genomic structural variation (SV) from ultra high-throughput genome resequencing data. Recent surveys show that comprehensive detection of SV events of different types between an individual resequenced genome and a reference sequence is best achieved through the combination of methods based on different principles (split mapping, reassembly, read depth, insert size, etc.). The improvement of individual pr ...[more]

PMID: 22735696

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Project description:Since the read lengths of high throughput sequencing (HTS) technologies are short, de novo assembly which plays significant roles in many applications remains a great challenge. Most of the state-of-the-art approaches base on de Bruijn graph strategy and overlap-layout strategy. However, these approaches which depend on k-mers or read overlaps do not fully utilize information of paired-end and single-end reads when resolving branches. Since they treat all single-end reads with overlapped length larger than a fix threshold equally, they fail to use the more confident long overlapped reads for assembling and mix up with the relative short overlapped reads. Moreover, these approaches have not been special designed for handling tandem repeats (repeats occur adjacently in the genome) and they usually break down the contigs near the tandem repeats. We present PERGA (Paired-End Reads Guided Assembler), a novel sequence-reads-guided de novo assembly approach, which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds using paired-end reads and different read overlap size ranging from Omax to Omin to resolve the gaps and branches. By constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. When the correct extension cannot be determined, PERGA will try to extend the contig by all feasible extensions and determine the correct extension by using look-ahead approach. Many difficult-resolved branches are due to tandem repeats which are close in the genome. PERGA detects such different copies of the repeats to resolve the branches to make the extension much longer and more accurate. We evaluated PERGA on both Illumina real and simulated datasets ranging from small bacterial genomes to large human chromosome, and it constructed longer and more accurate contigs and scaffolds than other state-of-the-art assemblers. PERGA can be freely downloaded at https://github.com/hitbio/PERGA.

Project description:BackgroundLarge insert paired-end sequencing technologies are important tools for assembling genomes, delineating associated breakpoints and detecting structural rearrangements. To facilitate the comprehensive detection of inter- and intra-chromosomal structural rearrangements or variants (SVs) and complex genome assembly with long repeats and segmental duplications, we developed a new method based on single-molecule real-time synthesis sequencing technology for generating long paired-end sequences of large insert DNA libraries.ResultsA Fosmid vector, pHZAUFOS3, was developed with the following new features: (1) two 18-bp non-palindromic I-SceI sites flank the cloning site, and another two sites are present in the skeleton of the vector, allowing long DNA inserts (and the long paired-ends in this paper) to be recovered as single fragments and the vector (~?8 kb) to be fragmented into 2-3 kb fragments by I-SceI digestion and therefore was effectively removed from the long paired-ends (5-10 kb); (2) the chloramphenicol (Cm) resistance gene and replicon (oriV), necessary for colony growth, are located near the two sides of the cloning site, helping to increase the proportion of the paired-end fragments to single-end fragments in the paired-end libraries. Paired-end libraries were constructed by ligating the size-selected, mechanically sheared pooled Fosmid DNA fragments to the Ampicillin (Amp) resistance gene fragment and screening the colonies with Cm and Amp. We tested this method on yeast and Setaria italica Yugu1. Fosmid-size paired-ends with an average length longer than 2 kb for each end were generated. The N50 scaffold lengths of the de novo assemblies of the yeast and S. italica Yugu1 genomes were significantly improved. Five large and five small structural rearrangements or assembly errors spanning tens of bp to tens of kb were identified in S. italica Yugu1 including deletions, inversions, duplications and translocations.ConclusionsWe developed a new method for long paired-end sequencing of large insert libraries, which can efficiently improve the quality of de novo genome assembly and identify large and small structural rearrangements or assembly errors.

Dataset Information

SVM²: an improved paired-end-based tool for the detection of small genomic structural variations using high-throughput single-genome resequencing data.

Publications

SVM²: an improved paired-end-based tool for the detection of small genomic structural variations using high-throughput single-genome resequencing data.

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