- Open Access
SVachra: a tool to identify genomic structural variation in mate pair sequencing data containing inward and outward facing reads
© The Author(s). 2017
Published: 3 October 2017
Characterization of genomic structural variation (SV) is essential to expanding the research and clinical applications of genome sequencing. Reliance upon short DNA fragment paired end sequencing has yielded a wealth of single nucleotide variants and internal sequencing read insertions-deletions, at the cost of limited SV detection. Multi-kilobase DNA fragment mate pair sequencing has supplemented the void in SV detection, but introduced new analytic challenges requiring SV detection tools specifically designed for mate pair sequencing data. Here, we introduce SVachra – Structural Variation Assessment of CHRomosomal Aberrations, a breakpoint calling program that identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations utilizing both inward and outward facing read types generated by mate pair sequencing.
We demonstrate SVachra’s utility by executing the program on large-insert (Illumina Nextera) mate pair sequencing data from the personal genome of a single subject (HS1011). An additional data set of long-read (Pacific BioSciences RSII) was also generated to validate SV calls from SVachra and other comparison SV calling programs. SVachra exhibited the highest validation rate and reported the widest distribution of SV types and size ranges when compared to other SV callers.
SVachra is a highly specific breakpoint calling program that exhibits a more unbiased SV detection methodology than other callers.
The identification of genomic SV is an integral part of understanding human genetic diversity, gene and genome variation, evolution, and disease etiology. Numerous genetic diseases, most notably cancer, have been associated with genomic SV of somatic cells  whilst germline genomic rearrangements cause a wide range of genomic disorders by diverse structural variation mutagenesis mechanisms [2, 3]. Historically, clone-based methods, such as end sequence profiling of Bacterial Artificial Chromosome and fosmid clones [4, 5] have provided paired-end sequencing of DNA fragments containing aberrant junctions, necessary to identify genomic structural rearrangements. Unfortunately, these clone-based methods proved too laborious, time consuming, and costly for routine chromosome aberration analyses. Alternatively, the adoption of massively parallel sequencing delivering hundreds of millions of short fragment paired-end reads has accelerated the study of genomics. While the quantity of reads produced by massively parallel sequencing is impressive, the standard paired-end sequencing libraries have sacrificed fragment sizes compared to clone-based methods, thereby limiting the detection of large complex genomic SV . To alleviate the shortcomings of small fragment paired-end libraries, multi-kilobase mate pair and Nextera Tagmentation sequencing libraries have been introduced. For these long-range mate pair libraries, fragments (usually on the order of 3-10Kb) are isolated, end labeled with biotin and circularized. The circularized molecules are sheared and the library is enriched for biotin labeled junction fragments. Sequencing of these biotinylated fragments generates ‘outward-facing’ paired reads, meaning they align to the reference sequence in an outward facing direction from each other and at a distance in line with the selected long-range fragment size. The main restriction of such sequencing libraries is the contamination of inward facing reads, unbiotinylated fragments which map in an opposite orientation and smaller fragment size (usually between 200 and 300 bp) that confound the calling of chromosomal rearrangements by introducing contradictory discordant read information.
To improve the utility of multi-kilobase mate pair and Nextera Tagmentation sequencing libraries for genomic SV detection, we introduce a new freely accessible program called SVachra (Structural Variation Assessment of CHRomosomal Aberrations) that uses discordant mate pair reads consisting of both inward and outward facing read types. The SVachra program calculates the distributions of the inward and outward facing mate pair types and applies independent clustering of the inward and outward facing discordant mapped reads to call chromosomal structural variants. Both inward and outward facing reads contribute to SV calling, thereby improving the accuracy of the breakpoint location. SVachra identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations. Compared to other SV prediction tools that utilize mate pair mapping data; such as BreakDancer , SVDetect , and others (see review ), the utility and novelty of SVachra consists in its ability to (i) automatically segregate outward and inward facing reads based on K-Means clustering of fragment size distributions without a priori sequencing library information, (ii) independently cluster and merge discordant outward and inward facing reads to more accurately predict breakpoint locations, (iii) screen out user-defined segments of the reference for breakpoint consideration, such as centromeric and telomeric regions responsible for high false positive rates and heavy computation, and (iv) create various output file formats for visual assessment of SV and downstream processes, such as breakpoint spanning primer design.
SVachra provides numerous outputs for subsequent SV analysis; including: binned fragment lengths for plotting the mate pair insert distributions, lists of annotated SV calls in both .svp and .lff formats (see Additional file 1: S2 for output format definitions), .bed file of SV calls for intersection analysis, and Circos  input files for SV visualization. Two Circos input files are provided: a Circos link input file contains the SVachra chromosomal aberrations for the inter-chromosomal (purple) and intra-chromosomal (green) translocations, and a Circos tile input file contains the deletions (red), insertions (blue), and inversions (orange).
Results and discussion
SVachra was evaluated on a 6.2Kb average insert Nextera Tagmentation mate pair library (yielding over 90 million reads and 3X genomic sequence coverage) of the HS1011 human genome that contains a causative single nucleotide variant for an autosomal recessive Charcot-Marie-Tooth neuropathy [2, 11, 12]. The binned fragment lengths for the HS1011 Nextera mate pair sequencing library is shown in Fig. 1b and highlights the two separate insert size distributions, the inward facing reads with an average fragment length of ~450 bp and outward facing reads with an average fragment length of ~6.2Kb. The K-Means clustering calculated the upper and lower bound fragment size thresholds for the inward read set between 1 bp and 900 bp, and outward read set between 4.2Kb and 8Kb. SVachra_v1.0 was executed using an exclusionary screen out .bed file containing chromosomal centromere and telomere regions (responsible for numerous false positive), a minimum mapping quality threshold of “1”, the unique read mapped flag “-u”, and the clustering quality control heuristic option “-s” that filters overlapping alternate allele breakpoint calls that have lower contributing read counts. For the HS1011 Nextera mate pair data set, SVachra was run using a single node requiring 38Gb of memory and 28 h. SVachra reported a total of 5890 chromosomal aberrations in the HS1011 genome with the following breakpoint annotation type distributions: 57.7% insertions (ranging in size from 10 bp to 1.2 Mb), 17.3% deletions (ranging in size from 10 bp to 1.2 Mb), 4.5% inversions (ranging in size from 14 bp to 6 Mb), 8.2% intra-chromosomal (ranging in size from 64 bp to 223 Mb) and 2.3% inter-chromosomal translocation. The SVachra chromosomal aberrations reported for HS1011 are visualized in Fig. 1c Circos image showing tiled insertions (blue), deletions (red) and inversions (orange), and linked intra-chromosomal (green) and inter-chromosomal (purple) translocations.
The SVachra structural variant discovery tool, which is specific for next-generation mate pair sequencing data, identifies chromosomal aberrations with high specificity across a wide range of variant types and lengths when compared to alternative mate pair sequencing breakpoint calling algorithms. SVachra is designed for whole genome long insert circularized sequencing libraries and scales quadratically on the subset of inconsistently mapped mate pairs based on expected fragment size and orientation. While no built-in parallelization has been implemented, improved time efficiency could be achieved by distributing SV cluster computation across multiple cores, binning inconsistently mapped mate pairs on each possible chromosome pairing relationship. SVachra is unique in its ability to first characterize and then incorporate both inward and outward facing read distributions in mate pair sequencing libraries; providing highly specific breakpoint calling that exhibits a more unbiased detection methodology than alternate mate pair sequencing SV callers.
Publication of this article was supported in part by grants from the National Human Genome Research Institute (NHGRI) (U54HG003273) to RAG.
Availability of data and materials
Project name: SVachra
Project home page: https://github.com/oliverhampton/SVachra
Operating system(s): Platform independent
Programming language: Ruby
Other requirements: SAMTOOLS-0.1.18 or higher, ruby libraries getoptlong, fileutils, rubygems, and mathn
License: MIT License
Any restrictions to use by non-academics: none
The datasets analyzed in this study are available at NCBI under bioproject PRJNA203659 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA203659).
About this supplement
This article has been published as part of BMC Genomics Volume 18 Supplement 6, 2017: Selected articles from the International Conference on Intelligent Biology and Medicine (ICIBM) 2016: genomics. The full contents of the supplement are available online at https://bmcgenomics.biomedcentral.com/articles/supplements/volume-18-supplement-6).
OAH developed, implemented and refined the algorithm. OAH and ACE performed bioinformatics and statistical analysis for alternate algorithm comparisons and orthogonal long-read sequencing validation. MW, YH, and DMM performed and managed sequencing. YL performed primary analysis mapping and adapter trimming on the Nextera sequencing data. OAH wrote the manuscript. WJS, DAW, KCW, JRL, and RAG provided support and management of the project. All authors read and approved the final manuscript.
Ethics approval and consent to participate
The Institutional Review Board for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals (BCM IRB) approved the H-22599 – INDIVIDUAL GENOME SEQUENCING research protocol and consent form. The BCM IRB is organized, operates, and is registered with the United States Office for Human Research Protections according to the regulations codified in the United States Code of Federal Regulations at 45 CFR 46 and 21 CFR 56. The BCM IRB operates under the BCM Federal Wide Assurance No. 00000286, as well as those of hospitals and institutions affiliated with the College. HS1011 was consented for H-22599 protocol participation on July 2, 2009.
Consent for publication
HS1011 is a coauthor of this publication, and as a coauthor has read and approved the final manuscript.
There are no conflicts of interest to declare.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Stephens PJ, McBride DJ, Lin M-L, Varela I, Pleasance ED, Simpson JT, et al. Complex landscapes of somatic rearrangement in human breast cancer genomes. Nature. 2009;462:1005–10.View ArticlePubMedPubMed CentralGoogle Scholar
- Lupski JR, Gonzaga-Jauregui C, Yang Y, Bainbridge MN, Jhangiani S, Buhay CJ, et al. Exome sequencing resolves apparent incidental findings and reveals further complexity of SH3TC2 variant alleles causing Charcot-Marie-tooth neuropathy. Genome Med. 2013;5:57.View ArticlePubMedPubMed CentralGoogle Scholar
- Carvalho CMB, Lupski JR. Mechanisms underlying structural variant formation in genomic disorders. Nat Rev Genet. 2016;17:224–38.View ArticlePubMedPubMed CentralGoogle Scholar
- Hampton OA, Den Hollander P, Miller CA, Delgado DA, Li J, Coarfa C, et al. A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome. Genome Res. 2009;19:167–77.View ArticlePubMedPubMed CentralGoogle Scholar
- Volik S, Zhao S, Chin K, Brebner JH, Herndon DR, Tao Q, et al. End-sequence profiling: sequence-based analysis of aberrant genomes. Proc Natl Acad Sci U S A. 2003;100:7696–701.View ArticlePubMedPubMed CentralGoogle Scholar
- Hillmer AM, Yao F, Inaki K, Lee WH, Ariyaratne PN, Teo ASM, et al. Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes. Genome Res. 2011;21:665–75.View ArticlePubMedPubMed CentralGoogle Scholar
- Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS, et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009;6:677–81.View ArticlePubMedPubMed CentralGoogle Scholar
- Zeitouni B, Boeva V, Janoueix-Lerosey I, Loeillet S, Legoix-né P, Nicolas A, et al. SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data. Bioinforma Oxf Engl. 2010;26:1895–6.View ArticleGoogle Scholar
- Medvedev P, Stanciu M, Brudno M. Computational methods for discovering structural variation with next-generation sequencing. Nat Methods. 2009;6:S13–20.View ArticlePubMedGoogle Scholar
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45.View ArticlePubMedPubMed CentralGoogle Scholar
- Lupski JR, Reid JG, Gonzaga-Jauregui C, Rio Deiros D, Chen DCY, Nazareth L, et al. Whole-genome sequencing in a patient with Charcot-Marie-tooth neuropathy. N Engl J Med. 2010;362:1181–91.View ArticlePubMedPubMed CentralGoogle Scholar
- English AC, Salerno WJ, Hampton OA, Gonzaga-Jauregui C, Ambreth S, Ritter DI, et al. Assessing structural variation in a personal genome-towards a human reference diploid genome. BMC Genomics. 2015;16:286.View ArticlePubMedPubMed CentralGoogle Scholar
- English AC, Salerno WJ, Reid JG. PBHoney: identifying genomic variants via long-read discordance and interrupted mapping. BMC Bioinformatics. 2014;15:180.View ArticlePubMedPubMed CentralGoogle Scholar