Dataset Information

StLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads.

ABSTRACT: Co-barcoded reads originating from long DNA fragments (mean length >30 kbp) maintain both single base level accuracy and long-range genomic information. We propose a pipeline, stLFRsv, to detect structural variation using co-barcoded reads. stLFRsv identifies abnormal large gaps between co-barcoded reads to detect potential breakpoints and reconstruct complex structural variants (SVs). Haplotype phasing by co-barcoded reads increases the signal to noise ratio, and barcode sharing profiles are used to filter out false positives. We integrate the short read SV caller smoove for smaller variants with stLFRsv. The integrated pipeline was evaluated on the well-characterized genome HG002/NA24385, and 74.5% precision and a 22.4% recall rate were obtained for deletions. stLFRsv revealed some large variants not included in the benchmark set that were verified by long reads or assembly. For the HG001/NA12878 genome, stLFRsv also achieved the best performance for both resource usage and the detection of large variants. Our work indicates that co-barcoded read technology has the potential to improve genome completeness.

SUBMITTER: Guo J

PROVIDER: S-EPMC8012683 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

stLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads.

Guo Junfu J Shi Chang C Chen Xi X Wang Ou O Liu Ping P Yang Huanming H Xu Xun X Zhang Wenwei W Zhu Hongmei H

Frontiers in genetics 20210318

Co-barcoded reads originating from long DNA fragments (mean length >30 kbp) maintain both single base level accuracy and long-range genomic information. We propose a pipeline, stLFRsv, to detect structural variation using co-barcoded reads. stLFRsv identifies abnormal large gaps between co-barcoded reads to detect potential breakpoints and reconstruct complex structural variants (SVs). Haplotype phasing by co-barcoded reads increases the signal to noise ratio, and barcode sharing profiles are us ...[more]

PMID: 33815469

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Project description:BackgroundMany genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. It is important to fully understand the order and orientation of rearranged fragments, with precise breakpoints, to know the pathogenicity of the rearrangements.MethodsWe performed whole-genome-coverage nanopore sequencing of long DNA reads from four patients with chromosomal translocations. We identified rearrangements relative to a reference human genome, subtracted rearrangements shared by any of 33 control individuals, and determined the order and orientation of rearranged fragments, with our newly developed analysis pipeline.ResultsWe describe the full characterization of complex chromosomal rearrangements, by filtering out genomic rearrangements seen in controls without the same disease, reducing the number of loci per patient from a few thousand to a few dozen. Breakpoint detection was very accurate; we usually see ~ 0 ± 1 base difference from Sanger sequencing-confirmed breakpoints. For one patient with two reciprocal chromosomal translocations, we find that the translocation points have complex rearrangements of multiple DNA fragments involving 5 chromosomes, which we could order and orient by an automatic algorithm, thereby fully reconstructing the rearrangement. A rearrangement is more than the sum of its parts: some properties, such as sequence loss, can be inferred only after reconstructing the whole rearrangement. In this patient, the rearrangements were evidently caused by shattering of the chromosomes into multiple fragments, which rejoined in a different order and orientation with loss of some fragments.ConclusionsWe developed an effective analytic pipeline to find chromosomal aberration in congenital diseases by filtering benign changes, only from long read sequencing. Our algorithm for reconstruction of complex rearrangements is useful to interpret rearrangements with many breakpoints, e.g., chromothripsis. Our approach promises to fully characterize many congenital germline rearrangements, provided they do not involve poorly understood loci such as centromeric repeats.

Project description:BackgroundWith the continuing decrease in cost of whole genome sequencing (WGS), we have already approached the point of inflection where WGS testing has become economically feasible, facilitating broader access to the benefits that are helping to define WGS as the new diagnostic standard. WGS provides unique opportunities for detection of structural variants; however, such analyses, despite being recognized by the research community, have not previously made their way into routine clinical practice.ResultsWe have developed a clinically validated pipeline for highly specific and sensitive detection of structural variants basing on 30X PCR-free WGS. Using a combination of breakpoint analysis of split and discordant reads, and read depth analysis, the pipeline identifies structural variants down to single base pair resolution. False positives are minimized using calculations for loss of heterozygosity and bi-modal heterozygous variant allele frequencies to enhance heterozygous deletion and duplication detection respectively. Compound and potential compound combinations of structural variants and small sequence changes are automatically detected. To facilitate clinical interpretation, identified variants are annotated with phenotype information derived from HGMD Professional and population allele frequencies derived from public and Variantyx allele frequency databases. Single base pair resolution enables easy visual inspection of potentially causal variants using the IGV genome browser as well as easy biochemical validation via PCR. Analytical and clinical sensitivity and specificity of the pipeline has been validated using analysis of Genome in a Bottle reference genomes and known positive samples confirmed by orthogonal sequencing technologies.ConclusionConsistent read depth of PCR-free WGS enables reliable detection of structural variants of any size. Annotation both on gene and variant level allows clinicians to match reported patient phenotype with detected variants and confidently report causative finding in all clinical cases used for validation.

Dataset Information

StLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads.

Publications

stLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads.

Similar Datasets

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