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BMC Genomics. 2017 Jan 10;18(1):65. doi: 10.1186/s12864-016-3444-1.

Discovery of large genomic inversions using long range information.

Author information

1
Department of Computer Engineering, Bilkent University, Bilkent, 06800, Ankara, Turkey.
2
Department of Biology, University of Bari, Via Orabona 4, 70125, Bari, Italy.
3
Benaroya Research Institute, 1201 Ninth Avenue, 98101, Seattle, WA, USA.
4
Department of Genome Sciences and Howard Hughes Medical Institute, University of Washington, 3720 15th Avenue NE, 98195, Seattle, WA, USA.
5
Department of Biology, University of Bari, Via Orabona 4, 70125, Bari, Italy. francesca.antonacci@uniba.it.
6
Department of Computer Engineering, Bilkent University, Bilkent, 06800, Ankara, Turkey. calkan@cs.bilkent.edu.tr.

Abstract

BACKGROUND:

Although many algorithms are now available that aim to characterize different classes of structural variation, discovery of balanced rearrangements such as inversions remains an open problem. This is mainly due to the fact that breakpoints of such events typically lie within segmental duplications or common repeats, which reduces the mappability of short reads. The algorithms developed within the 1000 Genomes Project to identify inversions are limited to relatively short inversions, and there are currently no available algorithms to discover large inversions using high throughput sequencing technologies.

RESULTS:

Here we propose a novel algorithm, VALOR, to discover large inversions using new sequencing methods that provide long range information such as 10X Genomics linked-read sequencing, pooled clone sequencing, or other similar technologies that we commonly refer to as long range sequencing. We demonstrate the utility of VALOR using both pooled clone sequencing and 10X Genomics linked-read sequencing generated from the genome of an individual from the HapMap project (NA12878). We also provide a comprehensive comparison of VALOR against several state-of-the-art structural variation discovery algorithms that use whole genome shotgun sequencing data.

CONCLUSIONS:

In this paper, we show that VALOR is able to accurately discover all previously identified and experimentally validated large inversions in the same genome with a low false discovery rate. Using VALOR, we also predicted a novel inversion, which we validated using fluorescent in situ hybridization. VALOR is available at https://github.com/BilkentCompGen/VALOR.

KEYWORDS:

Inversion; Linked-reads; Long range sequencing; Read clouds; Structural variation

PMID:
28073353
PMCID:
PMC5223412
DOI:
10.1186/s12864-016-3444-1
[Indexed for MEDLINE]
Free PMC Article

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