Critical length in long read resequencing

AbstractLong read sequencing has a substantial advantage for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used simulated long reads and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 15 kbp. Haplotyping genes entirely only reaches its optimum from reads of 100 kbp. These findings are important for the design of future long read sequencing projects.

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Critical length in long-read resequencing

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqz027 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 1

Author(s):

Wouter De Coster ◽

Mojca Strazisar ◽

Peter De Rijk

Keyword(s):

Best Practice ◽

Critical Length ◽

Read Length ◽

Structural Variants ◽

Short Read ◽

Structural Variant ◽

Variant Discovery ◽

Human Genomes ◽

Long Reads ◽

Long Read

Abstract Long-read sequencing has substantial advantages for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used long reads simulated from human genomes and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 20 kb. Haplotyping variants across genes only reaches its optimum from reads of 100 kb. These findings are important for the design of future long-read sequencing projects.

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NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data

10.1101/092544 ◽

2016 ◽

Author(s):

Li Fang ◽

Jiang Hu ◽

Depeng Wang ◽

Kai Wang

Keyword(s):

Whole Genome ◽

Ashkenazi Jewish ◽

Structural Variants ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Human Genomes ◽

Long Read ◽

Personal Genomes ◽

Low Coverage

AbstractBackgroundStructural variants (SVs) in human genomes are implicated in a variety of human diseases. Long-read sequencing delivers much longer read lengths than short-read sequencing and may greatly improve SV detection. However, due to the relatively high cost of long-read sequencing, it is unclear what coverage is needed and how to optimally use the aligners and SV callers.ResultsIn this study, we developed NextSV, a meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purposes. We evaluated SV calling performance of NextSV under different PacBio coverages on two personal genomes, NA12878 and HX1. Our results showed that, compared with running any single SV caller, NextSV stringent call set had higher precision and balanced accuracy (F1 score) while NextSV sensitive call set had a higher recall. At 10X coverage, the recall of NextSV sensitive call set was 93.5% to 94.1% for deletions and 87.9% to 93.2% for insertions, indicating that ~10X coverage might be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. We further evaluated the Mendelian errors on an Ashkenazi Jewish trio dataset.ConclusionsOur results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.

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SVIM: Structural Variant Identification using Mapped Long Reads

10.1101/494096 ◽

2018 ◽

Cited By ~ 2

Author(s):

David Heller ◽

Martin Vingron

Keyword(s):

Single Molecule ◽

Simulated Data ◽

Structural Variants ◽

Human Phenotype ◽

Structural Variant ◽

Small Indels ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Long Read

AbstractMotivationStructural variants are defined as genomic variants larger than 50bp. They have been shown to affect more bases in any given genome than SNPs or small indels. Additionally, they have great impact on human phenotype and diversity and have been linked to numerous diseases. Due to their size and association with repeats, they are difficult to detect by shotgun sequencing, especially when based on short reads. Long read, single molecule sequencing technologies like those offered by Pacific Biosciences or Oxford Nanopore Technologies produce reads with a length of several thousand base pairs. Despite the higher error rate and sequencing cost, long read sequencing offers many advantages for the detection of structural variants. Yet, available software tools still do not fully exploit the possibilities.ResultsWe present SVIM, a tool for the sensitive detection and precise characterization of structural variants from long read data. SVIM consists of three components for the collection, clustering and combination of structural variant signatures from read alignments. It discriminates five different variant classes including similar types, such as tandem and interspersed duplications and novel element insertions. SVIM is unique in its capability of extracting both the genomic origin and destination of duplications. It compares favorably with existing tools in evaluations on simulated data and real datasets from PacBio and Nanopore sequencing machines.Availability and implementationThe source code and executables of SVIM are available on Github: github.com/eldariont/svim. SVIM has been implemented in Python 3 and published on bioconda and the Python Package [email protected]

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Structural variants in the Chinese population and their impact on phenotypes, diseases and population adaptation

Nature Communications ◽

10.1038/s41467-021-26856-x ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Zhikun Wu ◽

Zehang Jiang ◽

Tong Li ◽

Chuanbo Xie ◽

Liansheng Zhao ◽

...

Keyword(s):

Chinese Population ◽

Complete Characterization ◽

Loss Of Function ◽

Structural Variants ◽

Structural Variant ◽

Chinese Populations ◽

Variant Discovery ◽

Southern Chinese ◽

Long Read ◽

Clinical Measurements

AbstractA complete characterization of genetic variation is a fundamental goal of human genome research. Long-read sequencing has improved the sensitivity of structural variant discovery. Here, we conduct the long-read sequencing-based structural variant analysis for 405 unrelated Chinese individuals, with 68 phenotypic and clinical measurements. We discover a landscape of 132,312 nonredundant structural variants, of which 45.2% are novel. The identified structural variants are of high-quality, with an estimated false discovery rate of 3.2%. The concatenated length of all the structural variants is approximately 13.2% of the human reference genome. We annotate 1,929 loss-of-function structural variants affecting the coding sequence of 1,681 genes. We discover rare deletions in HBA1/HBA2/HBB associated with anemia. Furthermore, we identify structural variants related to immunity which differentiate the northern and southern Chinese populations. Our study describes the landscape of structural variants in the Chinese population and their contribution to phenotypes and disease.

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Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads

BMC Genomics ◽

10.1186/s12864-021-07702-2 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Seth Commichaux ◽

Kiran Javkar ◽

Padmini Ramachandran ◽

Niranjan Nagarajan ◽

Denis Bertrand ◽

...

Keyword(s):

Public Health ◽

Public Health Response ◽

High Quality ◽

Short Read ◽

Short Reads ◽

The Core ◽

Long Reads ◽

Health Response ◽

Long Read ◽

Core Genes

Abstract Background Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. Results We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. Conclusion The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

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Long read sequencing reveals sequential complex rearrangements driven by Hepatitis B virus integration

10.1101/2021.12.09.471697 ◽

2021 ◽

Author(s):

Songbo Wang ◽

Jiadong Lin ◽

Xiaofei Yang ◽

Zihang Li ◽

Tun Xu ◽

...

Keyword(s):

Hepatitis B ◽

Clinical Samples ◽

Metabolic Dysfunction ◽

Cellular Functions ◽

Human Genomes ◽

Long Reads ◽

B Virus ◽

Long Read ◽

Genetic Structures ◽

Virus Integration

Integration of Hepatitis B (HBV) virus into human genome disrupts genetic structures and cellular functions. Here, we conducted multiplatform long read sequencing on two cell lines and five clinical samples of HBV-induced hepatocellular carcinomas (HCC). We resolved two types of complex viral integration induced genome rearrangements and established a Time-phased Integration and Rearrangement Model (TIRM) to depict their formation progress by differentiating inserted HBV copies with HiFi long reads. We showed that the two complex types were initialized from focal replacements and the fragile virus-human junctions triggered subsequent rearrangements. We further revealed that these rearrangements promoted a prevalent loss-of-heterozygosity at chr4q, accounting for 19.5% of HCC samples in ICGC cohort and contributing to immune and metabolic dysfunction. Overall, our long read based analysis reveals a novel sequential rearrangement progress driven by HBV integration, hinting the structural and functional implications on human genomes.

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Genotyping structural variants in pangenome graphs using the vg toolkit

10.1101/654566 ◽

2019 ◽

Cited By ~ 7

Author(s):

Glenn Hickey ◽

David Heller ◽

Jean Monlong ◽

Jonas A. Sibbesen ◽

Jouni Sirén ◽

...

Keyword(s):

De Novo ◽

State Of The Art ◽

Effective Means ◽

Point Mutations ◽

Structural Variants ◽

Short Read ◽

Yeast Strains ◽

Sequencing Studies ◽

Long Read

AbstractStructural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmarked vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

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Towards a better understanding of the low recall of insertion variants with short-read based variant callers

10.1101/2020.06.09.142232 ◽

2020 ◽

Author(s):

Wesley Delage ◽

Julien Thevenon ◽

Claire Lemaitre

Keyword(s):

Gold Standard ◽

Insertion Site ◽

Structural Variants ◽

Genomic Context ◽

Breakpoint Junction ◽

Short Read ◽

Depth Analysis ◽

Long Read ◽

The Impact

AbstractSince 2009, numerous tools have been developed to detect structural variants (SVs) using short read technologies. Insertions >50 bp are one of the hardest type to discover and are drastically underrepresented in gold standard variant callsets. The advent of long read technologies has completely changed the situation. In 2019, two independent cross technologies studies have published the most complete variant callsets with sequence resolved insertions in human individuals. Among the reported insertions, only 17 to 37% could be discovered with short-read based tools. In this work, we performed an in-depth analysis of these unprecedented insertion callsets in order to investigate the causes of such failures. We have first established a precise classification of insertion variants according to four layers of characterization: the nature and size of the inserted sequence, the genomic context of the insertion site and the breakpoint junction complexity. Because these levels are intertwined, we then used simulations to characterize the impact of each complexity factor on the recall of several SV callers. Simulations showed that the most impacting factor was the insertion type rather than the genomic context, with various difficulties being handled differently among the tested SV callers, and they highlighted the lack of sequence resolution for most insertion calls. Our results explain the low recall by pointing out several difficulty factors among the observed insertion features and provide avenues for improving SV caller algorithms and their [email protected]

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Fast and sensitive mapping of error-prone nanopore sequencing reads with GraphMap

10.1101/020719 ◽

2015 ◽

Cited By ~ 1

Author(s):

Ivan Sovic ◽

Mile Sikic ◽

Andreas Wilm ◽

Shannon Nicole Fenlon ◽

Swaine Chen ◽

...

Keyword(s):

Human Genome ◽

Variant Calling ◽

Error Rates ◽

Nanopore Sequencing ◽

Structural Variants ◽

Specific Identification ◽

Long Reads ◽

Long Read ◽

Specific Error ◽

Very High

Exploiting the power of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. We present the first nanopore read mapper (GraphMap) that uses a read-funneling paradigm to robustly handle variable error rates and fast graph traversal to align long reads with speed and very high precision (>95%). Evaluation on MinION sequencing datasets against short and long-read mappers indicates that GraphMap increases mapping sensitivity by at least 15-80%. GraphMap alignments are the first to demonstrate consensus calling with <1 error in 100,000 bases, variant calling on the human genome with 76% improvement in sensitivity over the next best mapper (BWA-MEM), precise detection of structural variants from 100bp to 4kbp in length and species and strain-specific identification of pathogens using MinION reads. GraphMap is available open source under the MIT license at https://github.com/isovic/graphmap.

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Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

10.1101/2020.05.31.126490 ◽

2020 ◽

Author(s):

Andrew J. Page ◽

Nabil-Fareed Alikhan ◽

Michael Strinden ◽

Thanh Le Viet ◽

Timofey Skvortsov

Keyword(s):

Mycobacterium Tuberculosis ◽

State Of The Art ◽

Sequence Data ◽

Human Pathogen ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Long Reads ◽

Long Read

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.

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