Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

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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REscan: inferring repeat expansions and structural variation in paired-end short read sequencing data

Bioinformatics ◽

10.1093/bioinformatics/btaa753 ◽

2020 ◽

Author(s):

Russell Lewis McLaughlin

Keyword(s):

Structural Variation ◽

Sequence Data ◽

Neurological Diseases ◽

Repeat Expansion ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Repeat Expansions ◽

Paired End Sequencing

Abstract Motivation Repeat expansions are an important class of genetic variation in neurological diseases. However, the identification of novel repeat expansions using conventional sequencing methods is a challenge due to their typical lengths relative to short sequence reads and difficulty in producing accurate and unique alignments for repetitive sequence. However, this latter property can be harnessed in paired-end sequencing data to infer the possible locations of repeat expansions and other structural variation. Results This article presents REscan, a command-line utility that infers repeat expansion loci from paired-end short read sequencing data by reporting the proportion of reads orientated towards a locus that do not have an adequately mapped mate. A high REscan statistic relative to a population of data suggests a repeat expansion locus for experimental follow-up. This approach is validated using genome sequence data for 259 cases of amyotrophic lateral sclerosis, of which 24 are positive for a large repeat expansion in C9orf72, showing that REscan statistics readily discriminate repeat expansion carriers from non-carriers. Availabilityand implementation C source code at https://github.com/rlmcl/rescan (GNU General Public Licence v3).

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Highly accurate long-read HiFi sequencing data for five complex genomes

Scientific Data ◽

10.1038/s41597-020-00743-4 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Ting Hon ◽

Kristin Mars ◽

Greg Young ◽

Yu-Chih Tsai ◽

Joseph W. Karalius ◽

...

Keyword(s):

Sequence Data ◽

Genome Structure ◽

Data Sets ◽

Sequencing Data ◽

Complex Samples ◽

Bioinformatic Tools ◽

Long Reads ◽

Sequencing Method ◽

Sample Data ◽

Long Read

AbstractThe PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25 kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria × ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.

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Complete Genome Sequence of Rubrobacter xylanophilus Strain AA3-22, Isolated from Arima Onsen in Japan

Microbiology Resource Announcements ◽

10.1128/mra.00818-19 ◽

2019 ◽

Vol 8 (34) ◽

Cited By ~ 1

Author(s):

Natsuki Tomariguchi ◽

Kentaro Miyazaki

Keyword(s):

Genome Sequence ◽

Complete Genome Sequence ◽

Complete Genome ◽

Hot Spring ◽

Sequencing Data ◽

Short Read ◽

Content Type ◽

Short Read Sequencing ◽

Oxford Nanopore ◽

Long Read

Rubrobacter xylanophilus strain AA3-22, belonging to the phylum Actinobacteria, was isolated from nonvolcanic Arima Onsen (hot spring) in Japan. Here, we report the complete genome sequence of this organism, which was obtained by combining Oxford Nanopore long-read and Illumina short-read sequencing data.

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Fast and accurate HLA typing from short-read next-generation sequence data with xHLA

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1707945114 ◽

2017 ◽

Vol 114 (30) ◽

pp. 8059-8064 ◽

Cited By ~ 54

Author(s):

Chao Xie ◽

Zhen Xuan Yeo ◽

Marie Wong ◽

Jason Piper ◽

Tao Long ◽

...

Keyword(s):

Sequence Data ◽

Sequence Similarity ◽

Amino Acid Level ◽

Hla Typing ◽

Sequencing Data ◽

Desktop Computer ◽

Short Read ◽

Short Read Sequencing ◽

Hla Genes ◽

Human Chromosome 6

The HLA gene complex on human chromosome 6 is one of the most polymorphic regions in the human genome and contributes in large part to the diversity of the immune system. Accurate typing of HLA genes with short-read sequencing data has historically been difficult due to the sequence similarity between the polymorphic alleles. Here, we introduce an algorithm, xHLA, that iteratively refines the mapping results at the amino acid level to achieve 99–100% four-digit typing accuracy for both class I and II HLA genes, taking only∼3 min to process a 30× whole-genome BAM file on a desktop computer.

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LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data

10.1101/409789 ◽

2018 ◽

Cited By ~ 2

Author(s):

Li Fang ◽

Charlly Kao ◽

Michael V Gonzalez ◽

Fernanda A Mafra ◽

Renata Pellegrino da Silva ◽

...

Keyword(s):

Exome Sequencing ◽

Read Depth ◽

Structural Variants ◽

Sequencing Data ◽

High Coverage ◽

Short Read ◽

Short Read Sequencing ◽

Sequencing Studies ◽

Long Read ◽

Local Assembly

AbstractLinked-read sequencing provides long-range information on short-read sequencing data by barcoding reads originating from the same DNA molecule, and can improve the detection and breakpoint identification for structural variants (SVs). We present LinkedSV for SV detection on linked-read sequencing data. LinkedSV considers barcode overlapping and enriched fragment endpoints as signals to detect large SVs, while it leverages read depth, paired-end signals and local assembly to detect small SVs. Benchmarking studies demonstrates that LinkedSV outperforms existing tools, especially on exome data and on somatic SVs with low variant allele frequencies. We demonstrate clinical cases where LinkedSV identifies disease causal SVs from linked-read exome sequencing data missed by conventional exome sequencing, and show examples where LinkedSV identifies SVs missed by high-coverage long-read sequencing. In summary, LinkedSV can detect SVs missed by conventional short-read and long-read sequencing approaches, and may resolve negative cases from clinical genome/exome sequencing studies.

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Systematic analysis of dark and camouflaged genes: disease-relevant genes hiding in plain sight

10.1101/514497 ◽

2019 ◽

Cited By ~ 1

Author(s):

Mark T. W. Ebbert ◽

Tanner D. Jensen ◽

Karen Jansen-West ◽

Jonathon P. Sens ◽

Joseph S. Reddy ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sequencing Data ◽

Systematic Analysis ◽

Protein Coding ◽

Short Read ◽

Sequencing Project ◽

Short Read Sequencing ◽

Sequencing Technologies ◽

Long Read

AbstractBackgroundThe human genome contains ‘dark’ gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions that are ‘dark by depth’ (few mappable reads) and others that are ‘camouflaged’ (ambiguous alignment), and we assess how well long-read technologies resolve these regions. We further present an algorithm to resolve most camouflaged regions (including in short-read data) and apply it to the Alzheimer’s Disease Sequencing Project (ADSP; 13142 samples), as a proof of principle.ResultsBased on standard whole-genome lllumina sequencing data, we identified 37873 dark regions in 5857 gene bodies (3635 protein-coding) from pathways important to human health, development, and reproduction. Of the 5857 gene bodies, 494 (8.4%) were 100% dark (142 protein-coding) and 2046 (34.9%) were ≥5% dark (628 protein-coding). Exactly 2757 dark regions were in protein-coding exons (CDS) across 744 genes. Long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduced dark CDS regions to approximately 45.1%, 33.3%, and 18.2% respectively. Applying our algorithm to the ADSP, we rescued 4622 exonic variants from 501 camouflaged genes, including a rare, ten-nucleotide frameshift deletion in CR1, a top Alzheimer’s disease gene, found in only five ADSP cases and zero controls.ConclusionsWhile we could not formally assess the CR1 frameshift mutation in Alzheimer’s disease (insufficient sample-size), we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.

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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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An Improved Genome Assembly of Azadirachta indica A. Juss.

10.1101/033290 ◽

2015 ◽

Author(s):

Neeraja M Krishnan ◽

Prachi Jain ◽

Saurabh Gupta ◽

Arun K Hariharan ◽

Binay Panda

Keyword(s):

Azadirachta Indica ◽

Genome Assembly ◽

Draft Genome ◽

Fold Increase ◽

Sequencing Data ◽

Short Read ◽

Short Reads ◽

Short Read Sequencing ◽

Long Reads ◽

Ncbi Short Read Archive

Neem (Azadirachta indica A. Juss.), an evergreen tree of the Meliaceae family, is known for its medicinal, cosmetic, pesticidal and insecticidal properties. We had previously sequenced and published the draft genome of the plant, using mainly short read sequencing data. In this report, we present an improved genome assembly generated using additional short reads from Illumina and long reads from Pacific Biosciences SMRT sequencer. We assembled short reads and error corrected long reads using Platanus, an assembler designed to perform well for heterozygous genomes. The updated genome assembly (v2.0) yielded 3- and 3.5-fold increase in N50 and N75, respectively; 2.6-fold decrease in the total number of scaffolds; 1.25-fold increase in the number of valid transcriptome alignments; 13.4-fold less mis-assembly and 1.85-fold increase in the percentage repeat, over the earlier assembly (v1.0). The current assembly also maps better to the genes known to be involved in the terpenoid biosynthesis pathway. Together, the data represents an improved assembly of the A. indica genome. The raw data described in this manuscript are submitted to the NCBI Short Read Archive under the accession numbers SRX1074131, SRX1074132, SRX1074133, and SRX1074134 (SRP013453).

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Using Short Read Sequencing to Characterise Balanced Reciprocal Translocations in Pigs

10.21203/rs.3.rs-28830/v1 ◽

2020 ◽

Author(s):

Aniek Cornelia Bouwman ◽

Martijn F.L. Derks ◽

Marleen L.W.J. Broekhuijse ◽

Barbara Harlizius ◽

Roel F. Veerkamp

Keyword(s):

Sequence Data ◽

Variant Calling ◽

Reciprocal Translocations ◽

Short Read ◽

Short Read Sequencing ◽

Long Read ◽

Short Read Sequence ◽

Staining Techniques ◽

Chromosome Staining ◽

Paired End Sequencing

Abstract Background A balanced constitutional reciprocal translocation (RT) is a mutual exchange of terminal segments of two non-homologous chromosomes without any loss or gain of DNA in germline cells. Carriers of balanced RTs are viable individuals with no apparent phenotypical consequences. These animals produce, however, unbalanced gametes and show therefore reduced fertility and offspring with congenital abnormalities. This cytogenetic abnormality is usually detected using chromosome staining techniques. The aim of this study was to test the possibilities of using paired end short read sequencing for detection of balanced RTs in boars and investigate their breakpoints and junctions.Results Balanced RTs were recovered in a blinded analysis, using structural variant calling software DELLY, in 6 of the 7 carriers with 30 fold short read paired end sequencing. In 15 non-carriers we did not detect any RTs. Reducing the coverage to 20 fold, 15 fold and 10 fold showed that at least 20 fold coverage is required to obtain good results. One RT was not detected using the blind screening, however, a highly likely RT was discovered after unblinding. This RT was located in a repetitive region, showing the limitations of short read sequence data. The detailed analysis of the breakpoints and junctions suggested three junctions showing microhomology, three junctions with blunt-end ligation, and three micro-insertions at the breakpoint junctions. The RTs detected also showed to disrupt genes.Conclusions We conclude that paired end short read sequence data can be used to detect and characterize balanced reciprocal translocations, if sequencing depth is at least 20 fold coverage. However, translocations in repetitive areas may require large fragments or even long read sequence data.

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SVJedi: Genotyping structural variations with long reads

10.1101/849208 ◽

2019 ◽

Author(s):

Lolita Lecompte ◽

Pierre Peterlongo ◽

Dominique Lavenier ◽

Claire Lemaitre

Keyword(s):

Sequencing Data ◽

Structural Variations ◽

Short Read ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Clinical Diagnoses ◽

Long Read ◽

Reference Sequences ◽

The One

AbstractMotivationStudies on structural variants (SV) are expanding rapidly. As a result, and thanks to third generation sequencing technologies, the number of discovered SVs is increasing, especially in the human genome. At the same time, for several applications such as clinical diagnoses, it is important to genotype newly sequenced individuals on well defined and characterized SVs. Whereas several SV genotypers have been developed for short read data, there is a lack of such dedicated tool to assess whether known SVs are present or not in a new long read sequenced sample, such as the one produced by Pacific Biosciences or Oxford Nanopore Technologies.ResultsWe present a novel method to genotype known SVs from long read sequencing data. The method is based on the generation of a set of reference sequences that represent the two alleles of each structural variant. Long reads are aligned to these reference sequences. Alignments are then analyzed and filtered out to keep only informative ones, to quantify and estimate the presence of each SV allele and the allele frequencies. We provide an implementation of the method, SVJedi, to genotype insertions and deletions with long reads. The tool has been applied to both simulated and real human datasets and achieves high genotyping accuracy. We also demonstrate that SV genotyping is considerably improved with SVJedi compared to other approaches, namely SV discovery and short read SV genotyping approaches.Availabilityhttps://github.com/llecompte/[email protected]

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