A benchmarking of human mitochondrial DNA haplogroup classifiers from whole-genome and whole-exome sequence data

AbstractThe mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short-read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

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Evaluation of a high-throughput, cost-effective Illumina library preparation kit

Scientific Reports ◽

10.1038/s41598-021-94911-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Eric S. Tvedte ◽

Jane Michalski ◽

Shaoji Cheng ◽

Rayanna S. Patkus ◽

Luke J. Tallon ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

De Novo ◽

Sequence Data ◽

Poor Performance ◽

Degraded Dna ◽

Library Preparation ◽

Sequencing Data ◽

Taxonomic Assignment ◽

Illumina Library

AbstractLibrary preparation for high-throughput sequencing applications is a critical step in producing representative, unbiased sequencing data. The iGenomX Riptide High Throughput Rapid Library Prep Kit purports to provide high-quality sequencing data with lower costs compared to other Illumina library kits. To test these claims, we compared sequence data quality of Riptide libraries to libraries constructed with KAPA Hyper and NEBNext Ultra. Across several single-source genome samples, mapping performance and de novo assembly of Riptide libraries were similar to conventional libraries prepared with the same DNA. Poor performance of some libraries resulted in low sequencing depth. In particular, degraded DNA samples may be challenging to sequence with Riptide. There was little cross-well plate contamination with the overwhelming majority of reads belong to the proper source genomes. The sequencing of metagenome samples using different Riptide primer sets resulted in variable taxonomic assignment of reads. Increased adoption of the Riptide kit will decrease library preparation costs. However, this method might not be suitable for degraded DNA.

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PlasmidSeeker: identification of known plasmids from bacterial whole genome sequencing reads

PeerJ ◽

10.7717/peerj.4588 ◽

2018 ◽

Vol 6 ◽

pp. e4588 ◽

Cited By ~ 26

Author(s):

Märt Roosaare ◽

Mikk Puustusmaa ◽

Märt Möls ◽

Mihkel Vaher ◽

Maido Remm

Keyword(s):

Antibiotic Resistance ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

De Novo ◽

Sequence Data ◽

Source Code ◽

Complex Problem ◽

Whole Genome ◽

Short Read ◽

Plasmid Sequence

BackgroundPlasmids play an important role in the dissemination of antibiotic resistance, making their detection an important task. Using whole genome sequencing (WGS), it is possible to capture both bacterial and plasmid sequence data, but short read lengths make plasmid detection a complex problem.ResultsWe developed a tool named PlasmidSeeker that enables the detection of plasmids from bacterial WGS data without read assembly. The PlasmidSeeker algorithm is based onk-mers and usesk-mer abundance to distinguish between plasmid and bacterial sequences. We tested the performance of PlasmidSeeker on a set of simulated and real bacterial WGS samples, resulting in 100% sensitivity and 99.98% specificity.ConclusionPlasmidSeeker enables quick detection of known plasmids and complements existing tools that assemble plasmids de novo. The PlasmidSeeker source code is stored on GitHub:https://github.com/bioinfo-ut/PlasmidSeeker.

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De novo whole-genome assembly of a wild type yeast isolate using nanopore sequencing

F1000Research ◽

10.12688/f1000research.11146.2 ◽

2018 ◽

Vol 6 ◽

pp. 618 ◽

Cited By ~ 2

Author(s):

Michael Liem ◽

Hans J. Jansen ◽

Ron P. Dirks ◽

Christiaan V. Henkel ◽

G. Paul H. van Heusden ◽

...

Keyword(s):

De Novo ◽

Sequence Data ◽

New Technology ◽

Whole Genome ◽

Nanopore Sequencing ◽

Short Read ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Before And After ◽

Long Read

Background: The introduction of the MinION sequencing device by Oxford Nanopore Technologies may greatly accelerate whole genome sequencing. Nanopore sequence data offers great potential for de novo assembly of complex genomes without using other technologies. Furthermore, Nanopore data combined with other sequencing technologies is highly useful for accurate annotation of all genes in the genome. In this manuscript we used nanopore sequencing as a tool to classify yeast strains. Methods: We compared various technical and software developments for the nanopore sequencing protocol, showing that the R9 chemistry is, as predicted, higher in quality than R7.3 chemistry. The R9 chemistry is an essential improvement for assembly of the extremely AT-rich mitochondrial genome. We double corrected assemblies from four different assemblers with PILON and assessed sequence correctness before and after PILON correction with a set of 290 Fungi genes using BUSCO. Results: In this study, we used this new technology to sequence and de novo assemble the genome of a recently isolated ethanologenic yeast strain, and compared the results with those obtained by classical Illumina short read sequencing. This strain was originally named Candida vartiovaarae (Torulopsis vartiovaarae) based on ribosomal RNA sequencing. We show that the assembly using nanopore data is much more contiguous than the assembly using short read data. We also compared various technical and software developments for the nanopore sequencing protocol, showing that nanopore-derived assemblies provide the highest contiguity. Conclusions: The mitochondrial and chromosomal genome sequences showed that our strain is clearly distinct from other yeast taxons and most closely related to published Cyberlindnera species. In conclusion, MinION-mediated long read sequencing can be used for high quality de novo assembly of new eukaryotic microbial genomes.

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De novo whole-genome assembly of a wild type yeast isolate using nanopore sequencing

F1000Research ◽

10.12688/f1000research.11146.1 ◽

2017 ◽

Vol 6 ◽

pp. 618 ◽

Cited By ~ 3

Author(s):

Hans J. Jansen ◽

Ron P. Dirks ◽

Michael Liem ◽

Christiaan V. Henkel ◽

G. Paul H. van Heusden ◽

...

Keyword(s):

De Novo ◽

Sequence Data ◽

New Technology ◽

Whole Genome ◽

Nanopore Sequencing ◽

Short Read ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Long Read ◽

Wild Type Yeast

Background: The introduction of the MinIONTM sequencing device by Oxford Nanopore Technologies may greatly accelerate whole genome sequencing. It has been shown that the nanopore sequence data, in combination with other sequencing technologies, is highly useful for accurate annotation of all genes in the genome. However, it also offers great potential for de novo assembly of complex genomes without using other technologies. In this manuscript we used nanopore sequencing as a tool to classify yeast strains. Methods: We compared various technical and software developments for the nanopore sequencing protocol, showing that the R9 chemistry is, as predicted, higher in quality than R7.3 chemistry. The R9 chemistry is an essential improvement for assembly of the extremely AT-rich mitochondrial genome. Results: In this study, we used this new technology to sequence and de novo assemble the genome of a recently isolated ethanologenic yeast strain, and compared the results with those obtained by classical Illumina short read sequencing. This strain was originally named Candida vartiovaarae (Torulopsis vartiovaarae) based on ribosomal RNA sequencing. We show that the assembly using nanopore data is much more contiguous than the assembly using short read data. Conclusions: The mitochondrial and chromosomal genome sequences showed that our strain is clearly distinct from other yeast taxons and most closely related to published Cyberlindnera species. In conclusion, MinION-mediated long read sequencing can be used for high quality de novo assembly of new eukaryotic microbial genomes.

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De Novo Assembly of Two Swedish Genomes Reveals Missing Segments from the Human GRCh38 Reference and Improves Variant Calling of Population-Scale Sequencing Data

Genes ◽

10.3390/genes9100486 ◽

2018 ◽

Vol 9 (10) ◽

pp. 486 ◽

Cited By ~ 22

Author(s):

Adam Ameur ◽

Huiwen Che ◽

Marcel Martin ◽

Ignas Bunikis ◽

Johan Dahlberg ◽

...

Keyword(s):

Genome Sequencing ◽

De Novo Assembly ◽

De Novo ◽

Variant Calling ◽

Whole Genome Sequencing Data ◽

Personal Genome ◽

Whole Genome ◽

Sequencing Data ◽

Short Read ◽

Population Scale

The current human reference sequence (GRCh38) is a foundation for large-scale sequencing projects. However, recent studies have suggested that GRCh38 may be incomplete and give a suboptimal representation of specific population groups. Here, we performed a de novo assembly of two Swedish genomes that revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have an elevated GC-content, and are primarily located in centromeric or telomeric regions. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are also missing from GRCh38 at chromosomes 14, 17, and 21. Inclusion of NS into the GRCh38 reference radically improves the alignment and variant calling from short-read whole-genome sequencing data at several genomic loci. A re-analysis of a Swedish population-scale sequencing project yields > 75,000 putative novel single nucleotide variants (SNVs) and removes > 10,000 false positive SNV calls per individual, some of which are located in protein coding regions. Our results highlight that the GRCh38 reference is not yet complete and demonstrate that personal genome assemblies from local populations can improve the analysis of short-read whole-genome sequencing data.

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Metavisitor, a suite of Galaxy tools for simple and rapid detection and discovery of viruses in deep sequence data

10.1101/048983 ◽

2016 ◽

Author(s):

Guillaume Carissimo ◽

Marius van den Beek ◽

Juliana Pegoraro ◽

Kenneth D Vernick ◽

Christophe Antoniewski

Keyword(s):

Small Rna ◽

De Novo ◽

Sequence Data ◽

Small Rna Sequencing ◽

Sequencing Data ◽

Viral Genomes ◽

Bioinformatic Tools ◽

The Galaxy ◽

Galaxy Server ◽

User Friendly

AbstractWe present user-friendly and adaptable software to provide biologists, clinical researchers and possibly diagnostic clinicians with the ability to robustly detect and reconstruct viral genomes from complex deep sequence datasets. A set of modular bioinformatic tools and workflows was implemented as the Metavisitor package in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor can be used on our Mississippi server, or can be installed on any Galaxy server instance and a pre-configured Metavisitor server image is provided. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions.

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High-precision and cost-efficient sequencing for real-time COVID-19 surveillance

Scientific Reports ◽

10.1038/s41598-021-93145-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sung Yong Park ◽

Gina Faraci ◽

Pamela M. Ward ◽

Jane F. Emerson ◽

Ha Youn Lee

Keyword(s):

Los Angeles ◽

Whole Genome Sequencing ◽

Real Time ◽

Genome Sequencing ◽

High Precision ◽

High Throughput Sequencing ◽

Whole Genome ◽

Sequencing Data ◽

Public Health Response ◽

Cost Efficient

AbstractCOVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients’ Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

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Comprehensive identification of transposable element insertions using multiple sequencing technologies

Nature Communications ◽

10.1038/s41467-021-24041-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Chong Chu ◽

Rebeca Borges-Monroy ◽

Vinayak V. Viswanadham ◽

Soohyun Lee ◽

Heng Li ◽

...

Keyword(s):

Transposable Element ◽

Structure And Function ◽

Endogenous Retroviruses ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Short Read ◽

Sequencing Technologies ◽

Long Read ◽

And Function

AbstractTransposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea.

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Estimating sequencing error rates using families

BioData Mining ◽

10.1186/s13040-021-00259-6 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Kelley Paskov ◽

Jae-Yoon Jung ◽

Brianna Chrisman ◽

Nate T. Stockham ◽

Peter Washington ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Genome Sequencing ◽

Variant Calling ◽

Error Rates ◽

Sequencing Error ◽

Whole Genome ◽

Sequencing Data ◽

Sequencing Platform ◽

Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

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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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