scholarly journals gplas: a comprehensive tool for plasmid analysis using short-read graphs

2019 ◽  
Author(s):  
Sergio Arredondo-Alonso ◽  
Martin Bootsma ◽  
Yaïr Hein ◽  
Malbert R.C. Rogers ◽  
Jukka Corander ◽  
...  
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Bacterial Genome ◽  
Workflow Management ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Genetic Traits ◽  
Short Read ◽  
Sequence Composition ◽  
Short Read Sequence

ABSTRACTSummaryPlasmids can horizontally transmit genetic traits, enabling rapid bacterial adaptation to new environments and hosts. Short-read whole-genome sequencing data is often applied to large-scale bacterial comparative genomics projects but the reconstruction of plasmids from these data is facing severe limitations, such as the inability to distinguish plasmids from each other in a bacterial genome. We developed gplas, a new approach to reliably separate plasmid contigs into discrete components using sequence composition, coverage, assembly graph information and clustering based on a pruned network of plasmid unitigs. Gplas facilitates the analysis of large numbers of bacterial isolates and allows a detailed analysis of plasmid epidemiology based solely on short read sequence data.Availability and implementationGplas is written in R, Bash and uses a Snakemake pipeline as a workflow management system. Gplas is available under the GNU General Public License v3.0 at https://gitlab.com/sirarredondo/[email protected]

scholarly journals gplas: a comprehensive tool for plasmid analysis using short-read graphs

2020 ◽  
Vol 36 (12) ◽  
pp. 3874-3876 ◽  
Author(s):  
Sergio Arredondo-Alonso ◽  
Martin Bootsma ◽  
Yaïr Hein ◽  
Malbert R C Rogers ◽  
Jukka Corander ◽  
...  
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Bacterial Genome ◽  
Workflow Management ◽  
Supplementary Information ◽  
Whole Genome Sequencing Data ◽  
Network Partitioning ◽  
Sequencing Data ◽  
Genetic Traits ◽  
Short Read

Abstract Summary Plasmids can horizontally transmit genetic traits, enabling rapid bacterial adaptation to new environments and hosts. Short-read whole-genome sequencing data are often applied to large-scale bacterial comparative genomics projects but the reconstruction of plasmids from these data is facing severe limitations, such as the inability to distinguish plasmids from each other in a bacterial genome. We developed gplas, a new approach to reliably separate plasmid contigs into discrete components using sequence composition, coverage, assembly graph information and network partitioning based on a pruned network of plasmid unitigs. Gplas facilitates the analysis of large numbers of bacterial isolates and allows a detailed analysis of plasmid epidemiology based solely on short-read sequence data. Availability and implementation Gplas is written in R, Bash and uses a Snakemake pipeline as a workflow management system. Gplas is available under the GNU General Public License v3.0 at https://gitlab.com/sirarredondo/gplas.git. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes

2021 ◽  
Author(s):  
Eric S Tvedte ◽  
Mark Gasser ◽  
Benjamin C Sparklin ◽  
Jane Michalski ◽  
Carl E Hjelmen ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Hybrid Approach ◽  
Cost Effective ◽  
Fruit Fly ◽  
Drosophila Ananassae ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
E Coli ◽  
Hybrid Approaches ◽  
Long Read

Abstract The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

scholarly journals Comprehensive identification of transposable element insertions using multiple sequencing technologies

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.

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

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).

scholarly journals Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

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.

EdClust: A heuristic sequence clustering method with higher sensitivity

2021 ◽  
Author(s):  
Ming Cao ◽  
Qinke Peng ◽  
Ze-Gang Wei ◽  
Fei Liu ◽  
Yi-Fan Hou
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Clustering Algorithms ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Clustering Method ◽  
Cluster Number ◽  
Sequence Clustering ◽  
Downstream Analysis ◽  
Heuristic Clustering

The development of high-throughput technologies has produced increasing amounts of sequence data and an increasing need for efficient clustering algorithms that can process massive volumes of sequencing data for downstream analysis. Heuristic clustering methods are widely applied for sequence clustering because of their low computational complexity. Although numerous heuristic clustering methods have been developed, they suffer from two limitations: overestimation of inferred clusters and low clustering sensitivity. To address these issues, we present a new sequence clustering method (edClust) based on Edlib, a C/C[Formula: see text] library for fast, exact semi-global sequence alignment to group similar sequences. The new method edClust was tested on three large-scale sequence databases, and we compared edClust to several classic heuristic clustering methods, such as UCLUST, CD-HIT, and VSEARCH. Evaluations based on the metrics of cluster number and seed sensitivity (SS) demonstrate that edClust can produce fewer clusters than other methods and that its SS is higher than that of other methods. The source codes of edClust are available from https://github.com/zhang134/EdClust.git under the GNU GPL license.

scholarly journals MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5895 ◽  
Author(s):  
Thomas Andreas Kohl ◽  
Christian Utpatel ◽  
Viola Schleusener ◽  
Maria Rosaria De Filippo ◽  
Patrick Beckert ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome Sequencing Data ◽  
Phylogenomic Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Desktop Computer

Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.

scholarly journals Rapid Diagnosis of Spinocerebellar Ataxia 36 in a Three‐Generation Family Using Short‐Read Whole‐Genome Sequencing Data

2020 ◽  
Vol 35 (9) ◽  
pp. 1675-1679
Author(s):  
Haloom Rafehi ◽  
David J. Szmulewicz ◽  
Kate Pope ◽  
Mathew Wallis ◽  
John Christodoulou ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Spinocerebellar Ataxia ◽  
Genome Sequencing ◽  
Rapid Diagnosis ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Generation Family

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

2017 ◽  
Vol 114 (30) ◽  
pp. 8059-8064 ◽  
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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