Ségolène Caboche

Comparison of mapping algorithms used in high-throughput sequencing: application to Ion Torrent data

BackgroundThe rapid evolution in high-throughput sequencing (HTS) technologies has opened up new perspectives in several research fields and led to the production of large volumes of sequence data. A fundamental step in HTS data analysis is the mapping of reads onto reference sequences. Choosing a suitable mapper for a given technology and a given application is a subtle task because of the difficulty of evaluating mapping algorithms.ResultsIn this paper, we present a benchmark procedure to compare mapping algorithms used in HTS using both real and simulated datasets and considering four evaluation criteria: computational resource and time requirements, robustness of mapping, ability to report positions for reads in repetitive regions, and ability to retrieve true genetic variation positions. To measure robustness, we introduced a new definition for a correctly mapped read taking into account not only the expected start position of the read but also the end position and the number of indels and substitutions. We developed CuReSim, a new read simulator, that is able to generate customized benchmark data for any kind of HTS technology by adjusting parameters to the error types. CuReSim and CuReSimEval, a tool to evaluate the mapping quality of the CuReSim simulated reads, are freely available. We applied our benchmark procedure to evaluate 14 mappers in the context of whole genome sequencing of small genomes with Ion Torrent data for which such a comparison has not yet been established.ConclusionsA benchmark procedure to compare HTS data mappers is introduced with a new definition for the mapping correctness as well as tools to generate simulated reads and evaluate mapping quality. The application of this procedure to Ion Torrent data from the whole genome sequencing of small genomes has allowed us to validate our benchmark procedure and demonstrate that it is helpful for selecting a mapper based on the intended application, questions to be addressed, and the technology used. This benchmark procedure can be used to evaluate existing or in-development mappers as well as to optimize parameters of a chosen mapper for any application and any sequencing platform.

Assessment of Common and Emerging Bioinformatics Pipelines for Targeted Metagenomics

Targeted metagenomics, also known as metagenetics, is a high-throughput sequencing application focusing on a nucleotide target in a microbiome to describe its taxonomic content. A wide range of bioinformatics pipelines are available to analyze sequencing outputs, and the choice of an appropriate tool is crucial and not trivial. No standard evaluation method exists for estimating the accuracy of a pipeline for targeted metagenomics analyses. This article proposes an evaluation protocol containing real and simulated targeted metagenomics datasets, and adequate metrics allowing us to study the impact of different variables on the biological interpretation of results. This protocol was used to compare six different bioinformatics pipelines in the basic user context: Three common ones (mothur, QIIME and BMP) based on a clustering-first approach and three emerging ones (Kraken, CLARK and One Codex) using an assignment-first approach. This study surprisingly reveals that the effect of sequencing errors has a bigger impact on the results that choosing different amplified regions. Moreover, increasing sequencing throughput increases richness overestimation, even more so for microbiota of high complexity. Finally, the choice of the reference database has a bigger impact on richness estimation for clustering-first pipelines, and on correct taxa identification for assignment-first pipelines. Using emerging assignment-first pipelines is a valid approach for targeted metagenomics analyses, with a quality of results comparable to popular clustering-first pipelines, even with an error-prone sequencing technology like Ion Torrent. However, those pipelines are highly sensitive to the quality of databases and their annotations, which makes clustering-first pipelines still the only reliable approach for studying microbiomes that are not well described.

High-Throughput Sequencing, a VersatileWeapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

The recent progresses of high-throughput sequencing (HTS) technologies enable easy and cost-reduced access to whole genome sequencing (WGS) or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose.

LeView: automatic and interactive generation of 2D diagrams for biomacromolecule/ligand interactions

Abstract2D diagrams are widely used in the scientific literature to represent interactions between ligands and biomacromolecules. Such schematic diagrams are very helpful to better understand the chemical interactions and biological processes in which ligands are involved. Here, a new tool for automatic and interactive generation of 2D diagrams for biomacromolecule/ligand interactions is presented. LeView (Ligand-Environment Viewer) produces customised and high-quality figures, with a good compromise between a faithful representation of the 3D data (structures and interactions) and aesthetic criteria. LeView can be freely downloaded at http://www.pegase-biosciences.com/tools/leview/.

Targeted metagenomic sequencing data of human gut microbiota associated with Blastocystis colonization

In the past decade, metagenomics studies have become widespread due to the arrival of second-generation sequencing platforms characterized by low costs, high throughput and short read lengths. Today, although benchtop sequencers are considered to be accurate platforms to deliver data for targeted metagenomics studies, the limiting factor has become the analysis of these data. In a previous paper, we performed an Ion Torrent PGM 16S rDNA gene sequencing of faecal DNAs from 48 Blastocystis-colonized patients and 48 Blastocystis-negative subjects, in order to decipher the impact of this widespread protist on gut microbiota composition and diversity. We report here on the Ion Torrent targeted metagenomic sequencing and analysis of these 96 human faecal samples, and the complete datasets from raw to analysed data. We also provide the key steps of the bioinformatic analyses, from library preparation to data filtering and OTUs tables generation. This data represents a valuable resource for the scientific community, enabling re-processing of these targeted metagenomic datasets through various pipelines and a comparative evaluation of microbiota analysis methods.

Primary transcriptome analysis reveals importance of IS elements for the shaping of the transcriptional landscape of Bordetella pertussis

ABSTRACT Bordetella pertussis is the causative agent of whooping cough, a respiratory disease still considered as a major public health threat and for which recent re-emergence has been observed. Constant reshuffling of Bordetella pertussis genome organization was observed during evolution. These rearrangements are essentially mediated by Insertion Sequences (IS), a mobile genetic elements present in more than 230 copies in the genome, which are supposed to be one of the driving forces enabling the pathogen to escape from vaccine-induced immunity. Here we use high-throughput sequencing approaches (RNA-seq and differential RNA-seq), to decipher Bordetella pertussis transcriptome characteristics and to evaluate the impact of IS elements on transcriptome architecture. Transcriptional organization was determined by identification of transcription start sites and revealed also a large variety of non-coding RNAs including sRNAs, leaderless mRNAs or long 3′ and 5′UTR including seven riboswitches. Unusual topological organizations, such as overlapping 5′- or 3′-extremities between oppositely orientated mRNA were also unveiled. The pivotal role of IS elements in the transcriptome architecture and their effect on the transcription of neighboring genes was examined. This effect is mediated by the introduction of IS harbored promoters or by emergence of hybrid promoters. This study revealed that in addition to their impact on genome rearrangements, most of the IS also impact on the expression of their flanking genes. Furthermore, the transcripts produced by IS are strain-specific due to the strain to strain variation in IS copy number and genomic context.

MICRA: an automatic pipeline for fast characterization of microbial genomes from high-throughput sequencing data

The increase in available sequence data has advanced the field of microbiology; however, making sense of these data without bioinformatics skills is still problematic. We describe MICRA, an automatic pipeline, available as a web interface, for microbial identification and characterization through reads analysis. MICRA uses iterative mapping against reference genomes to identify genes and variations. Additional modules allow prediction of antibiotic susceptibility and resistance and comparing the results of several samples. MICRA is fast, producing few false-positive annotations and variant calls compared to current methods, making it a tool of great interest for fully exploiting sequencing data.