Genometa - A Fast and Accurate Classifier for Short Metagenomic Shotgun Reads

Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.

High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

New Contig Creation Algorithm for the de novo DNA Assembly Problem

DNA assembly is among the most fundamental and difficult problems in bioinformatics. Near optimal assembly solutions are available for bacterial and small genomes, however assembling large and complex genomes especially the human genome using Next-Generation-Sequencing (NGS) technologies is shown to be very difficult because of the highly repetitive and complex nature of the human genome, short read lengths, uneven data coverage and tools that are not specifically built for human genomes. Moreover, many algorithms are not even scalable to human genome datasets containing hundreds of millions of short reads. The DNA assembly problem is usually divided into several subproblems including DNA data error detection and correction, contig creation, scaffolding and contigs orientation; each can be seen as a distinct research area. This thesis specifically focuses on creating contigs from the short reads and combining them with outputs from other tools in order to obtain better results. Three different assemblers including SOAPdenovo [Li09], Velvet [ZB08] and Meraculous [CHS+11] are selected for comparative purposes in this thesis. Obtained results show that this thesis’ work produces comparable results to other assemblers and combining our contigs to outputs from other tools, produces the best results outperforming all other investigated assemblers.

Typage de la classe génotypique du gène PRDM9 à partir de données de séquençage de Nouvelle Génération

Les positions des évènements de recombinaison s’agrègent ensemble, formant des hotspots déterminés en partie par la protéine à évolution rapide PRDM9. En particulier, ces positions de hotspots sont déterminées par le domaine de doigts de zinc (ZnF) de PRDM9 qui reconnait certains motifs d’ADN. Les allèles de PRDM9 contenant le ZnF de type k ont été préalablement associés avec une cohorte de patients affectés par la leucémie aigüe lymphoblastique. Les allèles de PRDM9 sont difficiles à identifier à partir de données de séquençage de nouvelle génération (NGS), en raison de leur nature répétitive. Dans ce projet, nous proposons une méthode permettant la caractérisation d’allèles de PRDM9 à partir de données de NGS, qui identifie le nombre d’allèles contenant un type spécifique de ZnF. Cette méthode est basée sur la corrélation entre les profils représentant le nombre de séquences nucléotidiques uniques à chaque ZnF retrouvés chez les lectures de NGS simulées sans erreur d’une paire d’allèles et chez les lectures d’un échantillon. La validité des prédictions obtenues par notre méthode est confirmée grâce à analyse basée sur les simulations. Nous confirmons également que la méthode peut correctement identifier le génotype d’allèles de PRDM9 qui n’ont pas encore été identifiés. Nous conduisons une analyse préliminaire identifiant le génotype des allèles de PRDM9 contenant un certain type de ZnF dans une cohorte de patients atteints de glioblastomes multiforme pédiatrique, un cancer du cerveau caractérisé par les mutations récurrentes dans le gène codant pour l’histone H3, la cible de l’activité épigénétique de PRDM9. Cette méthode ouvre la possibilité d’identifier des associations entre certains allèles de PRDM9 et d’autres types de cancers pédiatriques, via l’utilisation de bases de données de NGS de cellules tumorales.

Sequenciamento de DNA de nova geração e suas aplicações na genômica de plantas

As plataformas de sequenciamento de nova geração são uma alternativa poderosa para estudos de genômica estrutural e funcional. Na genômica de plantas, os trabalhos com as novas plataformas têm sido destinados ao sequenciamento de transcritos, ressequenciamento ou sequenciamento de novo de genomas plastidiais. Neste trabalho, são detalhadas as tecnologias das plataformas mais utilizadas atualmente, bem como é revisada a aplicação dessas tecnologias na genômica estrutural e funcional de plantas.

Genome Sequence of Exiguobacterium antarcticum B7, Isolated from a Biofilm in Ginger Lake, King George Island, Antarctica

Exiguobacterium antarcticum is a psychotropic bacterium isolated for the first time from microbial mats of Lake Fryxell in Antarctica. Many organisms of the genus Exiguobacterium are extremophiles and have properties of biotechnological interest, e. g., the capacity to adapt to cold, which make this genus a target for discovering new enzymes, such as lipases and proteases, in addition to improving our understanding of the mechanisms of adaptation and survival at low temperatures. This study presents the genome of E. antarcticum B7, isolated from a biofilm sample of Ginger Lake on King George Island, Antarctic peninsula.

Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

Some Eubacterium and Roseburia species are among the most prevalent motile bacteria present in the intestinal microbiota of healthy adults. These flagellate species contribute "cell motility" category genes to the intestinal microbiome and flagellin proteins to the intestinal proteome. We reviewed and revised the annotation of motility genes in the genomes of six Eubacterium and Roseburia species that occur in the human intestinal microbiota and examined their respective locus organization by comparative genomics. Motility gene order was generally conserved across these loci. Five of these species harbored multiple genes for predicted flagellins. Flagellin proteins were isolated from R. inulinivorans strain A2-194 and from E. rectale strains A1-86 and M104/1. The amino-termini sequences of the R. inulinivorans and E. rectale A1-86 proteins were almost identical. These protein preparations stimulated secretion of interleukin-8 (IL-8) from human intestinal epithelial cell lines, suggesting that these flagellins were pro-inflammatory. Flagellins from the other four species were predicted to be pro-inflammatory on the basis of alignment to the consensus sequence of pro-inflammatory flagellins from the beta- and gamma-proteobacteria. Many fliC genes were deduced to be under the control of sigma(28). The relative abundance of the target Eubacterium and Roseburia species varied across shotgun metagenomes from 27 elderly individuals. Genes involved in the flagellum biogenesis pathways of these species were variably abundant in these metagenomes, suggesting that the current depth of coverage used for metagenomic sequencing (3.13-4.79 Gb total sequence in our study) insufficiently captures the functional diversity of genomes present at low (<= 1%) relative abundance. E. rectale and R. inulinivorans thus appear to synthesize complex flagella composed of flagellin proteins that stimulate IL-8 production. A greater depth of sequencing, improved evenness of sequencing and improved metagenome assembly from short reads will be required to facilitate in silico analyses of complete complex biochemical pathways for low-abundance target species from shotgun metagenomes.

samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files

MOTIVATION: Data from RNA-seq experiments provide us with many new possibilities to gain insights into biological and disease mechanisms of cellular functioning. However, the reproducibility and robustness of RNA-seq data analysis results is often unclear. This is in part attributed to the two counter acting goals of (a) a cost efficient and (b) an optimal experimental design leading to a compromise, e.g., in the sequencing depth of experiments.

RESULTS: We introduce an R package called samExploreR that allows the subsampling (m out of n bootstraping) of short-reads based on SAM files facilitating the investigation of sequencing depth related questions for the experimental design. Overall, this provides a systematic way for exploring the reproducibility and robustness of general RNA-seq studies. We exemplify the usage of samExploreR by studying the influence of the sequencing depth and the annotation on the identification of differentially expressed genes.

AVAILABILITY: Availability: samExploreR is available as an R package from Bioconductor (after acceptance of the paper, download link: http://www.bio-complexity.com/samExploreR_1.0.0.tar.gz).

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Hybrid error correction and de novo assembly of single-molecule sequencing reads.

Single-molecule sequencing instruments can generate multikilobase sequences with the potential to greatly improve genome and transcriptome assembly. However, the error rates of single-molecule reads are high, which has limited their use thus far to resequencing bacteria. To address this limitation, we introduce a correction algorithm and assembly strategy that uses short, high-fidelity sequences to correct the error in single-molecule sequences. We demonstrate the utility of this approach on reads generated by a PacBio RS instrument from phage, prokaryotic and eukaryotic whole genomes, including the previously unsequenced genome of the parrot Melopsittacus undulatus, as well as for RNA-Seq reads of the corn (Zea mays) transcriptome. Our long-read correction achieves >99.9% base-call accuracy, leading to substantially better assemblies than current sequencing strategies: in the best example, the median contig size was quintupled relative to high-coverage, second-generation assemblies. Greater gains are predicted if read lengths continue to increase, including the prospect of single-contig bacterial chromosome assembly.

Short comment: To Nail a Jellyfish? Finding a progressive agenda for EU anti-discrimination law

The title of this short (about 4500 words) intervention translates to "To Nail a Jellyfish? Finding a progressive agenda for EU anti-discrimination law". I engage with those criticising EU anti-discrimination law as yet another emanation of the EU's "neo-liberal" nature which fails to establish a viable social policy regime. I criticise this in two directions. First, I take issue with the theory that anti-discrimination law and policy has to be part of social policy. Actually, the field has a mission which differs from social policy, in that it addresses disadvantage resulting from othering, combating stereotypes as well as promoting accomodation of difference. Second, I show how the critique of judicialisation of policy is not unique to anti-discrimination law and policy. The so called turn to rights based employment law has been criticised under this mantra by those who fear that collective labour law mechanisms will become less prevalent. Further, those who have engaged with anti-discrimination law for a much longer time than those criticising it have also devised means to overcome the individualistic tendencies of rights adjudication. They have (partly successfully) argued in favour of establishing equality bodies and creating positive obligations. Thus, the critique neglects the field it takes on, and does not accept the fact that anti-discrimination law and policy must be considered a field in its own right instead of the servant of social law and policy.
Now, this is more a summary than an abstract - since I realise that not everyone reads German.

Utilization of Probabilistic Models in Short Read Assembly from Second-Generation Sequencing

With the advent of cheaper and faster DNA sequencing technologies, assembly methods have greatly changed. Instead of outputting reads that are thousands of base pairs long, new sequencers parallelize the task by producing read lengths between 35 and 400 base pairs. Reconstructing an organism’s genome from these millions of reads is a computationally expensive task. Our algorithm solves this problem by organizing and indexing the reads using n-grams, which are short, fixed-length DNA sequences of length n. These n-grams are used to efficiently locate putative read joins, thereby eliminating the need to perform an exhaustive search over all possible read pairs. Our goal was develop a novel n-gram method for the assembly of genomes from next-generation sequencers. Specifically, a probabilistic, iterative approach was utilized to determine the most likely reads to join through development of a new metric that models the probability of any two arbitrary reads being joined together. Tests were run using simulated short read data based on randomly created genomes ranging in lengths from 10,000 to 100,000 nucleotides with 16 to 20x coverage. We were able to successfully re-assemble entire genomes up to 100,000 nucleotides in length.