As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

/pdf/fast-gapped-read-alignment-with-bowtie-2-2axet5ses2.pdf

Fast gapped-read alignment with Bowtie 2

Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

/pdf/star-ultrafast-universal-rna-seq-aligner-r1vlt61g3c.pdf

STAR: ultrafast universal RNA-seq aligner

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

http://genomebio.org/wp-content/uploads/2013/08/Haas_2013_Nature_Protocols-1.pdf

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of 'best available' primer pairs for Bacteria and Archaea for three amplicon size classes (100-400, 400-1000, ≥ 1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.

Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies

Paired Omics Data Platform

Genomic and functional analyses of bacterial sponge symbionts belonging to the uncultivated candidate genus 'Entotheonella' has revealed them as the prolific producers of bioactive compounds previously identified from their invertebrate hosts. These studies also suggested 'Entotheonella' as the first members of a new candidate phylum, 'Tectomicrobia'. Here we analyzed the phylogenetic structure and environmental distribution of this as-yet sparsely populated phylum-like lineage. The data show that 'Entotheonella' and other 'Tectomicrobia' are not restricted to marine habitats but widely distributed among terrestrial locations. The inferred phylogenetic trees suggest several intra-phylum lineages with diverse lifestyles. Of these, the previously described 'Entotheonella' lineage can be more accurately divided into at least three different candidate genera with the terrestrial 'Candidatus Prasianella', the largely terrestrial 'Candidatus Allonella', the 'Candidatus Thalassonella' comprising sponge-associated members, and the more widely distributed 'Candidatus Entotheonella'. Genomic characterization of 'Thalassonella' members from a range of sponge hosts did not suggest a role as providers of natural products, despite high genomic similarity to 'Entotheonella' regarding primary metabolism and implied lifestyle. In contrast, the analysis revealed a correlation between the revised 'Entotheonella' 16S rRNA gene phylogeny and a specific association with sponges and their natural products. This feature might serve as a discovery method to accelerate the identification of new chemically rich 'Entotheonella' variants, and led to the identification of the first 'Entotheonella' symbiont in a non-tetractinellid sponge, Psammocinia sp., indicating a wide host distribution of 'Entotheonella'-based chemical symbiosis. 

/pdf/distribution-and-diversity-of-tectomicrobia-a-deep-branching-1djo95ek.pdf

Distribution and diversity of ‘Tectomicrobia’, a deep-branching uncultivated bacterial lineage harboring rich producers of bioactive metabolites

Abstract Background Prebiotic feed additives aim to improve gut health by influencing the microbiota and the gut barrier. Most studies on feed additives concentrate on one or two (monodisciplinary) outcome parameters, such as immunity, growth, microbiota or intestinal architecture. A combinatorial and comprehensive approach to disclose the complex and multifaceted effects of feed additives is needed to understand their underlying mechanisms before making health benefit claims. Here, we used juvenile zebrafish as a model species to study effects of feed additives by integrating gut microbiota composition data and host gut transcriptomics with high-throughput quantitative histological analysis. Zebrafish received either control, sodium butyrate or saponin-supplemented feed. Butyrate-derived components such as butyric acid or sodium butyrate have been widely used in animal feeds due to their immunostimulant properties, thereby supporting intestinal health. Soy saponin is an antinutritional factor from soybean meal that promotes inflammation due to its amphipathic nature. Results We observed distinct microbial profiles associated with each diet, discovering that butyrate (and saponin to a lesser extent) affected gut microbial composition by reducing the degree of community-structure (co-occurrence network analysis) compared to controls. Analogously, butyrate and saponin supplementation impacted the transcription of numerous canonical pathways compared to control-fed fish. For example, both butyrate and saponin increased the expression of genes associated with immune response and inflammatory response, as well as oxidoreductase activity, compared to controls. Furthermore, butyrate decreased the expression of genes associated with histone modification, mitotic processes and G-coupled receptor activity. High-throughput quantitative histological analysis depicted an increase of eosinophils and rodlet cells in the gut tissue of fish receiving butyrate after one week of feeding and a depletion of mucus-producing cells after 3 weeks of feeding this diet. Combination of all datasets indicated that in juvenile zebrafish, butyrate supplementation increases the immune and the inflammatory response to a greater extent than the established inflammation-inducing anti-nutritional factor saponin. Such comprehensive analysis was supplemented by in vivo imaging of neutrophil and macrophage transgenic reporter zebrafish (mpeg1:mCherry/mpx:eGFPi 114 ) larvae. Upon exposure to butyrate and saponin, these larvae displayed a dose-dependent increase of neutrophils and macrophages in the gut area. Conclusion The omics and imaging combinatorial approach provided an integrated evaluation of the effect of butyrate on fish gut health and unraveled inflammatory-like features not previously reported that question the usage of butyrate supplementation to enhance fish gut health under basal conditions. The zebrafish model, due to its unique advantages, provides researchers with an invaluable tool to investigate effects of feed components on fish gut health throughout life. 

/pdf/omics-and-imaging-combinatorial-approach-reveals-butyrate-vq0x16fh.pdf

Michelle Schorn

Papers

Paired Omics Data Platform

Distribution and diversity of ‘Tectomicrobia’, a deep-branching uncultivated bacterial lineage harboring rich producers of bioactive metabolites

Omics and imaging combinatorial approach reveals butyrate-induced inflammatory effects in the zebrafish gut