Multi-amplicon microbiome data analysis pipelines for mixed orientation sequences using QIIME2: Assessing reference database, variable region and pre-processing bias in classification of mock bacterial community samples.

Microbiome research relies on next-generation sequencing and on downstream data analysis workflows. Several manufacturers have introduced multi-amplicon kits for microbiome characterization, improving speciation, but present unique challenges for analysis. The goal of this methodology study was to develop two analysis pipelines specific to mixed-orientation reads from multi-hypervariable (V) region amplicons. A secondary aim was to assess agreement with expected abundance, considering database and variable region. Mock community sequence data (n = 41) generated using the Ion16S™ Metagenomics Kit and Ion Torrent Sequencing Platform were analyzed using two workflows. Amplicons from V2, V3, V4, V6-7, V8 and V9 were deconvoluted using a specialized plugin based on CutPrimers. A separate workflow using Cutadapt is also presented. Three reference databases (Ribosomal Database Project, Greengenes and Silva) were used for taxonomic assignment. Bray-Curtis, Euclidean and Jensen-Shannon distance measures were used to evaluate overall annotation consistency, and specific taxon agreement was determined by calculating the ratio of observed to expected relative abundance. Reads that mapped to regions V2-V9 varied for both CutPrimers and Cutadapt-based methods. Within the CutPrimers-based pipeline, V3 amplicons had the best agreement with the expected distribution, tested using global distance measures, while V9 amplicons had the worst agreement. Accurate taxonomic annotation varied by genus-level taxon and V region analyzed. For the first time, we present a microbiome analysis pipeline that employs a specialized plugin to allow microbiome researchers to separate multi-amplicon data from the Ion16S Metagenomics Kit into V-specific reads. We also present an additional analysis workflow, modified for Ion Torrent mixed orientation reads. Overall, the global agreement of amplicons with the expected mock community abundances differed across V regions and reference databases. Benchmarking data should be referenced when planning a microbiome study to consider these biases related to sequencing and data analysis for multi-amplicon sequencing kits.

RHD and RHCE genotyping by next-generation sequencing is an effective strategy to identify molecular variants within sickle cell disease patients.

BACKGROUND: The complexity of Rh genetic variation among sickle cell disease (SCD) patients is high. Conventional molecular assays cannot identify all genetic variants already described for the RH locus as well as foresee novel alleles. Sequencing RHD and RHCE is indicated to broaden the search for Rh genetic variants. AIMS: To standardize the Next Generation Sequencing (NGS) strategy to assertively identify Rh genetic variants among SCD patients with serologic suspicion of Rh variants and evaluate if it can improve the transfusion support. METHODS: Thirty-five SCD patients with unexplained Rh antibodies were enrolled. A NGS-based strategy was developed to genotype RHD and RHCE using gene-specific primers. Genotype and serological data were compared. RESULTS: Data obtained from the NGS-based assay were gene-specific. Ten and 25 variant RHD and RHCE alleles were identified, respectively. Among all cases of unexplained Rh antibodies, 62% had been inaccurately classified by serological analysis and, of these, 73.1% were considered as relevant, as were associated with increased risk of hemolytic reactions and shortage of units suitable for transfusion. CONCLUSION: The NGS assay designed to genotype RH coding regions was effective and accurate in identifying variants. The proposed strategy clarified the Rh phenotype of most patients, improving transfusion support.

Draft Genome Sequence of Mycobacterium bovis 04-303, a Highly Virulent Strain from Argentina.

Mycobacterium bovis strain 04-303 was isolated from a wild boar living in a free-ranging field in Argentina. This work reports the draft genome sequence of this highly virulent strain and the genomic comparison of its major virulence-related genes with those of M. bovis strain AF2122/97 and Mycobacterium tuberculosis strain H37Rv.

High efficiency application of a mate-paired library from next-generation sequencing to postlight sequencing: Corynebacterium pseudotuberculosis as a case study for microbial de novo genome assembly.

With the advent of high-throughput DNA sequencing platforms, there has been a reduction in the cost and time of sequencing. With these advantages, new challenges have emerged, such as the handling of large amounts of data, quality assessment, and the assembly of short reads. Currently, benchtop high-throughput sequencers enable the genomes of prokaryotic organisms to be sequenced within two hours with a reduction in coverage compared with the SOLiD, Illumina and 454 FLX Titanium platforms, making it necessary to evaluate the efficiency of less expensive benchtop instruments for prokaryotic genomics. In the present work, we evaluate and propose a methodology for the use of the Ion Torrent PGM platform for decoding the gram-positive bacterium Corynebacterium pseudotuberculosis, for which 15 complete genome sequences have already been deposited based on fragment and mate-paired libraries with a 3-kb insert size. Despite the low coverage, a single sequencing run using a mate-paired library generated 39 scaffolds after de novo assembly without data curation. This result is superior to that obtained by sequencing using libraries generated from fragments marketed by the equipment's manufacturer, as well as that observed for mate-pairs sequenced by SOLiD. The generated sequence added an extra 91kb to the genome available at NCBI.

A comparative transcriptome analysis reveals expression profiles conserved across three Eimeria spp. of domestic fowl and associated with multiple developmental stages.

Coccidiosis of the domestic fowl is a worldwide disease caused by seven species of protozoan parasites of the genus Eimeria. The genome of the model species, Eimeria tenella, presents a complexity of 55-60MB distributed in 14 chromosomes. Relatively few studies have been undertaken to unravel the complexity of the transcriptome of Eimeria parasites. We report here the generation of more than 45,000 open reading frame expressed sequence tag (ORESTES) cDNA reads of E. tenella, Eimeria maxima and Eimeria acervulina, covering several developmental stages: unsporulated oocysts, sporoblastic oocysts, sporulated oocysts, sporozoites and second generation merozoites. All reads were assembled to constitute gene indices and submitted to a comprehensive functional annotation pipeline. In the case of E. tenella, we also incorporated publicly available ESTs to generate an integrated body of information. Orthology analyses have identified genes conserved across different apicomplexan parasites, as well as genes restricted to the genus Eimeria. Digital expression profiles obtained from ORESTES/EST countings, submitted to clustering analyses, revealed a high conservation pattern across the three Eimeria spp. Distance trees showed that unsporulated and sporoblastic oocysts constitute a distinct clade in all species, with sporulated oocysts forming a more external branch. This latter stage also shows a close relationship with sporozoites, whereas first and second generation merozoites are more closely related to each other than to sporozoites. The profiles were unambiguously associated with the distinct developmental stages and strongly correlated with the order of the stages in the parasite life cycle. Finally, we present The Eimeria Transcript Database (http://www.coccidia.icb.usp.br/eimeriatdb), a website that provides open access to all sequencing data, annotation and comparative analysis. We expect this repository to represent a useful resource to the Eimeria scientific community, helping to define potential candidates for the development of new strategies to control coccidiosis of the domestic fowl.

Ultra-deep sequencing reveals the microRNA expression pattern of the human stomach.

BACKGROUND: While microRNAs (miRNAs) play important roles in tissue differentiation and in maintaining basal physiology, little is known about the miRNA expression levels in stomach tissue. Alterations in the miRNA profile can lead to cell deregulation, which can induce neoplasia. METHODOLOGY/PRINCIPAL FINDINGS: A small RNA library of stomach tissue was sequenced using high-throughput SOLiD sequencing technology. We obtained 261,274 quality reads with perfect matches to the human miRnome, and 42% of known miRNAs were identified. Digital Gene Expression profiling (DGE) was performed based on read abundance and showed that fifteen miRNAs were highly expressed in gastric tissue. Subsequently, the expression of these miRNAs was validated in 10 healthy individuals by RT-PCR showed a significant correlation of 83.97% (P<0.05). Six miRNAs showed a low variable pattern of expression (miR-29b, miR-29c, miR-19b, miR-31, miR-148a, miR-451) and could be considered part of the expression pattern of the healthy gastric tissue. CONCLUSIONS/SIGNIFICANCE: This study aimed to validate normal miRNA profiles of human gastric tissue to establish a reference profile for healthy individuals. Determining the regulatory processes acting in the stomach will be important in the fight against gastric cancer, which is the second-leading cause of cancer mortality worldwide.

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. METHODS: Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. RESULTS: Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. CONCLUSION: To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor.

Simcluster: clustering enumeration gene expression data on the simplex space.

BACKGROUND: Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space. RESULTS: Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster. CONCLUSION: Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data.

EGene: a configurable pipeline generation system for automated sequence analysis.

UNLABELLED: EGene is a generic, flexible and modular pipeline generation system that makes pipeline construction a modular job. EGene allows for third-party programs to be used and integrated according to the needs of distinct projects and without any previous programming or formal language experience being required. EGene comes with CoEd, a visual tool to facilitate pipeline construction and documentation. A series of components to build pipelines for sequence processing is provided. AVAILABILITY: http://www.lbm.fmvz.usp.br/egene/ CONTACT: alan@ime.usp.br; argruber@usp.br SUPPLEMENTARY INFORMATION: http://www.lbm.fmvz.usp.br/egene/

Changes in G+C content of a neutrally evolving gene under a non-reversible dynamics measured by computer simulations based on experimental evolution data

To evaluate the effects of non-reversibility on compositional base changes and the distribution of branch lengths along a phylogeny, we extended, by means of computer simulations, our previous sequential PCR in vitro evolution experiment. In that study a 18S rRNA gene evolved neutrally for 280 generations and a homogeneous non-stationary model of base substitution based on a non-reversible dynamics was built from the in vitro evolution data to describe the observed pattern of nucleotide substitutions. Here, the process was extended to 840 generations without selection, using the model parameters calculated from the in vitro evolution experiment. We observed that under a non-reversible model the G+C content of the sequences significantly increases when compared to simulations with a reversible model. The values of mean and variance of the branch lengths are reduced under a non-reversible dynamics although they follow a Poisson distribution. We conclude that the major implication of non-reversibility is the overall decrease of branch lengths, although no transition from a stochastic to an ordered process is observed. According to our model the result of this neutral process will be the increase in the G+C content of the descendant sequences with an overall decrease in the frequency of substitutions.