Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing

Although protists are critical components of marine ecosystems, they are still poorly characterized. Here we analysed the taxonomic diversity of planktonic and benthic protist communities collected in six distant European coastal sites. Environmental deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from three size fractions (pico-, nano- and micro/mesoplankton), as well as from dissolved DNA and surface sediments were used as templates for tag pyrosequencing of the V4 region of the 18S ribosomal DNA. Beta-diversity analyses split the protist community structure into three main clusters: picoplankton-nanoplankton-dissolved DNA, micro/mesoplankton and sediments. Within each cluster, protist communities from the same site and time clustered together, while communities from the same site but different seasons were unrelated. Both DNA and RNA-based surveys provided similar relative abundances for most class-level taxonomic groups. Yet, particular groups were overrepresented in one of the two templates, such as marine alveolates (MALV)-I and MALV-II that were much more abundant in DNA surveys. Overall, the groups displaying the highest relative contribution were Dinophyceae, Diatomea, Ciliophora and Acantharia. Also, well represented were Mamiellophyceae, Cryptomonadales, marine alveolates and marine stramenopiles in the picoplankton, and Monadofilosa and basal Fungi in sediments. Our extensive and systematic sequencing of geographically separated sites provides the most comprehensive molecular description of coastal marine protist diversity to date.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results: We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions: This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity >= 2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.

IROme, a New High-Throughput Molecular Tool for the Diagnosis of Inherited Retinal Dystrophies.

The molecular diagnosis of retinal dystrophies is difficult because of the very important number of genes implicated and is rarely helped by genotype-phenotype correlations. This prompted us to develop IROme, a custom designed in solution-based targeted exon capture assay (SeqCap EZ Choice library, Roche NimbleGen) for 60 retinitis pigmentosa-linked genes and three candidate genes (942 exons). Pyrosequencing was performed on a Roche 454 GS Junior benchtop high-throughput sequencing platform. In total, 23 patients affected by retinitis pigmentosa were analyzed. Per patient, 39.6 Mb were generated, and 1111 sequence variants were detected on average, at a median coverage of 17-fold. After data filtering and sequence variant prioritization, disease-causing mutations were identified in ABCA4, CNGB1, GUCY2D, PROM1, PRPF8, PRPF31, PRPH2, RHO, RP2, and TULP1 for twelve patients (55%), ten mutations having never been reported previously. Potential mutations were identified in 5 additional patients, and in only 6 patients no molecular diagnosis could be established (26%). In conclusion, targeted exon capture and next-generation sequencing are a valuable and efficient approach to identify disease-causing sequence variants in retinal dystrophies.

HTPSELEX--a database of high-throughput SELEX libraries for transcription factor binding sites.

HTPSELEX is a public database providing access to primary and derived data from high-throughput SELEX experiments aimed at characterizing the binding specificity of transcription factors. The resource is primarily intended to serve computational biologists interested in building models of transcription factor binding sites from large sets of binding sequences. The guiding principle is to make available all information that is relevant for this purpose. For each experiment, we try to provide accurate information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, assembled clone sequences (concatemers) and complete sets of in vitro selected protein-binding tags. In addition, we offer in-house derived binding sites models. HTPSELEX also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols. The FTP site contains the trace archives and database flatfiles. The web server offers user-friendly interfaces for viewing individual entries and quality-controlled download of SELEX sequence libraries according to a user-defined sequencing quality threshold. HTPSELEX is available from ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex/ and http://www.isrec.isb-sib.ch/htpselex.

Desenvolvimento de metodologia high-throughput para estudo populacional do mosquito Aedes aegypti e comparação de dados de genes mitocondriais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A HIDDEN MARKOV MODEL FOR JOINT ESTIMATION OF GENOTYPE AND COPY NUMBER IN HIGH-THROUGHPUT SNP CHIPS

Amplifications and deletions of chromosomal DNA, as well as copy-neutral loss of heterozygosity have been associated with diseases processes. High-throughput single nucleotide polymorphism (SNP) arrays are useful for making genome-wide estimates of copy number and genotype calls. Because neighboring SNPs in high throughput SNP arrays are likely to have dependent copy number and genotype due to the underlying haplotype structure and linkage disequilibrium, hidden Markov models (HMM) may be useful for improving genotype calls and copy number estimates that do not incorporate information from nearby SNPs. We improve previous approaches that utilize a HMM framework for inference in high throughput SNP arrays by integrating copy number, genotype calls, and the corresponding confidence scores when available. Using simulated data, we demonstrate how confidence scores control smoothing in a probabilistic framework. Software for fitting HMMs to SNP array data is available in the R package ICE.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

PCR candidate region mismatch scanning: adaptation to quantitative, high-throughput genotyping

Linkage and association analyses were performed to identify loci affecting disease susceptibility by scoring previously characterized sequence variations such as microsatellites and single nucleotide polymorphisms. Lack of markers in regions of interest, as well as difficulty in adapting various methods to high-throughput settings, often limits the effectiveness of the analyses. We have adapted the Escherichia coli mismatch detection system, employing the factors MutS, MutL and MutH, for use in PCR-based, automated, high-throughput genotyping and mutation detection of genomic DNA. Optimal sensitivity and signal-to-noise ratios were obtained in a straightforward fashion because the detection reaction proved to be principally dependent upon monovalent cation concentration and MutL concentration. Quantitative relationships of the optimal values of these parameters with length of the DNA test fragment were demonstrated, in support of the translocation model for the mechanism of action of these enzymes, rather than the molecular switch model. Thus, rapid, sequence-independent optimization was possible for each new genomic target region. Other factors potentially limiting the flexibility of mismatch scanning, such as positioning of dam recognition sites within the target fragment, have also been investigated. We developed several strategies, which can be easily adapted to automation, for limiting the analysis to intersample heteroduplexes. Thus, the principal barriers to the use of this methodology, which we have designated PCR candidate region mismatch scanning, in cost-effective, high-throughput settings have been removed.

The impact of whey protein consumption and exercise on the composition and diversity of the gut microbiota: a high through-put DNA sequencing approach

Advances in culture independent technologies over the last decade have highlighted the pivotal role which the gut microbiota plays in maintaining human health. Conversely, perturbations to the composition or actions of the ‘normal/functioning’ microbiota have been frequently associated with the pathogenesis of several disease states. Therefore the selective modulation of enteric microbial communities represents a viable target for the development of novel treatments for such diseases. Notably, while bovine whey proteins and exercise have been shown to positively influence several physiological processes, such as energy balance, their effect on the composition or functionality of the gut microbiota remains largely unknown. In this thesis, a variety of ex vivo, murine and human models are used in conjunction with high-throughput DNA sequencing-based analysis to provide valuable and novel insights into the impact of both whey proteins and exercise on enteric microbial communities. Overall the results presented in this thesis highlight that the consumption both whey protein isolate (WPI), and individual component proteins of whey such as bovine serum albumin (BSA) and lactoferrin, reduce high fat diet associated body weight gain and are associated with beneficial alterations within the murine gut microbiota. Although the impact of exercise on enteric microbial communities remains less clear, it may be that longer term investigations are required for the true effect of exercise on the gut microbiota to be fully elucidated.

High-throughput Analysis By Sp-ldi-ms For Fast Identification Of Adulterations In Commercial Balsamic Vinegars.

Balsamic vinegar (BV) is a typical and valuable Italian product, worldwide appreciated thanks to its characteristic flavors and potential health benefits. Several studies have been conducted to assess physicochemical and microbial compositions of BV, as well as its beneficial properties. Due to highly-disseminated claims of antioxidant, antihypertensive and antiglycemic properties, BV is a known target for frauds and adulterations. For that matter, product authentication, certifying its origin (region or country) and thus the processing conditions, is becoming a growing concern. Striving for fraud reduction as well as quality and safety assurance, reliable analytical strategies to rapidly evaluate BV quality are very interesting, also from an economical point of view. This work employs silica plate laser desorption/ionization mass spectrometry (SP-LDI-MS) for fast chemical profiling of commercial BV samples with protected geographical indication (PGI) and identification of its adulterated samples with low-priced vinegars, namely apple, alcohol and red/white wines.

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.

Evaluation of the genetic variability of orchid fleck virus by single-strand conformational polymorphism analysis and nucleotide sequencing of a fragment from the nucleocapsid gene

The variability of a fragment of the nucleocapsid gene of orchid fleck virus (OFV) was investigated by single-strand conformational polymorphism (SSCP) analysis and nucleotide sequencing. Forty-eight samples of 18 genera of orchids were collected from Brazil, Costa Rica and Australia. The SSCP analysis yielded six different band patterns, and phylogenetic analysis based on the nucleotide fragment sequence obtained in this work and six available in GenBank showed two different groups, one with isolates 023Germany and So-Japan, and other with the rest of the isolates. None of the analyses showed geographic correlation among the Brazilian strains. The data obtained in this study showed a low genetic variation in this region of the genome; the d(N)/d(S) ratio of 0.251-0.405 demonstrated a negative selective pressure that maintains the stability of the analyzed fragments.

High Throughput Simultaneous Assay of Atenolol and Chlortalidone in Combined Dose Tablets by Liquid Chromatography and Capillary Zone Electrophoresis

New fast liquid chromatographic and capillary zone electrophoresis methods were developed and validated for simultaneous determination of atenolol and chlortalidone in combined dose tablets. The reversed phase HPLC method was carried out on a CN LiChrosorb (R) (125 x 4 mm, 5 mu m) column. The CZE method was carried out on an uncoated fused-silica capillary of 30 cm x 75 mu m i.d. with 25 mmol L(-1) sodium tetraborate, pH 9.4. The total analysis time was <6 and <2.5 min for HPLC and CZE methods, respectively. Both methods can be used for stability studies as well.

Novel colloidal materials for high-throughput screening applications in drug discovery and genomics

Tracking the reaction history is the means of choice to identify bioactive compounds in large combinatorial libraries. The authors describe two approaches to synthesis on silica beads: a) addition of a reporter dye tag during each synthesis step (see Figure), which attaches itself to the bead by colloidal forces, and b) encapsulating arrays of fluorescent dyes into the beads to encode them uniquely, for recognition with a flow cytometer after each reaction step.