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.

Molecular diagnosis for heterogeneous genetic diseases with high-throughput DNA sequencing applied to retinitis pigmentosa

BACKGROUND:
The genetic heterogeneity of many Mendelian disorders, such as retinitis pigmentosa which results from mutations in over 40 genes, is a major obstacle to obtaining a molecular diagnosis in clinical practice. Targeted high-throughput DNA sequencing offers a potential solution and was used to develop a molecular diagnostic screen for patients with retinitis pigmentosa.
METHODS:
A custom sequence capture array was designed to target the coding regions of all known retinitis pigmentosa genes and used to enrich these sequences from DNA samples of five patients. Enriched DNA was subjected to high-throughput sequencing singly or in pools, and sequence variants were identified by alignment of up to 10 million reads per sample to the normal reference sequence. Potential pathogenicity was assessed by functional predictions and frequency in controls.
RESULTS AND CONCLUSIONS:
Known homozygous PDE6B and compound heterozygous CRB1 mutations were detected in two patients. A novel homozygous missense mutation (c.2957A?T; p.N986I) in the cyclic nucleotide gated channel ß1 (CNGB1) gene predicted to have a deleterious effect and absent in 720 control chromosomes was detected in one case in which conventional genetic screening had failed to detect mutations. The detection of known and novel retinitis pigmentosa mutations in this study establishes high-throughput DNA sequencing with DNA pooling as an effective diagnostic tool for heterogeneous genetic diseases.

Wide-scale population genomics of Atlantic bluefin tuna (Thunnus thynnus) inferred by novel high-throughput technology

My PhD project was focused on Atlantic bluefin tuna, Thunnus thynnus, a fishery resource overexploited in the last decades. For a better management of stocks, it was necessary to improve scientific knowledge of this species and to develop novel tools to avoid collapse of this important commercial resource. To do this, we used new high throughput sequencing technologies, as Next Generation Sequencing (NGS), and markers linked to expressed genes, as SNPs (Single Nucleotide Polymorphisms). In this work we applied a combined approach: transcriptomic resources were used to build cDNA libreries from mRNA isolated by muscle, and genomic resources allowed to create a reference backbone for this species lacking of reference genome. All cDNA reads, obtained from mRNA, were mapped against this genome and, employing several bioinformatics tools and different restricted parameters, we achieved a set of contigs to detect SNPs. Once a final panel of 384 SNPs was developed, following the selection criteria, it was genotyped in 960 individuals of Atlantic bluefin tuna, including all size/age classes, from larvae to adults, collected from the entire range of the species. The analysis of obtained data was aimed to evaluate the genetic diversity and the population structure of Thunnus thynnus. We detect a low but significant signal of genetic differentiation among spawning samples, that can suggest the presence of three genetically separate reproduction areas. The adult samples resulted instead genetically undifferentiated between them and from the spawning populations, indicating a presence of panmictic population of adult bluefin tuna in the Mediterranean Sea, without different meta populations.

SNP Discovery in European Anchovy (Engraulis encrasicolus, L) by High-Throughput Transcriptome and Genome Sequencing

12 p.

Transcriptome of embryonic and neonatal mouse cortex by high-throughput RNA sequencing

Brain structure and function experience dramatic changes from embryonic to postnatal development. Microarray analyses have detected differential gene expression at different stages and in disease models, but gene expression information during early brain development is limited. We have generated >27 million reads to identify mRNAs from the mouse cortex for>16,000 genes at either embryonic day 18 (E18) or postnatal day 7 (P7), a period of significant synapto-genesis for neural circuit formation. In addition, we devised strategies to detect alternative splice forms and uncovered more splice variants. We observed differential expression of 3,758 genes between the 2 stages, many with known functions or predicted to be important for neural development. Neurogenesis-related genes, such as those encoding Sox4, Sox11, and zinc-finger proteins, were more highly expressed at E18 than at P7. In contrast, the genes encoding synaptic proteins such as synaptotagmin, complexin 2, and syntaxin were up-regulated from E18 to P7. We also found that several neurological disorder-related genes were highly expressed at E18. Our transcriptome analysis may serve as a blueprint for gene expression pattern and provide functional clues of previously unknown genes and disease-related genes during early brain development.

Translocation capture sequencing: A method for high throughput mapping of chromosomal rearrangements

Chromosomal translocations require formation and joining of DNA double strand breaks (DSBs). These events disrupt the integrity of the genome and are involved in producing leukemias, lymphomas and sarcomas. Translocations are frequent, clonal and recurrent in mature B cell lymphomas, which bear a particularly high DNA damage burden by virtue of activation-induced cytidine deaminase (AID) expression. Despite the ubiquity of genomic rearrangements, the forces that underlie their genesis are not well understood. Here, we provide a detailed description of a new method for studying these events, translocation capture sequencing (TC-Seq). TC-Seq provides the means to document chromosomal rearrangements genome-wide in primary cells, and to discover recombination hotspots. Demonstrating its effectiveness, we successfully estimate the frequency of c-myc/IgH translocations in primary B cells, and identify hotspots of AID-mediated recombination. Furthermore. TC-Seq can be adapted to generate genome-wide rearrangement maps in any cell type and under any condition. (C) 2011 Elsevier B.V. All rights reserved.

Exploring the environmental diversity of kinetoplastid flagellates in the high-throughput DNA sequencing era

The class Kinetoplastea encompasses both free-living and parasitic species from a wide range of hosts. Several representatives of this group are responsible for severe human diseases and for economic losses in agriculture and livestock. While this group encompasses over 30 genera, most of the available information has been derived from the vertebrate pathogenic genera Leishmania and Trypanosoma. Recent studies of the previously neglected groups of Kinetoplastea indicated that the actual diversity is much higher than previously thought. This article discusses the known segment of kinetoplastid diversity and how gene-directed Sanger sequencing and next-generation sequencing methods can help to deepen our knowledge of these interesting protists.

Novel tools for conservation genomics: comparing two high-throughput approaches for SNP discovery in the transcriptome of the European hake

The growing accessibility to genomic resources using next-generation sequencing (NGS) technologies has revolutionized the application of molecular genetic tools to ecology and evolutionary studies in non-model organisms. Here we present the case study of the European hake (Merluccius merluccius), one of the most important demersal resources of European fisheries. Two sequencing platforms, the Roche 454 FLX (454) and the Illumina Genome Analyzer (GAII), were used for Single Nucleotide Polymorphisms (SNPs) discovery in the hake muscle transcriptome. De novo transcriptome assembly into unique contigs, annotation, and in silico SNP detection were carried out in parallel for 454 and GAII sequence data. High-throughput genotyping using the Illumina GoldenGate assay was performed for validating 1,536 putative SNPs. Validation results were analysed to compare the performances of 454 and GAII methods and to evaluate the role of several variables (e.g. sequencing depth, intron-exon structure, sequence quality and annotation). Despite well-known differences in sequence length and throughput, the two approaches showed similar assay conversion rates (approximately 43%) and percentages of polymorphic loci (67.5% and 63.3% for GAII and 454, respectively). Both NGS platforms therefore demonstrated to be suitable for large scale identification of SNPs in transcribed regions of non-model species, although the lack of a reference genome profoundly affects the genotyping success rate. The overall efficiency, however, can be improved using strict quality and filtering criteria for SNP selection (sequence quality, intron-exon structure, target region score).

IMP: Imperial Metagenomics Pipeline for high-throughput sequence data

We have developed an in-house pipeline for the processing and analyses of sequence data generated during Illumina technology-based metagenomic studies of the human gut microbiota. Each component of the pipeline has been selected following comparative analysis of available tools; however, the modular nature of software facilitates replacement of any individual component with an alternative should a better tool become available in due course. The pipeline consists of quality analysis and trimming followed by taxonomic filtering of sequence data allowing reads associated with samples to be binned according to whether they represent human, prokaryotic (bacterial/archaeal), viral, parasite, fungal or plant DNA. Viral, parasite, fungal and plant DNA can be assigned to species level on a presence/absence basis, allowing – for example – identification of dietary intake of plant-based foodstuffs and their derivatives. Prokaryotic DNA is subject to taxonomic and functional analyses, with assignment to taxonomic hierarchies (kingdom, class, order, family, genus, species, strain/subspecies) and abundance determination. After de novo assembly of sequence reads, genes within samples are predicted and used to build a non-redundant catalogue of genes. From this catalogue, per-sample gene abundance can be determined after normalization of data based on gene length. Functional annotation of genes is achieved through mapping of gene clusters against KEGG proteins, and InterProScan. The pipeline is undergoing validation using the human faecal metagenomic data of Qin et al. (2014, Nature 513, 59–64). Outputs from the pipeline allow development of tools for the integration of metagenomic and metabolomic data, moving metagenomic studies beyond determination of gene richness and representation towards microbial-metabolite mapping. There is scope to improve the outputs from viral, parasite, fungal and plant DNA analyses, depending on the depth of sequencing associated with samples. The pipeline can easily be adapted for the analyses of environmental and non-human animal samples, and for use with data generated via non-Illumina sequencing platforms.

EST-PAC HPC - a web portal for high-throughput EST annotation and protein sequence prediction

Expressed Sequence Tags (ESTs) are short DNA sequences generated by sequencing the transcribed cDNAs coming from a gene expression. They can provide significant functional, structural and evolutionary information and thus are a primary resource for gene discovery. EST annotation basically refers to the analysis of unknown ESTs that can be performed by database similarity search for possible identities and database search for functional prediction of translation products. Such kind of annotation typically consists of a series of repetitive tasks which should be automated, and be customizable and amenable to using distributed computing resources. Furthermore, processing of EST data should be done efficiently using a high performance computing platform. In this paper, we describe an EST annotator, EST-PACHPC, which has been developed for harnessing HPC resources potentially from Grid and Cloud systems for high throughput EST annotations. The performance analysis of EST-PACHPC has shown that it provides substantial performance gain in EST annotation.

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.

A high-throughput panel for identifying clinically relevant mutation profiles in melanoma

Success with molecular-based targeted drugs in the treatment of cancer has ignited extensive research efforts within the field of personalized therapeutics. However, successful application of such therapies is dependent on the presence or absence of mutations within the patient's tumor that can confer clinical efficacy or drug resistance. Building on these findings, we developed a high-throughput mutation panel for the identification of frequently occurring and clinically relevant mutations in melanoma. An extensive literature search and interrogation of the Catalogue of Somatic Mutations in Cancer database identified more than 1,000 melanoma mutations. Applying a filtering strategy to focus on mutations amenable to the development of targeted drugs, we initially screened 120 known mutations in 271 samples using the Sequenom MassARRAY system. A total of 252 mutations were detected in 17 genes, the highest frequency occurred in BRAF (n = 154, 57%), NRAS (n = 55, 20%), CDK4 (n = 8, 3%), PTK2B (n = 7, 2.5%), and ERBB4 (n = 5, 2%). Based on this initial discovery screen, a total of 46 assays interrogating 39 mutations in 20 genes were designed to develop a melanoma-specific panel. These assays were distributed in multiplexes over 8 wells using strict assay design parameters optimized for sensitive mutation detection. The final melanoma-specific mutation panel is a cost effective, sensitive, high-throughput approach for identifying mutations of clinical relevance to molecular-based therapeutics for the treatment of melanoma. When used in a clinical research setting, the panel may rapidly and accurately identify potentially effective treatment strategies using novel or existing molecularly targeted drugs

High-throughput vectors for efficient gene silencing in plants

A major challenge in the post-genome era of plant biology is to determine the functions of all genes in the plant genome. A straightforward approach to this problem is to reduce or knockout expression of a gene with the hope of seeing a phenotype that is suggestive of its function. Insertional mutagenesis is a useful tool for this type of study but is limited by gene redundancy, lethal knockouts, non-tagged mutants, and the inability to target the inserted element to a specific gene. The efficacy of gene silencing in plants using inverted-repeat transgene constructs that encode a hairpin RNA (hpRNA) has been demonstrated by a number of groups, and has several advantages over insertional mutagenesis. In this paper we describe two improved pHellsgate vectors that facilitate rapid generation of hpRNA-encoding constructs, pHellsgate 4 allows the production of an hpRNA construct in a single step from a single polymerase chain reaction product, while pHellsgate 8 requires a two-step process via an intermediate vector. We show that these vectors are effective at silencing three endogenous genes in Arabidopsis, FLOWERING LOCUS C, PHYTOENE DESATURASE and ETHYLENE INSENSITIVE 2. We also show that a construct of sequences from two genes silences both genes.