RefSeq: an update on mammalian reference sequences

Arterivirus nsp12 versus the coronavirus nsp16 2'-O-methyltransferase: comparison of the C-terminal cleavage products of two nidovirus pp1ab polyproteins

The 3'-terminal domain of the most conserved ORF1b in three of the four families of the order Nidovirales (except for the family Arteriviridae) encodes a (putative) 2'-O-methyltransferase (2'-O-MTase), known as non structural protein (nsp) 16 in the family Coronaviridae and implicated in methylation of the 5' cap structure of nidoviral mRNAs. As with coronavirus transcripts, arterivirus mRNAs are assumed to possess a 5' cap although no candidate MTases have been identified thus far. To address this knowledge gap, we analysed the uncharacterized nsp12 of arteriviruses, which occupies the ORF1b position equivalent to that of the nidovirus 2'-O-MTase (coronavirus nsp16). In our in-depth bioinformatics analysis of nsp12, the protein was confirmed to be family specific whilst having diverged much further than other nidovirus ORF1b-encoded proteins, including those of the family Coronaviridae. Only one invariant and several partially conserved, predominantly aromatic residues were identified in nsp12, which may adopt a structure with alternating α-helices and β-strands, an organization also found in known MTases. However, no statistically significant similarity was found between nsp12 and the twofold larger coronavirus nsp16, nor could we detect MTase activity in biochemical assays using recombinant equine arteritis virus (EAV) nsp12. Our further analysis established that this subunit is essential for replication of this prototypic arterivirus. Using reverse genetics, we assessed the impact of 25 substitutions at 14 positions, yielding virus phenotypes ranging from WT-like to non-viable. Notably, replacement of the invariant phenylalanine 109 with tyrosine was lethal. We concluded that nsp12 plays an essential role during EAV replication, possibly by acting as a co-factor for another enzyme.

Key challenges for the creation and maintenance of specialist protein resources

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value.

Trends in IT Innovation to Build a Next Generation Bioinformatics Solution to Manage and Analyse Biological Big Data Produced by NGS Technologies

Sequencing the human genome began in 1994, and 10 years of work were necessary in order to provide a nearly complete sequence. Nowadays, NGS technologies allow sequencing of a whole human genome in a few days. This deluge of data challenges scientists in many ways, as they are faced with data management issues and analysis and visualization drawbacks due to the limitations of current bioinformatics tools. In this paper, we describe how the NGS Big Data revolution changes the way of managing and analysing data. We present how biologists are confronted with abundance of methods, tools, and data formats. To overcome these problems, focus on Big Data Information Technology innovations from web and business intelligence. We underline the interest of NoSQL databases, which are much more efficient than relational databases. Since Big Data leads to the loss of interactivity with data during analysis due to high processing time, we describe solutions from the Business Intelligence that allow one to regain interactivity whatever the volume of data is. We illustrate this point with a focus on the Amadea platform. Finally, we discuss visualization challenges posed by Big Data and present the latest innovations with JavaScript graphic libraries.

Transcription factor p63 bookmarks and regulates dynamic enhancers during epidermal differentiation

The transcription factor p63 plays a pivotal role in keratinocyte proliferation and differentiation in the epidermis. However, how p63 regulates epidermal genes during differentiation is not yet clear. Using epigenome profiling of differentiating human primary epidermal keratinocytes, we characterized a catalog of dynamically regulated genes and p63-bound regulatory elements that are relevant for epithelial development and related diseases. p63-bound regulatory elements occur as single or clustered enhancers, and remarkably, only a subset is active as defined by the co-presence of the active enhancer mark histone modification H3K27ac in epidermal keratinocytes. We show that the dynamics of gene expression correlates with the activity of p63-bound enhancers rather than with p63 binding itself. The activity of p63-bound enhancers is likely determined by other transcription factors that cooperate with p63. Our data show that inactive p63-bound enhancers in epidermal keratinocytes may be active during the development of other epithelial-related structures such as limbs and suggest that p63 bookmarks genomic loci during the commitment of the epithelial lineage and regulates genes through temporal- and spatial-specific active enhancers.

A pipeline for the systematic identification of non-redundant full-ORF cDNAs for polymorphic and evolutionary divergent genomes: Application to the ascidian Ciona intestinalis

Genome-wide resources, such as collections of cDNA clones encoding for complete proteins (full-ORF clones), are crucial tools for studying the evolution of gene function and genetic interactions. Non-model organisms, in particular marine organisms, provide a rich source of functional diversity. Marine organism genomes are, however, frequently highly polymorphic and encode proteins that diverge significantly from those of well-annotated model genomes. The construction of full-ORF clone collections from non-model organisms is hindered by the difficulty of predicting accurately the N-terminal ends of proteins, and distinguishing recent paralogs from highly polymorphic alleles. We report a computational strategy that overcomes these difficulties, and allows for accurate gene level clustering of transcript data followed by the automated identification of full-ORFs with correct 5'- and 3'-ends. It is robust to polymorphism, includes paralog calling and does not require evolutionary proximity to well annotated model organisms. We developed this pipeline for the ascidian Ciona intestinalis, a highly polymorphic member of the divergent sister group of the vertebrates, emerging as a powerful model organism to study chordate gene function, Gene Regulatory Networks and molecular mechanisms underlying human pathologies. Using this pipeline we have generated the first full-ORF collection for a highly polymorphic marine invertebrate. It contains 19,163 full-ORF cDNA clones covering 60% of Ciona coding genes, and full-ORF orthologs for approximately half of curated human disease-associated genes.

A modular open platform for systematic functional studies under physiological conditions

Any profound comprehension of gene function requires detailed information about the subcellular localization, molecular interactions and spatio-temporal dynamics of gene products. We developed a multifunctional integrase (MIN) tag for rapid and versatile genome engineering that serves not only as a genetic entry site for the Bxb1 integrase but also as a novel epitope tag for standardized detection and precipitation. For the systematic study of epigenetic factors, including Dnmt1, Dnmt3a, Dnmt3b, Tet1, Tet2, Tet3 and Uhrf1, we generated MIN-tagged embryonic stem cell lines and created a toolbox of prefabricated modules that can be integrated via Bxb1-mediated recombination. We used these functional modules to study protein interactions and their spatio-temporal dynamics as well as gene expression and specific mutations during cellular differentiation and in response to external stimuli. Our genome engineering strategy provides a versatile open platform for efficient generation of multiple isogenic cell lines to study gene function under physiological conditions.

A novel DNA sequence motif in human and mouse genomes

We report a novel DNA sequence motif in human and mouse genomes. This motif has several interesting features indicating that it is highly likely to be an unknown functional sequence element. The motif is highly enriched in promoter regions. Locations of the motif sites in the genome have strong tendency to be clustered together. Motif sites are associated with increased phylogenetic conservation as well as elevated DNase I hypersensitivity (DHS) in ENCODE cell lines. Clustered motif sites are found in promoter regions of a substantial fraction of the protein-coding genes in the genome. All together, these indicate that the motif may have important functions associated with a large number of genes.

Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).

A Combined Omics Approach to Generate the Surface Atlas of Human Naive CD4+ T Cells during Early T-Cell Receptor Activation

Naive CD4(+) T cells are the common precursors of multiple effector and memory T-cell subsets and possess a high plasticity in terms of differentiation potential. This stem-cell-like character is important for cell therapies aiming at regeneration of specific immunity. Cell surface proteins are crucial for recognition and response to signals mediated by other cells or environmental changes. Knowledge of cell surface proteins of human naive CD4(+) T cells and their changes during the early phase of T-cell activation is urgently needed for a guided differentiation of naive T cells and may support the selection of pluripotent cells for cell therapy. Periodate oxidation and aniline-catalyzed oxime ligation technology was applied with subsequent quantitative liquid chromatography-tandem MS to generate a data set describing the surface proteome of primary human naive CD4(+) T cells and to monitor dynamic changes during the early phase of activation. This led to the identification of 173 N-glycosylated surface proteins. To independently confirm the proteomic data set and to analyze the cell surface by an alternative technique a systematic phenotypic expression analysis of surface antigens via flow cytometry was performed. This screening expanded the previous data set, resulting in 229 surface proteins, which were expressed on naive unstimulated and activated CD4(+) T cells. Furthermore, we generated a surface expression atlas based on transcriptome data, experimental annotation, and predicted subcellular localization, and correlated the proteomics result with this transcriptional data set. This extensive surface atlas provides an overall naive CD4(+) T cell surface resource and will enable future studies aiming at a deeper understanding of mechanisms of T-cell biology allowing the identification of novel immune targets usable for the development of therapeutic treatments.

Ratios of Four STAT3 Splice Variants in Human Eosinophils and Diffuse Large B Cell Lymphoma Cells

Signal transducer and activator of transcription 3 (STAT3) is a key mediator of leukocyte differentiation and proliferation. The 3' end of STAT3 transcripts is subject to two alternative splicing events. One results in either full-length STAT3α or in STAT3β, which lacks part of the C-terminal transactivation domain. The other is at a tandem donor (5') splice site and results in the codon for Ser-701 being included (S) or excluded (ΔS). Despite the proximity of Ser-701 to the site of activating phosphorylation at Tyr-705, ΔS/S splicing has barely been studied. Sequencing of cDNA from purified eosinophils revealed the presence of four transcripts (S-α, ΔS-α, S-β, and ΔS-β) rather than the three reported in publically available databases from which ΔS-β is missing. To gain insight into regulation of the two alternative splicing events, we developed a quantitative(q) PCR protocol to compare transcript ratios in eosinophils in which STAT3 is upregulated by cytokines, activated B cell diffuse large B cell Lymphoma (DLBCL) cells in which STAT3 is dysregulated, and in germinal center B cell-like DLBCL cells in which it is not. With the exception of one line of activated B cell DLCBL cells, the four variants were found in roughly the same ratios despite differences in total levels of STAT3 transcripts. S-α was the most abundant, followed by S-β. ΔS-α and ΔS-β together comprised 15.6±4.0 % (mean±SD, n=21) of the total. The percentage of STAT3β variants that were ΔS was 1.5-fold greater than of STAT3α variants that were ΔS. Inspection of Illumina’s “BodyMap” RNA-Seq database revealed that the ΔS variant accounts for 10-26 % of STAT3 transcripts across 16 human tissues, with less variation than three other genes with the identical tandem donor splice site sequence. Thus, it seems likely that all cells contain the S-α, ΔS-α, S-β, and ΔS-β variants of STAT3.

The Shepherds' Tale: A Genome-Wide Study across 9 Dog Breeds Implicates Two Loci in the Regulation of Fructosamine Serum Concentration in Belgian Shepherds

Diabetes mellitus is a serious health problem in both dogs and humans. Certain dog breeds show high prevalence of the disease, whereas other breeds are at low risk. Fructosamine and glycated haemoglobin (HbA1c) are two major biomarkers of glycaemia, where serum concentrations reflect glucose turnover over the past few weeks to months. In this study, we searched for genetic factors influencing variation in serum fructosamine concentration in healthy dogs using data from nine dog breeds. Considering all breeds together, we did not find any genome-wide significant associations to fructosamine serum concentration. However, by performing breed-specific analyses we revealed an association on chromosome 3 (pcorrected ≈ 1:68 × 10-6) in Belgian shepherd dogs of the Malinois subtype. The associated region and its close neighbourhood harbours interesting candidate genes such as LETM1 and GAPDH that are important in glucose metabolism and have previously been implicated in the aetiology of diabetes mellitus. To further explore the genetics of this breed specificity, we screened the genome for reduced heterozygosity stretches private to the Belgian shepherd breed. This revealed a region with reduced heterozygosity that shows a statistically significant interaction (p = 0.025) with the association region on chromosome 3. This region also harbours some interesting candidate genes and regulatory regions but the exact mechanisms underlying the interaction are still unknown. Nevertheless, this finding provides a plausible explanation for breed-specific genetic effects for complex traits in dogs. Shepherd breeds are at low risk of developing diabetes mellitus. The findings in Belgian shepherds could be connected to a protective mechanism against the disease. Further insight into the regulation of glucose metabolism could improve diagnostic and therapeutic methods for diabetes mellitus.

The Confidence Information Ontology: a step towards a standard for asserting confidence in annotations

Biocuration has become a cornerstone for analyses in biology, and to meet needs, the amount of annotations has considerably grown in recent years. However, the reliability of these annotations varies; it has thus become necessary to be able to assess the confidence in annotations. Although several resources already provide confidence information about the annotations that they produce, a standard way of providing such information has yet to be defined. This lack of standardization undermines the propagation of knowledge across resources, as well as the credibility of results from high-throughput analyses. Seeded at a workshop during the Biocuration 2012 conference, a working group has been created to address this problem. We present here the elements that were identified as essential for assessing confidence in annotations, as well as a draft ontology—the Confidence Information Ontology—to illustrate how the problems identified could be addressed. We hope that this effort will provide a home for discussing this major issue among the biocuration community.

Tracker URL:https://github.com/BgeeDB/confidence-information-ontology

Ontology URL:https://raw.githubusercontent.com/BgeeDB/confidence-information-ontology/master/src/ontology/cio-simple.obo

Characterisation of hepcidin response to holotransferrin treatment in CHO TRVb-1 cells

Iron overload coupled with low hepcidin levels are characteristics of hereditary haemochromatosis. To understand the role of transferrin receptor (TFR) and intracellular iron in hepcidin secretion, Chinese hamster ovary transferrin receptor variant (CHO TRVb-1) cells were used that express iron-response-element-depleted human TFRC mRNA (TFRC∆IRE). Results showed that CHO TRVb-1 cells expressed higher basal levels of cell-surface TFR1 than HepG2 cells (2.2-fold; p < 0.01) and following 5 g/L holotransferrin treatment maintained constitutive over-expression at 24h and 48 h, contrasting the HepG2 cells where the receptor levels significantly declined. Despite this, the intracellular iron content was neither higher than HepG2 cells nor increased over time under basal or holotransferrin-treated conditions. Interestingly, hepcidin secretion in CHO TRVb-1 cells exceeded basal levels at all time-points (p < 0.02) and matched levels in HepG2 cells following treatment. While TFRC mRNA expression showed expected elevation (2h, p < 0.03; 4h; p < 0.05), slc40a1 mRNA expression was also elevated (2 h, p < 0.05; 4 h, p < 0.03), unlike the HepG2 cells. In conclusion, the CHO TRVb-1 cells prevented cellular iron-overload by elevating slc40a1 expression, thereby highlighting its significance in the absence of iron-regulated TFRC mRNA. Furthermore, hepcidin response to holotransferrin treatment was similar to HepG2 cells and resembled the human physiological response.

MIsoMine: a genome-scale high-resolution data portal of expression, function and networks at the splice isoform level in the mouse

Products of multiexon genes, especially in higher organisms, are a mixture of isoforms with different or even opposing functions, and therefore need to be treated separately. However, most studies and available resources such as Gene Ontology provide only gene-level function annotations, and therefore lose the differential information at the isoform level. Here we report MIsoMine, a high-resolution portal to multiple levels of functional information of alternatively spliced isoforms in the mouse. This data portal provides tissue-specific expression patterns and co-expression networks, along with such previously published functional genomic data as protein domains, predicted isoform-level functions and functional relationships. The core utility of MIsoMine is allowing users to explore a preprocessed, quality-controlled set of RNA-seq data encompassing diverse tissues and cell lineages. Tissue-specific co-expression networks were established, allowing a 2D ranking of isoforms and tissues by co-expression patterns. The results of the multiple isoforms of the same gene are presented in parallel to facilitate direct comparison, with cross-talking to prioritized functions at the isoform level. MIsoMine provides the first isoform-level resolution effort at genome-scale. We envision that this data portal will be a valuable resource for exploring functional genomic data, and will complement the existing functionalities of the mouse genome informatics database and the gene expression database for the laboratory mouse.

Database URL: http://guanlab.ccmb.med.umich.edu/misomine/

Targeted Integration of RNA-Seq and Metabolite Data to Elucidate Curcuminoid Biosynthesis in Four Curcuma Species

Curcuminoids, namely curcumin and its analogs, are secondary metabolites that act as the primary active constituents of turmeric (Curcuma longa). The contents of these curcuminoids vary among species in the genus Curcuma. For this reason, we compared two wild strains and two cultivars to understand the differences in the synthesis of curcuminoids. Because the fluxes of metabolic reactions depend on the amounts of their substrate and the activity of the catalysts, we analyzed the metabolite concentrations and gene expression of related enzymes. We developed a method based on RNA sequencing (RNA-Seq) analysis that focuses on a specific set of genes to detect expression differences between species in detail. We developed a 'selection-first' method for RNA-Seq analysis in which short reads are mapped to selected enzymes in the target biosynthetic pathways in order to reduce the effect of mapping errors. Using this method, we found that the difference in the contents of curcuminoids among the species, as measured by gas chromatography-mass spectrometry, could be explained by the changes in the expression of genes encoding diketide-CoA synthase, and curcumin synthase at the branching point of the curcuminoid biosynthesis pathway.

Under-detection of endospore-forming Firmicutes in metagenomic data

Microbial diversity studies based on metagenomic sequencing have greatly enhanced our knowledge of the microbial world. However, one caveat is the fact that not all microorganisms are equally well detected, questioning the universality of this approach. Firmicutes are known to be a dominant bacterial group. Several Firmicutes species are endospore formers and this property makes them hardy in potentially harsh conditions, and thus likely to be present in a wide variety of environments, even as residents and not functional players. While metagenomic libraries can be expected to contain endospore formers, endospores are known to be resilient to many traditional methods of DNA isolation and thus potentially undetectable. In this study we evaluated the representation of endospore-forming Firmicutes in 73 published metagenomic datasets using two molecular markers unique to this bacterial group (spo0A and gpr). Both markers were notably absent in well-known habitats of Firmicutes such as soil, with spo0A found only in three mammalian gut microbiomes. A tailored DNA extraction method resulted in the detection of a large diversity of endospore-formers in amplicon sequencing of the 16S rRNA and spo0A genes. However, shotgun classification was still poor with only a minor fraction of the community assigned to Firmicutes. Thus, removing a specific bias in a molecular workflow improves detection in amplicon sequencing, but it was insufficient to overcome the limitations for detecting endospore-forming Firmicutes in whole-genome metagenomics. In conclusion, this study highlights the importance of understanding the specific methodological biases that can contribute to improve the universality of metagenomic approaches.

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Endospore formers were under-detected by profile analysis of sporulation genes in metagenomes.

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Endospore formers were absent even from those habitats known to harbor them.

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A tailored DNA extraction method improved detection in amplicon sequencing.

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Ameliorated DNA extraction did not improve shotgun classification.

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Endospore-formers represent an undetectable community fraction by metagenomic approaches.

GWIPS-viz as a tool for exploring ribosome profiling evidence supporting the synthesis of alternative proteoforms

The boundaries of protein coding sequences are more difficult to define at the 5′ end than at the 3′ end due to potential multiple translation initiation sites (TISs). Even in the presence of phylogenetic data, the use of sequence information only may not be sufficient for the accurate identification of TISs. Traditional proteomics approaches may also fail because the N‐termini of newly synthesized proteins are often processed. Thus ribosome profiling (ribo‐seq), producing a snapshot of the ribosome distribution across the entire transcriptome, is an attractive experimental technique for the purpose of TIS location exploration. The GWIPS‐viz (Genome Wide Information on Protein Synthesis visualized) browser (http://gwips.ucc.ie) provides free access to the genomic alignments of ribo‐seq data and corresponding mRNA‐seq data along with relevant annotation tracks. In this brief, we illustrate how GWIPS‐viz can be used to explore the ribosome occupancy at the 5′ ends of protein coding genes to assess the activity of AUG and non‐AUG TISs responsible for the synthesis of proteoforms with alternative or heterogeneous N‐termini. The presence of ribo‐seq tracks for various organisms allows for cross‐species comparison of orthologous genes and the availability of datasets from multiple laboratories permits the assessment of the technical reproducibility of the ribosome densities.

mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data

Background

Over-representation of predicted miRNA targets in sets of genes regulated by a given transcription factor (e.g. as defined by ChIP-sequencing experiments) helps to identify biologically relevant miRNA targets and is useful to get insight into post-transcriptional regulation.

Findings

To facilitate the application of this approach we have created the mBISON web-application. mBISON calculates the significance of over-representation of miRNA targets in a given non-ranked gene set. The gene set can be specified either by a list of genes or by one or more ChIP-seq datasets followed by a user-defined peak-gene association procedure. mBISON is based on predictions from TargetScan and uses a randomization step to calculate False-Discovery-Rates for each miRNA, including a correction for gene set specific properties such as 3’UTR length. The tool can be accessed from the following web-resource: http://cbdm.mdc-berlin.de/~mgebhardt/cgi-bin/mbison/home.

Conclusion

mBISON is a web-application that helps to extract functional information about miRNAs from gene lists, which is in contrast to comparable applications easy to use by everyone and can be applied on ChIP-seq data directly.

Genetics of RA susceptibility, what comes next?

Genome-wide association studies (GWASs) have been used to great effect to identify genetic susceptibility loci for complex disease. A series of GWAS and meta-analyses have informed the discovery of over 100 loci for rheumatoid arthritis (RA). In common with findings in other autoimmune diseases the lead signals for the majority of these loci do not map to known gene sequences. In order to realise the benefit of investment in GWAS studies it is vital we determine how disease associated alleles function to influence disease processes. This is leading to rapid development in our knowledge as to the function of non-coding regions of the genome. Here we consider possible functional mechanisms for intergenic RA-associated variants which lie within lncRNA sequences.

Increased abundance of ADAM9 transcripts in the blood is associated with tissue damage

Background: Members of the ADAM (a disintegrin and metalloprotease domain) family have emerged as critical regulators of cell-cell signaling during development and homeostasis. ADAM9 is consistently overexpressed in various human cancers, and has been shown to play an important role in tumorigenesis. However, little is known about the involvement of ADAM9 during immune-mediated processes. Results: Mining of an extensive compendium of transcriptomic datasets identified important gaps in knowledge regarding the possible role of ADAM9 in immunological homeostasis and inflammation: 1) The abundance of ADAM9 transcripts in the blood was increased in patients with acute infection but, 2) changed very little after in vitro exposure to a wide range of pathogen-associated molecular patterns (PAMPs). 3) Furthermore it was found to increase significantly in subjects as a result of tissue injury or tissue remodeling, in absence of infectious processes. Conclusions: Our findings indicate that ADAM9 may constitute a valuable biomarker for the assessment of tissue damage, especially in clinical situations where other inflammatory markers are confounded by infectious processes.

Increased abundance of ADAM9 transcripts in the blood is associated with tissue damage

Background: Members of the ADAM (a disintegrin and metalloprotease domain) family have emerged as critical regulators of cell-cell signaling during development and homeostasis. ADAM9 is consistently overexpressed in various human cancers, and has been shown to play an important role in tumorigenesis. However, little is known about the involvement of ADAM9 during immune-mediated processes.

Results: Mining of an extensive compendium of transcriptomic datasets identified important gaps in knowledge regarding the possible role of ADAM9 in immunological homeostasis and inflammation: 1) The abundance of ADAM9 transcripts in the blood was increased in patients with acute infection but, 2) changed very little after in vitro exposure to a wide range of pathogen-associated molecular patterns (PAMPs). 3) Furthermore it was found to increase significantly in subjects as a result of tissue injury or tissue remodeling, in absence of infectious processes.

Conclusions: Our findings indicate that ADAM9 may constitute a valuable biomarker for the assessment of tissue damage, especially in clinical situations where other inflammatory markers are confounded by infectious processes.

GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles

Motivation: In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually.

Results: Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples.

Availability and Implementation: Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/.

Contact:umaan@leeds.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Necessary relations for nucleotide frequencies

Genome composition analysis of di-, tri- and tetra-nucleotide frequencies is known to be evolutionarily informative, and useful in metagenomic studies, where binning of raw sequence data is often an important first step. Patterns appearing in genome composition analysis may be due to evolutionary processes or purely mathematical relations. For example, the total number of dinucleotides in a sequence is equal to the sum of the individual totals of the sixteen types of dinucleotide, and this is entirely independent of any assumptions made regarding mutation or selection, or indeed any physical or chemical process. Before any statistical analysis can be attempted, a knowledge of all necessary mathematical relations is required. I show that 25% of di-, tri- and tetra-nucleotide frequencies can be written as simple sums and differences of the remainder. The vast majority of organisms have circular genomes, for which these relations are exact and necessary. In the case of linear molecules, the absolute error is very nearly zero, and does not grow with contiguous sequence length. As a result of the new, necessary relations presented here, the foundations of the statistical analysis of di-, tri- and tetra-nucleotide frequencies, and k-mer analysis in general, need to be revisited.

Whole-exome characterization of pancreatic neuroendocrine tumor cell lines BON-1 and QGP-1

The human BON-1 and QGP-1 cell lines are two frequently used models in pancreatic neuroendocrine tumor (PNET) research. Data on the whole-exome genetic constitution of these cell lines is largely lacking. This study presents, to our knowledge, the first whole-exome profile of the BON-1 and QGP-1 cell lines. Cell line identity was confirmed by short tandem repeat profiling. Using GTG-banding and a CytoSNP-12v2 Beadchip array, cell line ploidy and chromosomal alterations were determined in BON-1 and QGP-1. The exomes of both cell lines were sequenced on Ilumina's HiSeq next-generation sequencing (NGS) platform. Single-nucleotide variants (SNVs) and insertions and deletions (indels) were detected using the Genome Analysis ToolKit. SNVs were validated by Sanger sequencing. Ploidy of BON-1 and QGP-1 was 3 and 4 respectively, with long stretches of loss of heterozygosity across multiple chromosomes, which is associated with aggressive tumor behavior. In BON-1, 57 frameshift indels and 1725 possible protein-altering SNVs were identified in the NGS data. In the QGP-1 cell line, 56 frameshift indels and 1095 SNVs were identified. ATRX, a PNET-associated gene, was mutated in both cell lines, while mutation of TSC2 was detected in BON-1. A mutation in NRAS was detected in BON-1, while KRAS was mutated in QGP-1, implicating aberrations in the RAS pathway in both cell lines. Homozygous mutations in TP53 with possible loss of function were identified in both cell lines. Various MUC genes, implicated in cell signaling, lubrication and chemical barriers, which are frequently expressed in PNET tissue samples, showed homozygous protein-altering SNVs in the BON-1 and QGP-1 cell lines.

The KDM5 family of histone demethylases as targets in oncology drug discovery

There is growing evidence for a causal role of the KDM5 family of histone demethylases in human cancer. In particular, KDM5A (JARID1A/RBP2) and KDM5B (JARID1B/PLU1) contribute to cancer cell proliferation, reduce the expression of tumor suppressor genes, promote the development of drug tolerance and maintain tumor-initiating cells. KDM5 enzymes remove tri- and di-methylations of lysine 4 of histone H3 - modifications that occur at the start site of transcription in actively transcribed genes. However, the importance of the histone demethylase activity of KDM5 proteins for cancer cells has not been resolved so far. The currently available approaches suppress or remove the targeted proteins and thereby affect their putative functions as structural components and recruitment factors for other chromatin-associated proteins. Therefore, the development of specific enzymatic inhibitors for KDM5 will promote our understanding of the biological role of their catalytic activity and yield potential novel anticancer therapeutics.

Methylation-associated partial down-regulation of mesothelin causes resistance to anti-mesothelin immunotoxins in a pancreatic cancer cell line

Anti-mesothelin Pseudomonas exotoxin A-based recombinant immunotoxins (RITs) present a potential treatment modality for pancreatic ductal adenocarcinoma (PDAC). To study mechanisms of resistance, the sensitive PDAC cell line KLM-1 was intermittently exposed to the anti-mesothelin SS1-LR-GGS RIT. Surviving cells were resistant to various anti-mesothelin RITs (IC50s >1 μg/ml), including the novel de-immunized RG7787. These resistant KLM-1-R cells were equally sensitive to the anti-CD71 HB21(Fv)-PE40 RIT as KLM-1, indicating resistance was specific to anti-mesothelin RITs. Mesothelin gene expression was partially down-regulated in KLM-1-R, resulting in 5-fold lower surface protein levels and decreased cellular uptake of RG7787 compared to KLM-1. Bisulfite sequencing analysis found that the mesothelin promoter region was significantly more methylated in KLM-1-R (59 ± 3.6%) compared to KLM-1 (41 ± 4.8%), indicating hypermethylation as a mechanism of mesothelin downregulation. The DNA methyltransferase inhibitor 5-azacytidine restored original mesothelin surface expression to more than half in KLM-1-R and increased sensitivity to RG7787 (IC50 = 722.4 ± 232.6 ng/ml), although cells remained significantly less sensitive compared to parental KLM-1 cells (IC50 = 4.41 ± 0.38 ng/ml). Mesothelin cDNA introduction in KLM-1-R led to 5-fold higher surface protein levels and significantly higher RG7887 uptake compared to KLM-1. As a result, the original sensitivity to RG7787 was fully restored (IC50 = 4.49 ± 1.11 ng/ml). A significantly higher RG7787 uptake was thus required to reach the original cytotoxicity in resistant cells, hinting that intracellular RIT trafficking is also a limiting factor. RNA deep sequencing analysis of KLM-1 and KLM-1-R cells supported our experimental findings; compared to KLM-1, resistant cells displayed differential expression of genes linked to intracellular transport and an expression pattern that matched a more general hypermethylation status. In conclusion, resistance to anti-mesothelin RITs in KLM-1 is linked to a methylation-associated down-regulation of mesothelin, while aberrations in RIT trafficking could also play a role.

De novo origin of VCY2 from autosome to Y-transposed amplicon

The formation of new genes is a primary driving force of evolution in all organisms. The de novo evolution of new genes from non-protein-coding genomic regions is emerging as an important additional mechanism for novel gene creation. Y chromosomes underlie sex determination in mammals and contain genes that are required for male-specific functions. In this study, a search was undertaken for Y chromosome de novo genes derived from non-protein-coding sequences. The Y chromosome orphan gene variable charge, Y-linked (VCY)2, is an autosome-derived gene that has sequence similarity to large autosomal fragments but lacks an autosomal protein-coding homolog. VCY2 locates in the amplicon containing long DNA fragments that were transposed from autosomes to the Y chromosome before the ape-monkey split. We confirmed that VCY2cannot be encoded by autosomes due to the presence of multiple disablers that disrupt the open reading frame, such as the absence of start or stop codons and the presence of premature stop codons. Similar observations have been made for homologs in the autosomes of the chimpanzee, gorilla, rhesus macaque, baboon and out-group marmoset, which suggests that there was a non-protein-coding ancestral VCY2 that was common to apes and monkeys that predated the transposition event. Furthermore, while protein-coding orthologs are absent, a putative non-protein-coding VCY2 with conserved disablers was identified in the rhesus macaque Y chromosome male-specific region. This finding implies that VCY2 might have not acquired its protein-coding ability before the ape-monkey split. VCY2 encodes a testis-specific expressed protein and is involved in the pathologic process of male infertility, and the acquisition of this gene might improve male fertility. This is the first evidence that de novo genes can be generated from transposed autosomal non-protein-coding segments, and this evidence provides novel insights into the evolutionary history of the Y chromosome.

Global insights into the Chinese hamster and CHO cell transcriptomes

Transcriptomics is increasingly being used on Chinese hamster ovary (CHO) cells to unveil physiological insights related to their performance during production processes. The rich transcriptome data can be exploited to provide impetus for systems investigation such as modeling the central carbon metabolism or glycosylation pathways, or even building genome-scale models. To harness the power of transcriptome assays, we assembled and annotated a set of RNA-Seq data from multiple CHO cell lines and Chinese hamster tissues, and constructed a DNA microarray. The identity of genes involved in major functional pathways and their transcript levels generated in this study will serve as a reference for future studies employing kinetic models. In particular, the data on glycolysis and glycosylation pathways indicate that the variability of gene expression level among different cell lines and tissues may contribute to their differences in metabolism and glycosylation patterns. Thereby, these insights can potentially lead to opportunities for cell engineering. This repertoire of transcriptome data also enables the identification of potential sequence variants in cell lines and allows tracing of cell lineages. Overall the study is an illustration of the potential benefit of RNA-Seq that is yet to be exploited.

Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing

We compared quantitative RT-PCR (qRT-PCR), RNA-seq and capture sequencing (CaptureSeq) in terms of their ability to assemble and quantify long noncoding RNAs and novel coding exons across 20 human tissues. CaptureSeq was superior for the detection and quantification of genes with low expression, showed little technical variation and accurately measured differential expression. This approach expands and refines previous annotations and simultaneously generates an expression atlas.

Reproducible Analysis of Sequencing-Based RNA Structure Probing Data with User-Friendly Tools

RNA structure-probing data can improve the prediction of RNA secondary and tertiary structure and allow structural changes to be identified and investigated. In recent years, massive parallel sequencing has dramatically improved the throughput of RNA structure probing experiments, but at the same time also made analysis of the data challenging for scientists without formal training in computational biology. Here, we discuss different strategies for data analysis of massive parallel sequencing-based structure-probing data. To facilitate reproducible and standardized analysis of this type of data, we have made a collection of tools, which allow raw sequencing reads to be converted to normalized probing values using different published strategies. In addition, we also provide tools for visualization of the probing data in the UCSC Genome Browser and for converting RNA coordinates to genomic coordinates and vice versa. The collection is implemented as functions in the R statistical environment and as tools in the Galaxy platform, making them easily accessible for the scientific community. We demonstrate the usefulness of the collection by applying it to the analysis of sequencing-based hydroxyl radical probing data and comparing different normalization strategies.

Predicting the human epigenome from DNA motifs

The epigenome is established and maintained by the site-specific recruitment of chromatin-modifying enzymes and their cofactors. Identifying the cis elements that regulate epigenomic modification is critical for understanding the regulatory mechanisms that control gene expression patterns. We present Epigram, an analysis pipeline that predicts histone modification and DNA methylation patterns from DNA motifs. The identified cis elements represent interactions with the site-specific DNA-binding factors that establish and maintain epigenomic modifications. We cataloged the cis elements in embryonic stem cells and four derived lineages and found numerous motifs that have location preference, such as at the center of H3K27ac or at the edges of H3K4me3 and H3K9me3, which provides mechanistic insight about the shaping of the epigenome. The Epigram pipeline and predictive motifs are at http://wanglab.ucsd.edu/star/epigram/.

microRNAs regulate cell-to-cell variability of endogenous target gene expression in developing mouse thymocytes

The development and homeostasis of multicellular organisms relies on gene regulation within individual constituent cells. Gene regulatory circuits that increase the robustness of gene expression frequently incorporate microRNAs as post-transcriptional regulators. Computational approaches, synthetic gene circuits and observations in model organisms predict that the co-regulation of microRNAs and their target mRNAs can reduce cell-to-cell variability in the expression of target genes. However, whether microRNAs directly regulate variability of endogenous gene expression remains to be tested in mammalian cells. Here we use quantitative flow cytometry to show that microRNAs impact on cell-to-cell variability of protein expression in developing mouse thymocytes. We find two distinct mechanisms that control variation in the activation-induced expression of the microRNA target CD69. First, the expression of miR-17 and miR-20a, two members of the miR-17-92 cluster, is co-regulated with the target mRNA Cd69 to form an activation-induced incoherent feed-forward loop. Another microRNA, miR-181a, acts at least in part upstream of the target mRNA Cd69 to modulate cellular responses to activation. The ability of microRNAs to render gene expression more uniform across mammalian cell populations may be important for normal development and for disease.

microRNAs are integral to many developmental processes and may 'canalise' development by reducing cell-to-cell variation in gene expression. This idea is supported by computational studies that have modeled the impact of microRNAs on the expression of their targets and the construction of artificial incoherent feedforward loops using synthetic biology tools. Here we show that this interesting principle of microRNA regulation actually occurs in a mammalian developmental system. We examine cell-to-cell variation of protein expression in developing mouse thymocytes by quantitative flow cytometry and find that the absence of microRNAs results in increased cell-to-cell variation in the expression of the microRNA target Cd69. Mechanistically, T cell receptor signaling induces both Cd69 and miR-17 and miR-20a, two microRNAs that target Cd69. Co-regulation of microRNAs and their target mRNA dampens the expression of Cd69 and forms an incoherent feedforward loop that reduces cell-to-cell variation on CD69 expression. In addition, miR-181, which also targets Cd69 and is a known modulator of T cell receptor signaling, also affects cell-to-cell variation of CD69 expression. The ability of microRNAs to control the uniformity of gene expression across mammalian cell populations may be important for normal development and for disease.

Rock, paper, scissors: harnessing complementarity in ortholog detection methods improves comparative genomic inference

Ortholog detection (OD) is a lynchpin of most statistical methods in comparative genomics. This task involves accurately identifying genes across species that descend from a common ancestral sequence. OD methods comprise a wide variety of approaches, each with their own benefits and costs under a variety of evolutionary and practical scenarios. In this article, we examine the proteomes of ten mammals by using four methodologically distinct, rigorously filtered OD methods. In head-to-head comparisons, we find that these algorithms significantly outperform one another for 38–45% of the genes analyzed. We leverage this high complementarity through the development MOSAIC, or Multiple Orthologous Sequence Analysis and Integration by Cluster optimization, the first tool for integrating methodologically diverse OD methods. Relative to the four methods examined, MOSAIC more than quintuples the number of alignments for which all species are present while simultaneously maintaining or improving functional-, phylogenetic-, and sequence identity-based measures of ortholog quality. Further, this improvement in alignment quality yields more confidently aligned sites and higher levels of overall conservation, while simultaneously detecting of up to 180% more positively selected sites. We close by highlighting a MOSAIC-specific positively selected sites near the active site of TPSAB1, an enzyme linked to asthma, heart disease, and irritable bowel disease. MOSAIC alignments, source code, and full documentation are available at http://pythonhosted.org/bio-MOSAIC.

Biological databases for human research

The completion of the Human Genome Project lays a foundation for systematically studying the human genome from evolutionary history to precision medicine against diseases. With the explosive growth of biological data, there is an increasing number of biological databases that have been developed in aid of human-related research. Here we present a collection of human-related biological databases and provide a mini-review by classifying them into different categories according to their data types. As human-related databases continue to grow not only in count but also in volume, challenges are ahead in big data storage, processing, exchange and curation.

Bioinformatics approaches for the functional interpretation of protein lists: from ontology term enrichment to network analysis

The main result of a great deal of the published proteomics studies is a list of identified proteins, which then needs to be interpreted in relation to the research question and existing knowledge. In the early days of proteomics this interpretation was only based on expert insights, acquired by digesting a large amount of relevant literature. With the growing size and complexity of the experimental datasets, many computational techniques, databases, and tools have claimed a central role in this task. In this review we discuss commonly and less commonly used methods to functionally interpret experimental proteome lists and compare them with available knowledge. We first address several functional analysis and enrichment techniques based on ontologies and literature. Then we outline how various types of network and pathway information can be used. While the problem of functional interpretation of proteome data is to an extent equivalent to the interpretation of transcriptome or other ''omics'' data, this paper addresses some of the specific challenges and solutions of the proteomics field.

Systematic review and meta-analysis of Japanese familial Alzheimer's disease and FTDP-17

Mutations in APP, PSEN1 and PSEN2 as the genetic causes of familial Alzheimer's disease (FAD) have been found in various ethnic populations. A substantial number of FAD pedigrees with mutations have been reported in the Japanese population; however, it remains unclear whether the genetic and clinical features of FAD in the Japanese population differ from those in other populations. To address this issue, we conducted a systematic review and meta-analysis of Japanese FAD and frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17) by literature search. Using this analysis, we identified 39 different PSEN1 mutations in 140 patients, 5 APP mutations in 35 patients and 16 MAPT mutations in 84 patients. There was no PSEN2 mutation among Japanese patients. The age at onset in Japanese FAD patients with PSEN1 mutations was significantly younger than that in patients with APP mutations. Kaplan–Meier analysis revealed that patients with MAPT mutations showed a shorter survival than patients with PSEN1 or APP mutations. Patients with mutations in different genes exhibit characteristic clinical presentations, suggesting that mutations in causative genes may modify the clinical presentations. By collecting and cataloging genetic and clinical information on Japanese FAD and FTDP-17, we developed an original database designated as Japanese Familial Alzheimer's Disease Database, which is accessible at http://alzdb.bri.niigata-u.ac.jp/.

Comprehensive, structurally-informed alignment and phylogeny of vertebrate biogenic amine receptors

Biogenic amine receptors play critical roles in regulating behavior and physiology in both vertebrates and invertebrates, particularly within the central nervous system. Members of the G-protein coupled receptor (GPCR) family, these receptors interact with endogenous bioamine ligands such as dopamine, serotonin, and epinephrine, and are targeted by a wide array of pharmaceuticals. Despite the clear clinical and biological importance of these receptors, their evolutionary history remains poorly characterized. In particular, the relationships among biogenic amine receptors and any specific evolutionary constraints acting within distinct receptor subtypes are largely unknown. To advance and facilitate studies in this receptor family, we have constructed a comprehensive, high-quality sequence alignment of vertebrate biogenic amine receptors. In particular, we have integrated a traditional multiple sequence approach with robust structural domain predictions to ensure that alignment columns accurately capture the highly-conserved GPCR structural domains, and we demonstrate how ignoring structural information produces spurious inferences of homology. Using this alignment, we have constructed a structurally-partitioned maximum-likelihood phylogeny from which we deduce novel biogenic amine receptor relationships and uncover previously unrecognized lineage-specific receptor clades. Moreover, we find that roughly 1% of the 3039 sequences in our final alignment are either misannotated or unclassified, and we propose updated classifications for these receptors. We release our comprehensive alignment and its corresponding phylogeny as a resource for future research into the evolution and diversification of biogenic amine receptors.

Nijmegen breakage syndrome detected by newborn screening for T cell receptor excision circles (TRECs)

Purpose

Severe combined immunodeficiency (SCID) encompasses a group of disorders characterized by reduced or absent T-cell number and function and identified by newborn screening utilizing T-cell receptor excision circles (TRECs). This screening has also identified infants with T lymphopenia who lack mutations in typical SCID genes. We report an infant with low TRECs and non-SCID T lymphopenia, who proved upon whole exome sequencing to have Nijmegen breakage syndrome (NBS).

Methods

Exome sequencing of DNA from the infant and his parents was performed. Genomic analysis revealed deleterious variants in the NBN gene. Confirmatory testing included Sanger sequencing and immunoblotting and radiosensitivity testing of patient lymphocytes.

Results

Two novel nonsense mutations in NBN were identified in genomic DNA from the family. Immunoblotting showed absence of nibrin protein. A colony survival assay demonstrated radiosensitivity comparable to patients with ataxia telangiectasia.

Conclusions

Although TREC screening was developed to identify newborns with SCID, it has also identified T lymphopenic disorders that may not otherwise be diagnosed until later in life. Timely identification of an infant with T lymphopenia allowed for prompt pursuit of underlying etiology, making possible a diagnosis of NBS, genetic counseling, and early intervention to minimize complications.

Topological analysis of Hedgehog acyltransferase, a multipalmitoylated transmembrane protein

Hedgehog proteins are secreted morphogens that play critical roles in development and disease. During maturation of the proteins through the secretory pathway, they are modified by the addition of N-terminal palmitic acid and C-terminal cholesterol moieties, both of which are critical for their correct function and localization. Hedgehog acyltransferase (HHAT) is the enzyme in the endoplasmic reticulum that palmitoylates Hedgehog proteins, is a member of a small subfamily of membrane-bound O-acyltransferase proteins that acylate secreted proteins, and is an important drug target in cancer. However, little is known about HHAT structure and mode of function. We show that HHAT is comprised of ten transmembrane domains and two reentrant loops with the critical His and Asp residues on opposite sides of the endoplasmic reticulum membrane. We further show that HHAT is palmitoylated on multiple cytosolic cysteines that maintain protein structure within the membrane. Finally, we provide evidence that mutation of the conserved His residue in the hypothesized catalytic domain results in a complete loss of HHAT palmitoylation, providing novel insights into how the protein may function in vivo.

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population.

Is the growth rate of Protein Data Bank sufficient to solve the protein structure prediction problem using template-based modeling?

The Protein Data Bank (PDB) undergoes an exponential expansion in terms of the number of macromolecular structures deposited every year. A pivotal question is how this rapid growth of structural information improves the quality of three-dimensional models constructed by contemporary bioinformatics approaches. To address this problem, we performed a retrospective analysis of the structural coverage of a representative set of proteins using remote homology detected by COMPASS and HHpred. We show that the number of proteins whose structures can be confidently predicted increased during a 9-year period between 2005 and 2014 on account of the PDB growth alone. Nevertheless, this encouraging trend slowed down noticeably around the year 2008 and has yielded insignificant improvements ever since. At the current pace, it is unlikely that the protein structure prediction problem will be solved in the near future using existing template-based modeling techniques. Therefore, further advances in experimental structure determination, qualitatively better approaches in fold recognition, and more accurate template-free structure prediction methods are desperately needed.

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population.

The terminal enzymes of cholesterol synthesis, DHCR24 and DHCR7, interact physically and functionally

Cholesterol is essential to human health, and its levels are tightly regulated by a balance of synthesis, uptake, and efflux. Cholesterol synthesis requires the actions of more than twenty enzymes to reach the final product, through two alternate pathways. Here we describe a physical and functional interaction between the two terminal enzymes. 24-Dehydrocholesterol reductase (DHCR24) and 7-dehydrocholesterol reductase (DHCR7) coimmunoprecipitate, and when the DHCR24 gene is knocked down by siRNA, DHCR7 activity is also ablated. Conversely, overexpression of DHCR24 enhances DHCR7 activity, but only when a functional form of DHCR24 is used. DHCR7 is important for both cholesterol and vitamin D synthesis, and we have identified a novel layer of regulation, whereby its activity is controlled by DHCR24. This suggests the existence of a cholesterol "metabolon", where enzymes from the same metabolic pathway interact with each other to provide a substrate channeling benefit. We predict that other enzymes in cholesterol synthesis may similarly interact, and this should be explored in future studies.

An internal ribosome entry site in the 5' untranslated region of epidermal growth factor receptor allows hypoxic expression

The expression of epidermal growth factor receptor (EGFR/ERBB1/HER1) is implicated in the progress of numerous cancers, a feature that has been exploited in the development of EGFR antibodies and EGFR tyrosine kinase inhibitors as anti-cancer drugs. However, EGFR also has important normal cellular functions, leading to serious side effects when EGFR is inhibited. One damaging characteristic of many oncogenes is the ability to be expressed in the hypoxic conditions associated with the tumour interior. It has previously been demonstrated that expression of EGFR is maintained in hypoxic conditions via an unknown mechanism of translational control, despite global translation rates generally being attenuated under hypoxic conditions. In this report, we demonstrate that the human EGFR 5′ untranslated region (UTR) sequence can initiate the expression of a downstream open reading frame via an internal ribosome entry site (IRES). We show that this effect is not due to either cryptic promoter activity or splicing events. We have investigated the requirement of the EGFR IRES for eukaryotic initiation factor 4A (eIF4A), which is an RNA helicase responsible for processing RNA secondary structure as part of translation initiation. Treatment with hippuristanol (a potent inhibitor of eIF4A) caused a decrease in EGFR 5′ UTR-driven reporter activity and also a reduction in EGFR protein level. Importantly, we show that expression of a reporter gene under the control of the EGFR IRES is maintained under hypoxic conditions despite a fall in global translation rates.

Translation of 5' leaders is pervasive in genes resistant to eIF2 repression

Eukaryotic cells rapidly reduce protein synthesis in response to various stress conditions. This can be achieved by the phosphorylation-mediated inactivation of a key translation initiation factor, eukaryotic initiation factor 2 (eIF2). However, the persistent translation of certain mRNAs is required for deployment of an adequate stress response. We carried out ribosome profiling of cultured human cells under conditions of severe stress induced with sodium arsenite. Although this led to a 5.4-fold general translational repression, the protein coding open reading frames (ORFs) of certain individual mRNAs exhibited resistance to the inhibition. Nearly all resistant transcripts possess at least one efficiently translated upstream open reading frame (uORF) that represses translation of the main coding ORF under normal conditions. Site-specific mutagenesis of two identified stress resistant mRNAs (PPP1R15B and IFRD1) demonstrated that a single uORF is sufficient for eIF2-mediated translation control in both cases. Phylogenetic analysis suggests that at least two regulatory uORFs (namely, in SLC35A4 and MIEF1) encode functional protein products.

DOI:http://dx.doi.org/10.7554/eLife.03971.001

Proteins carry out essential tasks for living cells and genes contain the instructions to make proteins within their DNA. These instructions are copied to make a molecule of mRNA, and a molecular machine known as a ribosome then reads and translates the mRNA to build the protein.

The first step in the translation process is called ‘initiation’ and requires a protein called eIF2 to work together with the ribosome. This step involves identifying an instruction called the start codon that marks the beginning of the mRNA's coding sequence. The section of an mRNA molecule before the start codon is not normally translated by the ribosome and is hence called the 5′ untranslated region.

Building proteins requires energy and resources, and so it is carefully regulated. If a cell is stressed, such as by being exposed to harmful chemicals, it makes fewer proteins in order to conserve its resources. This down-regulation of protein production is achieved in part by the cell chemically modifying its eIF2 proteins to make them less able to initiate translation. However, stressed cells still continue to make more of certain proteins that help them to combat stress. The mRNA molecules for some of these proteins contain at least one other start codon in the 5′ untranslated region. The sequence that would be translated from such a start codon is known as an upstream open reading frame (or uORF for short)—and this feature is thought to help certain proteins to still be expressed despite low levels of active eIF2. Andreev, O'Connor et al. have now analysed which mRNAs are translated in human cells that have been treated with a chemical that induces stress and makes the eIF2 protein less able to initiate translation. To do so, a technique called ribosome profiling was used to identify all of the mRNA molecules bound to ribosomes shortly after treatment with this chemical.

Overall translation of most mRNAs in stressed cells was reduced to a quarter of the normal level. However, Andreev, O'Connor et al. observed that the translation of a few mRNAs continued almost as normal, or even increased, after the chemical treatment. Notably, most of these mRNAs encoded regulatory proteins, which are not required in large amounts. With one exception, all of these resistant mRNAs contained uORFs. In unstressed cells, these uORFs were efficiently translated, while the same mRNA's coding sequences were translated less efficiently. Andreev, O'Connor et al. suggest that these two features could be used to identify mRNAs that are still translated into working proteins when cells are stressed. Further work is now needed to explore the mechanisms by which translation of these uORFs allows mRNAs to resist the stress.

DOI:http://dx.doi.org/10.7554/eLife.03971.002

3USS: a web server for detecting alternative 3'UTRs from RNA-seq experiments

Summary: Protein-coding genes with multiple alternative polyadenylation sites can generate mRNA 3′UTR sequences of different lengths, thereby causing the loss or gain of regulatory elements, which can affect stability, localization and translation efficiency. 3USS is a web-server developed with the aim of giving experimentalists the possibility to automatically identify alternative 3′UTRs (shorter or longer with respect to a reference transcriptome), an option that is not available in standard RNA-seq data analysis procedures. The tool reports as putative novel the 3′UTRs not annotated in available databases. Furthermore, if data from two related samples are uploaded, common and specific alternative 3′UTRs are identified and reported by the server.

Availability and implementation: 3USS is freely available at http://www.biocomputing.it/3uss_server

Contact:anna.tramontano@uniroma1.it

Supplementary information:Supplementary data are available at Bioinformatics online.

The complexity, challenges and benefits of comparing two transporter classification systems in TCDB and Pfam

Transport systems comprise roughly 10% of all proteins in a cell, playing critical roles in many processes. Improving and expanding their classification is an important goal that can affect studies ranging from comparative genomics to potential drug target searches. It is not surprising that different classification systems for transport proteins have arisen, be it within a specialized database, focused on this functional class of proteins, or as part of a broader classification system for all proteins. Two such databases are the Transporter Classification Database (TCDB) and the Protein family (Pfam) database. As part of a long-term endeavor to improve consistency between the two classification systems, we have compared transporter annotations in the two databases to understand the rationale for differences and to improve both systems. Differences sometimes reflect the fact that one database has a particular transporter family while the other does not. Differing family definitions and hierarchical organizations were reconciled, resulting in recognition of 69 Pfam ‘Domains of Unknown Function’, which proved to be transport protein families to be renamed using TCDB annotations. Of over 400 potential new Pfam families identified from TCDB, 10% have already been added to Pfam, and TCDB has created 60 new entries based on Pfam data. This work, for the first time, reveals the benefits of comprehensive database comparisons and explains the differences between Pfam and TCDB.

Functional analysis of Girardia tigrina transcriptome seeds pipeline for anthelmintic target discovery

BACKGROUND

Neglected diseases caused by helminth infections impose a massive hindrance to progress in the developing world. While basic research on parasitic flatworms (platyhelminths) continues to expand, researchers have yet to broadly adopt a free-living model to complement the study of these important parasites.

METHODS

We report the high-coverage sequencing (RNA-Seq) and assembly of the transcriptome of the planarian Girardia tigrina across a set of dynamic conditions. The assembly was annotated and extensive orthology analysis was used to seed a pipeline for the rational prioritization and validation of putative anthelmintic targets. A small number of targets conserved between parasitic and free-living flatworms were comparatively interrogated.

RESULTS

240 million paired-end reads were assembled de novo to produce a strictly filtered predicted proteome consisting of over 22,000 proteins. Gene Ontology annotations were extended to 16,467 proteins. 2,693 sequences were identified in orthology groups spanning flukes, tapeworms and planaria, with 441 highlighted as belonging to druggable protein families. Chemical inhibitors were used on three targets in pharmacological screens using both planaria and schistosomula, revealing distinct motility phenotypes that were shown to correlate with planarian RNAi phenotypes.

CONCLUSIONS

This work provides the first comprehensive and annotated sequence resource for the model planarian G. tigrina, alongside a prioritized list of candidate drug targets conserved among parasitic and free-living flatworms. As proof of principle, we show that a simple RNAi and pharmacology pipeline in the more convenient planarian model system can inform parasite biology and serve as an efficient screening tool for the identification of lucrative anthelmintic targets.