Gerben Menschaert

An update on LNCipedia: a database for annotated human lncRNA sequences

The human genome is pervasively transcribed, producing thousands of non-coding RNA transcripts. The majority of these transcripts are long non-coding RNAs (lncRNAs) and novel lncRNA genes are being identified at rapid pace. To streamline these efforts, we created LNCipedia, an online repository of lncRNA transcripts and annotation. Here, we present LNCipedia 3.0 (http://www.lncipedia.org), the latest version of the publicly available human lncRNA database. Compared to the previous version of LNCipedia, the database grew over five times in size, gaining over 90 000 new lncRNA transcripts. Assessment of the protein-coding potential of LNCipedia entries is improved with state-of-the art methods that include large-scale reprocessing of publicly available proteomics data. As a result, a high-confidence set of lncRNA transcripts with low coding potential is defined and made available for download. In addition, a tool to assess lncRNA gene conservation between human, mouse and zebrafish has been implemented.

PubMeth: a cancer methylation database combining text-mining and expert annotation

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org. PubMeth is based on text-mining of Medline/PubMed abstracts, combined with manual reading and annotation of preselected abstracts. The text-mining approach results in increased speed and selectivity (as for instance many different aliases of a gene are searched at once), while the manual screening significantly raises the specificity and quality of the database. The summarized overview of the results is very useful in case more genes or cancer types are searched at the same time.

Deep Proteome Coverage Based on Ribosome Profiling Aids Mass Spectrometry-based Protein and Peptide Discovery and Provides Evidence of Alternative Translation Products and Near-cognate Translation Initiation Events*

An increasing number of studies involve integrative analysis of gene and protein expression data, taking advantage of new technologies such as next-generation transcriptome sequencing and highly sensitive mass spectrometry (MS) instrumentation. Recently, a strategy, termed ribosome profiling (or RIBO-seq), based on deep sequencing of ribosome-protected mRNA fragments, indirectly monitoring protein synthesis, has been described. We devised a proteogenomic approach constructing a custom protein sequence search space, built from both Swiss-Prot- and RIBO-seq-derived translation products, applicable for MS/MS spectrum identification. To record the impact of using the constructed deep proteome database, we performed two alternative MS-based proteomic strategies as follows: (i) a regular shotgun proteomic and (ii) an N-terminal combined fractional diagonal chromatography (COFRADIC) approach. Although the former technique gives an overall assessment on the protein and peptide level, the latter technique, specifically enabling the isolation of N-terminal peptides, is very appropriate in validating the RIBO-seq-derived (alternative) translation initiation site profile. We demonstrate that this proteogenomic approach increases the overall protein identification rate 2.5% (e.g. new protein products, new protein splice variants, single nucleotide polymorphism variant proteins, and N-terminally extended forms of known proteins) as compared with only searching UniProtKB-SwissProt. Furthermore, using this custom database, identification of N-terminal COFRADIC data resulted in detection of 16 alternative start sites giving rise to N-terminally extended protein variants besides the identification of four translated upstream ORFs. Notably, the characterization of these new translation products revealed the use of multiple near-cognate (non-AUG) start codons. As deep sequencing techniques are becoming more standard, less expensive, and widespread, we anticipate that mRNA sequencing and especially custom-tailored RIBO-seq will become indispensable in the MS-based protein or peptide identification process. The underlying mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000124.

PROTEOFORMER: deep proteome coverage through ribosome profiling and MS integration

An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for three- or six-frame-translation, impede the use of mRNA-seq data for the construction of a protein sequence search database. With that in mind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesis-based sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5′-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.

N-terminal Proteomics and Ribosome Profiling Provide a Comprehensive View of the Alternative Translation Initiation Landscape in Mice and Men

Usage of presumed 5′UTR or downstream in-frame AUG codons, next to non-AUG codons as translation start codons contributes to the diversity of a proteome as protein isoforms harboring different N-terminal extensions or truncations can serve different functions. Recent ribosome profiling data revealed a highly underestimated occurrence of database nonannotated, and thus alternative translation initiation sites (aTIS), at the mRNA level. N-terminomics data in addition showed that in higher eukaryotes around 20% of all identified protein N termini point to such aTIS, to incorrect assignments of the translation start codon, translation initiation at near-cognate start codons, or to alternative splicing. We here report on more than 1700 unique alternative protein N termini identified at the proteome level in human and murine cellular proteomes. Customized databases, created using the translation initiation mapping obtained from ribosome profiling data, additionally demonstrate the use of initiator methionine decoded near-cognate start codons besides the existence of N-terminal extended protein variants at the level of the proteome. Various newly identified aTIS were confirmed by mutagenesis, and meta-analyses demonstrated that aTIS reside in strong Kozak-like motifs and are conserved among eukaryotes, hinting to a possible biological impact. Finally, TargetP analysis predicted that the usage of aTIS often results in altered subcellular localization patterns, providing a mechanism for functional diversification.

Combining in silico prediction and ribosome profiling in a genome-wide search for novel putatively coding sORFs

BackgroundIt was long assumed that proteins are at least 100 amino acids (AAs) long. Moreover, the detection of short translation products (e.g. coded from small Open Reading Frames, sORFs) is very difficult as the short length makes it hard to distinguish true coding ORFs from ORFs occurring by chance. Nevertheless, over the past few years many such non-canonical genes (with ORFs < 100 AAs) have been discovered in different organisms like Arabidopsis thaliana, Saccharomyces cerevisiae, and Drosophila melanogaster. Thanks to advances in sequencing, bioinformatics and computing power, it is now possible to scan the genome in unprecedented scrutiny, for example in a search of this type of small ORFs.ResultsUsing bioinformatics methods, we performed a systematic search for putatively functional sORFs in the Mus musculus genome. A genome-wide scan detected all sORFs which were subsequently analyzed for their coding potential, based on evolutionary conservation at the AA level, and ranked using a Support Vector Machine (SVM) learning model. The ranked sORFs are finally overlapped with ribosome profiling data, hinting to sORF translation. All candidates are visually inspected using an in-house developed genome browser. In this way dozens of highly conserved sORFs, targeted by ribosomes were identified in the mouse genome, putatively encoding micropeptides.ConclusionOur combined genome-wide approach leads to the prediction of a comprehensive but manageable set of putatively coding sORFs, a very important first step towards the identification of a new class of bioactive peptides, called micropeptides.

Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing.

DNA-methylation is an important epigenetic feature in health and disease. Methylated sequence capturing by Methyl Binding Domain (MBD) based enrichment followed by second-generation sequencing provides the best combination of sensitivity and cost-efficiency for genome-wide DNA-methylation profiling. However, existing implementations are numerous, and quality control and optimization require expensive external validation. Therefore, this study has two aims: 1) to identify a best performing kit for MBD-based enrichment using independent validation data, and 2) to evaluate whether quality evaluation can also be performed solely based on the characteristics of the generated sequences. Five commercially available kits for MBD enrichment were combined with Illumina GAIIx sequencing for three cell lines (HCT15, DU145, PC3). Reduced representation bisulfite sequencing data (all three cell lines) and publicly available Illumina Infinium BeadChip data (DU145 and PC3) were used for benchmarking. Consistent large-scale differences in yield, sensitivity and specificity between the different kits could be identified, with Diagenodes MethylCap kit as overall best performing kit under the tested conditions. This kit could also be identified with the Fragment CpG-plot, which summarizes the CpG content of the captured fragments, implying that the latter can be used as a tool to monitor data quality. In conclusion, there are major quality differences between kits for MBD-based capturing of methylated DNA, with the MethylCap kit performing best under the used settings. The Fragment CpG-plot is able to monitor data quality based on inherent sequence data characteristics, and is therefore a cost-efficient tool for experimental optimization, but also to monitor quality throughout routine applications.

Diversity in Protein Glycosylation among Insect Species

Background A very common protein modification in multicellular organisms is protein glycosylation or the addition of carbohydrate structures to the peptide backbone. Although the Class of the Insecta is the largest animal taxon on Earth, almost all information concerning glycosylation in insects is derived from studies with only one species, namely the fruit fly Drosophila melanogaster. Methodology/Principal Findings In this report, the differences in glycoproteomes between insects belonging to several economically important insect orders were studied. Using GNA (Galanthus nivalis agglutinin) affinity chromatography, different sets of glycoproteins with mannosyl-containing glycan structures were purified from the flour beetle (Tribolium castaneum), the silkworm (Bombyx mori), the honeybee (Apis mellifera), the fruit fly (D. melanogaster) and the pea aphid (Acyrthosiphon pisum). To identify and characterize the purified glycoproteins, LC-MS/MS analysis was performed. For all insect species, it was demonstrated that glycoproteins were related to a broad range of biological processes and molecular functions. Moreover, the majority of glycoproteins retained on the GNA column were unique to one particular insect species and only a few glycoproteins were present in the five different glycoprotein sets. Furthermore, these data support the hypothesis that insect glycoproteins can be decorated with mannosylated O-glycans. Conclusions/Significance The results presented here demonstrate that oligomannose N-glycosylation events are highly specific depending on the insect species. In addition, we also demonstrated that protein O-mannosylation in insect species may occur more frequently than currently believed.

sORFs.org: a repository of small ORFs identified by ribosome profiling

With the advent of ribosome profiling, a next generation sequencing technique providing a “snap-shot’’ of translated mRNA in a cell, many short open reading frames (sORFs) with ribosomal activity were identified. Follow-up studies revealed the existence of functional peptides, so-called micropeptides, translated from these ‘sORFs’, indicating a new class of bio-active peptides. Over the last few years, several micropeptides exhibiting important cellular functions were discovered. However, ribosome occupancy does not necessarily imply an actual function of the translated peptide, leading to the development of various tools assessing the coding potential of sORFs. Here, we introduce sORFs.org (http://www.sorfs.org), a novel database for sORFs identified using ribosome profiling. Starting from ribosome profiling, sORFs.org identifies sORFs, incorporates state-of-the-art tools and metrics and stores results in a public database. Two query interfaces are provided, a default one enabling quick lookup of sORFs and a BioMart interface providing advanced query and export possibilities. At present, sORFs.org harbors 263 354 sORFs that demonstrate ribosome occupancy, originating from three different cell lines: HCT116 (human), E14_mESC (mouse) and S2 (fruit fly). sORFs.org aims to provide an extensive sORFs database accessible to researchers with limited bioinformatics knowledge, thus enabling easy integration into personal projects.

Colorado potato beetle (Coleoptera) gut transcriptome analysis: expression of RNA interference-related genes.

In the search for new methods of pest control, the potential of RNA interference (RNAi) is being explored. Because the gut is the first barrier for the uptake of double‐stranded (ds)RNA, pyrosequencing of the gut transcriptome is a powerful tool for obtaining the necessary sequences for specific dsRNA‐mediated pest control. In the present study, a dataset representing the gut transcriptome of the Colorado potato beetle (CPB; Leptinotarsa decemlineata) was generated and analysed for the presence of RNAi‐related genes. Almost all selected genes that were implicated in silencing efficiency at different levels in the RNAi pathway (core machinery, associated intracellular factors, dsRNA uptake, antiviral RNAi, nucleases), which uses different types of small RNA (small interfering RNA, microRNA and piwi‐RNA), were expressed in the CPB gut. Although the database is of lower quality, the majority of the RNAi genes are also found to be present in the gut transcriptome of the tobacco hornworm [TH; Manduca sexta (19 out of 35 genes analysed)]. The high quality of the CPB transcriptome database will lay the foundation for future gene expression and functional studies regarding the gut and RNAi.