Sandra Steyaert

Prevalent, Dynamic, and Conserved R-Loop Structures Associate with Specific Epigenomic Signatures in Mammals

R-loops are three-stranded nucleic acid structures formed upon annealing of an RNA strand to one strand of duplex DNA. We profiled R-loops using a high-resolution, strand-specific methodology in human and mouse cell types. R-loops are prevalent, collectively occupying up to 5% of mammalian genomes. R-loop formation occurs over conserved genic hotspots such as promoter and terminator regions of poly(A)-dependent genes. In most cases, R-loops occur co-transcriptionally and undergo dynamic turnover. Detailed epigenomic profiling revealed that R-loops associate with specific chromatin signatures. At promoters, R-loops associate with a hyper-accessible state characteristic of unmethylated CpG island promoters. By contrast, terminal R-loops associate with an enhancer- and insulator-like state and define a broad class of transcription terminators. Together, this suggests that the retention of nascent RNA transcripts at their site of expression represents an abundant, dynamic, and programmed component of the mammalian chromatin that affects chromatin patterning and the control of gene expression.

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.

A proteogenomics approach integrating proteomics and ribosome profiling increases the efficiency of protein identification and enables the discovery of alternative translation start sites

Next‐generation transcriptome sequencing is increasingly integrated with MS to enhance MS‐based protein and peptide identification. Recently, a breakthrough in transcriptome analysis was achieved with the development of ribosome profiling (ribo‐seq). This technology is based on the deep sequencing of ribosome‐protected mRNA fragments, thereby enabling the direct observation of in vivo protein synthesis at the transcript level. In order to explore the impact of a ribo‐seq‐derived protein sequence search space on MS/MS spectrum identification, we performed a comprehensive proteome study on a human cancer cell line, using both shotgun and N‐terminal proteomics, next to ribosome profiling, which was used to delineate (alternative) translational reading frames. By including protein‐level evidence of sample‐specific genetic variation and alternative translation, this strategy improved the identification score of 69 proteins and identified 22 new proteins in the shotgun experiment. Furthermore, we discovered 18 new alternative translation start sites in the N‐terminal proteomics data and observed a correlation between the quantitative measures of ribo‐seq and shotgun proteomics with a Pearson correlation coefficient ranging from 0.483 to 0.664. Overall, this study demonstrated the benefits of ribosome profiling for MS‐based protein and peptide identification and we believe this approach could develop into a common practice for next‐generation proteomics.

A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq

Learning and memory formation are known to require dynamic CpG (de)methylation and gene expression changes. Here, we aimed at establishing a genome-wide DNA methylation map of the zebra finch genome, a model organism in neuroscience, as well as identifying putatively epigenetically regulated genes. RNA- and MethylCap-seq experiments were performed on two zebra finch cell lines in presence or absence of 5-aza-2′-deoxycytidine induced demethylation. First, the MethylCap-seq methodology was validated in zebra finch by comparison with RRBS-generated data. To assess the influence of (variable) methylation on gene expression, RNA-seq experiments were performed as well. Comparison of RNA-seq and MethylCap-seq results showed that at least 357 of the 3,457 AZA-upregulated genes are putatively regulated by methylation in the promoter region, for which a pathway analysis showed remarkable enrichment for neurological networks. A subset of genes was validated using Exon Arrays, quantitative RT-PCR and CpG pyrosequencing on bisulfite-treated samples. To our knowledge, this study provides the first genome-wide DNA methylation map of the zebra finch genome as well as a comprehensive set of genes of which transcription is under putative methylation control.

SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post-enrichment. Here, we present a new methodology based on classical population genetic theory, i.e. the Hardy–Weinberg theorem, that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation was done using both 14 whole-genome bisulfite sequencing data sets and 16 mRNA-seq data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, like the ChIP-seq-based identification of monoallelic histone modifications.

Erratum: Corrigendum: A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq

Scientific Reports 6: Article number: 20957; 10.1038/srep20957 published online: February112016; updated: March172016 The original version of this Article contained an error in the title of the paper, where the word “epigenetically” was incorrectly given as “eigenetically”. This has now been corrected in the PDF and HTML versions of the Article.

Corrigendum: A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq

Scientific Reports 6: Article number: 20957; 10.1038/srep20957 published online: February112016; updated: March172016 The original version of this Article contained an error in the title of the paper, where the word “epigenetically” was incorrectly given as “eigenetically”. This has now been corrected in the PDF and HTML versions of the Article.

A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq (vol 6, 20957, 2016)

Scientific Reports 6: Article number: 20957; 10.1038/srep20957 published online: February112016; updated: March172016 The original version of this Article contained an error in the title of the paper, where the word “epigenetically” was incorrectly given as “eigenetically”. This has now been corrected in the PDF and HTML versions of the Article.