Open science in practice: A personal perspective

This presentation was part of Day 5 of the Open Science in Practice Summer School #osip2017. Additional information can be found on osip2017.epfl.ch

A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

Background Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes. Results By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks. Conclusion wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all user

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users

It’s all about beliefs: Believing emotions are uncontrollable is linked to symptoms of anxiety and depression through cognitive reappraisal and expressive suppression

The aim of this study was to examine the link between personal beliefs about emotion controllability and symptoms of anxiety and depression, with a particular focus on the mediating role of emotion regulation. To date, there has been little research examining the mediating role of cognitive reappraisal or expressive suppression in the link between beliefs about emotion controllability and symptoms of anxiety. Online questionnaires measuring emotion regulation, beliefs about emotion controllability, and depression and anxiety, were completed by 1227 participants (n = 336 males; Mage = 25.3, SD = 10.1; range = 16 to 83 years). The results indicated that perceived control over one’s own emotions predicted better psychological health (fewer symptoms of anxiety and depression). This link between beliefs about emotion controllability and psychological heath was partially mediated by cognitive reappraisal and expressive suppression, with cognitive reappraisal predicting a reduction in clinical symptoms and expressive suppression predicting an increase in clinical symptoms. These findings suggest that individuals’ beliefs about emotion controllability, leads to the use of certain emotion regulation strategies which in turn, have important consequences for psychological health

iSLIM: a comprehensive approach to mapping and characterizing gene regulatory networks

Mapping gene regulatory networks is a significant challenge in systems biology, yet only a few methods are currently capable of systems-level identification of transcription factors (TFs) that bind a specific regulatory element. We developed a microfluidic method for integrated systems-level interaction mapping of TF-DNA interactions, generating and interrogating an array of 423 full-length Drosophila TFs. With integrated systems-level interaction mapping, it is now possible to rapidly and quantitatively map gene regulatory networks of higher eukaryote

Marian Walhout: Transcriptional mapmaker

Walhout uses the genome as a base camp for exploring transcriptional regulation

Transcription factor proteomics - Tools, applications, and challenges

Transcription factors (TFs) are a family of DNA-binding proteins whose gene regulatory capabilities are of vital importance in defining the molecular state of a cell. Despite their biological significance, our understanding of TF behavior and function is still limited. This is because we have so far mostly relied on gene expression data to approximate TF protein levels given that the latter information has been notoriously difficult to obtain due to the relatively low expression levels of many TFs. However, significant advances in mass spectrometry technologies combined with the development of sensitive methodologies aimed at detecting TFs are now allowing a transition from a predominantly qualitative to a quantitative protein landscape. Such a paradigm shift is expected to unravel dynamic aspects of TF function, potentially linking TF copy number fluctuations in cells with specific regulatory functions. This in turn may provide novel insights into the regulatory mechanisms underlying a wide range of fundamental and disease-related biological processes. In this review, we will present the latest advances in mass spectrometry-based TF proteomics and describe novel strategies tailored around the quantification of this important family of DNA-binding proteins

DNA-centered approaches to characterize regulatory protein–DNA interaction complexes

Gene regulation is mediated by site-specific DNA-binding proteins or transcription factors (TFs), which form protein complexes at regulatory loci either to activate or repress the expression of a target gene. The study of the dynamic properties of these regulatory DNA-binding complexes has so far been dominated by protein-centered methodologies, aiming to characterize the DNA-binding behavior of one specific protein at a time. With the emerging evidence for a role of DNA in allosterically influencing DNA-binding protein complex formation, there is renewed interest in DNA-centered approaches to capture protein complexes on defined regulatory loci and to correlate changes in their composition with alterations in target gene expression. In this review, we present the current state-of-the-art in such DNA-centered approaches and evaluate recent technological improvements in the purification as well as in the identification of regulatory DNA-binding protein complexes within or outside their biological context. Finally, we suggest possible areas of improvement and assess the putative impact of DNA-centered methodologies on the gene regulation field for the forthcoming years

The Genetics of Transcription Factor DNA Binding Variation

Most complex trait-associated variants are located in non-coding regulatory regions of the genome, where they have been shown to disrupt transcription factor (TF)-DNA binding motifs. Variable TF-DNA interactions are therefore increasingly considered as key drivers of phenotypic variation. However, recent genome-wide studies revealed that the majority of variable TF-DNA binding events are not driven by sequence alterations in the motif of the studied TF. This observation implies that the molecular mechanisms underlying TF-DNA binding variation and, by extrapolation, inter-individual phenotypic variation are more complex than originally anticipated. Here, we summarize the findings that led to this important paradigm shift and review proposed mechanisms for local, proximal, or distal genetic variation-driven variable TF-DNA binding. In addition, we discuss the biomedical implications of these findings for our ability to dissect the molecular role(s) of non-coding genetic variants in complex traits, including disease susceptibility