John S. Reece-Hoyes

Genome-scale spatiotemporal analysis of Caenorhabditis elegans microRNA promoter activity

The Caenorhabditis elegans genome encodes more than 100 microRNAs (miRNAs). Genetic analyses of miRNA deletion mutants have only provided limited insights into miRNA function. To gain insight into the function of miRNAs, it is important to determine their spatiotemporal expression pattern. Here, we use miRNA promoters driving the expression of GFP as a proxy for miRNA expression. We describe a set of 73 transgenic C. elegans strains, each expressing GFP under the control of a miRNA promoter. Together, these promoters control the expression of 89 miRNAs (66% of all predicted miRNAs). We find that miRNA promoters drive GFP expression in a variety of tissues and that, overall, their activity is similar to that of protein-coding gene promoters. However, miRNAs are expressed later in development, which is consistent with functions after initial body-plan specification. We find that miRNA members belonging to families are more likely to be expressed in overlapping tissues than miRNAs that do not belong to the same family, and provide evidence that intronic miRNAs may be controlled by their own, rather than a host gene promoter. Finally, our data suggest that post-transcriptional mechanisms contribute to differential miRNA expression. The data and strains described here will provide a valuable guide and resource for the functional analysis of C. elegans miRNAs.

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

BackgroundTranscription 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.ResultsBy 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.ConclusionwTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

Insight into transcription factor gene duplication from Caenorhabditis elegans Promoterome-driven expression patterns

BackgroundThe C. elegans Promoterome is a powerful resource for revealing the regulatory mechanisms by which transcription is controlled pan-genomically. Transcription factors will form the core of any systems biology model of genome control and therefore the promoter activity of Promoterome inserts for C. elegans transcription factor genes was examined, in vivo, with a reporter gene approach.ResultsTransgenic C. elegans strains were generated for 366 transcription factor promoter/gfp reporter gene fusions. GFP distributions were determined, and then summarized with reference to developmental stage and cell type. Reliability of these data was demonstrated by comparison to previously described gene product distributions. A detailed consideration of the results for one C. elegans transcription factor gene family, the Six family, comprising ceh-32, ceh-33, ceh-34 and unc-39 illustrates the value of these analyses. The high proportion of Promoterome reporter fusions that drove GFP expression, compared to previous studies, led to the hypothesis that transcription factor genes might be involved in local gene duplication events less frequently than other genes. Comparison of transcription factor genes of C. elegans and Caenorhabditis briggsae was therefore carried out and revealed very few examples of functional gene duplication since the divergence of these species for most, but not all, transcription factor gene families.ConclusionExamining reporter expression patterns for hundreds of promoters informs, and thereby improves, interpretation of this data type. Genes encoding transcription factors involved in intrinsic developmental control processes appear acutely sensitive to changes in gene dosage through local gene duplication, on an evolutionary time scale.

DamID in C. elegans reveals longevity-associated targets of DAF-16/FoxO

Insulin/IGF‐1 signaling controls metabolism, stress resistance and aging in Caenorhabditis elegans by regulating the activity of the DAF‐16/FoxO transcription factor (TF). However, the function of DAF‐16 and the topology of the transcriptional network that it crowns remain unclear. Using chromatin profiling by DNA adenine methyltransferase identification (DamID), we identified 907 genes that are bound by DAF‐16. These were enriched for genes showing DAF‐16‐dependent upregulation in long‐lived daf‐2 insulin/IGF‐1 receptor mutants (P=1.4e−11). Cross‐referencing DAF‐16 targets with these upregulated genes (daf‐2 versus daf‐16; daf‐2) identified 65 genes that were DAF‐16 regulatory targets. These 65 were enriched for signaling genes, including known determinants of longevity, but not for genes specifying somatic maintenance functions (e.g. detoxification, repair). This suggests that DAF‐16 acts within a relatively small transcriptional subnetwork activating (but not suppressing) other regulators of stress resistance and aging, rather than directly regulating terminal effectors of longevity. For most genes bound by DAF‐16∷DAM, transcriptional regulation by DAF‐16 was not detected, perhaps reflecting transcriptionally non‐functional TF ‘parking sites’. This study demonstrates the efficacy of DamID for chromatin profiling in C. elegans.

Enhanced Y1H assays for Arabidopsis

We present an Arabidopsis thaliana full-length transcription factor resource of 92% of root stele–expressed transcription factors and 74.5% of root-expressed transcription factors. We demonstrate its use with enhanced yeast one-hybrid (eY1H) screening for rapid, systematic mapping of plant transcription factor–promoter interactions. We identified 158 interactions with 13 stele-expressed promoters, many of which occur physically or are regulatory in planta.

Matrix and Steiner-triple-system smart pooling assays for high-performance transcription regulatory network mapping

Yeast one-hybrid (Y1H) assays provide a gene-centered method for the identification of interactions between gene promoters and regulatory transcription factors (TFs). To date, Y1H assays have involved library screens that are relatively expensive and laborious. We present two Y1H strategies that allow immediate prey identification: matrix assays that use an array of 755 individual Caenorhabditis elegans TFs, and smart-pool assays that use TF multiplexing. Both strategies simplify the Y1H pipeline and reduce the cost of protein-DNA interaction identification. We used a Steiner triple system (STS) to create smart pools of 4–25 TFs. Notably, we uniplexed a small number of highly connected TFs to allow efficient assay deconvolution. Both strategies outperform library screens in terms of coverage, confidence and throughput. These versatile strategies can be adapted both to TFs in other systems and, likely, to other biomolecules and assays as well.

Enhanced yeast one-hybrid assays for high-throughput gene-centered regulatory network mapping

A major challenge in systems biology is to understand the gene regulatory networks that drive development, physiology and pathology. Interactions between transcription factors and regulatory genomic regions provide the first level of gene control. Gateway-compatible yeast one-hybrid (Y1H) assays present a convenient method to identify and characterize the repertoire of transcription factors that can bind a DNA sequence of interest. To delineate genome-scale regulatory networks, however, large sets of DNA fragments need to be processed at high throughput and high coverage. Here we present enhanced Y1H (eY1H) assays that use a robotic mating platform with a set of improved Y1H reagents and automated readout quantification. We demonstrate that eY1H assays provide excellent coverage and identify interacting transcription factors for multiple DNA fragments in a short time. eY1H assays will be an important tool for mapping gene regulatory networks in Caenorhabditis elegans and other model organisms as well as in humans.

Yeast one-hybrid assays for gene-centered human gene regulatory network mapping

Gateway-compatible yeast one-hybrid (Y1H) assays provide a convenient gene-centered (DNA to protein) approach to identify transcription factors that can bind a DNA sequence of interest. We present Y1H resources, including clones for 988 of 1,434 (69%) predicted human transcription factors, that can be used to detect both known and new interactions between human DNA regions and transcription factors.

YEAST ONE-HYBRID ASSAYS: A HISTORICAL AND TECHNICAL PERSPECTIVE

Since its development about two decades ago, the yeast one-hybrid (Y1H) assay has become an important technique for detecting physical interactions between sequence-specific regulatory transcription factor proteins (TFs) and their DNA target sites. Multiple versions of the Y1H methodology have been developed, each with technical differences and unique advantages. We will discuss several of these technical variations in detail, and also provide some ideas for how Y1H assays can be further improved.

The C. elegans Snail homolog CES-1 can activate gene expression in vivo and share targets with bHLH transcription factors

Snail-type transcription factors (TFs) are found in numerous metazoan organisms and function in a plethora of cellular and developmental processes including mesoderm and neuronal development, apoptosis and cancer. So far, Snail-type TFs are exclusively known as transcriptional repressors. They repress gene expression by recruiting transcriptional co-repressors and/or by preventing DNA binding of activators from the basic helix-loop-helix (bHLH) family of TFs to CAGGTG E-box sequences. Here we report that the Caenorhabditis elegans Snail-type TF CES-1 can activate transcription in vivo. Moreover, we provide results that suggest that CES-1 can share its binding site with bHLH TFs, in different tissues, rather than only occluding bHLH DNA binding. Together, our data indicate that there are at least two types of CES-1 target genes and, therefore, that the molecular function of Snail-type TFs is more plastic than previously appreciated.