Enhanced yeast one-hybrid assays for high-throughput gene-centered regulatory network mapping
John S Reece-Hoyes, Alos Diallo, Bryan Lajoie, Amanda Kent, Shaleen Shrestha, Sreenath Kadreppa, Colin Pesyna, Job Dekker, Chad L Myers & Albertha J M Walhout
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.Link to Paper Link to Data
Enhanced Y1H assays for Arabidopsis
Allison Gaudinier, Lifang Zhang, John S Reece-Hoyes, Mallorie Taylor-Teeples, Li Pu, Zhijie Liu, Ghislain Breton, Jose L Pruneda-Paz, Dahae Kim, Steve A Kay, Albertha J M Walhout, Doreen Ware & Siobhan M Brady
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.Link to Paper
Yeast one-hybrid assays for gene-centered human gene regulatory network mapping
John S Reece-Hoyes, A Rasim Barutcu, Rachel Patton McCord, Jun Seop Jeong, Lizhi Jiang, Andrew MacWilliams, Xinping Yang, Kourosh Salehi-Ashtiani, David E Hill, Seth Blackshaw, Heng Zhu, Job Dekker & Albertha J M Walhout
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.Link to Paper
A Gene-Centered C. elegans Protein-DNA Interaction Network
Bart Deplancke,1 Arnab Mukhopadhyay,1,6 Wanyuan Ao,2,5,6 Ahmed M. Elewa,1 Christian A. Grove, Natalia J. Martinez, Reynaldo Sequerra, Lynn Doucette-Stamm, John S. Reece-Hoyes, Ian A. Hope,Heidi A. Tissenbaum, Susan E. Mango, and Albertha J.M. Walhout,
Transcription regulatory networks consist of physical and functional interactions between transcription factors (TFs) and their target genes. The systematic mapping of TF-target gene interactions has been pioneered in unicellular systems, using “TF-centered” methods (e.g., chromatin immunoprecipitation). However, metazoan systems are less amenable to such methods. Here, we used “gene-centered” high-throughput yeast one-hybrid (Y1H) assays to identify 283 interactions between 72 C. elegans digestive tract gene promoters and 117 proteins. The resulting protein-DNA interaction (PDI) network is highly connected and enriched for TFs that are expressed in the digestive tract. We provide functional annotations for ?10% of all worm TFs, many of which were previously uncharacterized, and find ten novel putative TFs, illustrating the power of a gene-centered approach. We provide additional in vivo evidence for multiple PDIs and illustrate how the PDI network provides insights into metazoan differential gene expression at a systems level.Link to Paper Link to Data
A Gateway-Compatible Yeast One-Hybrid System
Bart Deplancke, Denis Dupuy, Marc Vidal and Albertha J.M. Walhout
Since the advent of microarrays, vast amounts of gene expression data have been generated. However, these microarray data fail to reveal the transcription regulatory mechanisms that underlie differential gene expression, because the identity of the responsible transcription factors (TFs) often cannot be directly inferred from such data sets. Regulatory TFs activate or repress transcription of their target genes by binding to cis-regulatory elements that are frequently located in a gene\'s promoter. To understand the mechanisms underlying differential gene expression, it is necessary to identify physical interactions between regulatory TFs and their target genes. We developed a Gateway-compatible yeast one-hybrid (Y1H) system that enables the rapid, large-scale identification of protein-DNA interactions using both small (i.e., DNA elements of interest) and large (i.e., gene promoters) DNA fragments. We used four well-characterized Caenorhabditis elegans promoters as DNA baits to test the functionality of this Y1H system. We could detect ?40% of previously reported TF-promoter interactions. By performing screens using two complementary libraries, we found novel potentially interacting TFs for each promoter. We recapitulated several of the Y1H-based protein-DNA interactions using luciferase reporter assays in mammalian cells. Taken together, the Gateway-compatible Y1H system will allow the high-throughput identification of protein-DNA interactions and may be a valuable tool to decipher transcription regulatory networks.Link to Paper Link to Data
Genomics in 2011: challenges and opportunities
Adams D, Berger B, Harismendy O, Huttenhower C, Liu SX, Myers C, Oshlack A, Rinn J, Walhout M.
As we come to the end of 2011, Genome Biology has asked some members of our Editorial Board for their views on the state of play in genomics. What was their favorite paper of 2011? What are the challenges in their particular research area? Who has had the biggest influence on their careers? What advice would they give to young researchers embarking on a career in research?Link to Paper
Functional modularity of nuclear hormone receptors
in a Caenorhabditis elegans metabolic gene regulatory
Arda HE, Taubert S, MacNeil LT, Conine CC, Tsuda B, Van Gilst M, Sequerra R, Doucette-Stamm L, Yamamoto KR, Walhout AJ.
Gene regulatory networks (GRNs) provide insights into the mechanisms of differential gene expression at a systems level. GRNs that relate to metazoan development have been studied extensively. However, little is still known about the design principles, organization and functionality of GRNs that control physiological processes such as metabolism, homeostasis and responses to environmental cues. In this study, we report the first experimentally mapped metazoan GRN of Caenorhabditis elegans metabolic genes. This network is enriched for nuclear hormone receptors (NHRs). The NHR family has greatly expanded in nematodes: humans have 48 NHRs, but C. elegans has 284, most of which are uncharacterized. We find that the C. elegans metabolic GRN is highly modular and that two GRN modules predominantly consist of NHRs. Network modularity has been proposed to facilitate a rapid response to different cues. As NHRs are metabolic sensors that are poised to respond to ligands, this suggests that C. elegans GRNs evolved to enable rapid and adaptive responses to different cues by a concurrence of NHR family expansion and modular GRN wiring.Link to Paper Link to Data
Matrix and Steiner-triple-system smart pooling assays for high-performance transcription regulatory network mapping
Vanessa Vermeirssen*, Bart Deplancke*, M Inmaculada Barrasa*, John S Reece-Hoyes*, H Efsun Arda, Christian A Grove, Natalia J Martinez, Reynaldo Sequerra, Lynn Doucette-Stamm, Michael R Brent & Albertha J M Walhout *These authors contributed equally to this work
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.Link to Paper Link to Data
A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks
John S Reece-Hoyes, Bart Deplancke, Jane Shingles,
Christian A Grove, Ian A Hope and Albertha JM Walhout
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.
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.Link to Paper
Unraveling transcription regulatory networks by protein-DNA and protein-protein interaction mapping
Albertha J.M. Walhout
Metazoan genomes contain thousands of protein-coding and noncoding RNA genes, most of which are differentially expressed, i.e., at different locations or at different times during development, function, or pathology of the organism. Differential gene expression is achieved in part by the action of regulatory transcription factors (TFs) that bind to cis-regulatory elements that are often located in or near their target genes. Each TF likely regulates many targets in the context of intricate transcription regulatory networks. Up to 10% of a genome may encode TFs, but only a handful of these have been studied in detail. Here, I will discuss the different steps involved in the mapping and analysis of transcription regulatory networks, including the identification of network nodes (TFs and their target sequences) and edges (TF–TF dimers and TF–DNA target interactions), integration with other data types, and network properties and emerging principles that provide insights into differential gene expression.Link to Paper
Networking at the second Interactome Meeting.
Walhout AJ.Link to Paper
Transcription factor modularity in a gene-centered C. elegans core neuronal protein-DNA interaction network.
Vermeirssen V, Barrasa MI, Hidalgo CA, Babon JA, Sequerra R, Doucette-Stamm L, Barabási AL, Walhout AJ.
Transcription regulatory networks play a pivotal role in the development, function, and pathology of metazoan organisms. Such networks are comprised of protein-DNA interactions between transcription factors (TFs) and their target genes. An important question pertains to how the architecture of such networks relates to network functionality. Here, we show that a Caenorhabditis elegans core neuronal protein-DNA interaction network is organized into two TF modules. These modules contain TFs that bind to a relatively small number of target genes and are more systems specific than the TF hubs that connect the modules. Each module relates to different functional aspects of the network. One module contains TFs involved in reproduction and target genes that are expressed in neurons as well as in other tissues. The second module is enriched for paired homeodomain TFs and connects to target genes that are often exclusively neuronal. We find that paired homeodomain TFs are specifically expressed in C. elegans and mouse neurons, indicating that the neuronal function of paired homeodomains is evolutionarily conserved. Taken together, we show that a core neuronal C. elegans protein-DNA interaction network possesses TF modules that relate to different functional aspects of the complete network.Link to Paper Link to Data