Differential gene expression plays a critical role in the development and physiology of multicellular organisms. At a ‘systems level’ (e.g. at the level of a tissue, organ or whole organism), this process can be studied using gene regulatory network (GRN) models that capture physical and regulatory interactions between genes and their regulators. In the past years, significant progress has been made toward the mapping of GRNs using a variety of experimental and computational approaches. Here, we will discuss gene-centered approaches that we employed to characterize GRNs and describe insights that we have obtained into the global design principles of gene regulation in complex metazoan systems.

Gene expression is regulated at multiple levels, including transcription and translation, as well as mRNA and protein stability. Although systems-level functions of transcription factors and microRNAs are rapidly being characterized, few studies have focused on the posttranscriptional gene regulation by RNA binding proteins (RBPs). RBPs are important to many aspects of gene regulation. Thus, it is essential to know which genes encode RBPs, which RBPs regulate which gene(s), and how RBP genes are themselves regulated. Here we provide a comprehensive compendium of RBPs from the nematode Caenorhabditis elegans (wRBP1.0). We predict that as many as 887 (4.4%) of C. elegans genes may encode RBPs ~250 of which likely function in a gene-specific manner. In addition, we find that RBPs, and most notably gene-specific RBPs, are themselves enriched for binding and modification by regulatory proteins, indicating the potential for extensive regulation of RBPs at many different levels. wRBP1.0 will provide a significant contribution toward the comprehensive delineation of posttranscriptional regulatory networks and will provide a resource for further studies regulation by RBPs.

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?

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 utilize 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 amount of time. eY1H assays will be an important tool for gene regulatory network mapping in Caenorhabditis elegans and other model organisms, as well as humans.

Homeobox proteins are critical regulators of developmental gene transcription and cell specification. Many insights into transcriptional regulation have been gained from studies in the nematode Caenorhabditis elegans. We investigated the expression and regulation of the C. elegans homeobox gene ceh-63, which encodes a single-homeodomain transcription factor of 152 amino acids. ceh-63 is expressed in the interneuron DVC in both sexes, from late embryogenesis through adulthood, and two pairs of uterine cells in reproductive hermaphrodites only. A reporter gene fusion, encoding GFP fused to the full-length CEH-63, also drove weak inconsistent expression in additional unidentified cells in the head and tail. A potential ceh-63 null mutant had no obvious abnormalities, except for a possible increase in subtle defects of the DVC axon projection. No behavioural responses were observed upon either laser ablation of DVC or activation of DVC through light stimulation of channelrhodopsin-2 specifically expressed in this neuron. The function of DVC therefore remains enigmatic. A transcriptional regulatory cascade operating in DVC was defined from the LIM-homeodomain protein CEH-14 through CEH-63 to the helix–turn–helix transcription factor MBR-1. Both CEH-14 and CEH-63 individually bound the mbr-1 promoter in a yeast one-hybrid assay. A model is proposed suggesting that CEH-14 activates ceh-63 and then along with CEH-63 co-ordinately activates mbr-1.

Highlights

► The C. elegans homeobox gene ceh-63 is expressed in a single interneuron, DVC. ► Although a highly conserved gene, a ceh-63 null mutant had no major phenotype. ► A transcription factor regulatory cascade operating in DVC was defined.

Metazoan genomes contain thousands of protein-coding and non-coding RNA genes, most of which are differentially expressed, i.e., at different locations, at different times during development, or in response to environmental signals. Differential gene expression is achieved through complex regulatory networks that are controlled in part by two types of trans-regulators: transcription factors (TFs) and microRNAs (miRNAs). TFs bind to cis-regulatory DNA elements that are often located in or near their target genes, while miRNAs hybridize to cis-regulatory RNA elements mostly located in the 3′ untranslated region of their target mRNAs. Here, we describe how these trans-regulators interact with each other in the context of gene regulatory networks to coordinate gene expression at the genome-scale level, and discuss future challenges of integrating these networks with other types of functional networks.

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein–DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH–DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.

Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one-hybrid (Y1H) and two-hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue-specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered.

SUMMARY

Differences in expression, protein interactions and DNA binding of paralogous transcription factors (“TF parameters”) are thought to be important determinants of regulatory and biological specificity. However, both the extent of TF divergence and the relative contribution of individual TF parameters remain undetermined. We comprehensively identify dimerization partners, spatiotemporal expression patterns and DNA binding specificities for the C. elegans bHLH family of TFs, and model these data into an integrated network. This network displays both specificity and promiscuity, as some bHLH proteins, DNA sequences, and tissues are highly connected, whereas others are not. By comparing all bHLH TFs, we find extensive divergence, and that all three parameters contribute equally to bHLH divergence. Our approach provides a framework for examining divergence for other protein families in C. elegans and in other complex multicellular organisms, including humans. Cross-species comparisons of integrated networks may provide further insights into molecular features underlying protein family evolution.

We present the first gene regulatory network (GRN) that pertains to post-developmental gene expression. Specifically, we mapped a transcription regulatory network of Caenorhabditis elegans metabolic gene promoters using gene-centered yeast one-hybrid assays. We found that the metabolic GRN is enriched for nuclear hormone receptors (NHRs) compared with other gene-centered regulatory networks, and that these NHRs organize into functional network modules.The NHR family has greatly expanded in nematodes; C. elegans has 284 NHRs, whereas humans have only 48. We show that the NHRs in the metabolic GRN have metabolic phenotypes, suggesting that they do not simply function redundantly.The mediator subunit MDT-15 preferentially interacts with NHRs that occur in the metabolic GRN.We describe an NHR circuit that responds to nutrient availability and propose a model for the evolution and organization of NHRs in C. elegans metabolic regulatory networks.

Physical and/or regulatory interactions between transcription factors (TFs) and their target genes are essential to establish body plans of multicellular organisms during development, and these interactions have been studied extensively in the context of GRNs. The precise control of differential gene expression is also of critical importance to maintain physiological homeostasis, and many metabolic disorders such as obesity and diabetes coincide with substantial changes in gene expression. Much work has focused on the GRNs that control metazoan development; however, the design principles and organization of the GRNs that control systems physiology remain largely unexplored.

In this study, we present the first gene-centered GRN that includes ∼70 genes involved in C. elegans metabolism and physiology, 100 TFs and more than 500 protein–DNA interactions between them. The resulting metabolic GRN is enriched for NHRs, compared with other gene-centered regulatory networks. NHRs are well-known regulators of lipid meta-qj;bolism in mammals. The transcriptional activity of NHRs can be modified by diffusible ligands, which allows these TFs to function as molecular sensors and rapidly alter the expression of their target genes. Interestingly, NHRs comprise the largest family of TFs in nematodes; the C. elegans genome encodes 284 NHRs, most of which are uncharacterized. Furthermore, their organization in GRNs has not yet been investigated. In our study, we show that the C. elegans NHRs that we retrieved in the metabolic GRN organize into network modules, and that most of these NHRs function to maintain lipid homeostasis in the nematode. Interestingly, network modularity has been proposed to facilitate rapid and robust changes in gene expression. Our results suggest that the C. elegans metabolic GRN may have evolved by combining NHR family expansion with the specific modular wiring of NHRs to enable the rapid adaptation of the animal to different environmental cues.

NHRs can interact with transcriptional cofactors such as chromatin remodeling complexes and Mediator components. For instance, the C. elegans Mediator subunit, MDT-15, can interact with NHR-49 to regulate the expression of its target genes. To find all the TFs that MDT-15 can interact with, we performed systematic yeast two-hybrid assays with MDT-15 versus 755 full-length TFs. We found that MDT-15 preferentially associates with NHRs, and specifically with those NHRs that confer a metabolic phenotype and that occur in the metabolic GRN. This illustrates the central role of MDT-15 in the regulation of metabolic gene expression.

Using a variety of genetic and biochemical approaches, we characterized NHR-86 in more detail. NHR-86 participates in one of the two NHR modules, and has a high-flux capacity; that is it has both a high incoming and a high outgoing degree. We obtained an nhr-86 mutant and generated an NHR-86 antibody, and showed that NHR-86 functions as an auto-repressor in vivo and that nhr-86 mutant animals store abnormally high levels of body fat.

Finally, we discovered a novel NHR circuit that responds to nutrient availability. In this circuit NHR-45 regulates the activity of nhr-178 promoter in two distinct physiologically important tissues: the intestine and the hypodermis. Both of these NHRs are required to maintain lipid homeostasis in C. elegans. The expression of nhr-178 is responsive to the nutritional status of the animal, which switches between ON and OFF states in the hypodermis. We found that NHR-45 activity is necessary to control this switch in the hypodermis. Interestingly, NHR-45 has opposite effects on the activity of the nhr-178 promoter in these tissues: NHR-45 activates this promoter in the intestine, but represses it in the hypodermis.

Altogether our study leads to a model in which the expansion of the NHR family, TFs that have the capacity to act as fast molecular sensors, is combined with a modular network organization to enable rapid and robust responses to various environmental cues.

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.

In order to determine how signaling pathways differentially regulate gene expression, it is necessary to identify the interactions between transcription factors (TFs) and their cognate cis-regulatory DNA elements. Here, we have outlined a chromatin immunoprecipitation (ChIP) protocol for use in whole Caenorhabditis elegans extracts. We discuss optimization of the procedure, including growth and harvesting of the worms, formaldehyde fixation, TF immunoprecipitation and analysis of bound sequences through real-time PCR. It takes ∼10–12 d to obtain the worm culture for ChIP; the ChIP procedure is spaced out over a period of 2.5 d with two overnight incubations.

Now that numerous high-quality complete genome sequences are available, many efforts are focusing on the “second genomic code”, namely the code that determines how the precise temporal and spatial expression of each gene in the genome is achieved. In this regard, the elucidation of transcription regulatory networks that describe combined transcriptional circuits for an organism of interest has become valuable to our understanding of gene expression at a systems level. Such networks describe physical and regulatory interactions between transcription factors (TFs) and the target genes they regulate under different developmental, physiological, or pathological conditions. The mapping of high-quality transcription regulatory networks depends not only on the accuracy of the experimental or computational method chosen, but also relies on the quality of TF predictions. Moreover, the total repertoire of TFs is not only determined by the protein-coding capacity of the genome, but also by different protein properties, including dimerization, co-factor interactions and post-translational modifications. Here, we discuss the factors that influence TF functionality and, hence, the functionality of the networks in which they operate.

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.

The availability of complete genome sequences necessitates the development of standardized functional assays to analyse the tens of thousands of predicted gene products in high-throughput experimental settings. Such approaches are collectively referred to as ‘functional genomics’. One approach to investigate the properties of a proteome of interest is by systematic analysis of protein–protein interactions. So far, the yeast two-hybrid system is the most commonly used method for large-scale, high-throughput identification of potential protein–protein interactions. Here, we discuss several technical features of variants of the two-hybrid systems in light of data recently obtained from different protein interaction mapping projects for the budding yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans.

Gateway-compatible yeast one-hybrid (Y1H) assays provide a convenient gene-centered (DNA-to-protein) approach to identify the repertoire of transcription factors that can bind a DNA sequence of interest. We present a set of Y1H resources, including clones for 988 of 1,434 (69%) predicted human transcription factors, for the interrogation of interactions using either low or high-throughput settings. These approaches detect both known and novel interactions between human DNA regions and transcription factors.

DRM is a conserved transcription factor complex that includes E2F/DP and pRB family proteins and plays important roles in development and cancer. Here we describe new aspects of DRM binding and function revealed through genome-wide analyses of the Caenorhabditis elegans DRM subunit LIN-54. We show that LIN-54 DNA-binding activity recruits DRM to promoters enriched for adjacent putative E2F/DP and LIN-54 binding sites, suggesting that these two DNA–binding moieties together direct DRM to its target genes. Chromatin immunoprecipitation and gene expression profiling reveals conserved roles for DRM in regulating genes involved in cell division, development, and reproduction. We find that LIN-54 promotes expression of reproduction genes in the germline, but prevents ectopic activation of germline-specific genes in embryonic soma. Strikingly, C. elegans DRM does not act uniformly throughout the genome: the DRM recruitment motif, DRM binding, and DRM-regulated embryonic genes are all under-represented on the X chromosome. However, germline genes down-regulated in lin-54 mutants are over-represented on the X chromosome. We discuss models for how loss of autosome-bound DRM may enhance germline X chromosome silencing. We propose that autosome-enriched binding of DRM arose in C. elegans as a consequence of germline X chromosome silencing and the evolutionary redistribution of germline-expressed and essential target genes to autosomes. Sex chromosome gene regulation may thus have profound evolutionary effects on genome organization and transcriptional regulatory networks.

Author Summary

X chromosomes differ in number between the sexes and differ from autosomes in their associated proteins and gene regulatory properties. In C. elegans both X chromosomes are partially silenced in hermaphrodite germlines. Germline-expressed and essential genes are autosome-enriched and are thought to have fled the X chromosome during evolution because silencing these genes would result in sterility or lethality. We discovered that the C. elegans DRM complex, which controls transcription of genes implicated in development and cancer, avoids the X chromosome. We first describe how DNA–binding components of the DRM complex together recognize DNA sequences upstream of its target genes, and we describe that DRM controls different target genes in the germline versus the soma. We show that the DRM binding motif, the genes bound by DRM, and the embryonic genes regulated by DRM are all under-represented on the X chromosome. Interestingly, compromising DRM function in the germline enhances X chromosome silencing, and we discuss how autosome-bound DRM might regulate X-linked genes in trans. We propose that autosome-enriched binding of DRM co-evolved with the redistribution of its germline-expressed and essential target genes to autosomes. Our data highlight how X chromosome gene regulation may impact both the genomic distribution of gene sets and their transcriptional regulators.