The developmental expression dynamics of Drosophila melanogaster transcription factors

Genome-Wide Analysis of the TCP Transcription Factor Gene Family in Pepper (Capsicum annuum L.)

TCP transcription factors play a key role in regulating various developmental processes, particularly in shoot branching, flower development, and leaf development, and these factors are exclusively found in plants. However, comprehensive studies investigating TCP transcription factors in pepper (Capsicum annuum L.) are lacking. In this study, we identified 27 CaTCP members in the pepper genome, which were classified into Class I and Class II through phylogenetic analysis. The motif analysis revealed that CaTCPs in the same class exhibit similar numbers and distributions of motifs. We predicted that 37 previously reported miRNAs target 19 CaTCPs. The expression levels of CaTCPs varied in various tissues and growth stages. Specifically, CaTCP16, a member of Class II (CIN), exhibited significantly high expression in flowers. Class I CaTCPs exhibited high expression levels in leaves, while Class II CaTCPs showed high expression in lateral branches, especially in the CYC/TB1 subclass. The expression profile suggests that CaTCPs play specific roles in the developmental processes of pepper. We provide a theoretical basis that will assist in further functional validation of the CaTCPs.

MAGE genes encoding for embryonic development in cattle is mainly regulated by zinc finger transcription factor family and slightly by CpG Islands

Background

Melanoma Antigen Genes (MAGEs) are a family of genes that have piqued the interest of scientists for their unique expression pattern. The MAGE genes can be classified into type I MAGEs that expressed in testis and other reproductive tissues while type II MAGEs that have broad expression in many tissues. Several MAGE gene families are expressed in embryonic tissues in almost all eukaryotes, which is essential for embryo development mainly during germ cell differentiation. The aim of this study was to analyze the promoter regions and regulatory elements (transcription factors and CpG islands) of MAGE genes encoding for embryonic development in cattle.

Results

The in silico analysis revealed the highest promoter prediction scores (1.0) for TSS were obtained for two gene sequences (MAGE B4-like and MAGE-L2) while the lowest promoter prediction scores (0.8) was obtained for MAGE B17-like. It also revealed that the best common motif, motif IV, bear a resemblance with three TF families including Zinc-finger family, SMAD family and E2A related factors. From thirteen identified TFs candidates, majority of them (11/13) were clustered to Zinc-finger family serving as transcriptionally activator role whereas three (SP1, SP3 and Znf423) of them as activator or repressor in response to physiological and pathological stimuli. On the other hand we revealed slightly rich CpG islands in the gene body and promoter regions of MAGE genes encoding for embryonic development in cattle.

Conclusion

This in silico analysis of gene promoter regions and regulatory elements in MAGE genes could be useful for understanding regulatory networks and gene expression patterns during embryo development in bovine.

Automated generation of context-specific gene regulatory networks with a weighted approach in Drosophila melanogaster

The regulation of gene expression is a key factor in the development and maintenance of life in all organisms. Even so, little is known at whole genome scale for most genes and contexts. We propose a method, Tool for Weighted Epigenomic Networks in Drosophila melanogaster (Fly T-WEoN), to generate context-specific gene regulatory networks starting from a reference network that contains all known gene regulations in the fly. Unlikely regulations are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from the literature. Experimental data files can be generated with several standard procedures and used solely when and if available. Fly T-WEoN is available as a Cytoscape application that permits integration with other tools and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster. Fly T-WEoN together with its step-by-step guide is available at https://weon.readthedocs.io.

A Comprehensive Drosophila melanogaster Transcription Factor Interactome

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. We further demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

Combinatorial regulation by transcription factors (TFs) is one mechanism for achieving condition and tissue-specific gene regulation. Shokri et al. mapped TF-TF interactions between most Drosophila TFs, reporting a comprehensive TF-TF network integrated with previously known interactions. They used this network to discern distinct TF-DNA binding modes.

Dynamics of Gene Co-expression Networks in Time-Series Data: A Case Study in Drosophila melanogaster Embryogenesis

Co-expression networks tightly coordinate the spatiotemporal patterns of gene expression unfolding during development. Due to the dynamic nature of developmental processes simply overlaying gene expression patterns onto static representations of co-expression networks may be misleading. Here, we aim to formally quantitate topological changes of co-expression networks during embryonic development using a publicly available Drosophila melanogaster transcriptome data set comprising 14 time points. We deployed a network approach which inferred 10 discrete co-expression networks by smoothly sliding along from early to late development using 5 consecutive time points per window. Such an approach allows changing network structure, including the presence of hubs, modules and other topological parameters to be quantitated. To explore the dynamic aspects of gene expression captured by our approach, we focused on regulator genes with apparent influence over particular aspects of development. Those key regulators were selected using a differential network algorithm to contrast the first 7 (early) with the last 7 (late) developmental time points. This assigns high scores to genes whose connectivity to abundant differentially expressed target genes has changed dramatically between states. We have produced a list of key regulators – some increasing (e.g., Tusp, slbo, Sidpn, DCAF12, and chinmo) and some decreasing (Rfx, bap, Hmx, Awh, and mld) connectivity during development – which reflects their role in different stages of embryogenesis. The networks we have constructed can be explored and interpreted within Cytoscape software and provide a new systems biology approach for the Drosophila research community to better visualize and interpret developmental regulation of gene expression.

Exploring a Drosophila Transcription Factor Interaction Network to Identify Cis-Regulatory Modules

Multiple transcription factors (TFs) bind to specific sites in the genome and interact among themselves to form the cis-regulatory modules (CRMs). They are essential in modulating the expression of genes, and it is important to study this interplay to understand gene regulation. In the present study, we integrated experimentally identified TF binding sites collected from published studies with computationally predicted TF binding sites to identify Drosophila CRMs. Along with the detection of the previously known CRMs, this approach identified novel protein combinations. We determined high-occupancy target sites, where a large number of TFs bind. Investigating these sites revealed that Giant, Dichaete, and Knirp are highly enriched in these locations. A common TAG team motif was observed at these sites, which might play a role in recruiting other TFs. While comparing the binding sites at distal and proximal promoters, we found that certain regulatory TFs, such as Zelda, were highly enriched in enhancers. Our study has shown that, from the information available concerning the TF binding sites, the real CRMs could be predicted accurately and efficiently. Although we only may claim co-occurrence of these proteins in this study, it may actually point to their interaction (as known interaction proteins typically co-occur together). Such an integrative approach can, therefore, help us to provide a better understanding of the interplay among the factors, even though further experimental verification is required.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

Regulation of transcription factors on sexual dimorphism of fig wasps

Fig wasps exhibit extreme intraspecific morphological divergence in the wings, compound eyes, antennae, body color, and size. Corresponding to this, behaviors and lifestyles between two sexes are also different: females can emerge from fig and fly to other fig tree to oviposit and pollinate, while males live inside fig for all their lifetime. Genetic regulation may drive these extreme intraspecific morphological and behavioral divergence. Transcription factors (TFs) involved in morphological development and physiological activity may exhibit sex-specific expressions. Herein, we detect 865 TFs by using genomic and transcriptomic data of the fig wasp Ceratosolen solmsi. Analyses of transcriptomic data indicated that up-regulated TFs in females show significant enrichment in development of the wing, eye and antenna in all stages, from larva to adult. Meanwhile, TFs related to the development of a variety of organs display sex-specific patterns of expression in the adults and these may contribute significantly to their sexual dimorphism. In addition, up-regulated TFs in adult males exhibit enrichment in genitalia development and circadian rhythm, which correspond with mating and protandry. This finding is consistent with their sex-specific behaviors. In conclusion, our results strongly indicate that TFs play important roles in the sexual dimorphism of fig wasps.

Transcription factor networks in Drosophila melanogaster

Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional level and is controlled by complex regulatory networks of transcription factors (TFs). TFs act through combinatorial interactions with other TFs, cofactors, and chromatin-remodeling proteins. Here, we define protein-protein interactions using a coaffinity purification/mass spectrometry method and study 459 Drosophila melanogaster transcription-related factors, representing approximately half of the established catalog of TFs. We probe this network in vivo, demonstrating functional interactions for many interacting proteins, and test the predictive value of our data set. Building on these analyses, we combine regulatory network inference models with physical interactions to define an integrated network that connects combinatorial TF protein interactions to the transcriptional regulatory network of the cell. We use this integrated network as a tool to connect the functional network of genetic modifiers related to mastermind, a transcriptional cofactor of the Notch pathway.

Spatial expression of transcription factors in Drosophila embryonic organ development

Background

Site-specific transcription factors (TFs) bind DNA regulatory elements to control expression of target genes, forming the core of gene regulatory networks. Despite decades of research, most studies focus on only a small number of TFs and the roles of many remain unknown.

Results

We present a systematic characterization of spatiotemporal gene expression patterns for all known or predicted Drosophila TFs throughout embryogenesis, the first such comprehensive study for any metazoan animal. We generated RNA expression patterns for all 708 TFs by in situ hybridization, annotated the patterns using an anatomical controlled vocabulary, and analyzed TF expression in the context of organ system development. Nearly all TFs are expressed during embryogenesis and more than half are specifically expressed in the central nervous system. Compared to other genes, TFs are enriched early in the development of most organ systems, and throughout the development of the nervous system. Of the 535 TFs with spatially restricted expression, 79% are dynamically expressed in multiple organ systems while 21% show single-organ specificity. Of those expressed in multiple organ systems, 77 TFs are restricted to a single organ system either early or late in development. Expression patterns for 354 TFs are characterized for the first time in this study.

Conclusions

We produced a reference TF dataset for the investigation of gene regulatory networks in embryogenesis, and gained insight into the expression dynamics of the full complement of TFs controlling the development of each organ system.

A comparative analysis of transcription factor expression during metazoan embryonic development

During embryonic development, a complex organism is formed from a single starting cell. These processes of growth and differentiation are driven by large transcriptional changes, which are following the expression and activity of transcription factors (TFs). This study sought to compare TF expression during embryonic development in a diverse group of metazoan animals: representatives of vertebrates (Danio rerio, Xenopus tropicalis), a chordate (Ciona intestinalis) and invertebrate phyla such as insects (Drosophila melanogaster, Anopheles gambiae) and nematodes (Caenorhabditis elegans) were sampled, The different species showed overall very similar TF expression patterns, with TF expression increasing during the initial stages of development. C2H2 zinc finger TFs were over-represented and Homeobox TFs were under-represented in the early stages in all species. We further clustered TFs for each species based on their quantitative temporal expression profiles. This showed very similar TF expression trends in development in vertebrate and insect species. However, analysis of the expression of orthologous pairs between more closely related species showed that expression of most individual TFs is not conserved, following the general model of duplication and diversification. The degree of similarity between TF expression between Xenopus tropicalis and Danio rerio followed the hourglass model, with the greatest similarity occuring during the early tailbud stage in Xenopus tropicalis and the late segmentation stage in Danio rerio. However, for Drosophila melanogaster and Anopheles gambiae there were two periods of high TF transcriptome similarity, one during the Arthropod phylotypic stage at 8-10 hours into Drosophila development and the other later at 16-18 hours into Drosophila development.

Global analysis of target genes of 21 members of the ZAD transcription factor family in Drosophila melanogaster

The zinc-finger associated domain (ZAD) family is the largest transcription factor family in dipteran insects. Still, their functional significance is barely recognized in the literature due in part to their resistance to mutagenesis screens in genetic studies. Therefore, we employed in vitro techniques to identify the DNA-binding characteristics of several members of the Drosophila melanogaster ZAD family in an effort to study their target genes. In this comprehensive investigation, we constructed a panel of GST-Zinc finger (ZnF) array chimera from 21 selected ZAD proteins and used them to select binding sites from an oligonucleotide library by employing electrophoretic mobility shift assays (EMSA). Samples of the binding population were sequenced and used to derive DNA-binding consensus sequence for each member. These consensus sequences were tested for complex formation with their respective protein chimera and the specificity of binding ascertained by competition EMSA. Bioinformatics tools were used to identify potential genetic targets. The identified consensus sequences were distinct for each member and the putative genomic targets were clustered in the regulatory regions of specific genes. This appears to be consistent with a conservation of function between members and also suggests that the overlapping functions of ZAD proteins are the result of positive selection to maintain redundancy and not simply artifacts of recent expansion. Putative target genes suggest a major role of the ZAD family members in the regulation of several early developmental genes including homeobox transcription factors.

Genome-wide transcription factor gene prediction and their expressional tissue-specificities in maize

Transcription factors (TFs) are important regulators of gene expression. To better understand TF-encoding genes in maize (Zea mays L.), a genome-wide TF prediction was performed using the updated B73 reference genome. A total of 2298 TF genes were identified, which can be classified into 56 families. The largest family, known as the MYB superfamily, comprises 322 MYB and MYB-related TF genes. The expression patterns of 2 014 (87.64%) TF genes were examined using RNA-seq data, which resulted in the identification of a subset of TFs that are specifically expressed in particular tissues (including root, shoot, leaf, ear, tassel and kernel). Similarly, 98 kernel-specific TF genes were further analyzed, and it was observed that 29 of the kernel-specific genes were preferentially expressed in the early kernel developmental stage, while 69 of the genes were expressed in the late kernel developmental stage. Identification of these TFs, particularly the tissue-specific ones, provides important information for the understanding of development and transcriptional regulation of maize.

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

Background

Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts.

Results

On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns.

Conclusions

Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

Dynamic reprogramming of chromatin accessibility during Drosophila embryo development

Background

The development of complex organisms is believed to involve progressive restrictions in cellular fate. Understanding the scope and features of chromatin dynamics during embryogenesis, and identifying regulatory elements important for directing developmental processes remain key goals of developmental biology.

Results

We used in vivo DNaseI sensitivity to map the locations of regulatory elements, and explore the changing chromatin landscape during the first 11 hours of Drosophila embryonic development. We identified thousands of conserved, developmentally dynamic, distal DNaseI hypersensitive sites associated with spatial and temporal expression patterning of linked genes and with large regions of chromatin plasticity. We observed a nearly uniform balance between developmentally up- and down-regulated DNaseI hypersensitive sites. Analysis of promoter chromatin architecture revealed a novel role for classical core promoter sequence elements in directing temporally regulated chromatin remodeling. Another unexpected feature of the chromatin landscape was the presence of localized accessibility over many protein-coding regions, subsets of which were developmentally regulated or associated with the transcription of genes with prominent maternal RNA contributions in the blastoderm.

Conclusions

Our results provide a global view of the rich and dynamic chromatin landscape of early animal development, as well as novel insights into the organization of developmentally regulated chromatin features.

Mapping the complexity of transcription control in higher eukaryotes

Recent large analyses suggest the importance of combinatorial regulation by broadly expressed transcription factors rather than expression domains characterized by highly specific factors.

Recent genomic analyses suggest the importance of combinatorial regulation by broadly expressed transcription factors rather than expression domains characterized by highly specific factors.