Challenges for modeling global gene regulatory networks during development: Insights from Drosophila

AbstractDevelopment is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative “coarse-grain” models operating at the gene level to very “fine-grain” quantitative models operating at the biophysical “transcription factor-DNA level”. Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans

Divergence in cis-regulatory networks: taking the 'species' out of cross-species analysis

Significant differences between species in genomic occupancy of conserved transcription factors are mostly due to species-specificity of cis-regulatory sequences

Dynamic Regulation by Polycomb Group Protein Complexes Controls Pattern Formation and the Cell Cycle in Drosophila

SummaryPolycomb group (PcG) proteins form conserved regulatory complexes that modify chromatin to repress transcription. Here, we report genome-wide binding profiles of PhoRC, the Drosophila PcG protein complex containing the DNA-binding factor Pho/dYY1 and dSfmbt. PhoRC constitutively occupies short Polycomb response elements (PREs) of a large set of developmental regulator genes in both embryos and larvae. The majority of these PREs are co-occupied by the PcG complexes PRC1 and PRC2. Analysis of PcG mutants shows that the PcG system represses genes required for anteroposterior, dorsoventral, and proximodistal patterning of imaginal discs and that it also represses cell cycle regulator genes. Many of these genes are regulated in a dynamic manner, and our results suggest that the PcG system restricts signaling-mediated activation of target genes to appropriate cells. Analysis of cell cycle regulators indicates that the PcG system also dynamically modulates the expression levels of certain genes, providing a possible explanation for the tumor phenotype of PcG mutants

A bridge from uncertainty to understanding : the meaning of symptom management digital health technology during cancer treatment

Objective: Digital health technology is valued as a tool to provide person-centred care and improve health outcomes amongst people with cancer and their family caregivers. Although the evidence to date shows encouraging effectiveness, there is limited knowledge regarding the lived experience and personal meaning of using supportive technology during cancer treatment. The aim of this study was to explore the lived experiences of people with colorectal cancer receiving chemotherapy using digital health symptom management technology and their family caregivers. Methods: A longitudinal and multi-perspective interpretative phenomenological analytical approach was adopted including three people with newly diagnosed colorectal cancer and four family caregivers. Findings: Three superordinate themes and related subthemes were identified. The first theme (The 3 Cs of symptom management technology) centred on the continuity of care that participants felt while using the technology. The second theme (Digital health technology as a psychosocial support) offered insights into the psychological benefits using technology incurred as they navigated their cancer diagnosis including sense of control and psychological safety. The final theme (Impact of digital health technology on family caregivers) details the supportive effect the technology had on family caregivers’ role, responsibilities and well-being during the cancer experience. Conclusion: Digital health technology can act as a bridge from uncertainty to an understanding regarding a cancer diagnosis and its treatment. Digital health technology can support peoples' understanding of cancer and enhance self-management practices, while being a psychological support in navigating the uncertain and often worrying period of receiving cancer treatment

Relationship and attachment to digital health technology during cancer treatment

Objective The aim of this study is to explore the relationship that people with cancer and their family caregivers develop with symptom management technology during chemotherapy. Data Sources A longitudinal and multi-perspective interpretative phenomenological approach was adopted. Data were collected using one-to-one in-depth interviews with people with colorectal cancer using supportive digital health symptom management technology (n=3) and their family caregivers (n=4) at two time points during chemotherapy treatment. Data were analyzed using interpretative phenomenological analysis and followed COREQ guidelines. Conclusion People with cancer and their family caregivers can develop emotional bonds with supportive symptom management technology during cancer treatment. Digital health technology can be experienced as a person guiding them during their cancer treatment. Participants felt vulnerable after the technology was returned to the research team. Participants recognized that it was not the technology that successfully facilitated them through their initial chemotherapy cycles; rather, the technology helped them learn to manage their symptoms and promoted their self-efficacy, as well as how to emotionally respond. Implications for Nursing Practice: The relationship and psychological bonds people with cancer and their family caregivers develop with technology during treatment may be critically important for oncology nurses to be aware of should digital health be prescribed within the outpatient model of cancer care. This study indicates that technology may not be needed for a full treatment experience, as digital health can promote confidence and self-efficacy regarding symptom management and prepare people with cancer to be independent after the digital health technology is returned to the research team. However, further research is needed regarding individual preferences for digital health provision

The degree of enhancer or promoter activity is reflected by the levels and directionality of eRNA transcription

Gene expression is regulated by promoters, which initiate transcription, and enhancers, which control their temporal and spatial activity. However, the discovery that mammalian enhancers also initiate transcription questions the inherent differences between enhancers and promoters. Here, we investigate the transcriptional properties of enhancers during Drosophila embryogenesis using characterized developmental enhancers. We show that while the timing of enhancer transcription is generally correlated with enhancer activity, the levels and directionality of transcription are highly varied among active enhancers. To assess how this impacts function, we developed a dual transgenic assay to simultaneously measure enhancer and promoter activities from a single element in the same embryo. Extensive transgenic analysis revealed a relationship between the direction of endogenous transcription and the ability to function as an enhancer or promoter in vivo, although enhancer RNA (eRNA) production and activity are not always strictly coupled. Some enhancers (mainly bidirectional) can act as weak promoters, producing overlapping spatio–temporal expression. Conversely, bidirectional promoters often act as strong enhancers, while unidirectional promoters generally cannot. The balance between enhancer and promoter activity is generally reflected in the levels and directionality of eRNA transcription and is likely an inherent sequence property of the elements themselves.Fil: Mikhaylichenko, Olga. European Molecular Biology Laboratory; AlemaniaFil: Bondarenko, Vladyslav. European Molecular Biology Laboratory; AlemaniaFil: Harnett, Dermot. European Molecular Biology Laboratory; AlemaniaFil: Schor, Ignacio Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Males, Matilda. European Molecular Biology Laboratory; AlemaniaFil: Viales, Rebecca R.. European Molecular Biology Laboratory; AlemaniaFil: Furlong, Eileen E. M.. European Molecular Biology Laboratory; Alemani

Non-coding RNA Expression, Function, and Variation during Drosophila Embryogenesis

Long non-coding RNAs (lncRNAs) can often function in the regulation of gene expression during development; however, their generality as essential regulators in developmental processes and organismal phenotypes remains unclear. Here, we performed a tailored investigation of lncRNA expression and function during Drosophila embryogenesis, interrogating multiple stages, tissue specificity, nuclear localization, and genetic backgrounds. Our results almost double the number of annotated lncRNAs expressed at these embryonic stages. lncRNA levels are generally positively correlated with those of their neighboring genes, with little evidence of transcriptional interference. Using fluorescent in situ hybridization, we report the spatiotemporal expression of 15 new lncRNAs, revealing very dynamic tissue-specific patterns. Despite this, deletion of selected lncRNA genes had no obvious developmental defects or effects on viability under standard and stressed conditions. However, two lncRNA deletions resulted in modest expression changes of a small number of genes, suggesting that they fine-tune expression of non-essential genes. Several lncRNAs have strain-specific expression, indicating that they are not fixed within the population. This intra-species variation across genetic backgrounds may thereby be a useful tool to distinguish rapidly evolving lncRNAs with as yet non-essential roles.Fil: Schor, Ignacio Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina. European Molecular Biology Laboratory; AlemaniaFil: Bussotti, Giovanni. European Bioinformatics Institute; Reino UnidoFil: Maleš, Matilda. European Molecular Biology Laboratory; AlemaniaFil: Forneris, Mattia. European Molecular Biology Laboratory; AlemaniaFil: Viales, Rebecca R.. European Molecular Biology Laboratory; AlemaniaFil: Enright, Anton J.. European Bioinformatics Institute; Reino UnidoFil: Furlong, Eileen E. M.. European Molecular Biology Laboratory; Alemani

Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development

Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current in situ hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatiotemporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver http://find.princeton.edu, which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles.Fil: Zhou, Jian*. University of Princeton; Estados UnidosFil: Schor, Ignacio Esteban. European Molecular Biology Laboratory; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Yao, Victoria. University of Princeton; Estados UnidosFil: Theesfeld, Chandra L.. University of Princeton; Estados UnidosFil: Marco-Ferreres, Raquel. European Molecular Biology Laboratory; AlemaniaFil: Tadych, Alicja. University of Princeton; Estados UnidosFil: Furlong, Eileen E. M.. European Molecular Biology Laboratory; AlemaniaFil: Troyanskaya, Olga G.. University of Princeton; Estados Unido