The C. elegans anchor cell: A model to elucidate mechanisms underlying invasion through basement membrane

Cell invasion through basement membrane barriers is crucial during many developmental processes and in immune surveillance. Dysregulation of invasion also drives the pathology of numerous human diseases, such as metastasis and inflammatory disorders. Cell invasion involves dynamic interactions between the invading cell, basement membrane, and neighboring tissues. Owing to this complexity, cell invasion is challenging to study in vivo, which has hampered the understanding of mechanisms controlling invasion. Caenorhabditis elegans anchor cell invasion is a powerful in vivo model where subcellular imaging of cell-basement membrane interactions can be combined with genetic, genomic, and single-cell molecular perturbation studies. In this review, we outline insights gained by studying anchor cell invasion, which span transcriptional networks, translational regulation, secretory apparatus expansion, dynamic and adaptable protrusions that breach and clear basement membrane, and a complex, localized metabolic network that fuels invasion. Together, investigation of anchor cell invasion is building a comprehensive understanding of the mechanisms that underlie invasion, which we expect will ultimately facilitate better therapeutic strategies to control cell invasive activity in human disease.

Bioinformatics for wet-lab scientists: practical application in sequencing analysis

BACKGROUND

Genomics data is available to the scientific community after publication of research projects and can be investigated for a multitude of research questions. However, in many cases deposited data is only assessed and used for the initial publication, resulting in valuable resources not being exploited to their full depth. MAIN: A likely reason for this is that many wetlab-based researchers are not formally trained to apply bioinformatic tools and may therefore assume that they lack the necessary experience to do so themselves. In this article, we present a series of freely available, predominantly web-based platforms and bioinformatic tools that can be combined in analysis pipelines to interrogate different types of next-generation sequencing data. Additionally to the presented exemplary route, we also list a number of alternative tools that can be combined in a mix-and-match fashion. We place special emphasis on tools that can be followed and used correctly without extensive prior knowledge in programming. Such analysis pipelines can be applied to existing data downloaded from the public domain or be compared to the results of own experiments.

CONCLUSION

Integrating transcription factor binding to chromatin (ChIP-seq) with transcriptional output (RNA-seq) and chromatin accessibility (ATAC-seq) can not only assist to form a deeper understanding of the molecular interactions underlying transcriptional regulation but will also help establishing new hypotheses and pre-testing them in silico.

Mapping of de novo mutations in primary biliary cholangitis to a disease-specific co-expression network underlying homeostasis and metabolism

Primary biliary cholangitis (PBC) is an autoimmune disease involving dysregulation of a broad array of homeostatic and metabolic processes. Although considerable single-nucleotide polymorphisms have been unveiled, a large fraction of risk factors remains enigmatic. Candidate genes with rare mutations that tend to confer more deleterious effects need to be identified. To help pinpoint cellular and developmental mechanisms beyond common noncoding variants, we integrated whole exome sequencing with integrative network analysis to investigate genes harboring de novo mutations. Prominent convergence has been revealed on a network of disease-specific co-expression comprised of 55 genes associated with homeostasis and metabolism. The transcription factor MEF2D and the DNA repair gene PARP2 were highlighted as hub genes and identified to be up- and down-regulated, respectively, in peripheral blood data set. Enrichment analysis demonstrated altered expression of MEF2D and PARP2 may trigger a series of molecular and cellular processes with pivotal roles in PBC pathophysiology. Our study identified genes with de novo mutations in PBC and suggested a subset of genes in homeostasis and metabolism tend to act in synergy through converging on co-expression network, providing novel insights into the etiology of PBC and expanding the pool of molecular candidates for discovering clinically actionable biomarkers.

Comparison of Gene Expression Patterns in Articular Cartilage and Xiphoid Cartilage

Cartilage is a resilient and smooth connective tissue that is found throughout the body. Among the three major types of cartilage, namely hyaline cartilage, elastic cartilage, and fibrocartilage, hyaline cartilage is the most widespread type of cartilage predominantly located in the joint surfaces (articular cartilage, AC). It remains a huge challenge for orthopedic surgeons to deal with AC damage since it has limited capacity for self-repair. Xiphoid cartilage (XC) is a vestigial cartilage located in the distal end of the sternum. XC-derived chondrocytes exhibit strong chondrogenic differentiation capacity. Thus, XC could become a potential donor site of chondrocytes for cartilage repair and regeneration. However, the underlying gene expression patterns between AC and XC are still largely unknown. In the present study, we used state-of-the-art RNA-seq technology combined with validation method to investigate the gene expression patterns between AC and XC, and identified a series of differentially expressed genes (DEGs) involved in chondrocyte commitment and differentiation including growth factors, transcription factors, and extracellular matrices. We demonstrated that the majority of significantly up-regulated DEGs (XC vs. AC) in XC were involved in regulating cartilage regeneration and repair, whereas the majority of significantly up-regulated DEGs (XC vs. AC) in AC were involved in regulating chondrocyte differentiation and maturation. This study has increased our knowledge of transcriptional networks in hyaline cartilage and elastic cartilage. It also supports the use of XC-derived chondrocytes as a potential cell resource for cartilage regeneration and repair.

Conservation of neural progenitor identity and the emergence of neocortical neuronal diversity

One paramount challenge for neuroscientists over the past century has been to identify the embryonic origins of the enormous diversity of cortical neurons found in the adult human neocortex and to unravel the developmental processes governing their emergence. In all mammals, including humans, the radial glia lining the ventricles of the embryonic telencephalon, more recently reclassified as apical radial glia (aRGs), have been identified as the neural progenitors giving rise to all excitatory neurons and inhibitory interneurons of the six-layered cortex. In this review, we explore the fundamental molecular and cellular mechanisms that regulate aRG function and the generation of neuronal diversity in the dorsal telencephalon. We survey the key structural features essential for the retention of the highly polarized aRG morphology and therefore impose aRG identity after cytokinesis. We discuss how these structures and associated molecular signaling complexes influence aRG proliferative capacity and the decision to undergo proliferative self-renewing symmetric or neurogenic asymmetric divisions. We also explore the intriguing and complex question of how the extensive neuronal diversity within the adult neocortex arises from the small aRG population located within the cortical proliferative zone. We further highlight the recent clonal lineage tracing and single-cell transcriptomic profiling studies providing compelling evidence that individual neuronal identity emerges as a consequence of exposure to temporally regulated extrinsic cues which coordinate waves of transcriptional activity that evolve over time to drive neuronal commitment and maturation.

Dynamic Modeling of Transcriptional Gene Regulatory Networks

Diverse cellular phenotypes are determined by groups of transcription factors (TFs) and other regulators that influence each others' gene expression, forming transcriptional gene regulatory networks (GRNs). In many biological contexts, especially in development and associated diseases, the expression of the genes in GRNs is not static but evolves in time. Modeling the dynamics of GRN state is an important approach for understanding diverse cellular phenomena such as cell-fate specification, pluripotency and cell-fate reprogramming, oncogenesis, and tissue regeneration. In this protocol, we describe how to model GRNs using a data-driven dynamic modeling methodology, gene circuits. Gene circuits do not require knowledge of the GRN topology and connectivity but instead learn them from training data, making them very general and applicable to diverse biological contexts. We utilize the MATLAB-based gene circuit modeling software Fast Inference of Gene Regulation (FIGR) for training the model on quantitative gene expression data and simulating the GRN. We describe all the steps in the modeling life cycle, from formulating the model, training the model using FIGR, simulating the GRN, to analyzing and interpreting the model output. This protocol highlights these steps with the example of a dynamical model of the gap gene GRN involved in Drosophila segmentation and includes example MATLAB statements for each step.

Bromodomain and extra-terminal domain (BET) proteins regulate melanocyte differentiation

BACKGROUND

Pharmacologic inhibition of bromodomain and extra-terminal (BET) proteins is currently being explored as a new therapeutic approach in cancer. Some studies have also implicated BET proteins as regulators of cell identity and differentiation through their interactions with lineage-specific factors. However, the role of BET proteins has not yet been investigated in melanocyte differentiation. Melanocyte inducing transcription factor (MITF) is the master regulator of melanocyte differentiation, essential for pigmentation and melanocyte survival. In this study, we tested the hypothesis that BET proteins regulate melanocyte differentiation through interactions with MITF.

RESULTS

Here we show that chemical inhibition of BET proteins prevents differentiation of unpigmented melanoblasts into pigmented melanocytes and results in de-pigmentation of differentiated melanocytes. BET inhibition also slowed cell growth, without causing cell death, increasing the number of cells in G1. Transcriptional profiling revealed that BET inhibition resulted in decreased expression of pigment-specific genes, including many MITF targets. The expression of pigment-specific genes was also down-regulated in melanoma cells, but to a lesser extent. We found that RNAi depletion of the BET family members, bromodomain-containing protein 4 (BRD4) and bromodomain-containing protein 2 (BRD2) inhibited expression of two melanin synthesis enzymes, TYR and TYRP1. Both BRD4 and BRD2 were detected on melanocyte promoters surrounding MITF-binding sites, were associated with open chromatin structure, and promoted MITF binding to these sites. Furthermore, BRD4 and BRD2 physically interacted with MITF.

CONCLUSION

These findings indicate a requirement for BET proteins in the regulation of pigmentation and melanocyte differentiation. We identified changes in pigmentation specific gene expression that occur upon BET inhibition in melanoblasts, melanocytes, and melanoma cells.

MECoRank: cancer driver genes discovery simultaneously evaluating the impact of SNVs and differential expression on transcriptional networks

Background

Although there are huge volumes of genomic data, how to decipher them and identify driver events is still a challenge. The current methods based on network typically use the relationship between genomic events and consequent changes in gene expression to nominate putative driver genes. But there may exist some relationships within the transcriptional network.

Methods

We developed MECoRank, a novel method that improves the recognition accuracy of driver genes. MECoRank is based on bipartite graph to propagates the scores via an iterative process. After iteration, we will obtain a ranked gene list for each patient sample. Then, we applied the Condorcet voting method to determine the most impactful drivers in a population.

Results

We applied MECoRank to three cancer datasets to reveal candidate driver genes which have a greater impact on gene expression. Experimental results show that our method not only can identify more driver genes that have been validated than other methods, but also can recognize some impactful novel genes which have been proved to be more important in literature.

Conclusions

We propose a novel approach named MECoRank to prioritize driver genes based on their impact on the expression in the molecular interaction network. This method not only assesses mutation’s effect on the transcriptional network, but also assesses the differential expression’s effect within the transcriptional network. And the results demonstrated that MECoRank has better performance than the other competing approaches in identifying driver genes.

Novel transcriptional responses to heat revealed by turning up the heat at night

KEY MESSAGE

The circadian clock controls many molecular activities, impacting experimental interpretation. We quantify the genome-wide effects of time-of-day on the heat-shock response and the effects of "diurnal bias" in stress experiments. Heat stress has significant adverse effects on plant productivity worldwide. Most experiments examining heat stress are performed during daytime hours, generating a 'diurnal bias' in the pathways and regulatory mechanisms identified. Such bias may confound downstream interpretations and limit our understanding of the full response to heat stress. Here we show that the transcriptional and physiological responses to a sudden heat shock in Arabidopsis are profoundly sensitive to the time of day. We observe that plant tolerance and acclimation to heat shock vary throughout the day and are maximal at dusk. Consistently, over 75% of heat-responsive transcripts show a time of day-dependent response, including many previously characterized heat-response genes. This temporal sensitivity implies a complex interaction between time and temperature where daily variations in basal transcription influence thermotolerance. When we examined these transcriptional responses, we uncovered novel night-response genes and cis-regulatory elements, underpinning new aspects of heat stress responses not previously appreciated. Exploiting this temporal variation can be applied to most environmental responses to understand the underlying network wiring. Therefore, we propose that using time as a perturbagen is an approach that will enhance our understanding of plant regulatory networks and responses to environmental stresses.

Differential Connectivity in Colorectal Cancer Gene Expression Network

BACKGROUND

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease.

METHODS

In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified.

RESULTS

The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events.

DISCUSSION

Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

Female reproductive organ formation: A multitasking endeavor

Multicellular organisms, such as plants, fungi, and animals, develop organs with specialized functions. Major challenges in developing such structures include establishment of polarity along three axes (apical-basal, medio-lateral, and dorso-ventral/abaxial-adaxial), specification of tissue types and their coordinated growth, and maintenance of communication between the organ and the entire organism. The gynoecium of the model plant Arabidopsis thaliana embodies the female reproductive organ and has proven an excellent model system for studying organ establishment and development, given its division into different regions with distinct symmetries and highly diverse tissue types. Upon pollination, the gynoecium undergoes dramatic changes in morphology and developmental programming to form the seed-containing fruit. In this review, we wish to provide a detailed overview of the molecular and genetic mechanisms that are known to guide gynoecium and fruit development in A. thaliana. We describe networks of key genetic regulators and their interactions with hormonal dynamics in driving these developmental processes. The discoveries made to date clearly demonstrate that conclusions drawn from studying gynoecium and fruit development in flowering plants can be used to further our general understanding of organ formation across the plant kingdom. Importantly, this acquired knowledge is increasingly being used to improve fruit and seed crops, facilitated by the recent profound advances in genomics, cloning, and gene-editing technologies.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks

Background

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues.

Results

Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database.

Conclusions

HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2190-6) contains supplementary material, which is available to authorized users.

Molecular characterization of gene regulatory networks in primary human tracheal and bronchial epithelial cells

BACKGROUND

Robust methods to culture primary airway epithelial cells were developed several decades ago and these cells provide the model of choice to investigate many diseases of the human lung. However, the molecular signature of cells from different regions of the airway epithelium has not been well characterized.

METHODS

We utilize DNase-seq and RNA-seq to examine the molecular signatures of primary cells derived from human tracheal and bronchial tissues, as well as healthy and diseased (cystic fibrosis (CF)) donor lung tissue.

RESULTS

Our data reveal an airway cell signature that is divergent from other epithelial cell types and from common airway epithelial cell lines. The differences between tracheal and bronchial cells are clearly evident as are common regulatory features. Only minor variation is seen between bronchial cells from healthy or CF donors.

CONCLUSIONS

These data are a valuable resource for functional genomics analysis of airway epithelial tissues in human disease.

Cell interactions, signals and transcriptional hierarchy governing placode progenitor induction

In vertebrates, cranial placodes contribute to all sense organs and sensory ganglia and arise from a common pool of Six1/Eya2+ progenitors. Here we dissect the events that specify ectodermal cells as placode progenitors using newly identified genes upstream of the Six/Eya complex. We show in chick that two different tissues, namely the lateral head mesoderm and the prechordal mesendoderm, gradually induce placode progenitors: cells pass through successive transcriptional states, each identified by distinct factors and controlled by different signals. Both tissues initiate a common transcriptional state but over time impart regional character, with the acquisition of anterior identity dependent on Shh signalling. Using a network inference approach we predict the regulatory relationships among newly identified transcription factors and verify predicted links in knockdown experiments. Based on this analysis we propose a new model for placode progenitor induction, in which the initial induction of a generic transcriptional state precedes regional divergence.

Genetic evidence that Nkx2.2 acts primarily downstream of Neurog3 in pancreatic endocrine lineage development

Many pancreatic transcription factors that are essential for islet cell differentiation have been well characterized; however, because they are often expressed in several different cell populations, their functional hierarchy remains unclear. To parse out the spatiotemporal regulation of islet cell differentiation, we used a Neurog3-Cre allele to ablate Nkx2.2, one of the earliest and most broadly expressed islet transcription factors, specifically in the Neurog3⁺ endocrine progenitor lineage (Nkx2.2^△endo). Remarkably, many essential components of the β cell transcriptional network that were down-regulated in the Nkx2.2^KO mice, were maintained in the Nkx2.2^△endo mice - yet the Nkx2.2^△endo mice displayed defective β cell differentiation and recapitulated the Nkx2.2^KO phenotype. This suggests that Nkx2.2 is not only required in the early pancreatic progenitors, but has additional essential activities within the endocrine progenitor population. Consistently, we demonstrate Nkx2.2 functions as an integral component of a modular regulatory program to correctly specify pancreatic islet cell fates.

DOI:http://dx.doi.org/10.7554/eLife.20010.001

Runx1 Structure and Function in Blood Cell Development

RUNX transcription factors belong to a highly conserved class of transcriptional regulators which play various roles in the development of the majority of metazoans. In this review we focus on the founding member of the family, RUNX1, and its role in the transcriptional control of blood cell development in mammals. We summarize data showing that RUNX1 functions both as activator and repressor within a chromatin environment, a feature that requires its interaction with multiple other transcription factors and co-factors. Furthermore, we outline how RUNX1 works together with other factors to reshape the epigenetic landscape and the three-dimensional structure of gene loci within the nucleus. Finally, we review how aberrant forms of RUNX1 deregulate blood cell development and cause hematopoietic malignancies.

Evolution of transcriptional networks in yeast: alternative teams of transcriptional factors for different species

Background

The diversity in eukaryotic life reflects a diversity in regulatory pathways. Nocedal and Johnson argue that the rewiring of gene regulatory networks is a major force for the diversity of life, that changes in regulation can create new species.

Results

We have created a method (based on our new “ping-pong algorithm) for detecting more complicated rewirings, where several transcription factors can substitute for one or more transcription factors in the regulation of a family of co-regulated genes. An example is illustrative. A rewiring has been reported by Hogues et al. that RAP1 in Saccharomyces cerevisiae substitutes for TBF1/CBF1 in Candida albicans for ribosomal RP genes. There one transcription factor substitutes for another on some collection of genes. Such a substitution is referred to as a “rewiring”. We agree with this finding of rewiring as far as it goes but the situation is more complicated. Many transcription factors can regulate a gene and our algorithm finds that in this example a “team” (or collection) of three transcription factors including RAP1 substitutes for TBF1 for 19 genes. The switch occurs for a branch of the phylogenetic tree containing 10 species (including Saccharomyces cerevisiae), while the remaining 13 species (Candida albicans) are regulated by TBF1.

Conclusions

To gain insight into more general evolutionary mechanisms, we have created a mathematical algorithm that finds such general switching events and we prove that it converges. Of course any such computational discovery should be validated in the biological tests. For each branch of the phylogenetic tree and each gene module, our algorithm finds a sub-group of co-regulated genes and a team of transcription factors that substitutes for another team of transcription factors. In most cases the signal will be small but in some cases we find a strong signal of switching. We report our findings for 23 Ascomycota fungi species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3102-7) contains supplementary material, which is available to authorized users.

A somatic mutation of GFI1B identified in leukemia alters cell fate via a SPI1 (PU.1) centered genetic regulatory network

We identify a mutation (D262N) in the erythroid-affiliated transcriptional repressor GFI1B, in an acute myeloid leukemia (AML) patient with antecedent myelodysplastic syndrome (MDS). The GFI1B-D262N mutant functionally antagonizes the transcriptional activity of wild-type GFI1B. GFI1B-D262N promoted myelomonocytic versus erythroid output from primary human hematopoietic precursors and enhanced cell survival of both normal and MDS derived precursors. Re-analysis of AML transcriptome data identifies a distinct group of patients in whom expression of wild-type GFI1B and SPI1 (PU.1) have an inverse pattern. In delineating this GFI1B-SPI1 relationship we show that (i) SPI1 is a direct target of GFI1B, (ii) expression of GFI1B-D262N produces elevated expression of SPI1, and (iii) SPI1-knockdown restores balanced lineage output from GFI1B-D262N-expressing precursors. These results table the SPI1-GFI1B transcriptional network as an important regulatory axis in AML as well as in the development of erythroid versus myelomonocytic cell fate.

SOX9 modulates the expression of key transcription factors required for heart valve development

Heart valve formation initiates when endothelial cells of the heart transform into mesenchyme and populate the cardiac cushions. The transcription factor SOX9 is highly expressed in the cardiac cushion mesenchyme, and is essential for heart valve development. Loss of Sox9 in mouse cardiac cushion mesenchyme alters cell proliferation, embryonic survival, and valve formation. Despite this important role, little is known about how SOX9 regulates heart valve formation or its transcriptional targets. Therefore, we mapped putative SOX9 binding sites by ChIP-Seq in E12.5 heart valves, a stage at which the valve mesenchyme is actively proliferating and initiating differentiation. Embryonic heart valves have been shown to express a high number of genes that are associated with chondrogenesis, including several extracellular matrix proteins and transcription factors that regulate chondrogenesis. Therefore, we compared regions of putative SOX9 DNA binding between E12.5 heart valves and E12.5 limb buds. We identified context-dependent and context-independent SOX9-interacting regions throughout the genome. Analysis of context-independent SOX9 binding suggests an extensive role for SOX9 across tissues in regulating proliferation-associated genes including key components of the AP-1 complex. Integrative analysis of tissue-specific SOX9-interacting regions and gene expression profiles on Sox9-deficient heart valves demonstrated that SOX9 controls the expression of several transcription factors with previously identified roles in heart valve development, including Twist1, Sox4, Mecom and Pitx2. Together, our data identify SOX9-coordinated transcriptional hierarchies that control cell proliferation and differentiation during valve formation.

A theoretical framework for the regulation of Shh morphogen-controlled gene expression

How morphogen gradients govern the pattern of gene expression in developing tissues is not well understood. Here, we describe a statistical thermodynamic model of gene regulation that combines the activity of a morphogen with the transcriptional network it controls. Using Sonic hedgehog (Shh) patterning of the ventral neural tube as an example, we show that the framework can be used together with the principled parameter selection technique of approximate Bayesian computation to obtain a dynamical model that accurately predicts tissue patterning. The analysis indicates that, for each target gene regulated by Gli, which is the transcriptional effector of Shh signalling, there is a neutral point in the gradient, either side of which altering the Gli binding affinity has opposite effects on gene expression. This explains recent counterintuitive experimental observations. The approach is broadly applicable and provides a unifying framework to explain the temporospatial pattern of morphogen-regulated gene expression.

Coordinated repression and activation of two transcriptional programs stabilizes cell fate during myogenesis

Molecular models of cell fate specification typically focus on the activation of specific lineage programs. However, the concurrent repression of unwanted transcriptional networks is also essential to stabilize certain cellular identities, as shown in a number of diverse systems and phyla. Here, we demonstrate that this dual requirement also holds true in the context of Drosophila myogenesis. By integrating genetics and genomics, we identified a new role for the pleiotropic transcriptional repressor Tramtrack69 in myoblast specification. Drosophila muscles are formed through the fusion of two discrete cell types: founder cells (FCs) and fusion-competent myoblasts (FCMs). When tramtrack69 is removed, FCMs appear to adopt an alternative muscle FC-like fate. Conversely, ectopic expression of this repressor phenocopies muscle defects seen in loss-of-function lame duck mutants, a transcription factor specific to FCMs. This occurs through Tramtrack69-mediated repression in FCMs, whereas Lame duck activates a largely distinct transcriptional program in the same cells. Lineage-specific factors are therefore not sufficient to maintain FCM identity. Instead, their identity appears more plastic, requiring the combination of instructive repressive and activating programs to stabilize cell fate.

Integrated physiology and systems biology of PPARα

The Peroxisome Proliferator Activated Receptor alpha (PPARα) is a transcription factor that plays a major role in metabolic regulation. This review addresses the functional role of PPARα in intermediary metabolism and provides a detailed overview of metabolic genes targeted by PPARα, with a focus on liver. A distinction is made between the impact of PPARα on metabolism upon physiological, pharmacological, and nutritional activation. Low and high throughput gene expression analyses have allowed the creation of a comprehensive map illustrating the role of PPARα as master regulator of lipid metabolism via regulation of numerous genes. The map puts PPARα at the center of a regulatory hub impacting fatty acid uptake, fatty acid activation, intracellular fatty acid binding, mitochondrial and peroxisomal fatty acid oxidation, ketogenesis, triglyceride turnover, lipid droplet biology, gluconeogenesis, and bile synthesis/secretion. In addition, PPARα governs the expression of several secreted proteins that exert local and endocrine functions.

Recent progress using systems biology approaches to better understand molecular mechanisms of immunity

The immune system is composed of multiple dynamic molecular and cellular networks, the complexity of which has been revealed by decades of exacting reductionist research. However, understanding of the immune system sufficient to anticipate its response to novel perturbations requires a more integrative or systems approach to immunology. While methods for unbiased high-throughput data acquisition and computational integration of the resulting datasets are still relatively new, they have begun to substantially enhance our understanding of immunological phenomena. Such approaches have expanded our view of interconnected signaling and transcriptional networks and have highlighted the function of non-linear processes such as spatial regulation and feedback loops. In addition, advances in single cell measurement technology have demonstrated potential sources and functions of response heterogeneity in system behavior. The success of the studies reviewed here often depended upon integration of one or more systems biology approaches with more traditional methods. We hope these examples will inspire a broader range of immunologists to probe questions in a quantitative and integrated manner, advancing collective efforts to understand the immune "system".