Epidermal differentiation gene regulatory networks controlled by MAF and MAFB

Numerous regulatory factors in epidermal differentiation and their role in regulating different cell states have been identified in recent years. However, the genetic interactions between these regulators over the dynamic course of differentiation have not been studied. In this Extra-View article, we review recent work by Lopez-Pajares et al. that explores a new regulatory network in epidermal differentiation. They analyze the changing transcriptome throughout epidermal regeneration to identify 3 separate gene sets enriched in the progenitor, early and late differentiation states. Using expression module mapping, MAF along with MAFB, are identified as transcription factors essential for epidermal differentiation. Through double knock-down of MAF:MAFB using siRNA and CRISPR/Cas9-mediated knockout, epidermal differentiation was shown to be impaired both in-vitro and in-vivo, confirming MAF:MAFB's role to activate genes that drive differentiation. Lopez-Pajares and collaborators integrated 42 published regulator gene sets and the MAF:MAFB gene set into the dynamic differentiation gene expression landscape and found that lncRNAs TINCR and ANCR act as upstream regulators of MAF:MAFB. Furthermore, ChIP-seq analysis of MAF:MAFB identified key transcription factor genes linked to epidermal differentiation as downstream effectors. Combined, these findings illustrate a dynamically regulated network with MAF:MAFB as a crucial link for progenitor gene repression and differentiation gene activation.

Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches, and small regulatory RNAs. Overall, regulatory information is included in the model for ∼2500 of the ∼4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology.

Identification of Biomarkers Associated With Alzheimer's Disease by Bioinformatics Analysis

BACKGROUND

This study aimed to explore the biomarkers of Alzheimer's disease (AD).

METHODS

The microarray data of GSE16759 were from the expression profile samples of 4 parietal lobe tissues from patients with AD and 4 ones from age-matched control participants. The differentially expressed micro RNAs (miRNAs) and genes (DEGs) underwent hierarchical clustering and function analysis followed by target genes prediction. Finally, DEGs were mapped to the target genes to construct miRNA-regulated networks.

RESULTS

A total of 427 DEGs were obtained and clustered into 5 functions. After DEGs were mapped to the predicted target genes, 313 regulatory pairs were established. The target genes SEC22 vesicle trafficking protein homolog B (SEC22B) and SEC63 homolog (SEC63) regulated by miRNA-206, RAB10, member RAS oncogene family (RAB10) regulated by miRNA-655, and fms-related tyrosine kinase 1 (FLT1) regulated by miRNA-30e-3p and miRNA-369-3p were involved in the biological processes of protein transport and regulation of cell motion.

CONCLUSION

The target genes SEC22B, RAB10, and FLT1 may be potential biomarkers of AD.

Two MYB transcription factors regulate flavonoid biosynthesis in pear fruit (Pyrus bretschneideri Rehd.)

Flavonoid compounds play important roles in the modern diet, and pear fruits are an excellent dietary source of these metabolites. However, information on the regulatory network of flavonoid biosynthesis in pear fruits is rare. In this work, 18 putative flavonoid-related MYB transcription factors (TFs) were screened by phylogenetic analysis and four of them were correlated with flavonoid biosynthesis patterns in pear fruits. Among these MYB-like genes, the specific functions of two novel MYB TFs, designated as PbMYB10b and PbMYB9, were further verified by both overexpression and RNAi transient assays. PbMYB10b, a PAP-type MYB TF with atypical motifs in its conserved region, regulated the anthocyanin and proanthocyanidin pathways by inducing the expression of PbDFR, but its function could be complemented by other MYB TFs. PbMYB9, a TT2-type MYB, not only acted as the specific activator of the proanthocyanidin pathway by activating the PbANR promoter, but also induced the synthesis of anthocyanins and flavonols by binding the PbUFGT1 promoter in pear fruits. The MYBCORE-like element has been identified in both the PbUFGT1 promoter and ANR promoters in most species, but it was not found in UFGT promoters isolated from other species. This finding was also supported by a yeast one-hybrid assay and thus enhanced the likelihood of the interaction between PbMYB9 and the PbUFGT1 promoter.

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes.

Trait Specific Expression Profiling of Salt Stress Responsive Genes in Diverse Rice Genotypes as Determined by Modified Significance Analysis of Microarrays

Stress responsive gene expression is commonly profiled in a comparative manner involving different stress conditions or genotypes with contrasting reputation of tolerance/resistance. In contrast, this research exploited a wide natural variation in terms of taxonomy, origin and salt sensitivity in eight genotypes of rice to identify the trait specific patterns of gene expression under salt stress. Genome wide transcptomic responses were interrogated by the weighted continuous morpho-physiological trait responses using modified Significance Analysis of Microarrays. More number of genes was found to be differentially expressed under salt stressed compared to that of under unstressed conditions. Higher numbers of genes were observed to be differentially expressed for the traits shoot Na(+)/K(+), shoot Na(+), root K(+), biomass and shoot Cl(-), respectively. The results identified around 60 genes to be involved in Na(+), K(+), and anion homeostasis, transport, and transmembrane activity under stressed conditions. Gene Ontology (GO) enrichment analysis identified 1.36% (578 genes) of the entire transcriptome to be involved in the major molecular functions such as signal transduction (>150 genes), transcription factor (81 genes), and translation factor activity (62 genes) etc., under salt stress. Chromosomal mapping of the genes suggests that majority of the genes are located on chromosomes 1, 2, 3, 6, and 7. The gene network analysis showed that the transcription factors and translation initiation factors formed the major gene networks and are mostly active in nucleus, cytoplasm and mitochondria whereas the membrane and vesicle bound proteins formed a secondary network active in plasma membrane and vacuoles. The novel genes and the genes with unknown functions thus identified provide picture of a synergistic salinity response representing the potentially fundamental mechanisms that are active in the wide natural genetic background of rice and will be of greater use once their roles are functionally verified.

High-Throughput Sequencing Reveals H2O2 Stress-Associated MicroRNAs and a Potential Regulatory Network in Brachypodium distachyon Seedlings

Oxidative stress in plants can be triggered by many environmental stress factors, such as drought and salinity. Brachypodium distachyon is a model organism for the study of biofuel plants and crops, such as wheat. Although recent studies have found many oxidative stress response-related proteins, the mechanism of microRNA (miRNA)-mediated oxidative stress response is still unclear. Using next generation high-throughput sequencing technology, the small RNAs were sequenced from the model plant B. distachyon 21 (Bd21) under H₂O₂ stress and normal growth conditions. In total, 144 known B. distachyon miRNAs and 221 potential new miRNAs were identified. Further analysis of potential new miRNAs suggested that 36 could be clustered into known miRNA families, while the remaining 185 were identified as B. distachyon-specific new miRNAs. Differential analysis of miRNAs from the normal and H₂O₂ stress libraries identified 31 known and 30 new H₂O₂ stress responsive miRNAs. The expression patterns of seven representative miRNAs were verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis, which produced results consistent with those of the deep sequencing method. Moreover, we also performed RT-qPCR analysis to verify the expression levels of 13 target genes and the cleavage site of 5 target genes by known or novel miRNAs were validated experimentally by 5' RACE. Additionally, a miRNA-mediated gene regulatory network for H₂O₂ stress response was constructed. Our study identifies a set of H₂O₂-responsive miRNAs and their target genes and reveals the mechanism of oxidative stress response and defense at the post-transcriptional regulatory level.

In silico Transcriptional Regulatory Networks Involved in Tomato Fruit Ripening

Tomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs) which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37, and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening.

Neuronal specification exploits the inherent flexibility of cell-cycle gap phases

Starting from pluripotent stem cells that virtually proliferate indefinitely, the orderly emergence during organogenesis of lineage-restricted cell types exhibiting a decreased proliferative capacity concurrently with an increasing range of differentiation traits implies the occurrence of a stringent spatiotemporal coupling between cell-cycle progression and cell differentiation. A recent computational modeling study has explored in the context of neurogenesis whether and how the peculiar pattern of connections among the proneural Neurog2 factor, the Hes1 Notch effector and antagonistically-acting G1-phase regulators would be instrumental in this event. This study highlighted that the strong opposition to G1/S transit imposed by accumulating Neurog2 and CKI enables a sensitive control of G1-phase lengthening and terminal differentiation to occur concomitantly with late-G1 exit. Contrastingly, Hes1 promotes early-G1 cell-cycle arrest and its cell-autonomous oscillations combined with a lateral inhibition mechanism help maintain a labile proliferation state in dynamic balance with diverse cell-fate outputs, thereby, offering cells the choice to either keep self-renewing or differentiate into distinct cell types. These results, discussed in connection with Ascl1-dependent neural differentiation, suggest that developmental fate decisions exploit the inherent flexibility of cell-cycle gap phases to generate diversity by selecting subtly-differing patterns of connections among components of the cell-cycle machinery and differentiation pathways.

A regulatory gene network related to the porcine umami taste receptor (TAS1R1/TAS1R3)

Taste perception plays an important role in the mediation of food choices in mammals. The first porcine taste receptor genes identified, sequenced and characterized, TAS1R1 and TAS1R3, were related to the dimeric receptor for umami taste. However, little is known about their regulatory network. The objective of this study was to unfold the genetic network involved in porcine umami taste perception. We performed a meta-analysis of 20 gene expression studies spanning 480 porcine microarray chips and screened 328 taste-related genes by selective mining steps among the available 12,320 genes. A porcine umami taste-specific regulatory network was constructed based on the normalized coexpression data of the 328 genes across 27 tissues. From the network, we revealed the 'taste module' and identified a coexpression cluster for the umami taste according to the first connector with the TAS1R1/TAS1R3 genes. Our findings identify several taste-related regulatory genes and extend previous genetic background of porcine umami taste.

Long noncoding RNAs could be potential key players in the pathophysiology of Sjögren's syndrome

Long noncoding RNAs (lncRNAs) are a recently discovered class of noncoding functional RNAs encoded by metazoan genomes. Recent studies suggest a larger regulatory role for lncRNAs in critical biological and disease processes. Mounting evidence on the role of lncRNAs in regulating key processes of the immune system prompted us to hypothesize the role of lncRNAs as key regulators of the pathophysiology of Sjögren's syndrome (SS). We used two similar approaches based on reanalysis of microarray expression datasets and curation of lncRNA-protein coding gene interactions from literature to derive support for our hypothesis. We also discuss potential caveats to our approach and suggest approaches to validate the hypothesis. Our analysis suggests the potential larger and hitherto unknown role of lncRNA regulatory networks in modulating the expression of key genes involved in the pathogenesis of SS and thereby modulating the pathophysiology of SS.

Interactions of OsMADS1 with Floral Homeotic Genes in Rice Flower Development

During reproductive development, rice plants develop unique flower organs which determine the final grain yield. OsMADS1, one of SEPALLATA-like MADS-box genes, has been unraveled to play critical roles in rice floral organ identity specification and floral meristem determinacy. However, the molecular mechanisms underlying interactions of OsMADS1 with other floral homeotic genes in regulating flower development remains largely elusive. In this work, we studied the genetic interactions of OsMADS1 with B-, C-, and D-class genes along with physical interactions among their proteins. We show that the physical and genetic interactions between OsMADS1 and OsMADS3 are essential for floral meristem activity maintenance and organ identity specification; while OsMADS1 physically and genetically interacts with OsMADS58 in regulating floral meristem determinacy and suppressing spikelet meristem reversion. We provided important genetic evidence to support the neofunctionalization of two rice C-class genes (OsMADS3 and OsMADS58) during flower development. Gene expression profiling and quantitative RT-PCR analyses further revealed that OsMADS1 affects the expression of many genes involved in floral identity and hormone signaling, and chromatin immunoprecipitation (ChIP)-PCR assay further demonstrated that OsMADS17 is a direct target gene of OsMADS1. Taken together, these results reveal that OsMADS1 has diversified regulatory functions in specifying rice floral organ and meristem identity, probably through its genetic and physical interactions with different floral homeotic regulators.

Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks

The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA-mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA-mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks.

The regulatory network of B-cell differentiation: a focused view of early B-cell factor 1 function

During the last decades, many studies have investigated the transcriptional and epigenetic regulation of lineage decision in the hematopoietic system. These efforts led to a model in which extrinsic signals and intrinsic cues establish a permissive chromatin context upon which a regulatory network of transcription factors and epigenetic modifiers act to guide the differentiation of hematopoietic lineages. These networks include lineage-specific factors that further modify the epigenetic landscape and promote the generation of specific cell types. The process of B lymphopoiesis requires a set of transcription factors, including Ikaros, PU.1, E2A, and FoxO1 to 'prime' cis-regulatory regions for subsequent activation by the B-lineage-specific transcription factors EBF1 and Pax-5. The expression of EBF1 is initiated by the combined action of E2A and FoxO1, and it is further enhanced and maintained by several positive feedback loops that include Pax-5 and IL-7 signaling. EBF1 acts in concert with Ikaros, PU.1, Runx1, E2A, FoxO1, and Pax-5 to establish the B cell-specific transcription profile. EBF1 and Pax-5 also collaborate to repress alternative cell fates and lock cells into the B-lineage fate. In addition to the functions of EBF1 in establishing and maintaining B-cell identity, EBF1 is required to coordinate differentiation with cell proliferation and survival.

Mathematical modelling of metabolic regulation in aging

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area.

Implications of miR166 and miR159 induction to the basal response mechanisms of an andigena potato (Solanum tuberosum subsp. andigena) to salinity stress, predicted from network models in Arabidopsis

MicroRNA (miRNA) mediated changes in gene expression by post-transcriptional modulation of major regulatory transcription factors is a potent mechanism for integrating growth and stress-related responses. Exotic plants including many traditional varieties of Andean potatoes (Solanum tuberosum subsp. andigena) are known for better adaptation to marginal environments. Stress physiological studies confirmed earlier reports on the salinity tolerance potentials of certain andigena cultivars. Guided by the hypothesis that certain miRNAs play important roles in growth modulation under suboptimal conditions, we identified and characterized salinity stress-responsive miRNA-target gene pairs in the andigena cultivar Sullu by parallel analysis of noncoding and coding RNA transcriptomes. Inverse relationships were established by the reverse co-expression between two salinity stress-regulated miRNAs (miR166, miR159) and their target transcriptional regulators HD-ZIP-Phabulosa/Phavulota and Myb101, respectively. Based on heterologous models in Arabidopsis, the miR166-HD-ZIP-Phabulosa/Phavulota network appears to be involved in modulating growth perhaps by mediating vegetative dormancy, with linkages to defense-related pathways. The miR159-Myb101 network may be important for the modulation of vegetative growth while also controlling stress-induced premature transition to reproductive phase. We postulate that the induction of miR166 and miR159 under salinity stress represents important network hubs for balancing gene expression required for basal growth adjustments.

Candidate pathways and genes for nasopharyngeal carcinoma based on bioinformatics study

PURPOSE

To reveal the potential microRNAs (miRNAs), genes, pathways and regulatory network involved in the process of nasopharyngeal carcinoma (NPC) by using the method of bioinformatics.

METHODS

Gene expression profiles GSE12452 (31 NPC and 10 normal samples) and GSE53819 (18 NPC and 18 normal samples), as well as miRNA expression profiles GSE32960 (312 NPC and 18 normal samples) and GSE36682 (62 NPC and 6 normal samples) were obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) between NPC and normal samples were identified by using t-test based on MATLAB software (FDR < 0.01), followed by pathway enrichment analysis based on DAVID software (P-value < 0.1). Then, DEmiRNA-DEG regulatory network was constructed.

RESULTS

A total of 1254 DEGs and 107 DEmiRNAs were identified, respectively. Then, 16 pathways (including cell cycle) and 32 pathways (including pathways in cancer) were enriched by DEGs and target genes of DEmiRNAs, respectively. Furthermore, DEmiRNA-DEG regulatory network was constructed, containing 12 DEmiRNAs (including has-miR-615-3P) and 180 DEGs (including MCM4 and CCNE2).

CONCLUSION

has-miR-615-3p might take part in the pathogenetic process of NPC through regulating MCM4 which is enriched in cell cycle. The DEmiRNAs identified in the present study might serve as new biomarkers for NPC.

Protein-tyrosine phosphorylation in Bacillus subtilis: a 10-year retrospective

The discovery of tyrosine-phosphorylated proteins in Bacillus subtilis in the year 2003 was followed by a decade of intensive research activity. Here we provide an overview of the lessons learned in that period. While the number of characterized kinases and phosphatases involved in reversible protein-tyrosine phosphorylation in B. subtilis has remained essentially unchanged, the number of proteins known to be targeted by this post-translational modification has increased dramatically. This is mainly due to phosphoproteomics and interactomics studies, which were instrumental in identifying new tyrosine-phosphorylated proteins. Despite their structural similarity, the two B. subtilis protein-tyrosine kinases (BY-kinases), PtkA and PtkB (EpsB), seem to accomplish different functions in the cell. The PtkB is encoded by a large operon involved in exopolysaccharide production, and its main role appears to be the control of this process. The PtkA seems to have a more complex role; it phosphorylates and regulates a large number of proteins involved in the DNA, fatty acid and carbon metabolism and engages in physical interaction with other types of kinases (Ser/Thr kinases), leading to mutual phosphorylation. PtkA also seems to respond to several activator proteins, which direct its activity toward different substrates. In that respect PtkA seems to function as a highly connected signal integration device.

Summarizing and exploring data of a decade of cytokinin-related transcriptomics

The genome-wide transcriptional response of the model organism Arabidopsis thaliana to cytokinin has been investigated by different research groups as soon as large-scale transcriptomic techniques became affordable. Over the last 10 years many transcriptomic datasets related to cytokinin have been generated using different technological platforms, some of which are published only in databases, culminating in an RNA sequencing experiment. Two approaches have been made to establish a core set of cytokinin-regulated transcripts by meta-analysis of these datasets using different preferences regarding their selection. Here we add another meta-analysis derived from an independent microarray platform (CATMA), combine all the meta-analyses available with RNAseq data in order to establish an advanced core set of cytokinin-regulated transcripts, and compare the results with the regulation of orthologous rice genes by cytokinin. We discuss the functions of some of the less known cytokinin-regulated genes indicating areas deserving further research to explore cytokinin function. Finally, we investigate the promoters of the core set of cytokinin-induced genes for the abundance and distribution of known cytokinin-responsive cis elements and identify a set of novel candidate motifs.

Differential expression of seven conserved microRNAs in response to abiotic stress and their regulatory network in Helianthus annuus

Biotic and abiotic stresses affect plant development and production through alternation of the gene expression pattern. Gene expression itself is under the control of different regulators such as miRNAs and transcription factors (TFs). MiRNAs are known to play important roles in regulation of stress responses via interacting with their target mRNAs. Here, for the first time, seven conserved miRNAs, associated with drought, heat, salt and cadmium stresses were characterized in sunflower. The expression profiles of miRNAs and their targets were comparatively analyzed between leaves and roots of plants grown under the mentioned stress conditions. Gene ontology analysis of target genes revealed that they are involved in several important pathways such as auxin and ethylene signaling, RNA mediated silencing and DNA methylation processes. Gene regulatory network highlighted the existence of cross-talks between these stress-responsive miRNAs and the other stress responsive genes in sunflower. Based on network analysis, we suggest that some of these miRNAs in sunflower such as miR172 and miR403 may play critical roles in epigenetic responses to stress. It seems that depending on the stress type, theses miRNAs target several pathways and cellular processes to help sunflower to cope with drought, heat, salt and cadmium stress conditions in a tissue-associated manner.

Distinct subclades of Aux/IAA genes are direct targets of ARF5/MP transcriptional regulation

The regulatory interactions between AUXIN RESPONSE FACTORS (ARFs) and Aux/IAA repressors play a central role in auxin signal transduction. Yet, the systems properties of this regulatory network are not well established. We generated a steroid-inducible ARF5/MONOPTEROS (MP) transgenic background to survey the involvement of this factor in the transcriptional regulation of the entire Aux/IAA family in Arabidopsis thaliana. Target genes of ARF5/MP identified by this approach were confirmed by chromatin immunoprecipitation, in vitro gel retardation assays and gene expression analyses. Our study shows that ARF5/MP is indispensable for the correct regulation of nearly one-half of all Aux/IAA genes, and that these targets coincide with distinct subclades. Further, genetic analyses demonstrate that the protein products of multiple Aux/IAA targets negatively feed back onto ARF5/MP activity. This work indicates that ARF5/MP broadly influences the expression of the Aux/IAA gene family, and suggests that such regulation involves the activation of specific subsets of redundantly functioning factors. These groups of factors may then act together to control various processes within the plant through negative feedback on ARF5. Similar detailed analyses of other Aux/IAA-ARF regulatory modules will be required to fully understand how auxin signal transduction influences virtually every aspect of plant growth and development.

Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer

While previous studies reported aberrant expression of microRNAs (miRNAs) in non-small cell lung cancer (NSCLC), little is known about which miRNAs play central roles in NSCLC's pathogenesis and its regulatory mechanisms. To address this issue, we presented a robust computational framework that integrated matched miRNA and mRNA expression profiles in NSCLC using feed-forward loops. The network consists of miRNAs, transcription factors (TFs), and their common predicted target genes. To discern the biological meaning of their associations, we introduced the direction of regulation. A network edge validation strategy using three independent NSCLC expression profiling data sets pinpointed reproducible biological regulations. Reproducible regulation, which may reflect the true molecular interaction, has not been applied to miRNA-TF co-regulatory network analyses in cancer or other diseases yet. We revealed eight hub miRNAs that connected to a higher proportion of targets validated by independent data sets. Network analyses showed that these miRNAs might have strong oncogenic characteristics. Furthermore, we identified a novel miRNA-TF co-regulatory module that potentially suppresses the tumor suppressor activity of the TGF-β pathway by targeting a core pathway molecule (TGFBR2). Follow-up experiments showed two miRNAs (miR-9-5p and miR-130b-3p) in this module had increased expression while their target gene TGFBR2 had decreased expression in a cohort of human NSCLC. Moreover, we demonstrated these two miRNAs directly bind to the 3' untranslated region of TGFBR2. This study enhanced our understanding of miRNA-TF co-regulatory mechanisms in NSCLC. The combined bioinformatics and validation approach we described can be applied to study other types of diseases.

Evolution of communication protocols using an artificial regulatory network

I describe the Utrecht Machine (UM), a discrete artificial regulatory network designed for studying how evolution discovers biochemical computation mechanisms. The corresponding binary genome format is compatible with gene deletion, duplication, and recombination. In the simulation presented here, an agent consisting of two UMs, a sender and a receiver, must encode, transmit, and decode a binary word over time using the narrow communication channel between them. This communication problem has chicken-and-egg structure in that a sending mechanism is useless without a corresponding receiving mechanism. An in-depth case study reveals that a coincidence creates a minimal partial solution, from which a sequence of partial sending and receiving mechanisms evolve. Gene duplications contribute by enlarging the regulatory network. Analysis of 60,000 sample runs under a variety of parameter settings confirms that crossover accelerates evolution, that stronger selection tends to find clumsier solutions and finds them more slowly, and that there is implicit selection for robust mechanisms and genomes at the codon level. Typical solutions associate each input bit with an activation speed and combine them almost additively. The parents of breakthrough organisms sometimes have lower fitness scores than others in the population, indicating that populations can cross valleys in the fitness landscape via outlying members. The simulation exhibits back mutations and population-level memory effects not accounted for in traditional population genetics models. All together, these phenomena suggest that new evolutionary models are needed that incorporate regulatory network structure.

Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

BACKGROUND

Plant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis.

RESULTS

The dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes' expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50 TFs were identified to comprehend the underlying mechanism of TFs' regulatory rewiring.

CONCLUSION

Overall, this dynamic regulatory network largely improves the understanding of perplexed regulatory rewiring in secondary metabolism in Arabidopsis.

Symbolic extensions applied to multiscale structure of genomes

A genome of a living organism consists of a long string of symbols over a finite alphabet carrying critical information for the organism. This includes its ability to control post natal growth, homeostasis, adaptation to changes in the surrounding environment, or to biochemically respond at the cellular level to various specific regulatory signals. In this sense, a genome represents a symbolic encoding of a highly organized system of information whose functioning may be revealed as a natural multilayer structure in terms of complexity and prominence. In this paper we use the mathematical theory of symbolic extensions as a framework to shed light onto how this multilayer organization is reflected in the symbolic coding of the genome. The distribution of data in an element of a standard symbolic extension of a dynamical system has a specific form: the symbolic sequence is divided into several subsequences (which we call layers) encoding the dynamics on various "scales". We propose that a similar structure resides within the genomes, building our analogy on some of the most recent findings in the field of regulation of genomic DNA functioning.

Inferring the evolutionary history of primate microRNA binding sites: overcoming motif counting biases

The first microRNAs (miRNAs) were identified as essential, conserved regulators of gene expression, targeting the same genes across nearly all bilaterians. However, there are also prominent examples of conserved miRNAs whose functions appear to have shifted dramatically, sometimes over very brief periods of evolutionary time. To determine whether the functions of conserved miRNAs are stable or dynamic over evolutionary time scales, we have here defined the neutral turnover rates of short sequence motifs in predicted primate 3'-UTRs. We find that commonly used approaches to quantify motif turnover rates, which use a presence/absence scoring in extant lineages to infer ancestral states, are inherently biased to infer the accumulation of new motifs, leading to the false inference of continually increasing regulatory complexity over time. Using a maximum likelihood approach to reconstruct individual ancestral nucleotides, we observe that binding sites of conserved miRNAs in fact have roughly equal numbers of gain and loss events relative to ancestral states and turnover extremely slowly relative to nearly identical permutations of the same motif. Contrary to case studies showing examples of functional turnover, our systematic study of miRNA binding sites suggests that in primates, the regulatory roles of conserved miRNAs are strongly conserved. Our revised methodology may be used to quantify the mechanism by which regulatory networks evolve.

elegans development is revealed by a genome-wide RNAi screen

The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development.

Regulatory network features in Listeria monocytogenes-changing the way we talk

Our understanding of how pathogens shape their gene expression profiles in response to environmental changes is ever growing. Advances in Bioinformatics have made it possible to model complex systems and integrate data from variable sources into one large regulatory network. In these analyses, regulatory networks are typically broken down into regulatory motifs such as feed-forward loops (FFL) or auto-regulatory feedbacks, which serves to simplify the structure, while the functional implications of different regulatory motifs allow to make informed assumptions about the function of a specific regulatory pathway. Here we review the basic concepts of network features and use this language to break down the regulatory networks that govern the interactions between the main regulators of stress response, virulence, and transmission in Listeria monocytogenes. We point out the advantage that taking a “systems approach” could have for our understanding of gene functions, the detection of distant regulatory inputs, interspecies comparisons, and co-expression.

DNA-binding specificities of plant transcription factors and their potential to define target genes

Transcription factors (TFs) regulate gene expression through binding to cis-regulatory specific sequences in the promoters of their target genes. In contrast to the genetic code, the transcriptional regulatory code is far from being deciphered and is determined by sequence specificity of TFs, combinatorial cooperation between TFs and chromatin competence. Here we addressed one of these determinants by characterizing the target sequence specificity of 63 plant TFs representing 25 families, using protein-binding microarrays. Remarkably, almost half of these TFs recognized secondary motifs, which in some cases were completely unrelated to the primary element. Analyses of coregulated genes and transcriptomic data from TFs mutants showed the functional significance of over 80% of all identified sequences and of at least one target sequence per TF. Moreover, combining the target sequence information with coexpression analysis we could predict the function of a TF as activator or repressor through a particular DNA sequence. Our data support the correlation between cis-regulatory elements and the sequence determined in vitro using the protein-binding microarray and provides a framework to explore regulatory networks in plants.

DNA-binding specificities of plant transcription factors and their potential to define target genes

Transcription factors (TFs) regulate gene expression through binding to cis-regulatory specific sequences in the promoters of their target genes. In contrast to the genetic code, the transcriptional regulatory code is far from being deciphered and is determined by sequence specificity of TFs, combinatorial cooperation between TFs and chromatin competence. Here we addressed one of these determinants by characterizing the target sequence specificity of 63 plant TFs representing 25 families, using protein-binding microarrays. Remarkably, almost half of these TFs recognized secondary motifs, which in some cases were completely unrelated to the primary element. Analyses of coregulated genes and transcriptomic data from TFs mutants showed the functional significance of over 80% of all identified sequences and of at least one target sequence per TF. Moreover, combining the target sequence information with coexpression analysis we could predict the function of a TF as activator or repressor through a particular DNA sequence. Our data support the correlation between cis-regulatory elements and the sequence determined in vitro using the protein-binding microarray and provides a framework to explore regulatory networks in plants.

AURA 2: Empowering discovery of post-transcriptional networks

Post-transcriptional regulation (PTR) of gene expression is now recognized as a major determinant of cell phenotypes. The recent availability of methods to map protein-RNA interactions in entire transcriptomes such as RIP, CLIP and their variants, together with global polysomal and ribosome profiling techniques, are driving the exponential accumulation of vast amounts of data on mRNA contacts in cells, and of corresponding predictions of PTR events. However, this exceptional quantity of information cannot be exploited at its best to reconstruct potential PTR networks, as it still lies scattered throughout several databases and in isolated reports of single interactions. To address this issue, we developed the second and vastly enhanced version of the Atlas of UTR Regulatory Activity (AURA 2), a meta-database centered on mapping interaction of trans-factors with human and mouse UTRs. AURA 2 includes experimentally demonstrated binding sites for RBPs, ncRNAs, thousands of cis-elements, variations, RNA epigenetics data and more. Its user-friendly interface offers various data-mining features including co-regulation search, network generation and regulatory enrichment testing. Gene expression profiles for many tissues and cell lines can be also combined with these analyses to display only the interactions possible in the system under study. AURA 2 aims at becoming a valuable toolbox for PTR studies and at tracing the road for how PTR network-building tools should be designed. AURA 2 is available at http://aura.science.unitn.it.

Getting to the edge: protein dynamical networks as a new frontier in plant-microbe interactions

A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials, and biofuel production. A systems or "-omics" perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics is vital to expanding our knowledge of how the intercellular communication processes are executed. This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed "-omes" and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the "-omics" approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.

Beyond modules and hubs: the potential of gene coexpression networks for investigating molecular mechanisms of complex brain disorders

In a research environment dominated by reductionist approaches to brain disease mechanisms, gene network analysis provides a complementary framework in which to tackle the complex dysregulations that occur in neuropsychiatric and other neurological disorders. Gene-gene expression correlations are a common source of molecular networks because they can be extracted from high-dimensional disease data and encapsulate the activity of multiple regulatory systems. However, the analysis of gene coexpression patterns is often treated as a mechanistic black box, in which looming 'hub genes' direct cellular networks, and where other features are obscured. By examining the biophysical bases of coexpression and gene regulatory changes that occur in disease, recent studies suggest it is possible to use coexpression networks as a multi-omic screening procedure to generate novel hypotheses for disease mechanisms. Because technical processing steps can affect the outcome and interpretation of coexpression networks, we examine the assumptions and alternatives to common patterns of coexpression analysis and discuss additional topics such as acceptable datasets for coexpression analysis, the robust identification of modules, disease-related prioritization of genes and molecular systems and network meta-analysis. To accelerate coexpression research beyond modules and hubs, we highlight some emerging directions for coexpression network research that are especially relevant to complex brain disease, including the centrality-lethality relationship, integration with machine learning approaches and network pharmacology.

Reconstruction of gene regulatory network related to photosynthesis in Arabidopsis thaliana

Photosynthesis is one of the most important biological processes on the earth. So far, though the molecular mechanisms underlying photosynthesis is well understood, however, the regulatory networks of photosynthesis are poorly studied. Given the current interest in improving photosynthetic efficiency for greater crop yield, elucidating the detailed regulatory networks controlling the construction and maintenance of photosynthetic machinery is not only scientifically significant but also holding great potential in agricultural application. In this study, we first identified transcription factors (TFs) related to photosynthesis through the TRAP approach using position weight matrix information. Then, for TFs related to photosynthesis, interactions between them and their targets were also determined by the ARACNE approach. Finally, a gene regulatory network was established by combining TF-targets information generated by these two approaches. Topological analysis of the regulatory network suggested that (a) the regulatory network of photosynthesis has a property of "small world"; (b) there is substantial coordination mediated by transcription factors between different components in photosynthesis.

Integration of new genes into cellular networks, and their structural maturation

It has been recently discovered that new genes can originate de novo from noncoding DNA, and several biological traits including expression or sequence composition form a continuum from noncoding sequences to conserved genes. In this article, using yeast genes I test whether the integration of new genes into cellular networks and their structural maturation shows such a continuum by analyzing their changes with gene age. I show that 1) The number of regulatory, protein-protein, and genetic interactions increases continuously with gene age, although with very different rates. New regulatory interactions emerge rapidly within a few million years, while the number of protein-protein and genetic interactions increases slowly, with a rate of 2-2.25 × 10(-8)/year and 4.8 × 10(-8)/year, respectively. 2) Gene essentiality evolves relatively quickly: the youngest essential genes appear in proto-genes ∼14 MY old. 3) In contrast to interactions, the secondary structure of proteins and their robustness to mutations indicate that new genes face a bottleneck in their evolution: proto-genes are characterized by high β-strand content, high aggregation propensity, and low robustness against mutations, while conserved genes are characterized by lower strand content and higher stability, most likely due to the higher probability of gene loss among young genes and accumulation of neutral mutations.

Lessons about terminal differentiation from the specification of color-detecting photoreceptors in the Drosophila retina

Metazoans require highly diverse collections of cell types to sense, interpret, and react to the environment. Developmental programs incorporate deterministic and stochastic strategies in different contexts or different combinations to establish this multitude of cell fates. Precise genetic dissection of the processes controlling terminal photoreceptor differentiation in the Drosophila retina has revealed complex regulatory mechanisms required to generate differences in gene expression and cell fate. In this review, I discuss how a gene regulatory network interprets stochastic and regional inputs to determine the specification of color-detecting photoreceptor subtypes in the Drosophila retina. These combinatorial gene regulatory mechanisms will likely be broadly applicable to nervous system development and cell fate specification in general.

Protein-serine/threonine/tyrosine kinases in bacterial signaling and regulation

In this review, we address some recent developments in the field of bacterial protein phosphorylation, focusing specifically on serine/threonine and tyrosine kinases. We present an overview of recent studies outlining the scope of physiological processes that are regulated by phosphorylation, ranging from cell cycle, growth, cell morphology, to metabolism, developmental phenomena, and virulence. Specific emphasis is placed on Mycobacterium tuberculosis as a showcase organism for serine/threonine kinases, and Bacillus subtilis to illustrate the importance of protein phosphorylation in developmental processes. We argue that bacterial serine/threonine and tyrosine kinases have a distinctive feature of phosphorylating multiple substrates and might thus represent integration nodes in the signaling network. Some open questions regarding the evolutionary benefits of relaxed substrate selectivity of these kinases are treated, as well as the notion of nonfunctional 'background' phosphorylation of cellular proteins. We also argue that phosphorylation events for which an immediate regulatory effect is not clearly established should not be dismissed as unimportant, as they may have a role in cross-talk with other post-translational modifications. Finally, recently developed methods for studying protein phosphorylation networks in bacteria are briefly discussed.

SignaLink 2 - a signaling pathway resource with multi-layered regulatory networks

BACKGROUND

Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contains transcription factors and their binding sites on the DNA as well as microRNAs and their mRNA targets. Currently, most signaling and regulatory databases contain only a subsection of this network, making comprehensive analyses highly time-consuming and dependent on specific data handling expertise. The need for detailed mapping of signaling systems is also supported by the fact that several drug development failures were caused by undiscovered cross-talk or regulatory effects of drug targets. We previously created a uniformly curated signaling pathway resource, SignaLink, to facilitate the analysis of pathway cross-talks. Here, we present SignaLink 2, which significantly extends the coverage and applications of its predecessor.

DESCRIPTION

We developed a novel concept to integrate and utilize different subsections (i.e., layers) of the signaling network. The multi-layered (onion-like) database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The user-friendly website allows the interactive exploration of how each signaling protein is regulated. The customizable download page enables the analysis of any user-specified part of the signaling network. Compared to other signaling resources, distinctive features of SignaLink 2 are the following: 1) it involves experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; 2) combines manual curation with large-scale datasets; 3) provides confidence scores for each interaction; 4) operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML). Non-profit users can access SignaLink 2 free of charge at http://SignaLink.org.

CONCLUSIONS

With SignaLink 2 as a single resource, users can effectively analyze signaling pathways, scaffold proteins, modifier enzymes, transcription factors and miRNAs that are important in the regulation of signaling processes. This integrated resource allows the systems-level examination of how cross-talks and signaling flow are regulated, as well as provide data for cross-species comparisons and drug discovery analyses.

Small RNAs regulating biofilm formation and outer membrane homeostasis

Nowadays, the identification of small non-coding RNAs takes a prominent role in deciphering complex bacterial phenotypes. Evidences are given that the post-transcriptional layer of regulation mediated by sRNAs plays an important role in the formation of bacterial biofilms. These sRNAs exert their activity on various targets, be it directly or indirectly linked to biofilm formation. First, and best described, are the sRNAs that act in core regulatory pathways of biofilm formation, such as those regulating motility and matrix production. Second, overlaps between the regulation of biofilm formation and the outer membrane (OM) are becoming obvious. Additionally, different studies indicate that defects in the OM itself affect biofilm formation through this shared cascade, thereby forming a feedback mechanism. Interestingly, it is known that the OM itself is extensively regulated by different sRNAs. Third, biofilms are also linked to global metabolic changes. There is also evidence that metabolic pathways and the process of biofilm formation share sRNAs.

Non-coding RNAs in retinal development

Retinal development is dependent on an accurately functioning network of transcriptional and translational regulators. Among the diverse classes of molecules involved, non-coding RNAs (ncRNAs) play a significant role. Members of this family are present in the cell as transcripts, but are not translated into proteins. MicroRNAs (miRNAs) are small ncRNAs that act as post-transcriptional regulators. During the last decade, they have been implicated in a variety of biological processes, including the development of the nervous system. On the other hand, long-ncRNAs (lncRNAs) represent a different class of ncRNAs that act mainly through processes involving chromatin remodeling and epigenetic mechanisms. The visual system is a prominent model to investigate the molecular mechanisms underlying neurogenesis or circuit formation and function, including the differentiation of retinal progenitor cells to generate the seven principal cell classes in the retina, pathfinding decisions of retinal ganglion cell axons in order to establish the correct connectivity from the eye to the brain proper, and activity-dependent mechanisms for the functionality of visual circuits. Recent findings have associated ncRNAs in several of these processes and uncovered a new level of complexity for the existing regulatory mechanisms. This review summarizes and highlights the impact of ncRNAs during the development of the vertebrate visual system, with a specific focus on the role of miRNAs and a synopsis regarding recent findings on lncRNAs in the retina.

Gene regulation by cytokinin in Arabidopsis

The plant hormone cytokinin realizes at least part of its signaling output through the regulation of gene expression. A great part of the early transcriptional regulation is mediated by type-B response regulators, which are transcription factors of the MYB family. Other transcription factors, such as the cytokinin response factors of the AP2/ERF family, have also been shown to be involved in this process. Additional transcription factors mediate distinct parts of the cytokinin response through tissue- and cell-specific downstream transcriptional cascades. In Arabidopsis, only a single cytokinin response element, to which type-B response regulators bind, has been clearly proven so far, which has 5'-GAT(T/C)-3' as a core sequence. This motif has served to construct a synthetic cytokinin-sensitive two-component system response element, which is useful for monitoring the cellular cytokinin status. Insight into the extent of transcriptional regulation has been gained by genome-wide gene expression analyses following cytokinin treatment and from plants having an altered cytokinin content or signaling. This review presents a meta analysis of such microarray data resulting in a core list of cytokinin response genes. Genes encoding type-A response regulators displayed the most stable response to cytokinin, but a number of cytokinin metabolism genes (CKX4, CKX5, CYP735A2, UGT76C2) also belong to them, indicating homeostatic mechanisms operating at the transcriptional level. The cytokinin core response genes are also the target of other hormones as well as biotic and abiotic stresses, documenting crosstalk of the cytokinin system with other hormonal and environmental signaling pathways. The multiple links of cytokinin to diverse functions, ranging from control of meristem activity, hormonal crosstalk, nutrient acquisition, and various stress responses, are also corroborated by a compilation of genes that have been repeatedly found by independent gene expression profiling studies. Such functions are, at least in part, supported by genetic studies.

Neuroendocrinology of the skin: An overview and selective analysis

The concept on the skin neuro-endocrine has been formulated ten years ago, and recent advances in the field further strengthened this role. Thus, skin forms a bidirectional platform for a signal exchange with other peripheral organs, endocrine and immune systems or brain to enable rapid and selective responses to the environment in order to maintain local and systemic homeostasis. In this context, it is not surprising that the function of the skin is tightly regulated by systemic neuro-endocrine system. Skin cells and skin appendages not only respond to neuropeptides, steroids and other regulatory signals, but also actively synthesis variety of hormones. The stress responses within the skin are tightly regulated by locally synthesized factors and their receptor expression. There is growing evidence for alternative splicing playing an important role in stress signaling. Deregulation of the skin neuro-endocrine signaling can lead or/and be a marker of variety of skin diseases. The major problem in this area relates to their detailed mechanisms of crosstalk between skin and brain and between the local and global endocrine as well as immune systems.

Technologies and approaches to elucidate and model the virulence program of salmonella

Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches used to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

Comparative transcriptional profiling and preliminary study on heterosis mechanism of super-hybrid rice

Heterosis is a biological phenomenon whereby the offspring from two parents show improved and superior performance than either inbred parental lines. Hybrid rice is one of the most successful apotheoses in crops utilizing heterosis. Transcriptional profiling of F(1) super-hybrid rice Liangyou-2186 and its parents by serial analysis of gene expression (SAGE) revealed 1183 differentially expressed genes (DGs), among which DGs were found significantly enriched in pathways such as photosynthesis and carbon-fixation, and most of the key genes involved in the carbon-fixation pathway exhibited up-regulated expression in F(1) hybrid rice. Moreover, increased catabolic activity of corresponding enzymes and photosynthetic efficiency were also detected, which combined to indicate that carbon fixation is enhanced in F(1) hybrid, and might probably be associated with the yield vigor and heterosis in super-hybrid rice. By correlating DGs with yield-related quantitative trait loci (QTL), a potential relationship between differential gene expression and phenotypic changes was also found. In addition, a regulatory network involving circadian-rhythms and light signaling pathways was also found, as previously reported in Arabidopsis, which suggest that such a network might also be related with heterosis in hybrid rice. Altogether, the present study provides another view for understanding the molecular mechanism underlying heterosis in rice.

Systems approaches to polypharmacology and drug discovery

Systems biology uses experimental and computational approaches to characterize large sample populations systematically, process large datasets, examine and analyze regulatory networks, and model reactions to determine how components are joined to form functional systems. Systems biology technologies, data and knowledge are particularly useful in understanding disease processes and drug actions. An important area of integration between systems biology and drug discovery is the concept of polypharmacology: the treatment of diseases by modulating more than one target. Polypharmacology for complex diseases is likely to involve multiple drugs acting on distinct targets that are part of a network regulating physiological responses. This review discusses the current state of the systems-level understanding of diseases and both the therapeutic and adverse mechanisms of drug actions. Drug-target networks can be used to identify multiple targets and to determine suitable combinations of drug targets or drugs. Thus, the discovery of new drug therapies for complex diseases may be greatly aided by systems biology.

The interplay between transcription factors and microRNAs in genome-scale regulatory networks

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.

Potential regulation of gene expression in photosynthetic cells by redox and energy state: approaches towards better understanding

BACKGROUND

Photosynthetic electron transport is performed by a chain of redox components that are electrochemically connected in series. Its efficiency depends on the balanced action of the photosystems and on the interaction with the dark reaction. Plants are sessile and cannot escape from environmental conditions such as fluctuating illumination, limitation of CO(2) fixation by low temperatures, salinity, or low nutrient or water availability, which disturb the homeostasis of the photosynthetic process. Photosynthetic organisms, therefore, have developed various molecular acclimation mechanisms that maintain or restore photosynthetic efficiency under adverse conditions and counteract abiotic stresses. Recent studies indicate that redox signals from photosynthetic electron transport and reactive oxygen species (ROS) or ROS-scavenging molecules play a central role in the regulation of acclimation and stress responses.

SCOPE

The underlying signalling network of photosynthetic redox control is largely unknown, but it is already apparent that gene regulation by redox signals is of major importance for plants. Signalling cascades controlling the expression of chloroplast and nuclear genes have been identified and dissection of the different pathways is advancing. Because of the direction of information flow, photosynthetic redox signals can be defined as a distinct class of retrograde signals in addition to signals from organellar gene expression or pigment biosynthesis. They represent a vital signal of mature chloroplasts that report their present functional state to the nucleus. Here we describe possible problems in the elucidation of redox signalling networks and discuss some aspects of plant cell biology that are important for developing suitable experimental approaches.

CONCLUSIONS

The photosynthetic function of chloroplasts represents an important sensor that integrates various abiotic changes in the environment into corresponding molecular signals, which, in turn, regulate cellular activities to counterbalance the environmental changes or stresses.

Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output

Deciphering the design principles for regulatory networks is fundamental to an understanding of biological systems. We have explored the mapping from the space of network topologies to the space of dynamical phenotypes for small networks. Using exhaustive enumeration of a simple model of three- and four-node networks, we demonstrate that certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences. The network topologies that encode a highly designable dynamical phenotype possess two classes of connections: a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and a partially conserved set of variable connections that controls the transient dynamical flow. By comparing the topologies and dynamics of the three- and four-node network ensembles, we observe a large number of instances of the phenomenon of "mutational buffering," whereby addition of a fourth node suppresses phenotypic variation amongst a set of three-node networks.

Identifying the conserved network of cis-regulatory sites of a eukaryotic genome

A major focus of genome research has been to decipher the cis-regulatory code that governs complex transcriptional regulation. We report a computational approach for identifying conserved regulatory motifs of an organism directly from whole genome sequences of several related species without reliance on additional information. We first construct phylogenetic profiles for each promoter, then use a BLAST-like algorithm to efficiently search through the entire profile space of all of the promoters in the genome to identify conserved motifs and the promoters that contain them. Statistical significance is estimated by modified Karlin-Altschul statistics. We applied this approach to the analysis of 3,524 Saccharomyces cerevisiae promoters and identified a highly organized regulatory network involving 3,315 promoters and 296 motifs. This network includes nearly all of the currently known motifs and covers >90% of known transcription factor binding sites. Most of the predicted coregulated gene clusters in the network have additional supporting evidence. Theoretical analysis suggests that our algorithm should be applicable to much larger genomes, such as the human genome, without reaching its statistical limitation.