cisRED: a database system for genome-scale computational discovery of regulatory elements

Distinct patterns of whole blood transcriptional responses are induced in mice following immunisation with adenoviral and poxviral vector vaccines encoding the same antigen

BACKGROUND

Viral vectors, including adenovirus (Ad) and modified vaccinia Ankara (MVA), have gained increasing attention as vaccine platforms in recent years due to their capacity to express antigens from a wide array of pathogens, their rapid induction of humoral and cellular protective immune responses, and their relatively low production costs. In particular, the chimpanzee Ad vector, ChAdOx1, has taken centre stage as a leading COVID-19 vaccine candidate. However, despite mounting data, both clinical and pre-clinical, demonstrating effective induction of adaptive immune responses, the innate immune signals that precede the protective responses that make these vectors attractive vaccine platforms remain poorly understood.

RESULTS

In this study, a mouse immunisation model was used to evaluate whole blood gene expression changes 24 h after either a single dose or heterologous prime-boost regimen of an Ad and/or MVA vaccine. We demonstrate through comparative analysis of Ad vectors encoding different antigens that a transgene product-specific gene signature can be discerned from the vector-induced transcriptional response. Expression of genes involved in TLR2 stimulation and γδ T cell and natural killer cell activation were induced after a single dose of Ad, while MVA led to greater expression of type I interferon genes. The order of prime-boost combinations was found to influence the magnitude of the gene expression changes, with MVA/Ad eliciting greater transcriptional perturbation than Ad/MVA. Contrasting the two regimens revealed significant enrichment of epigenetic regulation pathways and augmented expression of MHC class I and II molecules associated with MVA/Ad.

CONCLUSION

These data demonstrate that the order in which vaccines from heterologous prime-boost regimens are administered leads to distinct transcriptional responses and may shape the immune response induced by such combinations. The characterisation of early vaccine-induce responses strengthens our understanding of viral vector vaccine mechanisms of action ahead of their characterisation in human clinical trials and are a valuable resource to inform the pre-clinical design of appropriate vaccine constructs for emerging infectious diseases.

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression by modulating the packaging of DNA in the nucleus. A plethora of studies have emphasized the importance of analyzing epigenetics data through genome-wide studies and high-throughput approaches, thereby providing key insights towards epigenetics-based diseases such as cancer. Recent advancements have been made towards translating epigenetics research into a high throughput approach such as genome-scale profiling. Amongst all, bioinformatics plays a pivotal role in achieving epigenetics-related computational studies. Despite significant advancements towards epigenomic profiling, it is challenging to understand how various epigenetic modifications such as chromatin modifications and DNA methylation regulate gene expression. Next-generation sequencing (NGS) provides accurate and parallel sequencing thereby allowing researchers to comprehend epigenomic profiling. In this review, we summarize different computational methods such as machine learning and other bioinformatics tools, publicly available databases and resources to identify key modifications associated with epigenetic machinery. Additionally, the review also focuses on understanding recent methodologies related to epigenome profiling using NGS methods ranging from library preparation, different sequencing platforms and analytical techniques to evaluate various epigenetic modifications such as DNA methylation and histone modifications. We also provide detailed information on bioinformatics tools and computational strategies responsible for analyzing large scale data in epigenetics.

Robust Transcription Factor Binding Site Prediction Using Deep Neural Networks

Aims:

Robust and more accurate method for identifying transcription factor binding sites (TFBS) for gene expression.

Background:

Deep neural networks (DNNs) have shown promising growth in solving complex machine learning problems. Conventional techniques are comfortably replaced by DNNs in computer vision, signal processing, healthcare, and genomics. Understanding DNA sequences is always a crucial task in healthcare and regulatory genomics. For DNA motif prediction, choosing the right dataset with a sufficient number of input sequences is crucial in order to design an effective model.

Objective:

Designing a new algorithm which works on different dataset while an improved performance for TFBS prediction.

Methods:

With the help of Layerwise Relevance Propagation, the proposed algorithm identifies the invariant features with adaptive noise patterns.

Results:

The performance is compared by calculating various metrics on standard as well as recent methods and significant improvement is noted.

Conclusion:

By identifying the invariant and robust features in the DNA sequences, the classification performance can be increased.

Regulation of Cyclin E by transcription factors of the naïve pluripotency network in mouse embryonic stem cells

Continuous, non-cell cycle-dependent expression of cyclin E is a characteristic feature of mouse embryonic stem cells (mESCs). We studied the 5′ regulatory region of Cyclin E, also known as Ccne1, and identified binding sites for transcription factors of the naïve pluripotency network, including Esrrb, Klf4, and Tfcp2l1 within 1 kilobase upstream of the transcription start site. Luciferase assay and chromatin immunoprecipitation-quantitative polymerase chain reaction (ChiP–qPCR) study highlighted one binding site for Esrrb that is essential to transcriptional activity of the promoter region, and three binding sites for Klf4 and Tfcp2l1. Knockdown of Esrrb, Klf4, and Tfcp2l1 reduced Cyclin E expression whereas overexpression of Esrrb and Klf4 increased it, indicating a strong correlation between the expression level of these factors and that of cyclin E. We observed that cyclin E overexpression delays differentiation induced by Esrrb depletion, suggesting that cyclin E is an important target of Esrrb for differentiation blockade. We observed that mESCs express a low level of miR-15a and that transfection of a miR-15a mimic decreases Cyclin E mRNA level. These results lead to the conclusion that the high expression level of Cyclin E in mESCs can be attributed to transcriptional activation by Esrrb as well as to the absence of its negative regulator, miR-15a.

Epithelial RNase H2 Maintains Genome Integrity and Prevents Intestinal Tumorigenesis in Mice

BACKGROUND & AIMS

RNase H2 is a holoenzyme, composed of 3 subunits (ribonuclease H2 subunits A, B, and C), that cleaves RNA:DNA hybrids and removes mis-incorporated ribonucleotides from genomic DNA through ribonucleotide excision repair. Ribonucleotide incorporation by eukaryotic DNA polymerases occurs during every round of genome duplication and produces the most frequent type of naturally occurring DNA lesion. We investigated whether intestinal epithelial proliferation requires RNase H2 function and whether RNase H2 activity is disrupted during intestinal carcinogenesis.

METHODS

We generated mice with epithelial-specific deletion of ribonuclease H2 subunit B (H2b^ΔIEC) and mice that also had deletion of tumor-suppressor protein p53 (H2b/p53^ΔIEC); we compared phenotypes with those of littermate H2b^fl/fl or H2b/p53^fl/fl (control) mice at young and old ages. Intestinal tissues were collected and analyzed by histology. We isolated epithelial cells, generated intestinal organoids, and performed RNA sequence analyses. Mutation signatures of spontaneous tumors from H2b/p53^ΔIEC mice were characterized by exome sequencing. We collected colorectal tumor specimens from 467 patients, measured levels of ribonuclease H2 subunit B, and associated these with patient survival times and transcriptome data.

RESULTS

The H2b^ΔIEC mice had DNA damage to intestinal epithelial cells and proliferative exhaustion of the intestinal stem cell compartment compared with controls and H2b/p53^ΔIEC mice. However, H2b/p53^ΔIEC mice spontaneously developed small intestine and colon carcinomas. DNA from these tumors contained T>G base substitutions at GTG trinucleotides. Analyses of transcriptomes of human colorectal tumors associated lower levels of RNase H2 with shorter survival times.

CONCLUSIONS

In analyses of mice with disruption of the ribonuclease H2 subunit B gene and colorectal tumors from patients, we provide evidence that RNase H2 functions as a colorectal tumor suppressor. H2b/p53^ΔIEC mice can be used to study the roles of RNase H2 in tissue-specific carcinogenesis.

Shifting Retroviral Vector Integrations Away from Transcriptional Start Sites via DNA-Binding Protein Domain Insertion into Integrase

The unique ability of retroviruses to integrate genes into host genomes is of great value for long-term expression in gene therapy, but only when integrations occur at safe genomic sites. To reap the benefit of using retroviruses without severe detrimental effects, we developed several murine leukemia virus (MLV)-based gammaretroviral vectors with safer integration patterns by perturbing the structure of the integrase via insertion of DNA-binding zinc-finger domains (ZFDs) into an internal position of the enzyme. ZFD insertion significantly reduced the inherent, strong MLV integration preference for genomic regions near transcriptional start sites (TSSs), which are the most dangerous spots. The altered retroviral integration pattern was related to increased formation of residual primer-binding site sequences at the 3' end of proviruses. Several ZFD insertion mutants showed lower frequencies of integrations into the TSS genome regions when having the residual primer-binding site sequences in the proviruses. Our findings not only can extend the use of retroviruses in biomedical applications, but also provide a glimpse into the mechanisms underlying retroviral integration.

E2F transcription factors associated with up-regulated genes in glioblastoma

BACKGROUND

Glioblastoma is considered to the most common and malignant brain tumor in adults. Patients have a median survival of approximately one year from diagnosis due to poor response to therapy.

OBJECTIVE

We applied bioinformatics approaches to predict transcription factors (TF) that are deregulated in glioblastoma in an attempt to point out molecular targets for therapy.

METHODS

Up-regulated genes in glioblastoma selected from public microarray data were submitted to two TF association analyses. Thereafter, the expression levels of TF obtained in the overlap of analyses were assessed by RT-qPCR carried out in seven glioblastoma cell lines (T98, U251, U138, U87, U343, M059J, and M059K).

RESULTS

E2F1 and E2F4 were highlighted in both TF analyses. However, only E2F1 was confirmed as significantly up-regulated in all glioblastoma cell lines in vitro.

CONCLUSION

E2F1 is a potential common regulator of differentially expressed genes in glioblastoma, despite the genetic heterogeneity of tumor cells.

High-throughput transcriptomics reveals common and strain-specific responses of human macrophages to infection with Mycobacterium abscessus Smooth and Rough variants

Background

Mycobacterium abscessus (MAB) is an emerging pathogen causing pulmonary infections in those with inflammatory lung disorders, such as Cystic Fibrosis (CF), and is associated with the highest fatality rate among rapidly growing mycobacteria (RGM). Phenotypically, MAB manifests as either a Smooth (MAB-S) or a Rough (MAB-R) morphotype, which differ in their levels of cell wall glycopeptidolipids (GPLs) and in their pathogenicity in vivo. As one of the primary immune cells encountered by MAB, we sought to examine the early transcriptional events within macrophages, following infection with both MAB-S or MAB-R.

Results

We sampled the transcriptomes (mRNA and miRNA) of THP-1-derived macrophages infected with both MAB-R and MAB-S at 1, 4 and 24 h post-infection (hpi) using RNA-seq. A core set of 606 genes showed consistent expression profiles in response to both morphotypes, corresponding to the early transcriptional response to MAB. The core response is type I Interferon (IFN)-driven, involving the NF-κB and MAPK signaling pathways with concomitant pro-inflammatory cytokine production, and network analysis identified STAT1, EGR1, and SRC as key hub and bottleneck genes. MAB-S elicited a more robust transcriptional response at both the mRNA and miRNA levels, which was reflected in higher cytokine levels in culture supernatants. The transcriptional profiles of macrophages infected with both morphotypes were highly correlated, however, and a direct comparison identified few genes to distinguish them. Most of the induced miRNAs have previously been associated with mycobacterial infection and overall miRNA expression patterns were similarly highly correlated between the morphotypes.

Conclusions

The report here details the first whole transcriptome analysis of the early macrophage response to MAB infection. The overall picture at the early stages of macrophage infection is similar to that of other mycobacteria, reflected in a core type I IFN and pro-inflammatory cytokine response. Large-scale transcriptional differences in the host response to the different MAB morphotypes are not evident in the early stages of infection, however the subset of genes with distinct expression profiles suggest potentially interesting differences in internal trafficking of MAB within macrophages.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2246-1) contains supplementary material, which is available to authorized users.

Rapid Aneuploidy Detection of Chromosomes 13, 18, 21, X and Y Using Quantitative Fluorescent Polymerase Chain Reaction with Few Microdissected Fetal Cells

Objectives: Analysis of DNA from small numbers of cells, such as fetal cells in maternal blood, is a major limiting factor for their use in clinical applications. Traditional methods of single-cells whole genome amplification (SCs-WGA) and accurate analysis have been challenging to date. Our purpose was to assess the feasibility of using a few fetal cells to determine fetal sex and major chromosomal abnormalities by quantitative fluorescent polymerase chain reaction (QF-PCR). Methods: Cultured cells from 26 amniotic fluid samples were used for standard DNA extraction and recovery of 5 fetal cells by laser-capture microdissection. SCs-WGA was performed using the DNA from the microdissected cells. PCR amplification of short tandem repeats specific for chromosomes 13, 18, 21, X and Y was performed on extracted and amplified DNA. Allele dosage and sexing were quantitatively analyzed following separation by capillary electrophoresis. Results: Microsatellite QF-PCR analysis showed high concordance in chromosomal copy number between extracted and amplified DNA when 5 or more cells were used. Results were in concordance with that of conventional cytogenetic analysis. Conclusion: Satisfactory genomic coverage can be obtained from SCs-WGA. Clinically, SCs-WGA coupled with QF-PCR can provide a reliable, accurate, rapid and cost-effective method for detection of major fetal chromosome abnormalities.

Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data

As an important subtype of structural variations, chromosomal translocation is associated with various diseases, especially cancers, by disrupting gene structures and functions. Traditional methods for identifying translocations are time consuming and have limited resolutions. Recently, a few studies have employed next-generation sequencing (NGS) technology for characterizing chromosomal translocations on human genome, obtaining high-throughput results with high resolutions. However, these studies are mainly focused on mechanism-specific or site-specific translocation mapping. In this study, we conducted a comprehensive genome-wide analysis on the characterization of human chromosomal material exchange with regard to the chromosome translocations. Using NGS data of 1,481 subjects from the 1000 Genomes Project, we identified 15,349,092 translocated DNA fragment pairs, ranging from 65 to 1,886 bp and with an average size of approximately 102 bp. On average, each individual genome carried about 10,364 pairs, covering approximately 0.069% of the genome. We identified 16 translocation hot regions, among which two regions did not contain repetitive fragments. Results of our study overlapped with a majority of previous results, containing approximately 79% of approximately 2,340 translocations characterized in three available translocation databases. In addition, our study identified five novel potential recurrent chromosomal material exchange regions with greater than 20% detection rates. Our results will be helpful for an accurate characterization of translocations in human genomes, and contribute as a resource for future studies of the roles of translocations in human disease etiology and mechanisms.

TNFα-mediated Hsd11b1 binding of NF-κB p65 is associated with suppression of 11β-HSD1 in muscle

The activity of the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), which converts inactive cortisone (11-dehydrocorticosterone (11-DHC)) (in mice) into the active glucocorticoid (GC) cortisol (corticosterone in mice), can amplify tissue GC exposure. Elevated TNFα is a common feature in a range of inflammatory disorders and is detrimental to muscle function in diseases such as rheumatoid arthritis and chronic obstructive pulmonary disease. We have previously demonstrated that 11β-HSD1 activity is increased in the mesenchymal stromal cells (MSCs) by TNFα treatment and suggested that this is an autoregulatory anti-inflammatory mechanism. This upregulation was mediated by the P2 promoter of the Hsd11b1 gene and was dependent on the NF-κB signalling pathway. In this study, we show that in contrast to MSCs, in differentiated C2C12 and primary murine myotubes, TNFα suppresses Hsd11b1 mRNA expression and activity through the utilization of the alternative P1 promoter. As with MSCs, in response to TNFα treatment, NF-κB p65 was translocated to the nucleus. However, ChIP analysis demonstrated that the direct binding was seen at position -218 to -245 bp of the Hsd11b1 gene's P1 promoter but not at the P2 promoter. These studies demonstrate the existence of differential regulation of 11β-HSD1 expression in muscle cells through TNFα/p65 signalling and the P1 promoter, further enhancing our understanding of the role of 11β-HSD1 in the context of inflammatory disease.

Characterizing the Retinoblastoma 1 locus: putative elements for Rb1 regulation by in silico analysis

Limited understanding of the Rb1 locus hinders genetic and epigenetic analyses of Retinoblastoma, a childhood cancer of the nervous systems. In this study, we used in silico tools to investigate and review putative genetic and epigenetic elements of the Rb1 gene. We report transcription start sites, CpG islands, and regulatory moieties that are likely to influence transcriptional states of this gene. These might contribute genetic and epigenetic information modulating tissue-specific transcripts and expression levels of Rb1. The elements we identified include tandem repeats that reside within or next to CpG islands near Rb1's transcriptional start site, and that are likely to be polymorphic among individuals. Our analyses highlight the complexity of this gene and suggest opportunities and limitations for future studies of retinoblastoma, genetic counseling, and the accurate identification of patients at greater risk of developing the malignancy.

Novel factors in the pathogenesis of psoriasis and potential drug candidates are found with systems biology approach

Psoriasis is a multifactorial inflammatory skin disease characterized by increased proliferation of keratinocytes, activation of immune cells and susceptibility to metabolic syndrome. Systems biology approach makes it possible to reveal novel important factors in the pathogenesis of the disease. Protein-protein, protein-DNA, merged (containing both protein-protein and protein-DNA interactions) and chemical-protein interaction networks were constructed consisting of differentially expressed genes (DEG) between lesional and non-lesional skin samples of psoriatic patients and/or the encoded proteins. DEGs were determined by microarray meta-analysis using MetaOMICS package. We used STRING for protein-protein, CisRED for protein-DNA and STITCH for chemical-protein interaction network construction. General network-, cluster- and motif-analysis were carried out in each network. Many DEG-coded proteins (CCNA2, FYN, PIK3R1, CTGF, F3) and transcription factors (AR, TFDP1, MEF2A, MECOM) were identified as central nodes, suggesting their potential role in psoriasis pathogenesis. CCNA2, TFDP1 and MECOM might play role in the hyperproliferation of keratinocytes, whereas FYN may be involved in the disturbed immunity in psoriasis. AR can be an important link between inflammation and insulin resistance, while MEF2A has role in insulin signaling. A controller sub-network was constructed from interlinked positive feedback loops that with the capability to maintain psoriatic lesional phenotype. Analysis of chemical-protein interaction networks detected 34 drugs with previously confirmed disease-modifying effects, 23 drugs with some experimental evidences, and 21 drugs with case reports suggesting their positive or negative effects. In addition, 99 unpublished drug candidates were also found, that might serve future treatments for psoriasis.

Rare single nucleotide polymorphisms in the regulatory regions of the superoxide dismutase genes in autism spectrum disorder

Oxidative stress is suspected to be one of the several contributing factors in the etiology of autism spectrum disorder (ASD). We analyzed genes of the superoxide dismutase family (SOD1, SOD2, and SOD3) that are part of a major antioxidative stress system in human in order to detect the genetic variants contributing to the development of ASD. Using the optimized high-resolution melting (HRM) analysis, we identified two rare single nucleotide polymorphisms (SNPs) associated with the etiology of ASD. Both are located in the superoxide dismutase 1 (SOD1) gene and have a minor allele frequency in healthy population ~5%. The SNP c.239 + 34A>C (rs2234694) and SNP g.3341C>G (rs36233090) were detected with an odds ratio of 2.65 and P < 0.01. Both are located in the noncoding potentially regulatory regions of the SOD1 gene. This adds to the importance of rare SNPs in the etiology of complex diseases as well as to the importance of noncoding genetic variants analysis with a potential influence on the regulation of gene expression.

New insights in osteogenic differentiation revealed by mass spectrometric assessment of phosphorylated substrates in murine skin mesenchymal cells

Background

Bone fractures and loss represent significant costs for the public health system and often affect the patients quality of life, therefore, understanding the molecular basis for bone regeneration is essential. Cytokines, such as IL-6, IL-10 and TNFα, secreted by inflammatory cells at the lesion site, at the very beginning of the repair process, act as chemotactic factors for mesenchymal stem cells, which proliferate and differentiate into osteoblasts through the autocrine and paracrine action of bone morphogenetic proteins (BMPs), mainly BMP-2. Although it is known that BMP-2 binds to ActRI/BMPR and activates the SMAD 1/5/8 downstream effectors, little is known about the intracellular mechanisms participating in osteoblastic differentiation. We assessed differences in the phosphorylation status of different cellular proteins upon BMP-2 osteogenic induction of isolated murine skin mesenchymal stem cells using Triplex Stable Isotope Dimethyl Labeling coupled with LC/MS.

Results

From 150 μg of starting material, 2,264 proteins were identified and quantified at five different time points, 235 of which are differentially phosphorylated. Kinase motif analysis showed that several substrates display phosphorylation sites for Casein Kinase, p38, CDK and JNK. Gene ontology analysis showed an increase in biological processes related with signaling and differentiation at early time points after BMP2 induction. Moreover, proteins involved in cytoskeleton rearrangement, Wnt and Ras pathways were found to be differentially phosphorylated during all timepoints studied.

Conclusions

Taken together, these data, allow new insights on the intracellular substrates which are phosphorylated early on during differentiation to BMP2-driven osteoblastic differentiation of skin-derived mesenchymal stem cells.

Nencki Genomics Database--Ensembl funcgen enhanced with intersections, user data and genome-wide TFBS motifs

We present the Nencki Genomics Database, which extends the functionality of Ensembl Regulatory Build (funcgen) for the three species: human, mouse and rat. The key enhancements over Ensembl funcgen include the following: (i) a user can add private data, analyze them alongside the public data and manage access rights; (ii) inside the database, we provide efficient procedures for computing intersections between regulatory features and for mapping them to the genes. To Ensembl funcgen-derived data, which include data from ENCODE, we add information on conserved non-coding (putative regulatory) sequences, and on genome-wide occurrence of transcription factor binding site motifs from the current versions of two major motif libraries, namely, Jaspar and Transfac. The intersections and mapping to the genes are pre-computed for the public data, and the result of any procedure run on the data added by the users is stored back into the database, thus incrementally increasing the body of pre-computed data. As the Ensembl funcgen schema for the rat is currently not populated, our database is the first database of regulatory features for this frequently used laboratory animal. The database is accessible without registration using the mysql client: mysql –h database.nencki-genomics.org –u public. Registration is required only to add or access private data. A WSDL webservice provides access to the database from any SOAP client, including the Taverna Workbench with a graphical user interface.

Database URL:http://www.nencki-genomics.org.

Importance of different types of prior knowledge in selecting genome-wide findings for follow-up

Biological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts' opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNPs established as being associated with seven disease traits through GWA meta-analysis and independent replication, with the corresponding frequency in a randomly selected set of SNPs. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta-analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.

TBCK influences cell proliferation, cell size and mTOR signaling pathway

Mammalian target of rapamycin (mTOR) is a central regulator for both cell proliferation and cell growth; however, little is known about the regulation of mTOR expression at the transcriptional level. Here, we provide evidences that a conserved human protein TBCK (TBC1 domain containing kinase) is involved in the regulation of mTOR signaling pathway. Depletion of TBCK significantly inhibits cell proliferation, reduces cell size, and disrupts the organization of actin, but not microtubule. Knockdown of TBCK induces a significant decrease in the protein levels of components of mTOR complex (mTORC), and suppresses the activity of mTOR signaling, but not MAPK or PDK1/Akt pathway. Further results show that TBCK influences the expression of mTORC components at the transcriptional level. Thus, these data suggest that TBCK may play an important role in cell proliferation, cell growth and actin organization possibly by modulating mTOR pathway.

Genome-wide analysis of H4K5 acetylation associated with fear memory in mice

BACKGROUND

Histone acetylation has been implicated in learning and memory in the brain, however, its function at the level of the genome and at individual genetic loci remains poorly investigated. This study examines a key acetylation mark, histone H4 lysine 5 acetylation (H4K5ac), genome-wide and its role in activity-dependent gene transcription in the adult mouse hippocampus following contextual fear conditioning.

RESULTS

Using ChIP-Seq, we identified 23,235 genes in which H4K5ac correlates with absolute gene expression in the hippocampus. However, in the absence of transcription factor binding sites 150 bp upstream of the transcription start site, genes were associated with higher H4K5ac and expression levels. We further establish H4K5ac as a ubiquitous modification across the genome. Approximately one-third of all genes have above average H4K5ac, of which ~15% are specific to memory formation and ~65% are co-acetylated for H4K12. Although H4K5ac is prevalent across the genome, enrichment of H4K5ac at specific regions in the promoter and coding region are associated with different levels of gene expression. Additionally, unbiased peak calling for genes differentially acetylated for H4K5ac identified 114 unique genes specific to fear memory, over half of which have not previously been associated with memory processes.

CONCLUSIONS

Our data provide novel insights into potential mechanisms of gene priming and bookmarking by histone acetylation following hippocampal memory activation. Specifically, we propose that hyperacetylation of H4K5 may prime genes for rapid expression following activity. More broadly, this study strengthens the importance of histone posttranslational modifications for the differential regulation of transcriptional programs in cognitive processes.

TdIF1 recognizes a specific DNA sequence through its Helix-Turn-Helix and AT-hook motifs to regulate gene transcription

TdIF1 was originally identified as a protein that directly binds to DNA polymerase TdT. TdIF1 is also thought to function in transcription regulation, because it binds directly to the transcriptional factor TReP-132, and to histone deacetylases HDAC1 and HDAC2. Here we show that TdIF1 recognizes a specific DNA sequence and regulates gene transcription. By constructing TdIF1 mutants, we identify amino acid residues essential for its interaction with DNA. An in vitro DNA selection assay, SELEX, reveals that TdIF1 preferentially binds to the sequence 5′-GNTGCATG-3′ following an AT-tract, through its Helix-Turn-Helix and AT-hook motifs. We show that four repeats of this recognition sequence allow TdIF1 to regulate gene transcription in a plasmid-based luciferase reporter assay. We demonstrate that TdIF1 associates with the RAB20 promoter, and RAB20 gene transcription is reduced in TdIF1-knocked-down cells, suggesting that TdIF1 stimulates RAB20 gene transcription.

Interferon-beta therapy in multiple sclerosis: the short-term and long-term effects on the patients' individual gene expression in peripheral blood

Therapy with interferon-beta (IFN-beta) is a mainstay in the management of relapsing-remitting multiple sclerosis (MS), with proven long-term effectiveness and safety. Much has been learned about the molecular mechanisms of action of IFN-beta in the past years. Previous studies described more than a hundred genes to be modulated in expression in blood cells in response to the therapy. However, for many of these genes, the precise temporal expression pattern and the therapeutic relevance are unclear. We used Affymetrix microarrays to investigate in more detail the gene expression changes in peripheral blood mononuclear cells from MS patients receiving subcutaneous IFN-beta-1a. The blood samples were obtained longitudinally at five different time points up to 2 years after the start of therapy, and the patients were clinically followed up for 5 years. We examined the functions of the genes that were upregulated or downregulated at the transcript level after short-term or long-term treatment. Moreover, we analyzed their mutual interactions and their regulation by transcription factors. Compared to pretreatment levels, 96 genes were identified as highly differentially expressed, many of them already after the first IFN-beta injection. The interactions between these genes form a large network with multiple feedback loops, indicating the complex crosstalk between innate and adaptive immune responses during therapy. We discuss the genes and biological processes that might be important to reduce disease activity by attenuating the proliferation of autoreactive immune cells and their migration into the central nervous system. In summary, we present novel insights that extend the current knowledge on the early and late pharmacodynamic effects of IFN-beta therapy and describe gene expression differences between the individual patients that reflect clinical heterogeneity.

Functional characterization of motif sequences under purifying selection

Diverse life forms are driven by the evolution of gene regulatory programs including changes in regulator proteins and cis-regulatory elements. Alterations of cis-regulatory elements are likely to dominate the evolution of the gene regulatory networks, as they are subjected to smaller selective constraints compared with proteins and hence may evolve quickly to adapt the environment. Prior studies on cis-regulatory element evolution focus primarily on sequence substitutions of known transcription factor-binding motifs. However, evolutionary models for the dynamics of motif occurrence are relatively rare, and comprehensive characterization of the evolution of all possible motif sequences has not been pursued. In the present study, we propose an algorithm to estimate the strength of purifying selection of a motif sequence based on an evolutionary model capturing the birth and death of motif occurrences on promoters. We term this measure as the 'evolutionary retention coefficient', as it is related yet distinct from the canonical definition of selection coefficient in population genetics. Using this algorithm, we estimate and report the evolutionary retention coefficients of all possible 10-nucleotide sequences from the aligned promoter sequences of 27 748. orthologous gene families in 34 mammalian species. Intriguingly, the evolutionary retention coefficients of motifs are intimately associated with their functional relevance. Top-ranking motifs (sorted by evolutionary retention coefficients) are significantly enriched with transcription factor-binding sequences according to the curated knowledge from the TRANSFAC database and the ChIP-seq data generated from the ENCODE Consortium. Moreover, genes harbouring high-scoring motifs on their promoters retain significantly coherent expression profiles, and those genes are over-represented in the functional classes involved in gene regulation. The validation results reveal the dependencies between natural selection and functions of cis-regulatory elements and shed light on the evolution of gene regulatory networks.

Ensembl 2013

The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat. Our resources include evidenced-based gene sets for all supported species; large-scale whole genome multiple species alignments across vertebrates and clade-specific alignments for eutherian mammals, primates, birds and fish; variation data resources for 17 species and regulation annotations based on ENCODE and other data sets. Ensembl data are accessible through the genome browser at http://www.ensembl.org and through other tools and programmatic interfaces.

Transcriptional Regulation of the Ufm1 Conjugation System in Response to Disturbance of the Endoplasmic Reticulum Homeostasis and Inhibition of Vesicle Trafficking

Homeostasis of the endoplasmic reticulum (ER) is essential for normal cellular functions. Disturbance of this homeostasis causes ER stress and activates the Unfolded Protein Response (UPR). The Ufm1 conjugation system is a novel Ubiquitin-like (Ubl) system whose physiological target(s) and biological functions remain largely undefined. Genetic study has demonstrated that the Ufm1-activating enzyme Uba5 is indispensible for erythroid differentiation in mice, highlighting the importance of this novel system in animal development. In this report we present the evidence for involvement of RCAD/Ufl1, a putative Ufm1-specific E3 ligase, and its binding partner C53/LZAP protein in ufmylation of endogenous Ufm1 targets. Moreover, we found that the Ufm1 system was transcriptionally up-regulated by disturbance of the ER homeostasis and inhibition of vesicle trafficking. Using luciferase reporter and ChIP assays, we dissected the Ufm1 promoter and found that Ufm1 was a potential target of Xbp-1, one of crucial transcription factors in UPR. We further examined the effect of Xbp-1 deficiency on the expression of the Ufm1 components. Interestingly, the expression of Ufm1, Uba5, RCAD/Ufl1 and C53/LZAP in wild-type mouse embryonic fibroblasts (MEFs) was significantly induced by inhibition of vesicle trafficking, but the induction was negated by Xbp-1 deficiency. Finally, we found that knockdown of the Ufm1 system in U2OS cells triggered UPR and amplification of the ER network. Taken together, our study provided critical insight into the regulatory mechanism of the Ufm1 system and established a direct link between this novel Ubl system and the ER network.

Statistical approaches to use a model organism for regulatory sequences annotation of newly sequenced species

A major goal of bioinformatics is the characterization of transcription factors and the transcriptional programs they regulate. Given the speed of genome sequencing, we would like to quickly annotate regulatory sequences in newly-sequenced genomes. In such cases, it would be helpful to predict sequence motifs by using experimental data from closely related model organism. Here we present a general algorithm that allow to identify transcription factor binding sites in one newly sequenced species by performing Bayesian regression on the annotated species. First we set the rationale of our method by applying it within the same species, then we extend it to use data available in closely related species. Finally, we generalise the method to handle the case when a certain number of experiments, from several species close to the species on which to make inference, are available. In order to show the performance of the method, we analyse three functionally related networks in the Ascomycota. Two gene network case studies are related to the G2/M phase of the Ascomycota cell cycle; the third is related to morphogenesis. We also compared the method with MatrixReduce and discuss other types of validation and tests. The first network is well known and provides a biological validation test of the method. The two cell cycle case studies, where the gene network size is conserved, demonstrate an effective utility in annotating new species sequences using all the available replicas from model species. The third case, where the gene network size varies among species, shows that the combination of information is less powerful but is still informative. Our methodology is quite general and could be extended to integrate other high-throughput data from model organisms.

cAMP response element-binding protein is a primary hub of activity-driven neuronal gene expression

Long-lasting forms of neuronal plasticity require de novo gene expression, but relatively little is known about the events that occur genome-wide in response to activity in a neuronal network. Here, we unveil the gene expression programs initiated in mouse hippocampal neurons in response to different stimuli and explore the contribution of four prominent plasticity-related transcription factors (CREB, SRF, EGR1, and FOS) to these programs. Our study provides a comprehensive view of the intricate genetic networks and interactions elicited by neuronal stimulation identifying hundreds of novel downstream targets, including novel stimulus-associated miRNAs and candidate genes that may be differentially regulated at the exon/promoter level. Our analyses indicate that these four transcription factors impinge on similar biological processes through primarily non-overlapping gene-expression programs. Meta-analysis of the datasets generated in our study and comparison with publicly available transcriptomics data revealed the individual and collective contribution of these transcription factors to different activity-driven genetic programs. In addition, both gain- and loss-of-function experiments support a pivotal role for CREB in membrane-to-nucleus signal transduction in neurons. Our data provide a novel resource for researchers wanting to explore the genetic pathways associated with activity-regulated neuronal functions.

Marked differences in neurochemistry and aggregates despite similar behavioural and neuropathological features of Huntington disease in the full-length BACHD and YAC128 mice

The development of animal models of Huntington disease (HD) has enabled studies that help define the molecular aberrations underlying the disease. The BACHD and YAC128 transgenic mouse models of HD harbor a full-length mutant huntingtin (mHTT) and recapitulate many of the behavioural and neuropathological features of the human condition. Here, we demonstrate that while BACHD and YAC128 animals exhibit similar deficits in motor learning and coordination, depressive-like symptoms, striatal volume loss and forebrain weight loss, they show obvious differences in key features characteristic of HD. While YAC128 mice exhibit significant and widespread accumulation of mHTT striatal aggregates, these mHTT aggregates are absent in BACHD mice. Furthermore, the levels of several striatally enriched mRNA for genes, such as DARPP-32, enkephalin, dopamine receptors D1 and D2 and cannabinoid receptor 1, are significantly decreased in YAC128 but not BACHD mice. These findings may reflect sequence differences in the human mHTT transgenes harboured by the BACHD and YAC128 mice, including both single nucleotide polymorphisms as well as differences in the nature of CAA interruptions of the CAG tract. Our findings highlight a similar profile of HD-like behavioural and neuropathological deficits and illuminate differences that inform the use of distinct endpoints in trials of therapeutic agents in the YAC128 and BACHD mice.

The regulatory epicenter of miRNAs

miRNAs are small non-coding RNAs with average length of ~21 bp. miRNA formation seems to be dependent upon multiple factors besides Drosha and Dicer, in a tissue/stage-specific manner, with interplay of several specific binding factors. In the present study, we have investigated transcription factor binding sites in and around the genomic sequences of precursor miRNAs and RNA-binding protein (RBP) sites in miRNA precursor sequences, analysed and tested in comprehensive manner. Here, we report that miRNA precursor regions are positionally enriched for binding of transcription factors as well as RBPs around the 3' end of mature miRNA region in 5' arm. The pattern and distribution of such regulatory sites appears to be a characteristic of precursor miRNA sequences when compared with non-miRNA sequences as negative dataset and tested statistically.When compared with 1 kb upstreamregions, a sudden sharp peak for binding sites arises in the enriched zone near the mature miRNA region. An expression-data-based correlation analysis was performed between such miRNAs and their corresponding transcription factors and RBPs for this region. Some specific groups of binding factors and associated miRNAs were identified. We also identified some of the overrepresented transcription factors and associated miRNAs with high expression correlation values which could be useful in cancer-related studies. The highly correlated groups were found to host experimentally validated composite regulatory modules, in which Lmo2-GATA1 appeared as the predominant one. For many of RBP-miRNAs associations, coexpression similarity was also evident among the associated miRNA common to given RBPs, supporting the Regulon model, suggesting a common role and common control of these miRNAs by the associated RBPs. Based on our findings, we propose that the observed characteristic distribution of regulatory sites in precursor miRNA sequence regions could be critical inmiRNA transcription, processing, stability and formation and are important for therapeutic studies. Our findings also support the recently proposed theory of self-sufficient mode of transcription by miRNAs, which states that miRNA transcription can be carried out in host-independent mode too.

GW8510 increases insulin expression in pancreatic alpha cells through activation of p53 transcriptional activity

BACKGROUND

Expression of insulin in terminally differentiated non-beta cell types in the pancreas could be important to treating type-1 diabetes. Previous findings led us to hypothesize involvement of kinase inhibition in induction of insulin expression in pancreatic alpha cells.

METHODOLOGY/PRINCIPAL FINDINGS

Alpha (αTC1.6) cells and human islets were treated with GW8510 and other small-molecule inhibitors for up to 5 days. Alpha cells were assessed for gene- and protein-expression levels, cell-cycle status, promoter occupancy status by chromatin immunoprecipitation (ChIP), and p53-dependent transcriptional activity. GW8510, a putative CDK2 inhibitor, up-regulated insulin expression in mouse alpha cells and enhanced insulin secretion in dissociated human islets. Gene-expression profiling and gene-set enrichment analysis of GW8510-treated alpha cells suggested up-regulation of the p53 pathway. Accordingly, the compound increased p53 transcriptional activity and expression levels of p53 transcriptional targets. A predicted p53 response element in the promoter region of the mouse Ins2 gene was verified by chromatin immunoprecipitation (ChIP). Further, inhibition of Jun N-terminal kinase (JNK) and p38 kinase activities suppressed insulin induction by GW8510.

CONCLUSIONS/SIGNIFICANCE

The induction of Ins2 by GW8510 occurred through p53 in a JNK- and p38-dependent manner. These results implicate p53 activity in modulation of Ins2 expression levels in pancreatic alpha cells, and point to a potential approach toward using small molecules to generate insulin in an alternative cell type.

Large-scale motif discovery using DNA Gray code and equiprobable oligomers

Motivation: How to find motifs from genome-scale functional sequences, such as all the promoters in a genome, is a challenging problem. Word-based methods count the occurrences of oligomers to detect excessively represented ones. This approach is known to be fast and accurate compared with other methods. However, two problems have hampered the application of such methods to large-scale data. One is the computational cost necessary for clustering similar oligomers, and the other is the bias in the frequency of fixed-length oligomers, which complicates the detection of significant words.

Results: We introduce a method that uses a DNA Gray code and equiprobable oligomers, which solve the clustering problem and the oligomer bias, respectively. Our method can analyze 18 000 sequences of ~1 kbp long in 30 s. We also show that the accuracy of our method is superior to that of a leading method, especially for large-scale data and small fractions of motif-containing sequences.

Availability: The online and stand-alone versions of the application, named Hegma, are available at our website: http://www.genome.ist.i.kyoto-u.ac.jp/~ichinose/hegma/

Contact:ichinose@i.kyoto-u.ac.jp; o.gotoh@i.kyoto-u.ac.jp

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

Background

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods.

Results

Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values.

Conclusions

Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Retinoic acid-induced upregulation of the metalloendopeptidase nardilysin is accelerated by co-expression of the brain-specific protein p42(IP4) (centaurin α 1; ADAP1) in neuroblastoma cells

The mainly neuronally expressed protein p42(IP4) (centaurin α1; ADAP1), which interacts with the metalloendopeptidase nardilysin (NRD) was found to be localized in neuritic plaques in Alzheimer disease (AD) brains. NRD was shown to enhance the cleavage of the amyloid precursor protein (APP) by α-secretases, thereby increasing the release of neuroprotective sAPPα. We here investigated in vitro the biochemical interaction of p42(IP4) and NRD and studied the physiological interaction in SH-SY5Y cells. NRD is a member of the M16 family of metalloendopeptidases. Some members of this M16 family act bi-functionally, as protease and as non-enzymatic scaffold protein. Here, we show that p42(IP4) enhances the enzymatic activity of NRD 3-4 times. However, p42(IP4) is not a substrate for NRD. Furthermore, we report that differentiation of SH-SY5Y cells by stimulation with 10μM retinoic acid (RA) results in upregulation of NRD protein levels, with a 6-fold rise after 15 days. NRD is expressed in the neurites of RA-stimulated SH-SY5Y cells, and localized in vesicular structures. Since p42(IP4) is not expressed in untreated SH-SY5Y cells, we could use this cell system as a model to find out, whether there is a functional interaction. Interestingly, SH-SY5Y cells, which we stably transfected with GFP-tagged-p42(IP4) showed an enhanced NRD protein expression already at an earlier time point after RA stimulation.

The differential disease regulome

Background

Transcription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studied on a per disease basis, and no current resources provide a global overview of the relations between transcription factors and disease. Furthermore, existing pipelines for related large-scale analysis are tailored for particular sources of input data, and there is a need for generic methodology for integrating complementary sources of genomic information.

Results

We here present a large-scale analysis of multiple diseases versus multiple transcription factors, with a global map of over-and under-representation of 446 transcription factors in 1010 diseases. This map, referred to as the differential disease regulome, provides a first global statistical overview of the complex interrelationships between diseases, genes and controlling elements. The map is visualized using the Google map engine, due to its very large size, and provides a range of detailed information in a dynamic presentation format.

The analysis is achieved through a novel methodology that performs a pairwise, genome-wide comparison on the cartesian product of two distinct sets of annotation tracks, e.g. all combinations of one disease and one TF.

The methodology was also used to extend with maps using alternative data sets related to transcription and disease, as well as data sets related to Gene Ontology classification and histone modifications. We provide a web-based interface that allows users to generate other custom maps, which could be based on precisely specified subsets of transcription factors and diseases, or, in general, on any categorical genome annotation tracks as they are improved or become available.

Conclusion

We have created a first resource that provides a global overview of the complex relations between transcription factors and disease. As the accuracy of the disease regulome depends mainly on the quality of the input data, forthcoming ChIP-seq based binding data for many TFs will provide improved maps. We further believe our approach to genome analysis could allow an advance from the current typical situation of one-time integrative efforts to reproducible and upgradable integrative analysis. The differential disease regulome and its associated methodology is available at http://hyperbrowser.uio.no.

TAFFEL: Independent Enrichment Analysis of gene sets

BACKGROUND

A major challenge in genomic research is identifying significant biological processes and generating new hypotheses from large gene sets. Gene sets often consist of multiple separate biological pathways, controlled by distinct regulatory mechanisms. Many of these pathways and the associated regulatory mechanisms might be obscured by a large number of other significant processes and thus not identified as significant by standard gene set enrichment analysis tools.

RESULTS

We present a novel method called Independent Enrichment Analysis (IEA) and software TAFFEL that eases the task by clustering genes to subgroups using Gene Ontology categories and transcription regulators. IEA indicates transcriptional regulators putatively controlling biological functions in studied condition.

CONCLUSIONS

We demonstrate that the developed method and TAFFEL tool give new insight to the analysis of differentially expressed genes and can generate novel hypotheses. Our comparison to other popular methods showed that the IEA method implemented in TAFFEL can find important biological phenomena, which are not reported by other methods.

Preferential regulation of miRNA targets by environmental chemicals in the human genome

Background

microRNAs (miRNAs) represent a class of small (typically 22 nucleotides in length) non-coding RNAs that can degrade their target mRNAs or block their translation. Recent disease research showed the exposure to some environmental chemicals (ECs) can regulate the expression patterns of miRNAs, which raises the intriguing question of how miRNAs and their targets cope with the exposure to ECs throughout the genome.

Results

In this study, we comprehensively analyzed the properties of genes regulated by ECs (EC-genes) and found miRNA targets were significantly enriched among the EC-genes. Compared with the non-miRNA-targets, miRNA targets were roughly twice as likely to be EC-genes. By investigating the collection methods and other properties of the EC-genes, we demonstrated that the enrichment of miRNA targets was not attributed to either the potential collection bias of EC-genes, the presence of paralogs, longer 3'UTRs or more conserved 3'UTRs. Finally, we identified 1,842 significant concurrent interactions between 407 miRNAs and 497 ECs. This association network of miRNAs-ECs was highly modular and could be separated into 14 interconnected modules. In each module, miRNAs and ECs were closely connected, providing a good method to design accurate miRNA markers for ECs in toxicology research.

Conclusions

Our analyses indicated that miRNAs and their targets played important roles in cellular responses to ECs. Association analyses of miRNAs and ECs will help to broaden the understanding of the pathogenesis of such chemical components.

LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data

All cellular processes are regulated by condition-specific and time-dependent interactions between transcription factors and their target genes. While in simple organisms, e.g. bacteria and yeast, a large amount of experimental data is available to support functional transcription regulatory interactions, in mammalian systems reconstruction of gene regulatory networks still heavily depends on the accurate prediction of transcription factor binding sites. Here, we present a new method, log-linear modeling of 3D contingency tables (LLM3D), to predict functional transcription factor binding sites. LLM3D combines gene expression data, gene ontology annotation and computationally predicted transcription factor binding sites in a single statistical analysis, and offers a methodological improvement over existing enrichment-based methods. We show that LLM3D successfully identifies novel transcriptional regulators of the yeast metabolic cycle, and correctly predicts key regulators of mouse embryonic stem cell self-renewal more accurately than existing enrichment-based methods. Moreover, in a clinically relevant in vivo injury model of mammalian neurons, LLM3D identified peroxisome proliferator-activated receptor γ (PPARγ) as a neuron-intrinsic transcriptional regulator of regenerative axon growth. In conclusion, LLM3D provides a significant improvement over existing methods in predicting functional transcription regulatory interactions in the absence of experimental transcription factor binding data.

Predicting functionally important SNP classes based on negative selection

Background

With the advent of cost-effective genotyping technologies, genome-wide association studies allow researchers to examine hundreds of thousands of single nucleotide polymorphisms (SNPs) for association with human disease. Recently, many researchers applying this strategy have detected strong associations to disease with SNP markers that are either not in linkage disequilibrium with any nonsynonymous SNP or large distances from any annotated gene. In such cases, no well-established standard practice for effective SNP selection for follow-up studies exists. We aim to identify and prioritize groups of SNPs that are more likely to affect phenotypes in order to facilitate efficient SNP selection for follow-up studies.

Results

Based on the annotations available in the Ensembl database, we categorized SNPs in the human genome into classes related to regulatory attributes, such as epigenetic modifications and transcription factor binding sites, in addition to classes related to gene structure and cross-species conservation. Using the distribution of derived allele frequencies (DAF) within each class, we assessed the strength of natural selection for each class relative to the genome as a whole. We applied this DAF analysis to Perlegen resequenced SNPs genome-wide. Regulatory elements annotated by Ensembl such as specific histone methylation sites as well as classes defined by cross-species conservation showed negative selection in comparison to the genome as a whole.

Conclusions

These results highlight which annotated classes are under purifying selection, have putative functional importance, and contain SNPs that are strong candidates for follow-up studies after genome-wide association. Such SNP annotation may also be useful in interpreting results of whole-genome sequencing studies.

Hippo/Mst1 stimulates transcription of the proapoptotic mediator NOXA in a FoxO1-dependent manner

The proapoptotic protein Noxa, a member of the BH3-only Bcl-2 protein family, can effectively induce apoptosis in cancer cells, although the relevant regulatory pathways have been obscure. Previous studies of the cytotoxic effects of α-tocopheryl succinate (α-TOS) on cancer cells identified a mechanism whereby α-TOS caused apoptosis requiring the Noxa-Bak axis. In the present study, ab initio analysis revealed a conserved FoxO-binding site (DBE; DAF-16 binding element) in the NOXA promoter, and specific affinity of FoxO proteins to this DBE was confirmed by fluorescence anisotropy. FoxO1 and FoxO3a proteins accumulated in the nucleus of α-TOS-treated cells, and the drug-induced specific FoxO1 association with the NOXA promoter and its activation were validated by chromatin immunoprecipitation. Using siRNA knockdown, a specific role for the FoxO1 protein in activating NOXA transcription in cancer cells was identified. Furthermore, the proapoptotic kinase Hippo/Mst1 was found to be strongly activated by α-TOS, and inhibiting Hippo/Mst1 by specific siRNA prevented phosphorylation of FoxO1 and its nuclear translocation, thereby reducing levels of NOXA transcription and apoptosis in cancer cells exposed to α-TOS. Thus, we have demonstrated that anticancer drugs, exemplified by α-TOS, induce apoptosis by a mechanism involving the Hippo/Mst1-FoxO1-Noxa pathway. We propose that activation of this pathway provides a new paradigm for developing targeted cancer treatments.

Bid regulates the immunological profile of murine microglia and macrophages

Apoptosis is a controlled cell-death process mediated inter alia by proteins of the Bcl-2 family. Some proteins previously shown to promote the apoptotic process were found to have nonapoptotic functions as well. Microglia, the resident immune cells of the central nervous system, respond to brain derangements by becoming activated to contend with the brain damage. Activated microglia can also undergo activation-induced cell death. Previous studies have addressed the role of core apoptotic proteins in the death process, but whether these proteins also play a role or not in the activation process is not been reported. Here we explore the effect of the BH3-only protein Bid on the immunological features of microglia and macrophages. Our results showed that Bid regulates both the phagocytotic activities and the inflammatory profiles of these cells. Deficiency of Bid attenuated the phagocytotic activity of primary microglia and peritoneal macrophages. It also changed the expression profile of distinct inflammation-related genes in lipopolysaccharide-activated microglia and peritoneal macrophages in vitro and in an in vivo sepsis-like paradigm. Notably, similar changes followed downregulation of Bid in the N9 microglial cell line. Cell death could not be detected in any of the systems examined. Our findings demonstrate that Bid can regulate the immunological profiles of activated microglial and macrophages, via a novel nonapoptotic activity. In view of the critical role of these cells in various pathologies, including acute and chronic brain insults, our findings suggest that impairments in Bid expression may contribute to these pathologies also via a nonapoptotic activity.

The early whole-blood transcriptional signature of dengue virus and features associated with progression to dengue shock syndrome in Vietnamese children and young adults

Dengue is a pantropic public health problem. In children, dengue shock syndrome (DSS) is the most common life-threatening complication. The ability to predict which patients may develop DSS may improve triage and treatment. To this end, we conducted a nested case-control comparison of the early host transcriptional features in 24 DSS patients and 56 sex-, age-, and virus serotype-matched uncomplicated (UC) dengue patients. In the first instance, we defined the "early dengue" profile. The transcriptional signature in acute rather than convalescent samples (≤72 h post-illness onset) was defined by an overabundance of interferon-inducible transcripts (31% of the 551 overabundant transcripts) and canonical gene ontology terms that included the following: response to virus, immune response, innate immune response, and inflammatory response. Pathway and network analyses identified STAT1, STAT2, STAT3, IRF7, IRF9, IRF1, CEBPB, and SP1 as key transcriptional factors mediating the early response. Strikingly, the only difference in the transcriptional signatures of early DSS and UC dengue cases was the greater abundance of several neutrophil-associated transcripts in patients who progressed to DSS, a finding supported by higher plasma concentrations of several canonical proteins associated with neutrophil degranulation (bactericidal/permeability-increasing protein [BPI], elastase 2 [ELA2], and defensin 1 alpha [DEF1A]). Elevated levels of neutrophil-associated transcripts were independent of the neutrophil count and also of the genotype of the infecting virus, as genome-length sequences of dengue virus serotype 1 (DENV-1) (n = 15) and DENV-2 (n = 3) sampled from DSS patients were phylogenetically indistinguishable from those sampled from uncomplicated dengue patients (32 DENV-1 and 9 DENV-2 sequences). Collectively, these data suggest a hitherto unrecognized association between neutrophil activation, pathogenesis, and the development of DSS and point to future strategies for guiding prognosis.

NGSmethDB: a database for next-generation sequencing single-cytosine-resolution DNA methylation data

Next-generation sequencing (NGS) together with bisulphite conversion allows the generation of whole genome methylation maps at single-cytosine resolution. This allows studying the absence of methylation in a particular genome region over a range of tissues, the differential tissue methylation or the changes occurring along pathological conditions. However, no database exists fully addressing such requirements. We propose here NGSmethDB (http://bioinfo2.ugr.es/NGSmethDB/gbrowse/) for the storage and retrieval of methylation data derived from NGS. Two cytosine methylation contexts (CpG and CAG/CTG) are considered. Through a browser interface coupled to a MySQL backend and several data mining tools, the user can search for methylation states in a set of tissues, retrieve methylation values for a set of tissues in a given chromosomal region, or display the methylation of promoters among different tissues. NGSmethDB is currently populated with human, mouse and Arabidopsis data, but other methylomes will be incorporated through an automatic pipeline as soon as new data become available. Dump downloads for three coverage levels (1, 5 or 10 reads) are available. NGSmethDB will be useful for experimental researchers, as well as for bioinformaticians, who might use the data as input for further research.

Genomic features of the human dopamine transporter gene and its potential epigenetic States: implications for phenotypic diversity

Human dopamine transporter gene (DAT1 or SLC6A3) has been associated with various brain-related diseases and behavioral traits and, as such, has been investigated intensely in experimental- and clinical-settings. However, the abundance of research data has not clarified the biological mechanism of DAT regulation; similarly, studies of DAT genotype-phenotype associations yielded inconsistent results. Hence, our understanding of the control of the DAT protein product is incomplete; having this knowledge is critical, since DAT plays the major role in the brain's dopaminergic circuitry. Accordingly, we reevaluated the genomic attributes of the SLC6A3 gene that might confer sensitivity to regulation, hypothesizing that its unique genomic characteristics might facilitate highly dynamic, region-specific DAT expression, so enabling multiple regulatory modes. Our comprehensive bioinformatic analyzes revealed very distinctive genomic characteristics of the SLC6A3, including high inter-individual variability of its sequence (897 SNPs, about 90 repeats and several CNVs spell out all abbreviations in abstract) and pronounced sensitivity to regulation by epigenetic mechanisms, as evident from the GC-bias composition (0.55) of the SLC6A3, and numerous intragenic CpG islands (27 CGIs). We propose that this unique combination of the genomic features and the regulatory attributes enables the differential expression of the DAT1 gene and fulfills seemingly contradictory demands to its regulation; that is, robustness of region-specific expression and functional dynamics.

Touring Ensembl: a practical guide to genome browsing

The number of databases in molecular biological fields has rapidly increased to provide a large-scale resource. Though valuable information is available, data can be difficult to access, compare and integrate due to different formats and presentations of web interfaces. This paper offers a practical guide to the integration of gene, comparative genomic, and functional genomics data using the Ensembl website at http://www.ensembl.org.The Ensembl genome browser and underlying databases focus on chordate organisms. More species such as plants and microorganisms can be investigated using our sister browser at http://www.ensemblgenomes.org.In this study, four examples are used that sample many pages and features of the Ensembl browser. We focus on comparative studies across over 50 mostly chordate organisms, variations linked to disease, functional genomics, and access of external information housed in databases outside the Ensembl project. Researchers will learn how to go beyond simply exporting one gene sequence, and explore how a genome browser can integrate data from various sources and databases to build a full and comprehensive biological picture.

Identification and characterization of putative methylation targets in the MAOA locus using bioinformatic approaches

Monoamine oxidase A (MAO A) is an enzyme that catalyzes the oxidation of neurotransmitter amines. A functional polymorphism in the human MAOA gene (high- and low-MAOA) has been associated with distinct behavioral phenotypes. To investigate directly the biological mechanism whereby this polymorphism influences brain function, we recently measured the activity of the MAO A enzyme in healthy volunteers. When found no relationship between the individual's brain MAO A level and the MAOA genotype, we postulated that there are additional regulatory mechanisms that control the MAOA expression. Given that DNA methylation is linked to the regulation of gene expression, we hypothesized that epigenetic mechanisms factor into the MAOA expression. Our underplaying assumption was that the differences in an individual's genotype play a key role in the epigenetic potential of the MAOA locus and, consequently, determine the individual's level of MAO A activity in the brain. As a first step towards experimental validation of the hypothesis, we performed a comprehensive bioinformatic analysis aiming to interrogate genomic features and attributes of the MAOA locus that might modulate its epigenetic sensitivity. Major findings of our analysis are the following: (1) the extended MAOA regulatory region contains two CpG islands (CGIs), one of which overlaps with the canonical MAOA promoter and the other is located further upstream; both CGIs exhibit sensitivity to differential methylation. (2) The uVNTR's effect on the MAOA's transcriptional activity might have epigenetic nature: this polymorphic region resides within the MAOA's CGI and itself contains CpGs, thus, the number of repeating increments effectively changes the number of methylatable cytosines in the MAOA promoter. An array of in silico analyses (the nucleosome positioning, the physical properties of the local DNA, the clustering of transcription-factor binding sites) together with experimental data on histone modifications and Pol 2 sites and data from the RefSeq mRNA library suggest that the MAOA gene might have an alternative promoter. Based on our findings, we propose a regulatory mechanism for the human MAOA according to which the MAOA expression in vivo is executed by the generation of tissue-specific transcripts initiated from the alternative promoters (both CGI-associated) where transcriptional activation of a particular promoter is under epigenetic control.

Contrasting genetic paths to morphological and physiological evolution

The relative importance of protein function change and gene expression change in phenotypic evolution is a contentious, yet central topic in evolutionary biology. Analyzing 5,199 mouse genes with recorded mutant phenotypes, we find that genes exclusively affecting morphological traits when mutated (dubbed "morphogenes") are grossly enriched with transcriptional regulators, whereas those exclusively affecting physiological traits (dubbed "physiogenes") are enriched with channels, transporters, receptors, and enzymes. Compared to physiogenes, morphogenes are more likely to be essential and pleiotropic and less likely to be tissue specific. Morphogenes evolve faster in expression profile, but slower in protein sequence and gene gain/loss than physiogenes. Thus, morphological and physiological changes have a differential molecular basis; separating them helps discern the genetic mechanisms of phenotypic evolution.

Functional profiling methods in cancer

The introduction of new high-throughput methodologies such as DNA microarrays constitutes a major breakthrough in cancer research. The unprecedented amount of data produced by such technologies has opened new avenues for interrogating living systems although, at the same time, it has demanded of the development of new data analytical methods as well as new strategies for testing hypotheses. A history of early successful applications in cancer boosted the use of microarrays and fostered further applications in other fields. Keeping the pace with these technologies, bioinformatics offers new solutions for data analysis and, what is more important, permits the formulation of a new class of hypotheses inspired in systems biology, more oriented to pathways or, in general, to modules of functionally related genes. Although these analytical methodologies are new, some options are already available and are discussed in this chapter.