Positional distribution of human transcription factor binding sites

Intergenic transcription in in vivo developed bovine oocytes and pre-implantation embryos

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and read-ins (transcribed 1 kb up-stream of reference genes, extending up to 15 kb up-stream). Read-throughs (continued transcription from TES of expressed reference genes, 4-15 kb in length), however, were much fewer. For example, the numbers of read-outs and read-ins ranged from 3,084 to 6,565 or 33.36-66.67% of expressed reference genes at different stages of embryo development. The less copious read-throughs were at an average of 10% and significantly correlated with reference gene expression (P < 0.05). Interestingly, intergenic transcription did not seem to be random because many intergenic transcripts (1,504 read-outs, 1,045 read-ins, and 1,021 read-throughs) were associated with common reference genes across all stages of pre-implantation development. Their expression also seemed to be regulated by developmental stages because many were differentially expressed (log2 fold change ≥ 2, P < 0.05). Additionally, while gradual but un-patterned decreases in DNA methylation densities 10 kb both up- and down-stream of the intergenic transcribed regions were observed, the correlation between intergenic transcription and DNA methylation was insignificant. Finally, transcription factor binding motifs and polyadenylation signals were found in 27.2% and 12.15% of intergenic transcripts, respectively, suggesting considerable novel transcription initiation and RNA processing.

Conclusion

In summary, in vivo developed oocytes and pre-implantation embryos express large numbers of intergenic transcripts, which are not related to the overall DNA methylation profiles either up- or down-stream.

Structural and genome-wide analyses suggest that transposon-derived protein SETMAR alters transcription and splicing

Extensive portions of the human genome have unknown function, including those derived from transposable elements. One such element, the DNA transposon Hsmar1, entered the primate lineage approximately 50 million years ago leaving behind terminal inverted repeat (TIR) sequences and a single intact copy of the Hsmar1 transposase, which retains its ancestral TIR-DNA-binding activity, and is fused with a lysine methyltransferase SET domain to constitute the chimeric SETMAR gene. Here, we provide a structural basis for recognition of TIRs by SETMAR and investigate the function of SETMAR through genome-wide approaches. As elucidated in our 2.37 Å crystal structure, SETMAR forms a dimeric complex with each DNA-binding domain bound specifically to TIR-DNA through the formation of 32 hydrogen bonds. We found that SETMAR recognizes primarily TIR sequences (∼5000 sites) within the human genome as assessed by chromatin immunoprecipitation sequencing analysis. In two SETMAR KO cell lines, we identified 163 shared differentially expressed genes and 233 shared alternative splicing events. Among these genes are several pre–mRNA-splicing factors, transcription factors, and genes associated with neuronal function, and one alternatively spliced primate-specific gene, TMEM14B, which has been identified as a marker for neocortex expansion associated with brain evolution. Taken together, our results suggest a model in which SETMAR impacts differential expression and alternative splicing of genes associated with transcription and neuronal function, potentially through both its TIR-specific DNA-binding and lysine methyltransferase activities, consistent with a role for SETMAR in simian primate development.

Detection and identification of cis-regulatory elements using change-point and classification algorithms

BACKGROUND

Transcriptional regulation is primarily mediated by the binding of factors to non-coding regions in DNA. Identification of these binding regions enhances understanding of tissue formation and potentially facilitates the development of gene therapies. However, successful identification of binding regions is made difficult by the lack of a universal biological code for their characterisation.

RESULTS

We extend an alignment-based method, changept, and identify clusters of biological significance, through ontology and de novo motif analysis. Further, we apply a Bayesian method to estimate and combine binary classifiers on the clusters we identify to produce a better performing composite.

CONCLUSIONS

The analysis we describe provides a computational method for identification of conserved binding sites in the human genome and facilitates an alternative interrogation of combinations of existing data sets with alignment data.

Elucidating evolutionarily conserved mechanisms of diapause regulation using an in silico approach

Embryonic diapause is an enigmatic phenomenon that appears in diverse species. Although regulatory mechanisms have been established, there is much to be discovered. Herein, we have made the first comprehensive attempt to elucidate diapause regulatory mechanisms using a computational approach. We found transcription factors unique to promoters of genes in diapause species. From pathway analysis and STRING PPI networks, the signaling pathways regulated by these unique transcription factors were identified. The pathways were then consolidated into a model to combine various known mechanisms of diapause regulation. This work also highlighted certain transcription factors that may act as 'master transcription factors' to regulate the phenomenon. Promoter analysis further suggested evidence for independent evolution for some of regulatory elements involved in diapause.

Species differences in phenobarbital-mediated UGT gene induction in rat and human liver microtissues

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Species differences in UGT induction could mediate thyroid cancer susceptibility.

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The effect of CAR activators on rat thyroid carcinogenesis could be partly explained by differential induction of Ugt 2b17.

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Human UGT changes would likely contribute less to species differences in T4 metabolism than rat UGT changes.

Species differences in hepatic metabolism of thyroxine (T4) by uridine diphosphate glucuronosyl transferase (UGT) and susceptibility to thyroid hormone imbalance could underlie differences in thyroid carcinogenesis caused by hepatic enzyme inducers in rats and humans. To investigate this hypothesis we examined profiles of hepatic UGT induction by the prototypical CAR activator phenobarbital (PB) in rat and human liver 3D microtissues. The rationale for this approach was that 3D microtissues would generate data more relevant to humans. Rat and human liver 3D microtissues were exposed to PB over a range of concentrations (500 u M - 2000 u M) and times (24−96 hr). Microarray and proteomics analyses were performed on parallel samples to generate integrated differentially expressed gene (DEG) datasets. Bioinformatics analysis of DEG data, including CAR response element (CRE) sequence analysis of UGT promoters, was used to assess species differences in UGT induction relative to CAR-mediated transactivation potential. A higher proportion of human UGT promoters were found to contain consensus CREs compared to the rat homologs. UGTs 1a6, 2b17 and 2b37 were upregulated by PB in rat liver 3D microtissues, but unaltered in human liver 3D microtissues. By contrast, human UGTs 1A8, 1A10 and 2B10 showed higher levels of induction (RNA and /or protein) compared to the rat homologs. There was general concordance between the presence of CREs and the induction of UGT RNA. As UGT1A and 2B isoforms metabolise T4, these results suggest that differences in UGT induction could contribute to differential susceptibility to CAR-mediated thyroid carcinogenesis in rats and humans.

COPD-dependent effects of genetic variation in key inflammation pathway genes on lung cancer risk

Genome-wide association studies (GWAS) have identified several loci contributing to lung cancer and COPD risk independently; however, inflammation-related pathways likely harbor additional lung cancer risk-associated variants in biologically relevant immune genes that differ dependent on COPD. We selected single nucleotide polymorphisms (SNPs) proximal to 2,069 genes within 48 immune pathways. We modeled the contribution of these variants to lung cancer risk in a discovery sample of 1,932 lung cancer cases and controls stratified by COPD status and validation sample of 953 cases and controls also stratified by COPD. There were 43 validated SNPs in those with COPD and 60 SNPs in those without COPD associated with lung cancer risk. Furthermore, 29 of 43 and 28 of 60 SNPs demonstrated a statistically significant interaction with COPD in the pooled sample. These variants demonstrated tissue-dependent effects on proximal gene expression, enhanced network connectivity and resided together in specific immune pathways. These results reveal that key inflammatory related genes and pathways, not found in prior GWAS, impact lung cancer risk in a COPD-dependent manner. Genetic variation identified in our study supplements prior lung cancer GWAS and serves as a foundation to further interrogate risk relationships in smoking and COPD populations.

LXRα Regulates ChREBPα Transactivity in a Target Gene-Specific Manner through an Agonist-Modulated LBD-LID Interaction

The cholesterol-sensing nuclear receptor liver X receptor (LXR) and the glucose-sensing transcription factor carbohydrate responsive element-binding protein (ChREBP) are central players in regulating glucose and lipid metabolism in the liver. More knowledge of their mechanistic interplay is needed to understand their role in pathological conditions like fatty liver disease and insulin resistance. In the current study, LXR and ChREBP co-occupancy was examined by analyzing ChIP-seq datasets from mice livers. LXR and ChREBP interaction was determined by Co-immunoprecipitation (CoIP) and their transactivity was assessed by real-time quantitative polymerase chain reaction (qPCR) of target genes and gene reporter assays. Chromatin binding capacity was determined by ChIP-qPCR assays. Our data show that LXRα and ChREBPα interact physically and show a high co-occupancy at regulatory regions in the mouse genome. LXRα co-activates ChREBPα and regulates ChREBP-specific target genes in vitro and in vivo. This co-activation is dependent on functional recognition elements for ChREBP but not for LXR, indicating that ChREBPα recruits LXRα to chromatin in trans. The two factors interact via their key activation domains; the low glucose inhibitory domain (LID) of ChREBPα and the ligand-binding domain (LBD) of LXRα. While unliganded LXRα co-activates ChREBPα, ligand-bound LXRα surprisingly represses ChREBPα activity on ChREBP-specific target genes. Mechanistically, this is due to a destabilized LXRα:ChREBPα interaction, leading to reduced ChREBP-binding to chromatin and restricted activation of glycolytic and lipogenic target genes. This ligand-driven molecular switch highlights an unappreciated role of LXRα in responding to nutritional cues that was overlooked due to LXR lipogenesis-promoting function.

PeakPass: Automating ChIP-Seq Blacklist Creation

ChIP-Seq blacklists contain genomic regions that frequently produce artifacts and noise in ChIP-Seq experiments. To improve signal-to-noise ratio, ChIP-Seq pipelines often remove data points that map to blacklist regions. Existing blacklists have been compiled in a manual or semiautomated way. In this article we describe PeakPass, an efficient method to generate blacklists, and demonstrate that blacklists can increase ChIP-Seq data quality. PeakPass leverages machine learning and attempts to automate blacklist generation. PeakPass uses a random forest classifier in combination with genomic features such as sequence, annotated repeats, complexity, assembly gaps, and the ratio of multimapping to uniquely mapping reads to identify artifact regions. We have validated PeakPass on a large data set and tested it for the purpose of upgrading a blacklist to a new reference genome version. We trained PeakPass on the ENCODE blacklist for the hg19 human reference genome, and created an updated blacklist for hg38. To assess the performance of this blacklist, we tested 42 ChIP-Seq replicates from 24 experiments using 10 ChIP-Seq quality metrics including relative strand coefficient, standardized standard deviation, and enrichment of reads in promoter regions. Using the blacklist generated by PeakPass resulted in a statistically significant improvement for nine of these metrics.

Computational Analysis Concerning the Impact of DNA Accessibility on CRISPR-Cas9 Cleavage Efficiency

Defining the variables that impact the specificity of CRISPR/Cas9 has been a major research focus. Whereas sequence complementarity between guide RNA and target DNA substantially dictates cleavage efficiency, DNA accessibility of the targeted loci has also been hypothesized to be an important factor. In this study, functional data from two genome-wide assays, genome-wide, unbiased identification of DSBs enabled by sequencing (GUIDE-seq) and circularization for in vitro reporting of cleavage effects by sequencing (CIRCLE-seq), have been computationally analyzed in conjunction with DNA accessibility determined via DNase I-hypersensitive sequencing from the Encyclopedia of DNA Elements (ENCODE) Database and transcriptome from the Sequence Read Archive to determine whether cellular factors influence CRISPR-induced cleavage efficiency. CIRCLE-seq and GUIDE-seq datasets were selected to represent the absence and presence of cellular factors, respectively. Data analysis revealed that correlations between sequence similarity and CRISPR-induced cleavage frequency were altered by the presence of cellular factors that modulated the level of DNA accessibility. The above-mentioned correlation was abolished when cleavage sites were located in less accessible regions. Furthermore, CRISPR-mediated edits were permissive even at regions that were insufficient for most endogenous genes to be expressed. These results provide a strong basis to dissect the contribution of local chromatin modulation markers on CRISPR-induced cleavage efficiency.

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs) whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor) and TUG1 and WT1-AS (inferred onco-lncRNAs) dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts.

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Hundreds of lncRNAs target cancer genes and pathways in each tumor context

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lncRNA copy numbers are predictive of target cancer gene dysregulation

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Most lncRNAs are predicted to be transcriptional or post-transcriptional specialists

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lncRNAs are predicted to synergistically regulate proliferation pathways in cancer

SalMotifDB: a tool for analyzing putative transcription factor binding sites in salmonid genomes

Background

Recently developed genome resources in Salmonid fish provides tools for studying the genomics underlying a wide range of properties including life history trait variation in the wild, economically important traits in aquaculture and the evolutionary consequences of whole genome duplications. Although genome assemblies now exist for a number of salmonid species, the lack of regulatory annotations are holding back our mechanistic understanding of how genetic variation in non-coding regulatory regions affect gene expression and the downstream phenotypic effects.

Results

We present SalMotifDB, a database and associated web and R interface for the analysis of transcription factors (TFs) and their cis-regulatory binding sites in five salmonid genomes. SalMotifDB integrates TF-binding site information for 3072 non-redundant DNA patterns (motifs) assembled from a large number of metazoan motif databases. Through motif matching and TF prediction, we have used these multi-species databases to construct putative regulatory networks in salmonid species. The utility of SalMotifDB is demonstrated by showing that key lipid metabolism regulators are predicted to regulate a set of genes affected by different lipid and fatty acid content in the feed, and by showing that our motif database explains a significant proportion of gene expression divergence in gene duplicates originating from the salmonid specific whole genome duplication.

Conclusions

SalMotifDB is an effective tool for analyzing transcription factors, their binding sites and the resulting gene regulatory networks in salmonid species, and will be an important tool for gaining a better mechanistic understanding of gene regulation and the associated phenotypes in salmonids. SalMotifDB is available at https://salmobase.org/apps/SalMotifDB.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6051-0) contains supplementary material, which is available to authorized users.

Placental DNA methylation levels at CYP2E1 and IRS2 are associated with child outcome in a prospective autism study

DNA methylation acts at the interface of genetic and environmental factors relevant for autism spectrum disorder (ASD). Placenta, normally discarded at birth, is a potentially rich source of DNA methylation patterns predictive of ASD in the child. Here, we performed whole methylome analyses of placentas from a prospective study MARBLES (Markers of Autism Risk in Babies-Learning Early Signs) of high-risk pregnancies. A total of 400 differentially methylated regions (DMRs) discriminated placentas stored from children later diagnosed with ASD compared to typically developing controls. These ASD DMRs were significantly enriched at promoters, mapped to 596 genes functionally enriched in neuronal development, and overlapped genetic ASD risk. ASD DMRs at CYP2E1 and IRS2 reached genome-wide significance, replicated by pyrosequencing and correlated with expression differences in brain. Methylation at CYP2E1 associated with both ASD diagnosis and genotype within the DMR. In contrast, methylation at IRS2 was unaffected by within DMR genotype but modified by preconceptional maternal prenatal vitamin use. This study therefore identified two potentially useful early epigenetic markers for ASD in placenta.

Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle

Background

Genome-wide association studies (GWAS) are widely used to identify regions of the genome that harbor genetic determinants of quantitative traits. However, the multiple-testing burden from scanning tens of millions of whole-genome sequence variants reduces the power to identify associated variants, especially if sample size is limited. In addition, factors such as inaccuracy of imputation, complex linkage disequilibrium structures, and multiple closely-located causal variants may result in an identified causative mutation not being the most significant single nucleotide polymorphism in a particular genomic region. Therefore, the use of information from different sources, particularly variant annotations, was proposed to enhance the fine-mapping of causal variants. Here, we tested whether applying significance thresholds based on variant annotation categories increases the power of GWAS compared with a flat Bonferroni multiple-testing correction.

Results

Whole-genome sequence variants in dairy cattle were categorized according to type and predicted impact. Then, GWAS between markers and 17 quantitative traits were analyzed for enrichment for association of each annotation category. By using annotation categories that were determined with the variants effect predictor software and datasets indicating regions of open chromatin, “low impact” variants were found to be highly enriched. Moreover, when the variants annotated as “modifier” and not located at open chromatin regions were further classified into different types of potential regulatory elements, the high impact variants, moderate impact variants, variants located in the 3′ and 5′ untranslated regions, and variants located in potential non-coding RNA regions exhibited relatively more enrichment. In contrast, a similar study on human GWAS data reported that enrichment of association signals was highest with high impact variants. We observed an increase in power when these variant category-based significance thresholds were applied for GWAS results on stature in Nordic Holstein cattle, as more candidate genes from previous large GWAS meta-analysis for cattle stature were confirmed.

Conclusions

Use of variant category-based genome-wide significance thresholds can marginally increase the power to detect the candidate genes in cattle. With the continued improvements in annotation of the bovine genome, we anticipate that the growing usefulness of variant category-based significance thresholds will be demonstrated.

Electronic supplementary material

The online version of this article (10.1186/s12711-019-0463-9) contains supplementary material, which is available to authorized users.

TICA: Transcriptional Interaction and Coregulation Analyzer

Transcriptional regulation is critical to cellular processes of all organisms. Regulatory mechanisms often involve more than one transcription factor (TF) from different families, binding together and attaching to the DNA as a single complex. However, only a fraction of the regulatory partners of each TF is currently known. In this paper, we present the Transcriptional Interaction and Coregulation Analyzer (TICA), a novel methodology for predicting heterotypic physical interaction of TFs. TICA employs a data-driven approach to infer interaction phenomena from chromatin immunoprecipitation and sequencing (ChIP-seq) data. Its prediction rules are based on the distribution of minimal distance couples of paired binding sites belonging to different TFs which are located closest to each other in promoter regions. Notably, TICA uses only binding site information from input ChIP-seq experiments, bypassing the need to do motif calling on sequencing data. We present our method and test it on ENCODE ChIP-seq datasets, using three cell lines as reference including HepG2, GM12878, and K562. TICA positive predictions on ENCODE ChIP-seq data are strongly enriched when compared to protein complex (CORUM) and functional interaction (BioGRID) databases. We also compare TICA against both motif/ChIP-seq based methods for physical TF-TF interaction prediction and published literature. Based on our results, TICA offers significant specificity (average 0.902) while maintaining a good recall (average 0.284) with respect to CORUM, providing a novel technique for fast analysis of regulatory effect in cell lines. Furthermore, predictions by TICA are complementary to other methods for TF-TF interaction prediction (in particular, TACO and CENTDIST). Thus, combined application of these prediction tools results in much improved sensitivity in detecting TF-TF interactions compared to TICA alone (sensitivity of 0.526 when combining TICA with TACO and 0.585 when combining with CENTDIST) with little compromise in specificity (specificity 0.760 when combining with TACO and 0.643 with CENTDIST). TICA is publicly available at http://geco.deib.polimi.it/tica/.

Control of human gene expression: High abundance of divergent transcription in genes containing both INR and BRE elements in the core promoter

Background

DNA sequence elements in the core promoter can play a central role in regulation of gene expression. Core elements (e.g. INR and TATA box) are located within ~50bp of the transcription start site and both upstream and downstream elements are known. Although all can affect the level of gene expression, their mechanism of action has yet to be fully defined. The studies described here are focused on two core promoter elements, INR and BRE, in the human genome. The locations of the two elements were determined in a large number of human promoters and the results were interpreted in terms of overall promoter function.

Results

A total of 13,406 promoters were collected from the reference version of the human genome and found to contain 62,891 INR sequences and 32,290 BRE. An INR sequence was found in the core region of 1231 (9.2%) promoters and a BRE in 2592 (19.3%); 121 promoters (0.9%) have both INR and BRE elements. Counts support the view that most human promoters lack an INR or BRE element in the core promoter. Further analysis was carried out with the aligned aggregate of promoters from each chromosome. The results showed distinct INR distributions in separate chromosome groups indicating a degree of chromosome specificity to the way core promoter elements are deployed in the genome. The rare promoters with both INR and BRE elements were found to be enriched among the genes with divergent transcription. Enrichment raises the possibility that core promoter elements can have a function in chromosome organization as well as in initiation of transcription.

Derivation and molecular characterization of pancreatic differentiated MODY1-iPSCs

Maturity onset diabetes of the young (MODY) is a hereditary form of diabetes mellitus presenting at childhood or adolescence, which eventually leads to pancreatic β-cells dysfunction. The underlying genetic basis of MODY disorders is haploinsufficiency, where loss-of-function mutations in a single allele cause the diabetic phenotype in heterozygous patients. MODY1 is a type of MODY disorder resulting from a mutation in the transcription factor hepatocyte nuclear factor 4 alpha (HNF4α). In order to establish a human based model to study MODY1, we generated patient-derived induced pluripotent stem cells (iPSCs). Differentiation of these pluripotent cells towards the pancreatic lineage enabled to evaluate the effects of the MODY1 mutation and its impact on endodermal and pancreatic cells. Analyzing the gene expression profiles of differentiated MODY1 cells, revealed the outcome of HNF4α haploinsufficiency on its targets. This molecular analysis suggests that the differential expression of HNF4α target genes in MODY1 is affected by the number of HNF4α binding sites, their distance from the transcription start site, and the number of other transcription factor binding sites. These features may help explain the molecular manifestations of haploinsufficiency in MODY1 disease.

An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis.

Virtual Genome Walking across the 32 Gb Ambystoma mexicanum genome; assembling gene models and intronic sequence

Large repeat rich genomes present challenges for assembly using short read technologies. The 32 Gb axolotl genome is estimated to contain ~19 Gb of repetitive DNA making an assembly from short reads alone effectively impossible. Indeed, this model species has been sequenced to 20× coverage but the reads could not be conventionally assembled. Using an alternative strategy, we have assembled subsets of these reads into scaffolds describing over 19,000 gene models. We call this method Virtual Genome Walking as it locally assembles whole genome reads based on a reference transcriptome, identifying exons and iteratively extending them into surrounding genomic sequence. These assemblies are then linked and refined to generate gene models including upstream and downstream genomic, and intronic, sequence. Our assemblies are validated by comparison with previously published axolotl bacterial artificial chromosome (BAC) sequences. Our analyses of axolotl intron length, intron-exon structure, repeat content and synteny provide novel insights into the genic structure of this model species. This resource will enable new experimental approaches in axolotl, such as ChIP-Seq and CRISPR and aid in future whole genome sequencing efforts. The assembled sequences and annotations presented here are freely available for download from https://tinyurl.com/y8gydc6n . The software pipeline is available from https://github.com/LooseLab/iterassemble .

MicroRNA-transcription factor interactions and their combined effect on target gene expression in colon cancer cases

Transcription factors (TFs) and microRNAs (miRNAs) regulate gene expression: TFs by influencing messenger RNA (mRNA) transcription and miRNAs by influencing mRNA translation and transcript degradation. Additionally, miRNAs and TFs alter each other's expression, making it difficult to ascertain the effect either one has on target gene (TG) expression. In this investigation, we use a two‐way interaction model with the TF and miRNA as independent variables to investigate whether miRNAs and TFs work together to influence TG expression levels in colon cancer subjects. We used known TF binding sites and validated miRNA targets to determine potential miRNA‐TF‐TG interactions, restricting interactions to those with a TF previously associated with altered risk of colorectal cancer death. We analyzed interactions using normal colonic mucosa expression as well as differential expression, which is measured as colonic carcinoma expression minus normal colonic mucosa expression. We analyzed 3518 miRNA‐TF‐TG triplets using normal mucosa expression and 617 triplets using differential expression. Normal colonic RNA‐Seq data were available for 168 individuals; of these, 159 also had carcinoma RNA‐Seq data. Thirteen unique miRNA‐TF‐TG interactions, comprising six miRNAs, four TFs, and 11 TGs, were statistically significant after adjustment for multiple comparisons in normal colonic mucosa, and 14 unique miRNA‐TF‐TG interactions, comprising two miRNAs, two TFs, and 13 TGs, were found for carcinoma‐normal differential expression. Our results show that TG expression is influenced by both miRNAs as well as TFs, and the influence of one regulator impacts the effect of the other on the shared TG expression.

De novo assembly and characterization of breast cancer transcriptomes identifies large numbers of novel fusion-gene transcripts of potential functional significance

Background

Gene-fusion or chimeric transcripts have been implicated in the onset and progression of a variety of cancers. Massively parallel RNA sequencing (RNA-Seq) of the cellular transcriptome is a promising approach for the identification of chimeric transcripts of potential functional significance. We report here the development and use of an integrated computational pipeline for the de novo assembly and characterization of chimeric transcripts in 55 primary breast cancer and normal tissue samples.

Methods

An integrated computational pipeline was employed to screen the transcriptome of breast cancer and control tissues for high-quality RNA-sequencing reads. Reads were de novo assembled into contigs followed by reference genome mapping. Chimeric transcripts were detected, filtered and characterized using our R-SAP algorithm. The relative abundance of reads was used to estimate levels of gene expression.

Results

De novo assembly allowed for the accurate detection of 1959 chimeric transcripts to nucleotide level resolution and facilitated detailed molecular characterization and quantitative analysis. A number of the chimeric transcripts are of potential functional significance including 79 novel fusion-protein transcripts and many chimeric transcripts with alterations in their un-translated leader regions. A number of chimeric transcripts in the cancer samples mapped to genomic regions devoid of any known genes. Several ‘pro-neoplastic’ fusions comprised of genes previously implicated in cancer are expressed at low levels in normal tissues but at high levels in cancer tissues.

Conclusions

Collectively, our results underscore the utility of deep sequencing technologies and improved bioinformatics workflows to uncover novel and potentially significant chimeric transcripts in cancer and normal somatic tissues.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-017-0289-7) contains supplementary material, which is available to authorized users.

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation

Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

Complex diseases such as hypertension often involve maladaptive autonomic nervous system control over the cardiovascular, renal, hepatic, immune, and endocrine systems. We studied the pathogenesis of physiological homeostasis by examining the temporal dynamics of gene expression levels from multiple organs in an animal model of autonomic dysfunction characterized by cardiovascular disease, metabolic dysregulation, and immune system aberrations. We employed a data-driven modeling approach to jointly predict continuous gene expression dynamics and gene regulatory interactions across organs in the disease and control phenotypes. We combined our analyses of multi-organ gene regulatory network dynamics and connectivity with bioinformatic analyses of genetic mutations that could regulate gene expression. Our multi-organ modeling approach to investigate the mechanisms of complex disease pathogenesis revealed novel candidates for therapeutic interventions against the development and progression of complex diseases involving autonomic nervous system dysfunction.

Identification and positional distribution analysis of transcription factor binding sites for genes from the wheat fl-cDNA sequences

The binding sites of transcription factors (TFs) in upstream DNA regions are called transcription factor binding sites (TFBSs). TFBSs are important elements for regulating gene expression. To date, there have been few studies on the profiles of TFBSs in plants. In total, 4,873 sequences with 5' upstream regions from 8530 wheat fl-cDNA sequences were used to predict TFBSs. We found 4572 TFBSs for the MADS TF family, which was twice as many as for bHLH (1951), B3 (1951), HB superfamily (1914), ERF (1820), and AP2/ERF (1725) TFs, and was approximately four times higher than the remaining TFBS types. The percentage of TFBSs and TF members showed a distinct distribution in different tissues. Overall, the distribution of TFBSs in the upstream regions of wheat fl-cDNA sequences had significant difference. Meanwhile, high frequencies of some types of TFBSs were found in specific regions in the upstream sequences. Both TFs and fl-cDNA with TFBSs predicted in the same tissues exhibited specific distribution preferences for regulating gene expression. The tissue-specific analysis of TFs and fl-cDNA with TFBSs provides useful information for functional research, and can be used to identify relationships between tissue-specific TFs and fl-cDNA with TFBSs. Moreover, the positional distribution of TFBSs indicates that some types of wheat TFBS have different positional distribution preferences in the upstream regions of genes.

Simvastatin-induced sphingosine 1-phosphate receptor 1 expression is KLF2-dependent in human lung endothelial cells

We have demonstrated that simvastatin and sphingosine 1−phosphate (S1P) both attenuate increased vascular permeability in preclinical models of acute respiratory distress syndrome. However, the underlying mechanisms remain unclear. As Krüppel-like factor 2 (KLF2) serves as a critical regulator for cellular stress response in endothelial cells (EC), we hypothesized that simvastatin enhances endothelial barrier function via increasing expression of the barrier-promoting S1P receptor, S1PR1, via a KLF2-dependent mechanism. S1PR1 luciferase reporter promoter activity in human lung artery EC (HPAEC) was tested after simvastatin (5 μM), and S1PR1 and KLF2 protein expression detected by immunoblotting. In vivo, transcription and expression of S1PR1 and KLF2 in mice lungs were detected by microarray profiling and immunoblotting after exposure to simvastatin (10 mg/kg). Endothelial barrier function was measured by trans-endothelial electrical resistance with the S1PR1 agonist FTY720-(S)-phosphonate. Both S1PR1 and KLF2 gene expression (mRNA, protein) were significantly increased by simvastatin in vitro and in vivo. S1PR1 promoter activity was significantly increased by simvastatin (P < 0.05), which was significantly attenuated by KLF2 silencing (siRNA). Simvastatin induced KLF2 recruitment to the S1PR1 promoter, and consequently, significantly augmented the effects of the S1PR1 agonist on EC barrier enhancement (P < 0.05), which was significantly attenuated by KLF2 silencing (P < 0.05). These results suggest that simvastatin upregulates S1PR1 transcription and expression via the transcription factor KLF2, and consequently augments the effects of S1PR1 agonists on preserving vascular barrier integrity. These results may lead to novel combinatorial therapeutic strategies for lung inflammatory syndromes.

RAG Recombinase as a Selective Pressure for Genome Evolution

The RAG recombinase is a domesticated transposable element co-opted in jawed vertebrates to drive the process of the so-called V(D)J recombination, which is the hallmark of the adaptive immune system to produce antigen receptors. RAG targets, namely, the Recombination Signal Sequences (RSS), are rather long and degenerated sequences, which highlights the ability of the recombinase to interact with a wide range of target sequences, including outside of antigen receptor loci. The recognition of such cryptic targets by the recombinase threatens genome integrity by promoting aberrant DNA recombination, as observed in lymphoid malignancies. Genomes evolution resulting from RAG acquisition is an ongoing discussion, in particular regarding the counter-selection of sequences resembling the RSS and the modifications of epigenetic regulation at these potential cryptic sites. Here, we describe a new bioinformatics tool to map potential RAG targets in all jawed vertebrates. We show that our REcombination Classifier (REC) outperforms the currently available tool and is suitable for full genomes scans from species other than human and mouse. Using the REC, we document a reduction in density of potential RAG targets at the transcription start sites of genes co-expressed with the rag genes and marked with high levels of the trimethylation of the lysine 4 of the histone 3 (H3K4me3), which correlates with the retention of functional RAG activity after the horizontal transfer.

Reprogramming cell fate with a genome-scale library of artificial transcription factors

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.

Precise mapping of the transcription start sites of human microRNAs using DROSHA knockout cells

Background

The expression of microRNAs (miRNAs) is primarily regulated during their transcription. However, the transcriptional regulation of miRNA genes has not been studied extensively owing to the lack of sufficient information about the promoters and transcription start sites of most miRNAs.

Results

In this study, we identified the transcription start sites of human primary miRNAs (pri-miRNAs) using DROSHA knockout cells. DROSHA knockout resulted in increased accumulation of pri-miRNAs and facilitated the precise mapping of their 5′ end nucleotides using the rapid amplification of cDNA ends (RACE) technique. By analyzing the promoter region encompassing the transcription start sites of miRNAs, we found that the unrelated miRNAs in their sequences have many common elements in their promoters for binding the same transcription factors. Moreover, by analyzing intronic miRNAs, we also obtained comprehensive evidence that miRNA-harboring introns are spliced more slowly than other introns.

Conclusions

The precisely mapped transcription start sites of pri-miRNAs, and the list of transcription factors for pri-miRNAs regulation, will be valuable resources for future studies to understand the regulatory network of miRNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3252-7) contains supplementary material, which is available to authorized users.

Genome-Wide Targets Regulated by the OsMADS1 Transcription Factor Reveals Its DNA Recognition Properties

OsMADS1 controls rice (Oryza sativa) floral fate and organ development. Yet, its genome-wide targets and the mechanisms underlying its role as a transcription regulator controlling developmental gene expression are unknown. We identify 3112 gene-associated OsMADS1-bound sites in the floret genome. These occur in the vicinity of transcription start sites, within gene bodies, and in intergenic regions. Majority of the bound DNA contained CArG motif variants or, in several cases, only A-tracts. Sequences flanking the binding peak had a higher AT nucleotide content, implying that broader DNA structural features may define in planta binding. Sequences for binding by other transcription factor families like MYC, AP2/ERF, bZIP, etc. are enriched in OsMADS1-bound DNAs. Target genes implicated in transcription, chromatin remodeling, cellular processes, and hormone metabolism were enriched. Combining expression data from OsMADS1 knockdown florets with these DNA binding data, a snapshot of a gene regulatory network was deduced where targets, such as AP2/ERF and bHLH transcription factors and chromatin remodelers form nodes. We show that the expression status of these nodal factors can be altered by inducing the OsMADS1-GR fusion protein and present a model for a regulatory cascade where the direct targets of OsMADS1, OsbHLH108/SPT, OsERF034, and OsHSF24, in turn control genes such as OsMADS32 and OsYABBY5 This cascade, with other similar relationships, cumulatively contributes to floral organ development. Overall, OsMADS1 binds to several regulatory genes and, probably in combination with other factors, controls a gene regulatory network that ensures rice floret development.

Ehrlichia chaffeensis TRP32 is a Nucleomodulin that Directly Regulates Expression of Host Genes Governing Differentiation and Proliferation

Ehrlichia chaffeensis is an obligately intracellular bacterium that reprograms the mononuclear phagocyte through diverse effector-host interactions to modulate numerous host cell processes, including transcription. In a previous study, we reported that E. chaffeensis TRP32, a type 1 secreted effector, interacts with multiple host nucleus-associated proteins and also auto-activates reporter gene expression in yeast. In this study, we demonstrate that TRP32 is a nucleomodulin that binds host DNA and alters host gene transcription. TRP32 enters the host cell nucleus via a noncanonical translocation mechanism that involves phosphorylation of Y179 located in a C-terminal tri-tyrosine motif. Both genistein and mutation of Y179 inhibited TRP32 nuclear entry. An electromobility shift assay (EMSA) demonstrated TRP32 host DNA binding via its tandem repeat domain. TRP32 DNA binding and motif preference were further confirmed by supershift assays, as well as competition and mutant probe analyses. Using ChIP-Seq, we determined that TRP32 binds a G-rich motif primarily within ±500 bp of the gene transcription start site. An ontology analysis identified genes involved in processes such as immune cell differentiation, chromatin remodeling, and RNA transcription and processing, as primary TRP32 targets. TRP32 bound genes (n=1223) were distributed on all chromosomes and included several global regulators of proliferation and inflammation such as FOS and JUN, AKT3 and NRAS, and non-coding RNA genes, miRNA 21 and miRNA 142. TRP32 target genes were differentially regulated during infection, the majority of which were repressed, and direct repression/activation of these genes by TRP32 was confirmed in vitro with a cellular luciferase reporter assay.

Positional distribution of transcription factor binding sites in Arabidopsis thaliana

Binding of a transcription factor (TF) to its DNA binding sites (TFBSs) is a critical step to initiate the transcription of its target genes. It is therefore interesting to know where the TFBSs of a gene are likely to locate in the promoter region. Here we studied the positional distribution of TFBSs in Arabidopsis thaliana, for which many known TFBSs are now available. We developed a method to identify the locations of TFBSs in the promoter sequences of genes in A. thaliana. We found that the distribution is nearly bell-shaped with a peak at 50 base pairs (bp) upstream of the transcription start site (TSS) and 86% of the TFBSs are in the region from -1,000 bp to +200 bp with respect to the TSS. Our distribution was supported by chromatin immunoprecipitation sequencing and microarray data and DNase I hypersensitive site sequencing data. When TF families were considered separately, differences in positional preference were observed between TF families. Our study of the positional distribution of TFBSs seems to be the first in a plant.

The oncogenic transcription factor c-Jun regulates glutaminase expression and sensitizes cells to glutaminase-targeted therapy

Many transformed cells exhibit altered glucose metabolism and increased utilization of glutamine for anabolic and bioenergetic processes. These metabolic adaptations, which accompany tumorigenesis, are driven by oncogenic signals. Here we report that the transcription factor c-Jun, product of the proto-oncogene JUN, is a key regulator of mitochondrial glutaminase (GLS) levels. Activation of c-Jun downstream of oncogenic Rho GTPase signalling leads to elevated GLS gene expression and glutaminase activity. In human breast cancer cells, GLS protein levels and sensitivity to GLS inhibition correlate strongly with c-Jun levels. We show that c-Jun directly binds to the GLS promoter region, and is sufficient to increase gene expression. Furthermore, ectopic overexpression of c-Jun renders breast cancer cells dependent on GLS activity. These findings reveal a role for c-Jun as a driver of cancer cell metabolic reprogramming, and suggest that cancers overexpressing JUN may be especially sensitive to GLS-targeted therapies.

Cancer cells have previously been shown to be addicted to glutamine and glutaminase enzyme activity. Here, the authors show that overexpression of the JUN proto-oncogene in breast cancer cells regulates glutaminase expression and is sufficient to confer sensitivity to glutaminase-targeted therapy.

The FOXO1 Transcription Factor Instructs the Germinal Center Dark Zone Program

The pathways regulating formation of the germinal center (GC) dark zone (DZ) and light zone (LZ) are unknown. In this study we show that FOXO1 transcription factor expression was restricted to the GC DZ and was required for DZ formation, since its absence in mice led to the loss of DZ gene programs and the formation of LZ-only GCs. FOXO1-negative GC B cells displayed normal somatic hypermutation but defective affinity maturation and class switch recombination. The function of FOXO1 in sustaining the DZ program involved the trans-activation of the chemokine receptor CXCR4, and cooperation with the BCL6 transcription factor in the trans-repression of genes involved in immune activation, DNA repair, and plasma cell differentiation. These results also have implications for the role of FOXO1 in lymphomagenesis because they suggest that constitutive FOXO1 activity might be required for the oncogenic activity of deregulated BCL6 expression.

DNA entropy reveals a significant difference in complexity between housekeeping and tissue specific gene promoters

BACKGROUND

The complexity of DNA can be quantified using estimates of entropy. Variation in DNA complexity is expected between the promoters of genes with different transcriptional mechanisms; namely housekeeping (HK) and tissue specific (TS). The former are transcribed constitutively to maintain general cellular functions, and the latter are transcribed in restricted tissue and cells types for specific molecular events. It is known that promoter features in the human genome are related to tissue specificity, but this has been difficult to quantify on a genomic scale. If entropy effectively quantifies DNA complexity, calculating the entropies of HK and TS gene promoters as profiles may reveal significant differences.

RESULTS

Entropy profiles were calculated for a total dataset of 12,003 human gene promoters and for 501 housekeeping (HK) and 587 tissue specific (TS) human gene promoters. The mean profiles show the TS promoters have a significantly lower entropy (p<2.2e-16) than HK gene promoters. The entropy distributions for the 3 datasets show that promoter entropies could be used to identify novel HK genes.

CONCLUSION

Functional features comprise DNA sequence patterns that are non-random and hence they have lower entropies. The lower entropy of TS gene promoters can be explained by a higher density of positive and negative regulatory elements, required for genes with complex spatial and temporary expression.

Conserved and divergent patterns of DNA methylation in higher vertebrates

DNA methylation in the genome plays a fundamental role in the regulation of gene expression and is widespread in the genome of eukaryotic species. For example, in higher vertebrates, there is a "global" methylation pattern involving complete methylation of CpG sites genome-wide, except in promoter regions that are typically enriched for CpG dinucleotides, or so called "CpG islands." Here, we comprehensively examined and compared the distribution of CpG sites within ten model eukaryotic species and linked the observed patterns to the role of DNA methylation in controlling gene transcription. The analysis revealed two distinct but conserved methylation patterns for gene promoters in human and mouse genomes, involving genes with distinct distributions of promoter CpGs and gene expression patterns. Comparative analysis with four other higher vertebrates revealed that the primary regulatory role of the DNA methylation system is highly conserved in higher vertebrates.

Functional annotation of colon cancer risk SNPs

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in the United States. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased risk for CRC. A molecular understanding of the functional consequences of this genetic variation has been complicated because each GWAS SNP is a surrogate for hundreds of other SNPs, most of which are located in non-coding regions. Here we use genomic and epigenomic information to test the hypothesis that the GWAS SNPs and/or correlated SNPs are in elements that regulate gene expression, and identify 23 promoters and 28 enhancers. Using gene expression data from normal and tumour cells, we identify 66 putative target genes of the risk-associated enhancers (10 of which were also identified by promoter SNPs). Employing CRISPR nucleases, we delete one risk-associated enhancer and identify genes showing altered expression. We suggest that similar studies be performed to characterize all CRC risk-associated enhancers.

Previous studies identified genetic variants associated with colorectal cancer (CRC), but the functional consequences of these genetic risk factors remain poorly understood. Here, the authors report that CRC risk variants reside in promoters and enhancers and could increase colon cancer risk through gene expression regulation.

A virulent strain of deformed wing virus (DWV) of honeybees (Apis mellifera) prevails after Varroa destructor-mediated, or in vitro, transmission

The globally distributed ectoparasite Varroa destructor is a vector for viral pathogens of the Western honeybee (Apis mellifera), in particular the Iflavirus Deformed Wing Virus (DWV). In the absence of Varroa low levels DWV occur, generally causing asymptomatic infections. Conversely, Varroa-infested colonies show markedly elevated virus levels, increased overwintering colony losses, with impairment of pupal development and symptomatic workers. To determine whether changes in the virus population were due Varroa amplifying and introducing virulent virus strains and/or suppressing the host immune responses, we exposed Varroa-naïve larvae to oral and Varroa-transmitted DWV. We monitored virus levels and diversity in developing pupae and associated Varroa, the resulting RNAi response and transcriptome changes in the host. Exposed pupae were stratified by Varroa association (presence/absence) and virus levels (low/high) into three groups. Varroa-free pupae all exhibited low levels of a highly diverse DWV population, with those exposed per os (group NV) exhibiting changes in the population composition. Varroa-associated pupae exhibited either low levels of a diverse DWV population (group VL) or high levels of a near-clonal virulent variant of DWV (group VH). These groups and unexposed controls (C) could be also discriminated by principal component analysis of the transcriptome changes observed, which included several genes involved in development and the immune response. All Varroa tested contained a diverse replicating DWV population implying the virulent variant present in group VH, and predominating in RNA-seq analysis of temporally and geographically separate Varroa-infested colonies, was selected upon transmission from Varroa, a conclusion supported by direct injection of pupae in vitro with mixed virus populations. Identification of a virulent variant of DWV, the role of Varroa in its transmission and the resulting host transcriptome changes furthers our understanding of this important viral pathogen of honeybees.

Honeybees are the most important managed pollinating insect, contributing billions of dollars to annual global agricultural production. Over the last century a parasitic mite, Varroa, has spread worldwide, with significant impacts on honeybee colony health as a consequence of its transmission of a cocktail of viruses while feeding on honeybee ‘blood’. The most important virus for colony health is deformed wing virus (DWV), high levels of which cause developmental deformities and premature ageing resulting in high overwintering colony losses. In experiments on individual Varroa-exposed pupae we demonstrate that a single type of virulent DWV is amplified 1,000–10,000 times in the recipient pupae, despite the mite containing a high diversity of replicating DWV strains. We could recapitulate this by direct injection of pupae with mixed virus populations, showing the virulent strain is advantaged by the route of transmission. In parallel, we detected changes in the immune response and developmental gene expression of the honeybee and propose that these contribute to the characteristic pathogenesis of DWV. Identification of a virulent strain of DWV has implications for therapeutic or prophylactic interventions to improve honeybee colony health, as well as contributing to our understanding of the biology of this important honeybee viral pathogen.

Epigenetic heredity of human height

Genome‐wide SNP analyses have identified genomic variants associated with adult human height. However, these only explain a fraction of human height variation, suggesting that significant information might have been systematically missed by SNP sequencing analysis. A candidate for such non‐SNP‐linked information is DNA methylation. Regulation by DNA methylation requires the presence of CpG islands in the promoter region of candidate genes. Seventy two of 87 (82.8%), height‐associated genes were indeed found to contain CpG islands upstream of the transcription start site (USC CpG island searcher; validation: UCSC Genome Browser), which were shown to correlate with gene regulation. Consistent with this, DNA hypermethylation modules were detected in 42 height‐associated genes, versus 1.5% of control genes (P = 8.0199e⁻¹⁷), as were dynamic methylation changes and gene imprinting. Epigenetic heredity thus appears to be a determinant of adult human height. Major findings in mouse models and in human genetic diseases support this model. Modulation of DNA methylation are candidate to mediate environmental influence on epigenetic traits. This may help to explain progressive height changes over multiple generations, through trans‐generational heredity of progressive DNA methylation patterns.

Epigenetic heredity appears to be a determinant of adult human height. Major findings in mouse models and in human genetic diseases support this model. Modulation of DNA methylation is candidate to mediate environmental influence on epigenetic traits.

Overcoming NS1-mediated immune antagonism involves both interferon-dependent and independent mechanisms

To ensure survival, our immune system must overcome the action of pathogen-encoded immune antagonists, such as influenza A nonstructural protein-1 (NS1). NS1 subverts the host interferon (IFN) response at multiple levels and blocks the induction of IFN-β, a critical antiviral cytokine. This immune antagonism can be overcome in some cases. It has been shown that IFN-β is upregulated by 48 h in the lungs of wild-type C57BL/6 mice infected with influenza A. In contrast, it is shown here that IFNB1 continues to be repressed in IFNAR1(-/-) IL28Rα(-/-) mice, which are deficient in Type-I and III IFN signaling, implying induction of IFNB1 depends on effective IFN signaling. Despite the complete lack of IFN signaling in this system, some IFN stimulated genes (ISGs) were induced following infection with a Flu strain lacking NS1. While the expression of these viral stress-inducible genes (VSIGs) was initially repressed following infection with wild-type Flu, many of these genes became upregulated by 48 h postinfection. These results demonstrate the existence of IFN-independent mechanisms that can overcome NS1-mediated immune antagonism of VSIGs.

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection

Background

H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology.

Results

Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog.

Conclusions

We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections.

Hepatitis B viral core protein disrupts human host gene expression by binding to promoter regions

BACKGROUND

The core protein (HBc) of hepatitis B virus (HBV) has been implicated in the malignant transformation of chronically-infected hepatocytes and displays pleiotropic functions, including RNA- and DNA-binding activities. However, the mechanism by which HBc interacts with the human genome to exert effects on hepatocyte function remains unknown. This study investigated the distribution of HBc binding to promoters in the human genome and evaluated its effects on the related genes' expression.

RESULTS

Whole-genome chromatin immunoprecipitation microarray (ChIP-on-chip) analysis was used to identify HBc-bound human gene promoters. Gene Ontology and pathway analyses were performed on related genes. The quantitative polymerase chain reaction assay was used to verify ChIP-on-chip results. Five novel genes were selected for luciferase reporter assay evaluation to assess the influence of HBc promoter binding. The HBc antibody immunoprecipitated approximately 3100 human gene promoters. Among these, 1993 are associated with known biological processes, and 2208 regulate genes with defined molecular functions. In total, 1286 of the related genes mediate primary metabolic processes, and 1398 encode proteins with binding activity. Sixty-four of the promoters regulate genes related to the mitogen-activated protein kinase (MAPK) pathways, and 41 regulate Wnt/beta-catenin pathway genes. The reporter gene assay indicated that HBc binding up-regulates proto-oncogene tyrosine-protein kinase (SRC), type 1 insulin-like growth factor receptor (IGF1R), and neurotrophic tyrosine kinase receptor 2 (NTRK2), and down-regulates v-Ha-ras Harvey rat sarcoma viral oncogene (HRAS).

CONCLUSION

HBc has the ability to bind a large number of human gene promoters, and can disrupt normal host gene expression. Manipulation of the transcriptional profile in HBV-infected hepatocytes may represent a key pathogenic mechanism of HBV infection.

Toward the identification and regulation of the Arabidopsis thaliana ABI3 regulon

The plant-specific, B3 domain-containing transcription factor ABSCISIC ACID INSENSITIVE3 (ABI3) is an essential component of the regulatory network controlling the development and maturation of the Arabidopsis thaliana seed. Genome-wide chromatin immunoprecipitation (ChIP-chip), transcriptome analysis, quantitative reverse transcriptase–polymerase chain reaction and a transient promoter activation assay have been combined to identify a set of 98 ABI3 target genes. Most of these presumptive ABI3 targets require the presence of abscisic acid for their activation and are specifically expressed during seed maturation. ABI3 target promoters are enriched for G-box-like and RY-like elements. The general occurrence of these cis motifs in non-ABI3 target promoters suggests the existence of as yet unidentified regulatory signals, some of which may be associated with epigenetic control. Several members of the ABI3 regulon are also regulated by other transcription factors, including the seed-specific, B3 domain-containing FUS3 and LEC2. The data strengthen and extend the notion that ABI3 is essential for the protection of embryonic structures from desiccation and raise pertinent questions regarding the specificity of promoter recognition.

Engineering synthetic TAL effectors with orthogonal target sites

The ability to engineer biological circuits that process and respond to complex cellular signals has the potential to impact many areas of biology and medicine. Transcriptional activator-like effectors (TALEs) have emerged as an attractive component for engineering these circuits, as TALEs can be designed de novo to target a given DNA sequence. Currently, however, the use of TALEs is limited by degeneracy in the site-specific manner by which they recognize DNA. Here, we propose an algorithm to computationally address this problem. We apply our algorithm to design 180 TALEs targeting 20 bp cognate binding sites that are at least 3 nt mismatches away from all 20 bp sequences in putative 2 kb human promoter regions. We generated eight of these synthetic TALE activators and showed that each is able to activate transcription from a targeted reporter. Importantly, we show that these proteins do not activate synthetic reporters containing mismatches similar to those present in the genome nor a set of endogenous genes predicted to be the most likely targets in vivo. Finally, we generated and characterized TALE repressors comprised of our orthogonal DNA binding domains and further combined them with shRNAs to accomplish near complete repression of target gene expression.

Enhancers regulate progression of development in mammalian cells

During development and differentiation of an organism, accurate gene regulation is central for cells to maintain and balance their differentiation processes. Transcriptional interactions between cis-acting DNA elements such as promoters and enhancers are the basis for precise and balanced transcriptional regulation. We identified modules of combinations of binding sites in proximal and distal regulatory regions upstream of all transcription start sites (TSSs) in silico and applied these modules to gene expression time-series of mouse embryonic development and differentiation of human stem cells. In addition to tissue-specific regulation controlled by combinations of transcription factors (TFs) binding at promoters, we observed that in particular the combination of TFs binding at promoters together with TFs binding at the respective enhancers regulate highly specifically temporal progression during development: whereas 40% of TFs were specific for time intervals, 79% of TF pairs and even 97% of promoter-enhancer modules showed specificity for single time intervals of the human stem cells. Predominantly SP1 and E2F contributed to temporal specificity at promoters and the forkhead (FOX) family of TFs at enhancer regions. Altogether, we characterized three classes of TFs: with binding sites being enriched at the TSS (like SP1), depleted at the TSS (like FOX), and rather uniformly distributed.

Identification of novel targets of CSL-dependent Notch signaling in hematopoiesis

Somatic activating mutations in the Notch1 receptor result in the overexpression of activated Notch1, which can be tumorigenic. The goal of this study is to understand the molecular mechanisms underlying the phenotypic changes caused by the overexpression of ligand independent Notch 1 by using a tetracycline inducible promoter in an in vitro embryonic stem (ES) cells/OP9 stromal cells coculture system, recapitulating normal hematopoiesis. First, an in silico analysis of the promoters of Notch regulated genes (previously determined by microarray analysis) revealed that the motifs recognized by regulatory proteins known to mediate hematopoiesis were overrepresented. Notch 1 does not bind DNA but instead binds the CSL transcription factor to regulate gene expression. The in silico analysis also showed that there were putative CSL binding sites observed in the promoters of 28 out of 148 genes. A custom ChIP-chip array was used to assess the occupancy of CSL in the promoter regions of the Notch1 regulated genes in vivo and showed that 61 genes were bound by activated Notch responsive CSL. Then, comprehensive mapping of the CSL binding sites genome-wide using ChIP-seq analysis revealed that over 10,000 genes were bound within 10 kb of the TSS (transcription start site). The majority of the targets discovered by ChIP-seq belong to pathways that have been shown by others to crosstalk with Notch signaling. Finally, 83 miRNAs were significantly differentially expressed by greater than 1.5-fold during the course of in vitro hematopoiesis. Thirty one miRNA were up-regulated and fifty two were down-regulated. Overexpression of Notch1 altered this pattern of expression of microRNA: six miRNAs were up-regulated and four were down regulated as a result of activated Notch1 overexpression during the course of hematopoiesis. Time course analysis of hematopoietic development revealed that cells with Notch 1 overexpression mimic miRNA expression of cells in a less mature stage, which is consistent with our previous biological characterization.

Predicting promoter activities of primary human DNA sequences

We developed a computer program that can predict the intrinsic promoter activities of primary human DNA sequences. We observed promoter activity using a quantitative luciferase assay and generated a prediction model using multiple linear regression. Our program achieved a prediction accuracy correlation coefficient of 0.87 between the predicted and observed promoter activities. We evaluated the prediction accuracy of the program using massive sequencing analysis of transcriptional start sites in vivo. We found that it is still difficult to predict transcript levels in a strictly quantitative manner in vivo; however, it was possible to select active promoters in a given cell from the other silent promoters. Using this program, we analyzed the transcriptional landscape of the entire human genome. We demonstrate that many human genomic regions have potential promoter activity, and the expression of some previously uncharacterized putatively non-protein-coding transcripts can be explained by our prediction model. Furthermore, we found that nucleosomes occasionally formed open chromatin structures with RNA polymerase II recruitment where the program predicted significant promoter activities, although no transcripts were observed.

Human transcription factor genes involved in neuronal development tend to have high GC content and CpG elements in the proximal promoter region

Transcription factors (TFs) play critical roles in the development of the nervous system, but the transcriptional regulatory mechanisms of these genes are poorly understood. Here we analyzed 5-kb of the 5' flanking genomic DNA sequences of 41 TF genes involved in neuronal development. The results showed that the TF genes tend to have higher GC contents in the proximal region and most of the TF genes have at least one proximal GC-rich (GC content > 60%) promoter with a CpG island. The promoter distribution analysis showed that the GC-poor promoters were sporadically distributed within the 5-kb flanking genomic sequence (FGS); however, more than half (37 of 70) of the GC-rich promoters were located in the proximal region between nucleotides -1 and -500. Luciferase assays showed that partial GC-rich promoters increased gene expression in SH-SY5Y cells and that CpG methylation repressed the promoter activity. This study suggests a potential general mechanism for regulation of TF expression.

Effect of the rs2259816 polymorphism in the HNF1A gene on circulating levels of c-reactive protein and coronary artery disease (the ludwigshafen risk and cardiovascular health study)

Background

C-reactive protein is a well established marker of inflammation and has been used to predict future cardiovascular disease. It is still controversial if it plays an active role in the development of cardiovascular disease. Recently, polymorphisms in the gene for HNF1α have been linked to the levels of C-reactive protein and coronary artery disease.

Methods

We investigated the association of the rs2259816 polymorphism in the HNF1A gene with the circulating level of C-reactive protein and the hazard of coronary artery disease in the LURIC Study cohort.

Results

Compared to CC homozygotes, the level of C-reactive protein was decreased in carriers of at least one A-allele. Each A-allele decreased CRP by approximately 15%. The odds ratio for coronary artery disease was only very slightly increased in carriers of the A-allele and this association did not reach statistical significance.

Conclusions

In the LURIC Study cohort the A-allele of rs2259816 is associated with decreased CRP but not with coronary artery disease.

Gene promoter evolution targets the center of the human protein interaction network

Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom⁺ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod⁺ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom⁺ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom⁺ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.

A quantitative model of transcriptional regulation reveals the influence of binding location on expression

Understanding the mechanistic basis of transcriptional regulation has been a central focus of molecular biology since its inception. New high-throughput chromatin immunoprecipitation experiments have revealed that most regulatory proteins bind thousands of sites in mammalian genomes. However, the functional significance of these binding sites remains unclear. We present a quantitative model of transcriptional regulation that suggests the contribution of each binding site to tissue-specific gene expression depends strongly on its position relative to the transcription start site. For three cell types, we show that, by considering binding position, it is possible to predict relative expression levels between cell types with an accuracy approaching the level of agreement between different experimental platforms. Our model suggests that, for the transcription factors profiled in these cell types, a regulatory site's influence on expression falls off almost linearly with distance from the transcription start site in a 10 kilobase range. Binding to both evolutionarily conserved and non-conserved sequences contributes significantly to transcriptional regulation. Our approach also reveals the quantitative, tissue-specific role of individual proteins in activating or repressing transcription. These results suggest that regulator binding position plays a previously unappreciated role in influencing expression and blurs the classical distinction between proximal promoter and distal binding events.

Gene expression is controlled, in large part, by regulatory proteins called transcription factors that bind specific sites in the genome. A major focus of molecular biology has been understanding how these transcription factors interact with the cell's transcriptional machinery, the genome, and with each other to turn genes' expression on and off in various physiological contexts. Previous approaches for modeling transcriptional regulation have focused on the complex combinatorial interactions between groups of transcription factors at regulatory sites, or on the specific activating or repressive functions of individual proteins. In this work, we present a new modeling framework and demonstrate that an equally important, and previously overlooked, consideration in predicting the effect that a regulatory site has on gene expression is simply its location relative to the transcription start site of nearby genes. Our results show that, in general, the closer a binding event is to a gene's transcription start site, the more it influences expression. We also show that considering the particular proteins bound at a regulatory site helps predict the expression of nearby genes. However, considering the sequence conservation level of these sites does not lead to more accurate predictions.

Localized motif discovery in gene regulatory sequences

MOTIVATION

Discovery of nucleotide motifs that are localized with respect to a certain biological landmark is important in several appli-cations, such as in regulatory sequences flanking the transcription start site, in the neighborhood of known transcription factor binding sites, and in transcription factor binding regions discovered by massively parallel sequencing (ChIP-Seq).

RESULTS

We report an algorithm called LocalMotif to discover such localized motifs. The algorithm is based on a novel scoring function, called spatial confinement score, which can determine the exact interval of localization of a motif. This score is combined with other existing scoring measures including over-representation and relative entropy to determine the overall prominence of the motif. The approach successfully discovers biologically relevant motifs and their intervals of localization in scenarios where the motifs cannot be discovered by general motif finding tools. It is especially useful for discovering multiple co-localized motifs in a set of regulatory sequences, such as those identified by ChIP-Seq.

AVAILABILITY AND IMPLEMENTATION

The LocalMotif software is available at http://www.comp.nus.edu.sg/~bioinfo/LocalMotif.