DNase I-hypersensitive exons colocalize with promoters and distal regulatory elements

Tissue-specific chromatin accessibility and transcriptional regulation in maize cold stress response

Maize, a vital crop globally, faces significant yield losses due to its sensitivity to cold stress, especially in temperate regions. Understanding the molecular mechanisms governing maize response to cold stress is crucial for developing strategies to enhance cold tolerance. However, the precise chromatin-level regulatory mechanisms involved remain largely unknown. In this study, we employed DNase-seq and RNA-seq techniques to investigate chromatin accessibility and gene expression changes in maize root, stem, and leaf tissues subjected to cold treatment. We discovered widespread changes in chromatin accessibility and gene expression across these tissues, with strong tissue specificity. Cold stress-induced DNase I hypersensitive sites (coiDHSs) were associated with differentially expressed genes, suggesting a direct link between chromatin accessibility and gene regulation under cold stress. Motif enrichment analysis identified ERF transcription factors (TFs) as central regulators conserved across tissues, with ERF5 emerging as pivotal in the cold response regulatory network. Additionally, TF co-localization analysis highlighted six TF pairs (ERF115-SHN3, ERF9-LEP, ERF7-SHN3, LEP-SHN3, LOB-SHN3, and AS2-LOB) conserved across tissues but showing tissue-specific binding preferences. These findings indicate intricate regulatory networks in maize cold response. Overall, our study provides insights into the chromatin-level regulatory mechanisms underpinning maize adaptive response to cold stress, offering potential targets for enhancing cold tolerance in agricultural contexts.

Predicting splicing patterns from the transcription factor binding sites in the promoter with deep learning

BACKGROUND

Alternative splicing is a pivotal mechanism of post-transcriptional modification that contributes to the transcriptome plasticity and proteome diversity in metazoan cells. Although many splicing regulations around the exon/intron regions are known, the relationship between promoter-bound transcription factors and the downstream alternative splicing largely remains unexplored.

RESULTS

In this study, we present computational approaches to unravel the regulatory relationship between promoter-bound transcription factor binding sites (TFBSs) and the splicing patterns. We curated a fine dataset that includes DNase I hypersensitive site sequencing and transcriptomes across fifteen human tissues from ENCODE. Specifically, we proposed different representations of TF binding context and splicing patterns to examine the associations between the promoter and downstream splicing events. While machine learning models demonstrated potential in predicting splicing patterns based on TFBS occupancies, the limitations in the generalization of predicting the splicing forms of singleton genes across diverse tissues was observed with carefully examination using different cross-validation methods. We further investigated the association between alterations in individual TFBS at promoters and shifts in exon splicing efficiency. Our results demonstrate that the convolutional neural network (CNN) models, trained on TF binding changes in the promoters, can predict the changes in splicing patterns. Furthermore, a systemic in silico substitutions analysis on the CNN models highlighted several potential splicing regulators. Notably, using empirical validation using K562 CTCFL shRNA knock-down data, we showed the significant role of CTCFL in splicing regulation.

CONCLUSION

In conclusion, our finding highlights the potential role of promoter-bound TFBSs in influencing the regulation of downstream splicing patterns and provides insights for discovering alternative splicing regulations.

DNA-binding factor footprints and enhancer RNAs identify functional non-coding genetic variants

BACKGROUND

Genome-wide association studies (GWAS) have revealed a multitude of candidate genetic variants affecting the risk of developing complex traits and diseases. However, the highlighted regions are typically in the non-coding genome, and uncovering the functional causative single nucleotide variants (SNVs) is challenging. Prioritization of variants is commonly based on genomic annotation with markers of active regulatory elements, but current approaches still poorly predict functional variants. To address this, we systematically analyze six markers of active regulatory elements for their ability to identify functional variants.

RESULTS

We benchmark against molecular quantitative trait loci (molQTL) from assays of regulatory element activity that identify allelic effects on DNA-binding factor occupancy, reporter assay expression, and chromatin accessibility. We identify the combination of DNase footprints and divergent enhancer RNA (eRNA) as markers for functional variants. This signature provides high precision, but with a trade-off of low recall, thus substantially reducing candidate variant sets to prioritize variants for functional validation. We present this as a framework called FINDER-Functional SNV IdeNtification using DNase footprints and eRNA.

CONCLUSIONS

We demonstrate the utility to prioritize variants using leukocyte count trait and analyze variants in linkage disequilibrium with a lead variant to predict a functional variant in asthma. Our findings have implications for prioritizing variants from GWAS, in development of predictive scoring algorithms, and for functionally informed fine mapping approaches.

Gene-to-gene coordinated regulation of transcription and alternative splicing by 3D chromatin remodeling upon NF-κB activation

The NF-κB protein p65/RelA plays a pivotal role in coordinating gene expression in response to diverse stimuli, including viral infections. At the chromatin level, p65/RelA regulates gene transcription and alternative splicing through promoter enrichment and genomic exon occupancy, respectively. The intricate ways in which p65/RelA simultaneously governs these functions across various genes remain to be fully elucidated. In this study, we employed the HTLV-1 Tax oncoprotein, a potent activator of NF-κB, to investigate its influence on the three-dimensional organization of the genome, a key factor in gene regulation. We discovered that Tax restructures the 3D genomic landscape, bringing together genes based on their regulation and splicing patterns. Notably, we found that the Tax-induced gene-gene contact between the two master genes NFKBIA and RELA is associated with their respective changes in gene expression and alternative splicing. Through dCas9-mediated approaches, we demonstrated that NFKBIA-RELA interaction is required for alternative splicing regulation and is caused by an intragenic enrichment of p65/RelA on RELA. Our findings shed light on new regulatory mechanisms upon HTLV-1 Tax and underscore the integral role of p65/RelA in coordinated regulation of NF-κB-responsive genes at both transcriptional and splicing levels in the context of the 3D genome.

Evidence for the role of transcription factors in the co-transcriptional regulation of intron retention

BACKGROUND

Alternative splicing is a widespread regulatory phenomenon that enables a single gene to produce multiple transcripts. Among the different types of alternative splicing, intron retention is one of the least explored despite its high prevalence in both plants and animals. The recent discovery that the majority of splicing is co-transcriptional has led to the finding that chromatin state affects alternative splicing. Therefore, it is plausible that transcription factors can regulate splicing outcomes.

RESULTS

We provide evidence for the hypothesis that transcription factors are involved in the regulation of intron retention by studying regions of open chromatin in retained and excised introns. Using deep learning models designed to distinguish between regions of open chromatin in retained introns and non-retained introns, we identified motifs enriched in IR events with significant hits to known human transcription factors. Our model predicts that the majority of transcription factors that affect intron retention come from the zinc finger family. We demonstrate the validity of these predictions using ChIP-seq data for multiple zinc finger transcription factors and find strong over-representation for their peaks in intron retention events.

CONCLUSIONS

This work opens up opportunities for further studies that elucidate the mechanisms by which transcription factors affect intron retention and other forms of splicing.

AVAILABILITY

Source code available at https://github.com/fahadahaf/chromir.

Genome-Wide Study of Colocalization between Genomic Stretches: A Method and Applications to the Regulation of Gene Expression

In this paper, we describe a method for the study of colocalization effects between stretch-stretch and stretch-point genome tracks based on a set of indices varying within the (-1, +1) interval. The indices combine the distances between the centers of neighboring stretches and their lengths. The extreme boundaries of the interval correspond to the complete colocalization of the genome tracks or its complete absence. We also obtained the relevant criteria of statistical significance for such indices using the complete permutation test. The method is robust with respect to strongly inhomogeneous positioning and length distribution of the genome tracks. On the basis of this approach, we created command-line software, the Genome Track Colocalization Analyzer. The software was tested, compared with other available packages, and applied to particular problems related to gene expression. The package, Genome Track Colocalization Analyzer (GTCA), is freely available to the users. GTCA complements our previous software, the Genome Track Analyzer, intended for the search for pairwise correlations between point-like genome tracks (also freely available). The corresponding details are provided in Data Availability Statement at the end of the text.

RNA helicase-dependent gene looping impacts messenger RNA processing

DDX5 and DDX17 are DEAD-box RNA helicase paralogs which regulate several aspects of gene expression, especially transcription and splicing, through incompletely understood mechanisms. A transcriptome analysis of DDX5/DDX17-depleted human cells confirmed the large impact of these RNA helicases on splicing and revealed a widespread deregulation of 3' end processing. In silico analyses and experiments in cultured cells showed the binding and functional contribution of the genome organizing factor CTCF to chromatin sites at or near a subset of DDX5/DDX17-dependent exons that are characterized by a high GC content and a high density of RNA Polymerase II. We propose the existence of an RNA helicase-dependent relationship between CTCF and the dynamics of transcription across DNA and/or RNA structured regions, that contributes to the processing of internal and terminal exons. Moreover, local DDX5/DDX17-dependent chromatin loops spatially connect RNA helicase-regulated exons with their cognate promoter, and we provide the first direct evidence that de novo gene looping modifies alternative splicing and polyadenylation. Overall our findings uncover the impact of DDX5/DDX17-dependent chromatin folding on pre-messenger RNA processing.

Somatic point mutations are enriched in non-coding RNAs with possible regulatory function in breast cancer

Non-coding RNAs (ncRNAs) form a large portion of the mammalian genome. However, their biological functions are poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we analyze de novo somatic point mutations from the International Cancer Genome Consortium (ICGC) whole-genome sequencing data of 1,855 breast cancer samples. We identify 1030 candidates of ncRNAs that are significantly and explicitly mutated in breast cancer samples. By integrating data from the ENCODE regulatory features and FANTOM5 expression atlas, we show that the candidate ncRNAs significantly enrich active chromatin histone marks (1.9 times), CTCF binding sites (2.45 times), DNase accessibility (1.76 times), HMM predicted enhancers (2.26 times) and eQTL polymorphisms (1.77 times). Importantly, we show that the 1030 ncRNAs contain a much higher level (3.64 times) of breast cancer-associated genome-wide association (GWAS) single nucleotide polymorphisms (SNPs) than genome-wide expectation. Such enrichment has not been seen with GWAS SNPs from other cancers. Using breast cell line related Hi-C data, we then show that 82% of our candidate ncRNAs (1.9 times) significantly interact with the promoter of protein-coding genes, including previously known cancer-associated genes, suggesting the critical role of candidate ncRNA genes in the activation of essential regulators of development and differentiation in breast cancer. We provide an extensive web-based resource (https://www.ihealthe.unsw.edu.au/research) to communicate our results with the research community. Our list of breast cancer-specific ncRNA genes has the potential to provide a better understanding of the underlying genetic causes of breast cancer. Lastly, the tool developed in this study can be used to analyze somatic mutations in all cancers.

The SomaGene tool is developed to identify non-coding RNAs (ncRNAs) mutated in breast cancer but can be used for other cancers. Candidate ncRNAs are shown to be enriched for regulatory features and to contain specific trait loci polymorphisms.

High frequency of intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs

BACKGROUND

It is established that protein-coding exons are preferentially localized in nucleosomes. To examine whether the same is true for non-coding exons, we analysed nucleosome occupancy in and adjacent to internal exons in genes encoding long non-coding RNAs (lncRNAs) in human CD4+ T cells and K562 cells.

RESULTS

We confirmed that internal exons in lncRNAs are preferentially associated with nucleosomes, but also observed an elevated signal from H3K4me3-marked nucleosomes in the sequences upstream of these exons. Examination of 200 genomic lncRNA loci chosen at random across all chromosomes showed that high-density regions of H3K4me3-marked nucleosomes, which we term 'slabs', are associated with genomic regions exhibiting intron retention. These retained introns occur in over 50% of lncRNAs examined and are mostly first introns with an average length of just 354 bp, compared to the average length of all human introns of 6355 and 7987 bp in mRNAs and lncRNAs, respectively. Removal of short introns from the dataset abrogated the high upstream H3K4me3 signal, confirming that the association of slabs and short lncRNA introns with intron retention holds genome-wide. The high upstream H3K4me3 signal is also associated with alternatively spliced exons, known to be prominent in lncRNAs. This phenomenon was not observed with mRNAs.

CONCLUSIONS

There is widespread intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs, which raises intriguing questions about the relationship of IR to lncRNA function and chromatin organization.

A cleavage-based surrogate reporter for the evaluation of CRISPR-Cas9 cleavage efficiency

CRISPR-Cas9 is a powerful tool for genome engineering, but its efficiency largely depends on guide RNA (gRNA). There are multiple methods available to evaluate the efficiency of gRNAs, including the T7E1 assay, surveyor nuclease assay, deep sequencing, and surrogate reporter systems. In the present study, we developed a cleavage-based surrogate that we have named the LacI-reporter to evaluate gRNA cleavage efficiency. The LacI repressor, under the control of the EF-1α promoter, represses luciferase or EGFP reporter expression by binding to the lac operator. Upon CRISPR-Cas9 cleavage at a target site located between the EF-1α promoter and the lacI gene, repressor expression is disrupted, thereby triggering luciferase or EGFP expression. Using this system, we can quantitate gRNA cleavage efficiency by assessing luciferase activity or EGFP expression. We found a strong positive correlation between the cleavage efficiency of gRNAs measured using this reporter and mutation frequency, measured using surveyor and deep sequencing. The genome-editing efficiency of gRNAs was validated in human liver organoids. Our LacI-reporter system provides a useful tool to select efficient gRNAs for genome editing.

Construction and characterization of EGFP reporter plasmid harboring putative human RAX promoter for in vitro monitoring of retinal progenitor cells identity

BACKGROUND

In retinal degenerative disease, progressive and debilitating conditions result in deterioration of retinal cells and visual loss. In human, retina lacks the inherent capacity for regeneration. Therefore, regeneration of retinal layer from human retinal progenitor cells (hRPCs) is a challenging task and restricted in vitro maintenance of hRPCs remains as the main hurdle. Retina and anterior neural fold homeobox gene (RAX) play critical roles in developing retina and maintenance of hRPCs. In this study, for the first time regulatory regions of human RAX gene with potential promoter activity were experimentally investigated.

RESULTS

For this purpose, after in silico analysis of regulatory regions of human RAX gene, the expression of EGFP reporter derived by putative promoter sequences was first evaluated in 293 T cells and then in hRPCS derived from human embryonic stem cells. The candidate region (RAX-3258 bp) showed the highest EGFP expression in hRPCs. This reporter construct can be used for in vitro monitoring of hRPC identity and verification of an efficient culture medium for maintenance of these cells.

CONCLUSIONS

Furthermore, our findings provide a platform for better insight into regulatory regions of human RAX gene and molecular mechanisms underlying its vital functions in retina development.

Chromatin loop anchors predict transcript and exon usage

Epigenomics and transcriptomics data from high-throughput sequencing techniques such as RNA-seq and ChIP-seq have been successfully applied in predicting gene transcript expression. However, the locations of chromatin loops in the genome identified by techniques such as Chromatin Interaction Analysis with Paired End Tag sequencing (ChIA-PET) have never been used for prediction tasks. Here, we developed machine learning models to investigate if ChIA-PET could contribute to transcript and exon usage prediction. In doing so, we used a large set of transcription factors as well as ChIA-PET data. We developed different Gradient Boosting Trees models according to the different tasks with the integrated datasets from three cell lines, including GM12878, HeLaS3 and K562. We validated the models via 10-fold cross validation, chromosome-split validation and cross-cell validation. Our results show that both transcript and splicing-derived exon usage can be effectively predicted with at least 0.7512 and 0.7459 of accuracy, respectively, on all cell lines from all kinds of validations. Examining the predictive features, we found that RNA Polymerase II ChIA-PET was one of the most important features in both transcript and exon usage prediction, suggesting that chromatin loop anchors are predictive of both transcript and exon usage.

Gene Architecture Facilitates Intron-Mediated Enhancement of Transcription

Introns impact several vital aspects of eukaryotic organisms like proteomic plasticity, genomic stability, stress response and gene expression. A role for introns in the regulation of gene expression at the level of transcription has been known for more than thirty years. The molecular basis underlying the phenomenon, however, is still not entirely clear. An important clue came from studies performed in budding yeast that indicate that the presence of an intron within a gene results in formation of a multi-looped gene architecture. When looping is defective, these interactions are abolished, and there is no enhancement of transcription despite normal splicing. In this review, we highlight several potential mechanisms through which looping interactions may enhance transcription. The promoter-5′ splice site interaction can facilitate initiation of transcription, the terminator-3′ splice site interaction can enable efficient termination of transcription, while the promoter-terminator interaction can enhance promoter directionality and expedite reinitiation of transcription. Like yeast, mammalian genes also exhibit an intragenic interaction of the promoter with the gene body, especially exons. Such promoter-exon interactions may be responsible for splicing-dependent transcriptional regulation. Thus, the splicing-facilitated changes in gene architecture may play a critical role in regulation of transcription in yeast as well as in higher eukaryotes.

Role of promoters in regulating alternative splicing

Alternative splicing (AS) plays a critical role in enhancing proteome complexity in higher eukaryotes. Almost all the multi intron-containing genes undergo AS in humans. Splicing mainly occurs co-transcriptionally, where RNA polymerase II (RNA pol II) plays a crucial role in coordinating transcription and pre-mRNA splicing. Aberrant AS leads to non-functional proteins causative in various pathophysiological conditions such as cancers, neurodegenerative diseases, and muscular dystrophies. Transcription and pre-mRNA splicing are deeply interconnected and can influence each other's functions. Several studies evinced that specific promoters employed by RNA pol II dictate the RNA processing decisions. Promoter-specific recruitment of certain transcriptional factors or transcriptional coactivators influences splicing, and the extent to which these factors affect splicing has not been discussed in detail. Here, in this review, various DNA-binding proteins and their influence on promoter-specific AS are extensively discussed. Besides, this review highlights how the promoter-specific epigenetic changes might regulate AS.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Modeling circRNA expression pattern with integrated sequence and epigenetic features demonstrates the potential involvement of H3K79me2 in circRNA expression

MOTIVATION

CircRNAs are an abundant class of non-coding RNAs with widespread, cell-/tissue-specific patterns. Previous work suggested that epigenetic features might be related to circRNA expression. However, the contribution of epigenetic changes to circRNA expression has not been investigated systematically. Here, we built a machine learning framework named CIRCScan, to predict circRNA expression in various cell lines based on the sequence and epigenetic features.

RESULTS

The predicted accuracy of the expression status models was high with area under the curve of receiver operating characteristic (ROC) values of 0.89-0.92 and the false-positive rates of 0.17-0.25. Predicted expressed circRNAs were further validated by RNA-seq data. The performance of expression-level prediction models was also good with normalized root-mean-square errors of 0.28-0.30 and Pearson's correlation coefficient r over 0.4 in all cell lines, along with Spearman's correlation coefficient ρ of 0.33-0.46. Noteworthy, H3K79me2 was highly ranked in modeling both circRNA expression status and levels across different cells. Further analysis in additional nine cell lines demonstrated a significant enrichment of H3K79me2 in circRNA flanking intron regions, supporting the potential involvement of H3K79me2 in circRNA expression regulation.

AVAILABILITY AND IMPLEMENTATION

The CIRCScan assembler is freely available online for academic use at https://github.com/johnlcd/CIRCScan.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses

As a key variance partitioning tool, linear mixed models (LMMs) using genome-based restricted maximum likelihood (GREML) allow both fixed and random effects. Classic LMMs assume independence between random effects, which can be violated, causing bias. Here we introduce a generalized GREML, named CORE GREML, that explicitly estimates the covariance between random effects. Using extensive simulations, we show that CORE GREML outperforms the conventional GREML, providing variance and covariance estimates free from bias due to correlated random effects. Applying CORE GREML to UK Biobank data, we find, for example, that the transcriptome, imputed using genotype data, explains a significant proportion of phenotypic variance for height (0.15, p-value = 1.5e-283), and that these transcriptomic effects correlate with the genomic effects (genome-transcriptome correlation = 0.35, p-value = 1.2e-14). We conclude that the covariance between random effects is a key parameter for estimation, especially when partitioning phenotypic variance by multi-omics layers.

Linear mixed models have bias due to the assumed independence between random effects. Here, the authors describe a genome-based restricted maximum likelihood, CORE GREML, which estimates covariance between random effects. Application to UK Biobank data highlights this as an important parameter for multi-omics analyses of phenotypic variance.

Alternative Enhancer Usage and Targeted Polycomb Marking Hallmark Promoter Choice during T Cell Differentiation

During thymic development and upon peripheral activation, T cells undergo extensive phenotypic and functional changes coordinated by lineage-specific developmental programs. To characterize the regulatory landscape controlling T cell identity, we perform a wide epigenomic and transcriptional analysis of mouse thymocytes and naive CD4 differentiated T helper cells. Our investigations reveal a dynamic putative enhancer landscape, and we could validate many of the enhancers using the high-throughput CapStarr sequencing (CapStarr-seq) approach. We find that genes using multiple promoters display increased enhancer usage, suggesting that apparent "enhancer redundancy" might relate to isoform selection. Furthermore, we can show that two Runx3 promoters display long-range interactions with specific enhancers. Finally, our analyses suggest a novel function for the PRC2 complex in the control of alternative promoter usage. Altogether, our study has allowed for the mapping of an exhaustive set of active enhancers and provides new insights into their function and that of PRC2 in controlling promoter choice during T cell differentiation.

The florigen interactor BdES43 represses flowering in the model temperate grass Brachypodium distachyon

FLOWERING LOCUS T (FT) protein, physiologically florigen, has been identified as a system integrator of numerous flowering time pathways in many studies, and its homologs are found throughout the plant lineage. It is important to uncover how precisely florigenic homologs contribute to flowering initiation and how these factors interact genetically. Here we dissected the function of Brachypodium FT orthologs BdFTL1 and BdFTL2 using overexpression and gene-editing experiments. Transgenic assays showed that both BdFTL1 and BdFTL2 could promote flowering, whereas BdFTL2 was essential for flowering initiation. Notably, BdFTL1 is subject to alternative splicing (AS), and its transcriptional level and AS are significantly affected by BdFTL2. Additionally, BdFTL2 could bind with the PHD-containing protein BdES43, an H3K4me3 reader. Furthermore, BdES43 was antagonistic to BdFTL2 in flowering initiation in a transcription-dependent manner and significantly affected BdFTL1 expression. BdFTL2, BdES43 and H3K4me3 also had highly similar distribution patterns within the BdFTL1 locus, indicating their interplay in regulating target genes. Taken together, florigen BdFTL2 functions as a potential epigenetic effector of BdFTL1 by interacting with a BdES43-H3K4me3 complex. This finding provides an additional insight for the regulatory mechanism underlying the multifaceted roles of florigen.

LncRNA GUARDIN suppresses cellular senescence through a LRP130-PGC1α-FOXO4-p21-dependent signaling axis

The long noncoding RNA GUARDIN functions to protect genome stability. Inhibiting GUARDIN expression can alter cell fate decisions toward senescence or apoptosis, but the underlying molecular signals are unknown. Here, we show that GUARDIN is an essential component of a transcriptional repressor complex involving LRP130 and PGC1α. GUARDIN acts as a scaffold to stabilize LRP130/PGC1α heterodimers and their occupancy at the FOXO4 promotor. Destabilizing this complex by silencing of GUARDIN, LRP130, or PGC1α leads to increased expression of FOXO4 and upregulation of its target gene p21, thereby driving cells into senescence. We also found that GUARDIN expression was induced by rapamycin, an agent that suppresses cell senescence. FOS-like antigen 2 (FOSL2) acts as a transcriptional repressor of GUARDIN, and lower FOSL2 levels in response to rapamycin correlate with increased levels of GUARDIN. Together, these results demonstrate that GUARDIN inhibits p21-dependent senescence through a LRP130-PGC1α-FOXO4 signaling axis, and moreover, GUARDIN contributes to the anti-aging activities of rapamycin.

Integrative prediction of gene expression with chromatin accessibility and conformation data

BACKGROUND

Enhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter-enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organization of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.

RESULTS

We have extended our [Formula: see text] framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We designed a novel machine learning approach that allows the prioritization of TFs binding to distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines.

CONCLUSION

We present a novel approach that can be used to prioritize TFs involved in distal and promoter-proximal regulatory events by integrating chromatin accessibility, conformation, and gene expression data. We show that the integration of chromatin conformation data can improve gene expression prediction and aids model interpretability.

Exon-Mediated Activation of Transcription Starts

The processing of RNA transcripts from mammalian genes occurs in proximity to their transcription. Here, we describe a phenomenon affecting thousands of genes that we call exon-mediated activation of transcription starts (EMATS), in which the splicing of internal exons impacts promoter choice and the expression level of the gene. We observed that evolutionary gain of internal exons is associated with gain of new transcription start sites (TSSs) nearby and increased gene expression. Inhibiting exon splicing reduced transcription from nearby promoters, and creation of new spliced exons activated transcription from cryptic promoters. The strongest effects occurred for weak promoters located proximal and upstream of efficiently spliced exons. Together, our findings support a model in which splicing recruits transcription machinery locally to influence TSS choice and identify exon gain, loss, and regulatory change as major contributors to the evolution of alternative promoters and gene expression in mammals.

Genome-wide histone modification profiling of inner cell mass and trophectoderm of bovine blastocysts by RAT-ChIP

Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) has revolutionized our understanding of chromatin-related biological processes. The method, however, requires thousands of cells and has therefore limited applications in situations where cell numbers are limited. Here we describe a novel method called Restriction Assisted Tagmentation Chromatin Immunoprecipitation (RAT-ChIP) that enables global histone modification profiling from as few as 100 cells. The method is simple, cost-effective and takes a single day to complete. We demonstrate the sensitivity of the method by deriving the first genome-wide maps of histone H3K4me3 and H3K27me3 modifications of inner cell mass and trophectoderm of bovine blastocyst stage embryos.

Challenges and opportunities in stroke genetics

Stroke, ischaemic stroke and subtypes of ischaemic stroke display substantial heritability. When compared with related vascular conditions, the number of established risk loci reaching genome-wide significance for association with stroke is still in the lower range, particularly for aetiological stroke subtypes such as large artery atherosclerotic stroke or small vessel stroke. Nevertheless, for individual loci substantial progress has been made in determining the specific mechanisms mediating stroke risk. In this review, we present a roadmap for functional follow-up of common risk variants associated with stroke. First, we discuss in silico strategies for characterizing signals in non-coding regions and highlight databases providing information on quantitative trait loci for mRNA and protein expression, as well as methylation, focussing on those with presumed relevance for stroke. Next, we discuss experimental strategies for following up on non-coding risk variants and regions such as massively parallel reporter assays, proteome-wide association studies, and chromatin conformation capture (3C) assays. These and other approaches are relevant for gaining insight into the specific variants and mechanisms mediating genetic stroke risk. Finally, we discuss how genetic findings could influence clinical practice by adding to diagnostic algorithms and eventually improve treatment options for stroke.

ChiCMaxima: a robust and simple pipeline for detection and visualization of chromatin looping in Capture Hi-C

Capture Hi-C (CHi-C) is a new technique for assessing genome organization based on chromosome conformation capture coupled to oligonucleotide capture of regions of interest, such as gene promoters. Chromatin loop detection is challenging because existing Hi-C/4C-like tools, which make different assumptions about the technical biases presented, are often unsuitable. We describe a new approach, ChiCMaxima, which uses local maxima combined with limited filtering to detect DNA looping interactions, integrating information from biological replicates. ChiCMaxima shows more stringency and robustness compared to previously developed tools. The tool includes a GUI browser for flexible visualization of CHi-C profiles alongside epigenomic tracks.

Causal Gene Regulatory Network Modeling and Genomics: Second-Generation Challenges

Gene regulatory network modeling has played a major role in advancing the understanding of developmental systems, by crystallizing structures of relevant extant information, by formally posing hypothetical functional relationships between network elements, and by offering clear predictive tests to improve understanding of the mechanisms driving developmental progression. Both ordinary differential equation (ODE)-based and Boolean models have also been highly successful in explaining dynamics within subcircuits of more complex processes. In a very small number of cases, gene regulatory network models of much more global scope have been proposed that successfully predict the dynamics of the processes establishing most of an embryonic body plan. Can such successes be expanded to very different developmental systems, including post-embryonic mammalian systems? This perspective discusses several problems that must be solved in more quantitative and predictive theoretical terms, to make this possible. These problems include: the effects of cellular history on chromatin state and how these affect gene accessibility; the dose dependence of activities of many transcription factors (a problem for Boolean models); stochasticity of some transcriptional outputs (a problem for simple ODE models); response timing delays due to epigenetic remodeling requirements; functionally different kinds of repression; and the regulatory syntax that governs responses of genes with multiple enhancers.

Colocalization analyses of genomic elements: approaches, recommendations and challenges

MOTIVATION

Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.

RESULTS

Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functions of DEAD box RNA helicases DDX5 and DDX17 in chromatin organization and transcriptional regulation

RNA helicases DDX5 and DDX17 are multitasking proteins that regulate gene expression in different biological contexts through diverse activities. Special attention has long been paid to their function as coregulators of transcription factors, providing insight about their functional association with a number of chromatin modifiers and remodelers. However, to date, the variety of described mechanisms has made it difficult to understand precisely how these proteins work at the molecular level, and the contribution of their ATPase domain to these mechanisms remains unclear as well. In light of their association with long noncoding RNAs that are key epigenetic regulators, an emerging view is that DDX5 and DDX17 may act through modulating the activity of various ribonucleoprotein complexes that could ensure their targeting to specific chromatin loci. This review will comprehensively describe the current knowledge on these different mechanisms. We will also discuss the potential roles of DDX5 and DDX17 on the 3D chromatin organization and how these could impact gene expression at the transcriptional and post-transcriptional levels.

ZBTB24 is a transcriptional regulator that coordinates with DNMT3B to control DNA methylation

The interplay between transcription factors and epigenetic writers like the DNA methyltransferases (DNMTs), and the role of this interplay in gene expression, is being increasingly appreciated. ZBTB24, a poorly characterized zinc-finger protein, or the de novo methyltransferase DNMT3B, when mutated, cause Immunodeficiency, Centromere Instability, and Facial anomalies (ICF) syndrome, suggesting an underlying mechanistic link. Chromatin immunoprecipitation coupled with loss-of-function approaches in model systems revealed common loci bound by ZBTB24 and DNMT3B, where they function to regulate gene body methylation. Genes coordinately regulated by ZBTB24 and DNMT3B are enriched for molecular mechanisms essential for cellular homeostasis, highlighting the importance of the ZBTB24-DNMT3B interplay in maintaining epigenetic patterns required for normal cellular function. We identify a ZBTB24 DNA binding motif, which is contained within the promoters of most of its transcriptional targets, including CDCA7, AXIN2, and OSTC. Direct binding of ZBTB24 at the promoters of these genes targets them for transcriptional activation. ZBTB24 binding at the promoters of RNF169 and CAMKMT, however, targets them for transcriptional repression. The involvement of ZBTB24 targets in diverse cellular programs, including the VDR/RXR and interferon regulatory pathways, suggest that ZBTB24's role as a transcriptional regulator is not restricted to immune cells.

Newborn blood DNA epigenetic variations and signaling pathway genes associated with Tetralogy of Fallot (TOF)

Tetralogy of Fallot (TOF) is the most common Critical Congenital Heart Defect (CCHD). The etiology of TOF is unknown in most cases. Preliminary data from our group and others suggest that epigenetic changes may play an important role in CHD. Epidemiologically, a significant percentage of CHD including TOF fail to be diagnosed in the prenatal and early newborn period which can negatively affect health outcomes. We performed genome-wide methylation assay in newborn blood in 24 non-syndromic TOF cases and 24 unaffected matched controls using Illumina Infinium HumanMethylation450 BeadChips. We identified 64 significantly differentially methylated CpG sites in TOF cases, of which 25 CpG sites had high predictive accuracy for TOF, based on the area under the receiver operating characteristics curve (AUC ROC) ≥ 0.90). The CpG methylation difference between TOF and controls was ≥10% in 51 CpG targets suggesting biological significance. Gene ontology analysis identified significant biological processes and functions related to these differentially methylated genes, including: CHD development, cardiomyopathy, diabetes, immunological, inflammation and other plausible pathways in CHD development. Multiple genes known or plausibly linked to heart development and post-natal heart disease were found to be differentially methylated in the blood DNA of newborns with TOF including: ABCB1, PPP2R5C, TLR1, SELL, SCN3A, CREM, RUNX and LHX9. We generated novel and highly accurate putative molecular markers for TOF detection using leucocyte DNA and thus provided information on pathogenesis of TOF.

Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs

BACKGROUND

Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection.

METHODS

Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure.

RESULTS

Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant.

CONCLUSIONS

In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.

MGA, L3MBTL2 and E2F6 determine genomic binding of the non-canonical Polycomb repressive complex PRC1.6

Diverse Polycomb repressive complexes 1 (PRC1) play essential roles in gene regulation, differentiation and development. Six major groups of PRC1 complexes that differ in their subunit composition have been identified in mammals. How the different PRC1 complexes are recruited to specific genomic sites is poorly understood. The Polycomb Ring finger protein PCGF6, the transcription factors MGA and E2F6, and the histone-binding protein L3MBTL2 are specific components of the non-canonical PRC1.6 complex. In this study, we have investigated their role in genomic targeting of PRC1.6. ChIP-seq analysis revealed colocalization of MGA, L3MBTL2, E2F6 and PCGF6 genome-wide. Ablation of MGA in a human cell line by CRISPR/Cas resulted in complete loss of PRC1.6 binding. Rescue experiments revealed that MGA recruits PRC1.6 to specific loci both by DNA binding-dependent and by DNA binding-independent mechanisms. Depletion of L3MBTL2 and E2F6 but not of PCGF6 resulted in differential, locus-specific loss of PRC1.6 binding illustrating that different subunits mediate PRC1.6 loading to distinct sets of promoters. Mga, L3mbtl2 and Pcgf6 colocalize also in mouse embryonic stem cells, where PRC1.6 has been linked to repression of germ cell-related genes. Our findings unveil strikingly different genomic recruitment mechanisms of the non-canonical PRC1.6 complex, which specify its cell type- and context-specific regulatory functions.

Polycomb group proteins assemble in two major repressive multi-subunit complexes (PRC1 and PRC2), which play important roles in many physiological processes, including stem cell maintenance, differentiation, cell cycle control and cancer. In mammals, six different groups of PRC1 complexes exist (PRC1.1 to PRC1.6), which differ in their subunit composition. The mechanisms that target the different PRC1 complexes to specific genomic sites appear diverse and are poorly understood. In this study, we have investigated the genomic targeting mechanisms of the non-canonical PRC1.6 complex. In PRC1.6, the defining subunit PCGF6 is specifically associated with several proteins including the transcription factors MGA and E2F6, and the histone-binding protein L3MBTL2. We found that MGA is absolutely essential for targeting PRC1.6. MGA executes recruitment of PRC1.6 to its target sites through two distinct functions. On the one hand it acts as a sequence-specific DNA-binding factor; on the other hand it has a scaffolding function, which is independent of its DNA binding capacity. E2F6 and L3MBTL2 are also important in genomic targeting of PRC1.6 as they promote binding of PRC1.6 to different sets of genes associated with distinct functions. Our finding that different components specify loading of PRC1.6 to distinct sets of genes could establish a paradigm for other chromatin-associated complexes.

Exploring the relationship between intron retention and chromatin accessibility in plants

Background

Intron retention (IR) is the most prevalent form of alternative splicing in plants. IR, like other forms of alternative splicing, has an important role in increasing gene product diversity and regulating transcript functionality. Splicing is known to occur co-transcriptionally and is influenced by the speed of transcription which in turn, is affected by chromatin structure. It follows that chromatin structure may have an important role in the regulation of splicing, and there is preliminary evidence in metazoans to suggest that this is indeed the case; however, nothing is known about the role of chromatin structure in regulating IR in plants. DNase I-seq is a useful experimental tool for genome-wide interrogation of chromatin accessibility, providing information on regions of chromatin with very high likelihood of cleavage by the enzyme DNase I, known as DNase I Hypersensitive Sites (DHSs). While it is well-established that promoter regions are highly accessible and are over-represented with DHSs, not much is known about DHSs in the bodies of genes, and their relationship to splicing in general, and IR in particular.

Results

In this study we use publicly available DNase I-seq data in arabidopsis and rice to investigate the relationship between IR and chromatin structure. We find that IR events are highly enriched in DHSs in both species. This implies that chromatin is more open in retained introns, which is consistent with a kinetic model of the process whereby higher speeds of transcription in those regions give less time for the spliceosomal machinery to recognize and splice out those introns co-transcriptionally. The more open chromatin in IR can also be the result of regulation mediated by DNA-binding proteins. To test this, we performed an exhaustive search for footprints left by DNA-binding proteins that are associated with IR. We identified several hundred short sequence elements that exhibit footprints in their DNase I-seq coverage, the telltale sign for binding events of a regulatory protein, protecting its binding site from cleavage by DNase I. A highly significant fraction of those sequence elements are conserved between arabidopsis and rice, a strong indication of their functional importance.

Conclusions

In this study we have established an association between IR and chromatin accessibility, and presented a mechanistic hypothesis that explains the observed association from the perspective of the co-transcriptional nature of splicing. Furthermore, we identified conserved sequence elements for DNA-binding proteins that affect splicing.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4393-z) contains supplementary material, which is available to authorized users.

Beyond Transcription: Roles of Transcription Factors in Pre-mRNA Splicing

Whereas individual steps of protein-coding gene expression in eukaryotes can be studied in isolation in vitro, it has become clear that these steps are intimately connected within cells. Connections not only ensure quality control but also fine-tune the gene expression process, which must adapt to environmental changes while remaining robust. In this review, we systematically present proven and potential mechanisms by which sequence-specific DNA-binding transcription factors can alter gene expression beyond transcription initiation and regulate pre-mRNA splicing, and thereby mRNA isoform production, by (i) influencing transcription elongation rates, (ii) binding to pre-mRNA to recruit splicing factors, and/or (iii) blocking the association of splicing factors with pre-mRNA. We propose various mechanistic models throughout the review, in some cases without explicit supportive evidence, in hopes of providing fertile ground for future studies.

Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome

Understanding transcriptome complexity is crucial for understanding human biology and disease. Technologies such as Synthetic long-read RNA sequencing (SLR-RNA-seq) delivered 5 million isoforms and allowed assessing splicing coordination. Pacific Biosciences and Oxford Nanopore increase throughput also but require high input amounts or amplification. Our new droplet-based method, sparse isoform sequencing (spISO-seq), sequences 100k–200k partitions of 10–200 molecules at a time, enabling analysis of 10–100 million RNA molecules. SpISO-seq requires less than 1 ng of input cDNA, limiting or removing the need for prior amplification with its associated biases. Adjusting the number of reads devoted to each molecule reduces sequencing lanes and cost, with little loss in detection power. The increased number of molecules expands our understanding of isoform complexity. In addition to confirming our previously published cases of splicing coordination (e.g., BIN1), the greater depth reveals many new cases, such as MAPT. Coordination of internal exons is found to be extensive among protein coding genes: 23.5%–59.3% (95% confidence interval) of highly expressed genes with distant alternative exons exhibit coordination, showcasing the need for long-read transcriptomics. However, coordination is less frequent for noncoding sequences, suggesting a larger role of splicing coordination in shaping proteins. Groups of genes with coordination are involved in protein–protein interactions with each other, raising the possibility that coordination facilitates complex formation and/or function. We also find new splicing coordination types, involving initial and terminal exons. Our results provide a more comprehensive understanding of the human transcriptome and a general, cost-effective method to analyze it.

Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis

Background

Monoallelic expression of autosomal genes has been implicated in human psychiatric disorders. However, there is a paucity of allelic expression studies in human brain cells at the single cell and genome wide levels.

Results

In this report, we reanalyzed a previously published single-cell RNA-seq dataset from several postmortem human brains and observed pervasive monoallelic expression in individual cells, largely in a random manner. Examining single nucleotide variants with a predicted functional disruption, we found that the “damaged” alleles were overall expressed in fewer brain cells than their counterparts, and at a lower level in cells where their expression was detected. We also identified many brain cell type-specific monoallelically expressed genes. Interestingly, many of these cell type-specific monoallelically expressed genes were enriched for functions important for those brain cell types. In addition, function analysis showed that genes displaying monoallelic expression and correlated expression across neuronal cells from different individual brains were implicated in the regulation of synaptic function.

Conclusions

Our findings suggest that monoallelic gene expression is prevalent in human brain cells, which may play a role in generating cellular identity and neuronal diversity and thus increasing the complexity and diversity of brain cell functions.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4261-x) contains supplementary material, which is available to authorized users.

Genome-wide association studies of cancer: current insights and future perspectives

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS.

Genome-wide discovery of active regulatory elements and transcription factor footprints in Caenorhabditis elegans using DNase-seq

Deep sequencing of size-selected DNase I–treated chromatin (DNase-seq) allows high-resolution measurement of chromatin accessibility to DNase I cleavage, permitting identification of de novo active cis-regulatory modules (CRMs) and individual transcription factor (TF) binding sites. We adapted DNase-seq to nuclei isolated from C. elegans embryos and L1 arrest larvae to generate high-resolution maps of TF binding. Over half of embryonic DNase I hypersensitive sites (DHSs) were annotated as noncoding, with 24% in intergenic, 12% in promoters, and 28% in introns, with similar statistics observed in L1 arrest larvae. Noncoding DHSs are highly conserved and enriched in marks of enhancer activity and transcription. We validated noncoding DHSs against known enhancers from myo-2, myo-3, hlh-1, elt-2, and lin-26/lir-1 and recapitulated 15 of 17 known enhancers. We then mined DNase-seq data to identify putative active CRMs and TF footprints. Using DNase-seq data improved predictions of tissue-specific expression compared with motifs alone. In a pilot functional test, 10 of 15 DHSs from pha-4, icl-1, and ceh-13 drove reporter gene expression in transgenic C. elegans. Overall, we provide experimental annotation of 26,644 putative CRMs in the embryo containing 55,890 TF footprints, as well as 15,841 putative CRMs in the L1 arrest larvae containing 32,685 TF footprints.

Initial high-resolution microscopic mapping of active and inactive regulatory sequences proves non-random 3D arrangements in chromatin domain clusters

BACKGROUND

The association of active transcription regulatory elements (TREs) with DNAse I hypersensitivity (DHS[+]) and an 'open' local chromatin configuration has long been known. However, the 3D topography of TREs within the nuclear landscape of individual cells in relation to their active or inactive status has remained elusive. Here, we explored the 3D nuclear topography of active and inactive TREs in the context of a recently proposed model for a functionally defined nuclear architecture, where an active and an inactive nuclear compartment (ANC-INC) form two spatially co-aligned and functionally interacting networks.

RESULTS

Using 3D structured illumination microscopy, we performed 3D FISH with differently labeled DNA probe sets targeting either sites with DHS[+], apparently active TREs, or DHS[-] sites harboring inactive TREs. Using an in-house image analysis tool, DNA targets were quantitatively mapped on chromatin compaction shaped 3D nuclear landscapes. Our analyses present evidence for a radial 3D organization of chromatin domain clusters (CDCs) with layers of increasing chromatin compaction from the periphery to the CDC core. Segments harboring active TREs are significantly enriched at the decondensed periphery of CDCs with loops penetrating into interchromatin compartment channels, constituting the ANC. In contrast, segments lacking active TREs (DHS[-]) are enriched toward the compacted interior of CDCs (INC).

CONCLUSIONS

Our results add further evidence in support of the ANC-INC network model. The different 3D topographies of DHS[+] and DHS[-] sites suggest positional changes of TREs between the ANC and INC depending on their functional state, which might provide additional protection against an inappropriate activation. Our finding of a structural organization of CDCs based on radially arranged layers of different chromatin compaction levels indicates a complex higher-order chromatin organization beyond a dichotomic classification of chromatin into an 'open,' active and 'closed,' inactive state.

Noncoding Variants Functional Prioritization Methods Based on Predicted Regulatory Factor Binding Sites

BACKGROUNDS

With the advent of the post genomic era, the research for the genetic mechanism of the diseases has found to be increasingly depended on the studies of the genes, the gene-networks and gene-protein interaction networks. To explore gene expression and regulation, the researchers have carried out many studies on transcription factors and their binding sites (TFBSs). Based on the large amount of transcription factor binding sites predicting values in the deep learning models, further computation and analysis have been done to reveal the relationship between the gene mutation and the occurrence of the disease. It has been demonstrated that based on the deep learning methods, the performances of the prediction for the functions of the noncoding variants are outperforming than those of the conventional methods. The research on the prediction for functions of Single Nucleotide Polymorphisms (SNPs) is expected to uncover the mechanism of the gene mutation affection on traits and diseases of human beings.

RESULTS

We reviewed the conventional TFBSs identification methods from different perspectives. As for the deep learning methods to predict the TFBSs, we discussed the related problems, such as the raw data preprocessing, the structure design of the deep convolution neural network (CNN) and the model performance measure et al. And then we summarized the techniques that usually used in finding out the functional noncoding variants from de novo sequence.

CONCLUSION

Along with the rapid development of the high-throughout assays, more and more sample data and chromatin features would be conducive to improve the prediction accuracy of the deep convolution neural network for TFBSs identification. Meanwhile, getting more insights into the deep CNN framework itself has been proved useful for both the promotion on model performance and the development for more suitable design to sample data. Based on the feature values predicted by the deep CNN model, the prioritization model for functional noncoding variants would contribute to reveal the affection of gene mutation on the diseases.

Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize

Background

While most cells in multicellular organisms carry the same genetic information, in each cell type only a subset of genes is being transcribed. Such differentiation in gene expression depends, for a large part, on the activation and repression of regulatory sequences, including transcriptional enhancers. Transcriptional enhancers can be located tens of kilobases from their target genes, but display characteristic chromatin and DNA features, allowing their identification by genome-wide profiling. Here we show that integration of chromatin characteristics can be applied to predict distal enhancer candidates in Zea mays, thereby providing a basis for a better understanding of gene regulation in this important crop plant.

Result

To predict transcriptional enhancers in the crop plant maize (Zea mays L. ssp. mays), we integrated available genome-wide DNA methylation data with newly generated maps for chromatin accessibility and histone 3 lysine 9 acetylation (H3K9ac) enrichment in young seedling and husk tissue. Approximately 1500 intergenic regions, displaying low DNA methylation, high chromatin accessibility and H3K9ac enrichment, were classified as enhancer candidates. Based on their chromatin profiles, candidate sequences can be classified into four subcategories. Tissue-specificity of enhancer candidates is defined based on the tissues in which they are identified and putative target genes are assigned based on tissue-specific expression patterns of flanking genes.

Conclusions

Our method identifies three previously identified distal enhancers in maize, validating the new set of enhancer candidates and enlarging the toolbox for the functional characterization of gene regulation in the highly repetitive maize genome.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1273-4) contains supplementary material, which is available to authorized users.

Prediction of Chromatin Accessibility in Gene-Regulatory Regions from Transcriptomics Data

The epigenetics landscape of cells plays a key role in the establishment of cell-type specific gene expression programs characteristic of different cellular phenotypes. Different experimental procedures have been developed to obtain insights into the accessible chromatin landscape including DNase-seq, FAIRE-seq and ATAC-seq. However, current downstream computational tools fail to reliably determine regulatory region accessibility from the analysis of these experimental data. In particular, currently available peak calling algorithms are very sensitive to their parameter settings and show highly heterogeneous results, which hampers a trustworthy identification of accessible chromatin regions. Here, we present a novel method that predicts accessible and, more importantly, inaccessible gene-regulatory chromatin regions solely relying on transcriptomics data, which complements and improves the results of currently available computational methods for chromatin accessibility assays. We trained a hierarchical classification tree model on publicly available transcriptomics and DNase-seq data and assessed the predictive power of the model in six gold standard datasets. Our method increases precision and recall compared to traditional peak calling algorithms, while its usage is not limited to the prediction of accessible and inaccessible gene-regulatory chromatin regions, but constitutes a helpful tool for optimizing the parameter settings of peak calling methods in a cell type specific manner.

Dynamic Reorganization of Chromatin Accessibility Signatures during Dedifferentiation of Secretory Precursors into Lgr5+ Intestinal Stem Cells

Replicating Lgr5⁺ stem cells and quiescent Bmi1⁺ cells behave as intestinal stem cells (ISCs) in vivo. Disrupting Lgr5⁺ ISCs triggers epithelial renewal from Bmi1⁺ cells, from secretory or absorptive progenitors, and from Paneth cell precursors, revealing a high degree of plasticity within intestinal crypts. Here, we show that GFP⁺ cells from Bmi1^GFP mice are preterminal enteroendocrine cells and we identify CD69⁺CD274⁺ cells as related goblet cell precursors. Upon loss of native Lgr5⁺ ISCs, both populations revert toward an Lgr5⁺ cell identity. While active histone marks are distributed similarly between Lgr5⁺ ISCs and progenitors of both major lineages, thousands of cis elements that control expression of lineage-restricted genes are selectively open in secretory cells. This accessibility signature dynamically converts to that of Lgr5⁺ ISCs during crypt regeneration. Beyond establishing the nature of Bmi1^GFP+ cells, these findings reveal how chromatin status underlies intestinal cell diversity and dedifferentiation to restore ISC function and intestinal homeostasis.

Taking promoters out of enhancers in sequence based predictions of tissue-specific mammalian enhancers

BACKGROUND

Many genetic diseases are caused by mutations in non-coding regions of the genome. These mutations are frequently found in enhancer sequences, causing disruption to the regulatory program of the cell. Enhancers are short regulatory sequences in the non-coding part of the genome that are essential for the proper regulation of transcription. While the experimental methods for identification of such sequences are improving every year, our understanding of the rules behind the enhancer activity has not progressed much in the last decade. This is especially true in case of tissue-specific enhancers, where there are clear problems in predicting specificity of enhancer activity.

RESULTS

We show a random-forest based machine learning approach capable of matching the performance of the current state-of-the-art methods for enhancer prediction. Then we show that it is, similarly to other published methods, frequently cross-predicting enhancers as active in different tissues, making it less useful for predicting tissue specific activity. Then we proceed to show that the problem is related to the fact that the enhancer predicting models exhibit a bias towards predicting gene promoters as active enhancers. Then we show that using a two-step classifier can lead to lower cross-prediction between tissues.

CONCLUSIONS

We provide whole-genome predictions of human heart and brain enhancers obtained with two-step classifier.

3D genome organization in health and disease: emerging opportunities in cancer translational medicine

Organizing the DNA to fit inside a spatially constrained nucleus is a challenging problem that has attracted the attention of scientists across all disciplines of science. Increasing evidence has demonstrated the importance of genome geometry in several cellular contexts that affect human health. Among several approaches, the application of sequencing technologies has substantially increased our understanding of this intricate organization, also known as chromatin interactions. These structures are involved in transcriptional control of gene expression by connecting distal regulatory elements with their target genes and regulating co-transcriptional splicing. In addition, chromatin interactions play pivotal roles in the organization of the genome, the formation of structural variants, recombination, DNA replication and cell division. Mutations in factors that regulate chromatin interactions lead to the development of pathological conditions, for example, cancer. In this review, we discuss key findings that have shed light on the importance of these structures in the context of cancers, and highlight the applicability of chromatin interactions as potential biomarkers in molecular medicine as well as therapeutic implications of chromatin interactions.

A Broad Set of Chromatin Factors Influences Splicing

Several studies propose an influence of chromatin on pre-mRNA splicing, but it is still unclear how widespread and how direct this phenomenon is. We find here that when assembled in vivo, the U2 snRNP co-purifies with a subset of chromatin-proteins, including histones and remodeling complexes like SWI/SNF. Yet, an unbiased RNAi screen revealed that the outcome of splicing is influenced by a much larger variety of chromatin factors not all associating with the spliceosome. The availability of this broad range of chromatin factors impacting splicing further unveiled their very context specific effect, resulting in either inclusion or skipping, depending on the exon under scrutiny. Finally, a direct assessment of the impact of chromatin on splicing using an in vitro co-transcriptional splicing assay with pre-mRNAs transcribed from a nucleosomal template, demonstrated that chromatin impacts nascent pre-mRNP in their competence for splicing. Altogether, our data show that numerous chromatin factors associated or not with the spliceosome can affect the outcome of splicing, possibly as a function of the local chromatin environment that by default interferes with the efficiency of splicing.

Splicing is an RNA editing step allowing to produce multiple transcripts from a single gene. The gene itself is organized in chromatin, associating DNA and multiple proteins. Some proteins regulating the compaction of the chromatin also affect RNA splicing. Yet, it was unclear whether these chromatin proteins were exceptions or whether chromatin very generally affected the outcome of splicing. Here, we show that a subset of chromatin proteins is physically in interaction with the enzyme responsible for RNA splicing. In addition, several chromatin proteins not found directly associated with the splicing machinery were also able to influence RNA splicing, suggesting that chromatin compaction very globally plays a role in splicing. This finding was confirmed using the first in vitro assay combining transcription and splicing in the context of chromatin; this assay showed that assembling DNA with chromatin proteins influences the efficiency of splicing.