Epigenomic analysis reveals DNA motifs regulating histone modifications in human and mouse

Interpretable prediction of mRNA abundance from promoter sequence using contextual regression models

While machine learning models have been successfully applied to predicting gene expression from promoter sequences, it remains a great challenge to derive intuitive interpretation of the model and reveal DNA motif grammar such as motif cooperation and distance constraint between motif sites. Previous interpretation approaches are often time-consuming or have difficulty to learn the combinatory rules. In this work, we designed interpretable neural network models to predict the mRNA expression levels from DNA sequences. By applying the Contextual Regression framework we developed, we extracted weighted features to cluster samples into different groups, which have different gene expression levels. We performed motif analysis in each cluster and found motifs with active or repressive regulation on gene expression. By comparing the co-occurrence locations of discovered motifs, we also uncovered multiple grammars of motif combination including communities of cooperative motifs and distance constraints between motif pairs. These results revealed new insights of the regulatory architecture of promoter sequences.

Epigenetic Modulation of GPER Expression in Gastric and Colonic Smooth Muscle of Male and Female Non-Obese Diabetic (NOD) Mice: Insights into H3K4me3 and H3K27ac Modifications

Type 1 diabetes (T1D) affects gastrointestinal (GI) motility, favoring gastroparesis, constipation, and fecal incontinence, which are more prevalent in women. The mechanisms are unknown. Given the G-protein-coupled estrogen receptor's (GPER) role in GI motility, we investigated sex-related diabetes-induced epigenetic changes in GPER. We assessed GPER mRNA and protein expression levels using qPCR and Western blot analyses, and quantified the changes in nuclear DNA methyltransferases and histone modifications (H3K4me3, H3Ac, and H3K27Ac) by ELISA kits. Targeted bisulfite and chromatin immunoprecipitation assays were used to evaluate DNA methylation and histone modifications around the GPER promoter by chromatin immunoprecipitation assays in gastric and colonic smooth muscle tissues of male and female control (CTR) and non-obese diabetic (NOD) mice. GPER expression was downregulated in NOD, with sex-dependent variations. In the gastric smooth muscle, not in colonic smooth muscle, downregulation coincided with differences in methylation ratios between regions 1 and 2 of the GPER promoter of NOD. DNA methylation was higher in NOD male colonic smooth muscle than in NOD females. H3K4me3 and H3ac enrichment decreased in NOD gastric smooth muscle. H3K4me3 levels diminished in the colonic smooth muscle of NOD. H3K27ac levels were unaffected, but enrichment decreased in NOD male gastric smooth muscle; however, it increased in the NOD male colonic smooth muscle and decreased in the female NOD colonic smooth muscle. Male NOD colonic smooth muscle exhibited decreased H3K27ac levels, not female, whereas female NOD colonic smooth muscle demonstrated diminished enrichment of H3ac at the GPER promoter, contrary to male NOD. Sex-specific epigenetic mechanisms contribute to T1D-mediated suppression of GPER expression in the GI tract. These insights advance our understanding of T1D complications and suggest promising avenues for targeted therapeutic interventions.

ALKHB5-demethylated lncRNA SNHG15 promotes myeloma tumorigenicity by increasing chromatin accessibility and recruiting H3K36me3 modifier SETD2

Chromatin instability plays a crucial role in multiple myeloma (MM) relapse and progression, but its mechanism remains obscure. Here, we uncovered that m6A-demethylase ALKBH5 upregulated and stabilized long noncoding RNA (lncRNA) small nucleolar RNA host gene 15 (SNHG15), which was elevated in MM and positively correlated with unfavorable clinical prognosis factors. ALKBH5-SNHG15 axis participated in viability and migration/invasion of myeloma cell lines and MM-xenografted SCID/NOD mice. Mechanically, ALKBH5 promoted the expression of trimethylated histone H3 at lysine 36 (H3K36me3) methyltransferase SETD2 through lncRNA SNHG15-mediated protein stability. ALKBH5-SNHG15 axis increased chromatin accessibility and altered the H3K36me3 enrichment at the gene body, which is responsible for transcription elongation. Our study suggested a novel epigenetically interaction of N6-methyladenosine (m6A) methylation, lncRNA SNHG15, and histone SETD2/H3K36me3 modifications in myeloma progression, indicating that ALKBH5 and lncRNA SNHG15 could serve as potential novel therapeutic targets for MM treatment.NEW & NOTEWORTHY To our knowledge, this study first demonstrated the prognostic significance and biological function of long noncoding RNA (lncRNA) small nucleolar RNA host gene 15 (SNHG15) in multiple myeloma (MM), and indicated a novel revelation on the effect of N6-methyladenosine (m6A)-regulated lncRNA on MM tumorigenicity. Moreover, the novel chromatin-regulatory mechanism of lncRNA by interacting with epigenetic modifiers including m6A demethylase ALKBH5 and H3K36me3 methyltransferase SETD2 in myeloma progression elucidated intricate mechanism of tumor pathogenesis.

Deep Resequencing of the 1q22 Locus in Non-Lobar Intracerebral Hemorrhage

OBJECTIVE

Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases, including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study, we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown.

METHODS

A total of 95,000 base pairs spanning 1q22, including SEMA4A, SLC25A44, and PMF1/PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and Rare Variant Influential Filtering Tool analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, chromatin immunoprecipitation followed by sequencing, and chromatin interaction analysis with paired-end tag databases. Multivariable Mendelian randomization assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk.

RESULTS

Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop, and that the genes therein belong to the same topologically associating domain. Chromatin immunoprecipitation followed by sequencing and chromatin interaction analysis with paired-end tag data analysis highlighted the presence of long-range interactions between the SEMA4A-promoter and PMF1-enhancer regions prioritized by association testing. Multivariable Mendelian randomization analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk.

INTERPRETATION

Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22, offering a potential new target for prevention of ICH and cerebral small vessel disease. ANN NEUROL 2024;95:325-337.

CamoTSS: analysis of alternative transcription start sites for cellular phenotypes and regulatory patterns from 5' scRNA-seq data

Five-prime single-cell RNA-seq (scRNA-seq) has been widely employed to profile cellular transcriptomes, however, its power of analysing transcription start sites (TSS) has not been fully utilised. Here, we present a computational method suite, CamoTSS, to precisely identify TSS and quantify its expression by leveraging the cDNA on read 1, which enables effective detection of alternative TSS usage. With various experimental data sets, we have demonstrated that CamoTSS can accurately identify TSS and the detected alternative TSS usages showed strong specificity in different biological processes, including cell types across human organs, the development of human thymus, and cancer conditions. As evidenced in nasopharyngeal cancer, alternative TSS usage can also reveal regulatory patterns including systematic TSS dysregulations.

Predicting regional somatic mutation rates using DNA motifs

How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.

Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

MOTIVATION

A growing amount of noncoding genetic variants, including single-nucleotide polymorphisms, are found to be associated with complex human traits and diseases. Their mechanistic interpretation is relatively limited and can use the help from computational prediction of their effects on epigenetic profiles. However, current models often focus on local, 1D genome sequence determinants and disregard global, 3D chromatin structure that critically affects epigenetic events.

RESULTS

We find that noncoding variants of unexpected high similarity in epigenetic profiles, with regards to their relatively low similarity in local sequences, can be largely attributed to their proximity in chromatin structure. Accordingly, we have developed a multimodal deep learning scheme that incorporates both data of 1D genome sequence and 3D chromatin structure for predicting noncoding variant effects. Specifically, we have integrated convolutional and recurrent neural networks for sequence embedding and graph neural networks for structure embedding despite the resolution gap between the two types of data, while utilizing recent DNA language models. Numerical results show that our models outperform competing sequence-only models in predicting epigenetic profiles and their use of long-range interactions complement sequence-only models in extracting regulatory motifs. They prove to be excellent predictors for noncoding variant effects in gene expression and pathogenicity, whether in unsupervised "zero-shot" learning or supervised "few-shot" learning.

AVAILABILITY AND IMPLEMENTATION

Codes and data can be accessed at https://github.com/Shen-Lab/ncVarPred-1D3D and https://zenodo.org/record/7975777.

Histone Maps in Gossypium darwinii Reveal Epigenetic Regulation Drives Subgenome Divergence and Cotton Domestication

The functional annotation of genomes, including chromatin modifications, is essential to understand the intricate architecture of chromatin and the consequential gene regulation. However, such an annotation remains limited for cotton genomes. Here, we conducted chromatin profiling in a wild allotetraploid cotton Gossypium darwinii (AD genome) by integrating the data of histone modification, transcriptome, and chromatin accessibility. We revealed that the A subgenome showed a higher level of active histone marks and lower level of repressive histone marks than the D subgenome, which was consistent with the expression bias between the two subgenomes. We show that the bias in transcription and histone modification between the A and D subgenomes may be caused by genes unique to the subgenome but not by homoeologous genes. Moreover, we integrate histone marks and open chromatin to define six chromatin states (S1-S6) across the cotton genome, which index different genomic elements including genes, promoters, and transposons, implying distinct biological functions. In comparison to the domesticated cotton species, we observed that 23.2% of genes in the genome exhibit a transition from one chromatin state to another at their promoter. Strikingly, the S2 (devoid of epigenetic marks) to S3 (enriched for the mark of open chromatin) was the largest transition group. These transitions occurred simultaneously with changes in gene expression, which were significantly associated with several domesticated traits in cotton. Collectively, our study provides a useful epigenetic resource for research on allopolyploid plants. The domestication-induced chromatin dynamics and associated genes identified here will aid epigenetic engineering, improving polyploid crops.

PyMEGABASE: Predicting cell-type-specific structural annotations of chromosomes using the epigenome

The folding patterns of interphase genomes in higher eukaryotes, as obtained from DNA-proximity-ligation or Hi-C experiments, are used to classify loci into structural classes called compartments and subcompartments. These structurally annotated (sub)compartments are known to exhibit specific epigenomic characteristics and cell-type-specific variations. To explore the relationship between genome structure and the epigenome, we present PyMEGABASE (PYMB), a maximum-entropy-based neural network model that predicts (sub)compartment annotations of a locus based solely on the local epigenome, such as ChIP-Seq of histone post-translational modifications. PYMB builds upon our previous model while improving robustness, capability to handle diverse inputs and user-friendly implementation. We employed PYMB to predict subcompartments for over a hundred human cell types available in ENCODE, shedding light on the links between subcompartments, cell identity, and epigenomic signals. The fact that PYMB, trained on data for human cells, can accurately predict compartments in mice suggests that the model is learning underlying physicochemical principles transferable across cell types and species. Reliable at higher resolutions (up to 5 kbp), PYMB is used to investigate compartment-specific gene expression. Not only can PYMB generate (sub)compartment information without Hi-C experiments, but its predictions are also interpretable. Analyzing PYMB's trained parameters, we explore the importance of various epigenomic marks in each subcompartment prediction. Furthermore, the predictions of the model can be used as input for OpenMiChroM software, which has been calibrated to generate three-dimensional structures of the genome. Detailed documentation of PYMB is available at https://pymegabase.readthedocs.io, including an installation guide using pip or conda, and Jupyter/Colab notebook tutorials.

Lactobacillus plantarum-derived indole-3-lactic acid ameliorates colorectal tumorigenesis via epigenetic regulation of CD8+ T cell immunity

Previous studies have shown that Lactobacillus species play a role in ameliorating colorectal cancer (CRC) in a mouse model. However, the underlying mechanisms remain largely unknown. Here, we found that administration of a probiotic strain, Lactobacillus plantarumL168 and its metabolite, indole-3-lactic acid, ameliorated intestinal inflammation, tumor growth, and gut dysbiosis. Mechanistically, we indicated that indole-3-lactic acid accelerated IL12a production in dendritic cells by enhancing H3K27ac binding at the enhancer regions of IL12a that contributed to priming CD8⁺ T cell immunity against tumor growth. Furthermore, indole-3-lactic acid was found to transcriptionally inhibit Saa3 expression related to cholesterol metabolism of CD8⁺ T cells through changing chromatin accessibility and subsequent enhancing function of tumor-infiltrating CD8⁺ T cells. Together, our findings provide new insights into the epigenetic regulation of probiotics-mediated anti-tumor immunity and suggest the potential of L. plantarumL168 and indole-3-lactic acid to develop therapeutic strategies for patients with CRC.

Deep resequencing of the 1q22 locus in non-lobar intracerebral hemorrhage

Objective

Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases (CSVDs), including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown.

Methods

95,000 base pairs spanning 1q22 , including SEMA4A, SLC25A44 and PMF1 / PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and RIFT analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, ChIP-Seq and ChIA-PET databases. Multivariable Mendelian randomization (MVMR) assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk.

Results

Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop and that the genes therein belong to the same Topologically Associating Domain. ChIP-Seq and ChIA-PET data analysis highlighted the presence of long-range interactions between the SEMA4A -promoter and PMF1 -enhancer regions prioritized by association testing. MVMR analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk.

Interpretation

Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22 , offering a potential new target for prevention of ICH and CSVD.

The Epigenetics of Animal Personality

Animal personality, consistent individual differences in behaviour, is an important concept for understanding how individuals vary in how they cope with environmental challenges. In order to understand the evolutionary significance of animal personality, it is crucial to understand the underlying regulatory mechanisms. Epigenetic marks such as DNA methylation are hypothesised to play a major role in explaining variation in phenotypic changes in response to environmental alterations. Several characteristics of DNA methylation also align well with the concept of animal personality. In this review paper, we summarise the current literature on the role that molecular epigenetic mechanisms may have in explaining personality variation. We elaborate on the potential for epigenetic mechanisms to explain behavioural variation, behavioural development and temporal consistency in behaviour. We then suggest future routes for this emerging field and point to potential pitfalls that may be encountered. We conclude that a more inclusive approach is needed for studying the epigenetics of animal personality and that epigenetic mechanisms cannot be studied without considering the genetic background.

How to Completely Squeeze a Fungus-Advanced Genome Mining Tools for Novel Bioactive Substances

Fungal species have the capability of producing an overwhelming diversity of bioactive substances that can have beneficial but also detrimental effects on human health. These so-called secondary metabolites naturally serve as antimicrobial "weapon systems", signaling molecules or developmental effectors for fungi and hence are produced only under very specific environmental conditions or stages in their life cycle. However, as these complex conditions are difficult or even impossible to mimic in laboratory settings, only a small fraction of the true chemical diversity of fungi is known so far. This also implies that a large space for potentially new pharmaceuticals remains unexplored. We here present an overview on current developments in advanced methods that can be used to explore this chemical space. We focus on genetic and genomic methods, how to detect genes that harbor the blueprints for the production of these compounds (i.e., biosynthetic gene clusters, BGCs), and ways to activate these silent chromosomal regions. We provide an in-depth view of the chromatin-level regulation of BGCs and of the potential to use the CRISPR/Cas technology as an activation tool.

Identification of essential element determining fruit-specific transcriptional activity in the tomato HISTIDINE DECARBOXYLASE A gene promoter

In SlHDC-A promoter, SlHDC-A core-ES is an essential region for fruit-specific expression and interacts with GATA, HSF and AP1. Triplication of essential region was proposed as a minimal fruit-specific promoter. In plant biotechnology, fruit-specific promoter is an important tool for the improvement and utilization of tomato fruit. To expand our understanding on fruit-specific expression, it is necessary to determine the promoter region involved in fruit-specific transcriptional activity and transcriptional regulations of the promoter. In previous study, we isolated a fruit-specific SlHDC-A core promoter specifically expressed during tomato ripening stages. In this study, we identified SlHDC-A promoter region (SlHDC-A core-ES) that is essential for fruit-specific expression of the SlHDC-A. To understand the molecular mechanisms of fruit-specific expression of the SlHDC-A promoter, we first identified the putative transcription factor binding elements in the SlHDC-A core promoter region and corresponding putative transcription factors which are highly expressed during fruit maturation. Yeast one hybrid analysis confirmed that GATA, HSF, and AP1 interact with the SlHDC-A core-ES promoter region. Further transactivation analysis revealed that expression of the three transcription factors significantly activated expression of a reporter gene driven by SlHDC-A core-ES promoter. These results suggest that GATA, HSF, and AP1 are involved in the fruit-specific expression of SlHDC-A promoter. Furthermore, the synthetic promoter composed of three tandem repeats of SlHDC-A core-ES showed relatively higher activity than the constitutive 35S promoter in the transgenic tomato fruits at the orange stage. Taken together, we propose a new synthetic promoter that is specifically expressed during fruit ripening stage.

Spi1 -14 Kb upstream regulatory element (URE) is not required for maintenance of PU.1 expression in macrophages

Background: Previous work suggested an upstream regulatory element (URE) of Spi1 was required to maintain constant expression of the PU.1 transcription factor in bone marrow and foetal liver cells. PU.1, encoded by Spi1, is essential for development and maintenance of myeloid and B-lymphocyte populations in mice. Deletion of this (-14 Kb) URE potentially reduces expression of PU.1 and therefore provides a way to investigate its role in myeloid populations in development and disease. This study aimed to examine the impact of removal of the -14 Kb Spi1 URE in Cx3cr1+ cells on the myeloid lineage formation and maintenance. Methods: B6;129-Spi1tm1.2Dgt/J mice, whose -14 Kb Spi1 URE mice is flanked by LoxP sites (‘floxed’), were bred to a strain with constitutively active Cre expressed under the Cx3cr1 promoter (B6J.B6N(Cg)-Cx3cr1tm1.1(cre)Jung/J) to delete the Spi1 URE in myeloid cells. The floxed mice were also bred to mice with a tamoxifen-inducible Cre expressed under the Cx3cr1 promoter (B6.129P2(C)-Cx3cr1tm2.1(cre/ERT2)Jung/J) to be used as URE intact controls and to permit temporally-controlled deletion of the URE if required. PU.1 protein expression was measured in the peritoneal macrophages and microglia by flow cytometry. Additionally, a Cre-encoding lentiviral vector was used to assess the impact on PU.1 expression in bone-marrow derived macrophages from these mice in vitro. Results: Expression of the PU.1 transcription factor was not significantly altered in the peritoneal macrophages or microglia in mice lacking the -14 Kb Spi1 URE. Moreover, initial experiments utilising Cre encoding lentivirus did not reduce PU.1 protein in bone-marrow derived macrophages differentiated from the -14 Kb Spi1 URE floxed mice. Conclusions: These observations suggest that the -14 Kb URE does not play a major role in PU.1 protein expression in either mature peritoneal macrophages or microglia.

Global Gene Expression Regulation Mediated by TGFβ Through H3K9me3 Mark

Background:

Epigenetic alterations play an important part in carcinogenesis. Different biological responses, including cell proliferation, migration, apoptosis, invasion, and senescence, are affected by epigenetic alterations in cancer. In addition, growth factors, such as transforming growth factor beta (TGFβ) are important regulators of tumorigenesis. Our understanding of the interplay between the epigenetic bases of tumorigenesis and growth factor signaling in tumorigenesis is rudimentary. Some studies suggest a link between TGFβ signaling and the heterochromatinizing histone mark H3K9me3. There is evidence for signal-dependent interactions between R-Smads and histone methyltransferases. However, the effects of TGFβ signaling on genome wide H3K9me3 landscape remains unknown. Our research examines TGFβ -induced genome-wide H3K9me3 in prostate cancer.

Method:

Chromatin-Immunoprecipitation followed by sequencing was performed to analyze genome-wide association of H3K9me3 epigenetic mark. DAVID Functional annotation tool was utilized to understand the involvement of different Biological Processes and Molecular Function. MEME-ChIP tool was also used to analyze known and novel DNA-binding motifs.

Results:

H3K9me3 occupancy appears to increase at intronic regions after short-term (6 hours) TGFβ stimulation and at distal intergenic regions during long-term stimulation (24 hours). We also found evidence for a possible association of SLC transporters with H3K9me3 mark in presence of TGFβ during tumorigenesis. No direct correlation was found between the occupancy of H3K9me3 mark and the expression of various genes. The epigenetic mechanisms-mediated regulation of gene expression by TGFβ was concentrated at promoters rich in SRY and FOXJ3 binding sites.

Conclusion:

Our results point toward a positive association of oncogenic function of TGFβ and the H3K9me3 mark and provide a context to the role of H3K9me3 in TGFβ-induced cell migration and cell adhesion. Interestingly, these functions of TGFβ through H3K9me3 mark regulation seem to depend on transcriptional activation in contrast to the conventionally known repressive nature of H3K9me3.

Chromatin Landscape Dynamics in the Early Development of the Plant Parasitic Nematode Meloidogyne incognita

In model organisms, epigenome dynamics underlies a plethora of biological processes. The role of epigenetic modifications in development and parasitism in nematode pests remains unknown. The root-knot nematode Meloidogyne incognita adapts rapidly to unfavorable conditions, despite its asexual reproduction. However, the mechanisms underlying this remarkable plasticity and their potential impact on gene expression remain unknown. This study provides the first insight into contribution of epigenetic mechanisms to this plasticity, by studying histone modifications in M. incognita. The distribution of five histone modifications revealed the existence of strong epigenetic signatures, similar to those found in the model nematode Caenorhabditis elegans. We investigated their impact on chromatin structure and their distribution relative to transposable elements (TE) loci. We assessed the influence of the chromatin landscape on gene expression at two developmental stages: eggs, and pre-parasitic juveniles. H3K4me3 histone modification was strongly correlated with high levels of expression for protein-coding genes implicated in stage-specific processes during M. incognita development. We provided new insights in the dynamic regulation of parasitism genes kept under histone modifications silencing. In this pioneering study, we establish a comprehensive framework for the importance of epigenetic mechanisms in the regulation of the genome expression and its stability in plant-parasitic nematodes.

Biophysics is reshaping our perception of the epigenome: from DNA-level to high-throughput studies

Epigenetic research holds great promise to advance our understanding of biomarkers and regulatory processes in health and disease. An increasing number of new approaches, ranging from molecular to biophysical analyses, enable identifying epigenetic changes on the level of a single gene or the whole epigenome. The aim of this review is to highlight how the field is shifting from completely molecular-biology-driven solutions to multidisciplinary strategies including more reliance on biophysical analysis tools. Biophysics not only offers technical advancements in imaging or structure analysis but also helps to explore regulatory interactions. New computational methods are also being developed to meet the demand of growing data volumes and their processing. Therefore, it is important to capture these new directions in epigenetics from a biophysical perspective and discuss current challenges as well as multiple applications of biophysical methods and tools. Specifically, we gradually introduce different biophysical research methods by first considering the DNA-level information and eventually higher-order chromatin structures. Moreover, we aim to highlight that the incorporation of bioinformatics, machine learning, and artificial intelligence into biophysical analysis allows gaining new insights into complex epigenetic processes. The gained understanding has already proven useful in translational and clinical research providing better patient stratification options or new therapeutic insights. Together, this offers a better readiness to transform bench-top experiments into industrial high-throughput applications with a possibility to employ developed methods in clinical practice and diagnostics.

The Potential of Induced Pluripotent Stem Cells to Treat and Model Alzheimer's Disease

An estimated 6.2 million Americans aged 65 or older are currently living with Alzheimer's disease (AD), a neurodegenerative disease that disrupts an individual's ability to function independently through the degeneration of key regions in the brain, including but not limited to the hippocampus, the prefrontal cortex, and the motor cortex. The cause of this degeneration is not known, but research has found two proteins that undergo posttranslational modifications: tau, a protein concentrated in the axons of neurons, and amyloid precursor protein (APP), a protein concentrated near the synapse. Through mechanisms that have yet to be elucidated, the accumulation of these two proteins in their abnormal aggregate forms leads to the neurodegeneration that is characteristic of AD. Until the invention of induced pluripotent stem cells (iPSCs) in 2006, the bulk of research was carried out using transgenic animal models that offered little promise in their ability to translate well from benchtop to bedside, creating a bottleneck in the development of therapeutics. However, with iPSC, patient-specific cell cultures can be utilized to create models based on human cells. These human cells have the potential to avoid issues in translatability that have plagued animal models by providing researchers with a model that closely resembles and mimics the neurons found in humans. By using human iPSC technology, researchers can create more accurate models of AD ex vivo while also focusing on regenerative medicine using iPSC in vivo. The following review focuses on the current uses of iPSC and how they have the potential to regenerate damaged neuronal tissue, in the hopes that these technologies can assist in getting through the bottleneck of AD therapeutic research.

ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach

BACKGROUND

ChIP-seq combines chromatin immunoprecipitation assays with sequencing and identifies genome-wide binding sites for DNA binding proteins. While many binding sites have strong ChIP-seq 'peak' observations and are well captured, there are still regions bound by proteins weakly, with a relatively low ChIP-seq signal enrichment. These weak binding sites, especially those at promoters and enhancers, are functionally important because they also regulate nearby gene expression. Yet, it remains a challenge to accurately identify weak binding sites in ChIP-seq data due to the ambiguity in differentiating these weak binding sites from the amplified background DNAs.

RESULTS

ChIP-BIT2 ( http://sourceforge.net/projects/chipbitc/ ) is a software package for ChIP-seq peak detection. ChIP-BIT2 employs a mixture model integrating protein and control ChIP-seq data and predicts strong or weak protein binding sites at promoters, enhancers, or other genomic locations. For binding sites at gene promoters, ChIP-BIT2 simultaneously predicts their target genes. ChIP-BIT2 has been validated on benchmark regions and tested using large-scale ENCODE ChIP-seq data, demonstrating its high accuracy and wide applicability.

CONCLUSION

ChIP-BIT2 is an efficient ChIP-seq peak caller. It provides a better lens to examine weak binding sites and can refine or extend the existing binding site collection, providing additional regulatory regions for decoding the mechanism of gene expression regulation.

Deciphering the genetic code of DNA methylation

DNA methylation plays crucial roles in many biological processes and abnormal DNA methylation patterns are often observed in diseases. Recent studies have shed light on cis-acting DNA elements that regulate locus-specific DNA methylation, which involves transcription factors, histone modification and DNA secondary structures. In addition, several recent studies have surveyed DNA motifs that regulate DNA methylation and suggest potential applications in diagnosis and prognosis. Here, we discuss the current biological foundation for the cis-acting genetic code that regulates DNA methylation. We review the computational models that predict DNA methylation with genetic features and discuss the biological insights revealed from these models. We also provide an in-depth discussion on how to leverage such knowledge in clinical applications, particularly in the context of liquid biopsy for early cancer diagnosis and treatment.

Motto: Representing Motifs in Consensus Sequences with Minimum Information Loss

Sequence analysis frequently requires intuitive understanding and convenient representation of motifs. Typically, motifs are represented as position weight matrices (PWMs) and visualized using sequence logos. However, in many scenarios, in order to interpret the motif information or search for motif matches, it is compact and sufficient to represent motifs by wildcard-style consensus sequences (such as [GC][AT]GATAAG[GAC]). Based on mutual information theory and Jensen-Shannon divergence, we propose a mathematical framework to minimize the information loss in converting PWMs to consensus sequences. We name this representation as sequence Motto and have implemented an efficient algorithm with flexible options for converting motif PWMs into Motto from nucleotides, amino acids, and customized characters. We show that this representation provides a simple and efficient way to identify the binding sites of 1156 common transcription factors (TFs) in the human genome. The effectiveness of the method was benchmarked by comparing sequence matches found by Motto with PWM scanning results found by FIMO. On average, our method achieves a 0.81 area under the precision-recall curve, significantly (P-value < 0.01) outperforming all existing methods, including maximal positional weight, Cavener's method, and minimal mean square error. We believe this representation provides a distilled summary of a motif, as well as the statistical justification.

An atlas of dynamic chromatin landscapes in mouse fetal development

The Encyclopedia of DNA Elements (ENCODE) project has established a genomic resource for mammalian development, profiling a diverse panel of mouse tissues at 8 developmental stages from 10.5 days after conception until birth, including transcriptomes, methylomes and chromatin states. Here we systematically examined the state and accessibility of chromatin in the developing mouse fetus. In total we performed 1,128 chromatin immunoprecipitation with sequencing (ChIP-seq) assays for histone modifications and 132 assay for transposase-accessible chromatin using sequencing (ATAC-seq) assays for chromatin accessibility across 72 distinct tissue-stages. We used integrative analysis to develop a unified set of chromatin state annotations, infer the identities of dynamic enhancers and key transcriptional regulators, and characterize the relationship between chromatin state and accessibility during developmental gene regulation. We also leveraged these data to link enhancers to putative target genes and demonstrate tissue-specific enrichments of sequence variants associated with disease in humans. The mouse ENCODE data sets provide a compendium of resources for biomedical researchers and achieve, to our knowledge, the most comprehensive view of chromatin dynamics during mammalian fetal development to date.

Identification of DNA motifs that regulate DNA methylation

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidence. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with "somatic QTLs" (quantitative trait loci) of methylation and expression. Fourth, disruption of these motifs by mutation is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic mutations are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting a possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

Genetic Contexts Characterize Dynamic Histone Modification Patterns Among Cell Types

Histone modifications play critical roles in mammalian development, regulating chromatin structure and gene expression. Dynamic histone modifications among cell types have been shown to associate with changes in mammalian development. However, how to quantitatively measure the histone modification alterations and how histone modifications vary across cell types under different genetic contexts remain largely unexplored and whether these changes are related to the primary DNA sequence remains limited. Here, we employed an entropy-based method to measure histone modification alterations in six definite genomic regions across five cell types and identified lineage-specific histone modification genes. We observed that histone modification alterations prefer to enrich in 5'-UTR exons, and also in 3'-UTR exons and its downstream. Then we built a model to predict the histone modification patterns from the primary DNA sequence. We found that the frequencies of k-mer sequence compositions are predictive of histone modification patterns, suggesting that the primary DNA sequence correlated with the histone modification alterations among cell types. Additionally, the lineage-specific histone modification genes display a higher conservation and lower GC-content. Together, we performed a systematic analysis for histone modification alterations and demonstrated how to identify genomic region-specific elements of epigenetic and genetic regulation and histone modification patterns across different cell types.