In silico identification of enhancers on the basis of a combination of transcription factor binding motif occurrences

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

BACKGROUND

Regulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging.

RESULTS

Here we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes. We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters.

CONCLUSION

Based on these associations of (linearly) distal genes' transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.

Gene expression changes during the evolution of the tetrapod limb

Major changes in the vertebrate anatomy have preceded the conquest of land by the members of this taxon, and continuous changes in limb shape and use have occurred during the later radiation of tetrapods. While the main, conserved mechanisms of limb development have been discerned over the past century using a combination of classical embryological and molecular methods, only recent advances made it possible to identify and study the regulatory changes that have contributed to the evolution of the tetrapod appendage. These advances include the expansion of the model repertoire from traditional genetic model species to non-conventional ones, a proliferation of predictive mathematical models that describe gene interactions, an explosion in genomic data and the development of high-throughput methodologies. These revolutionary innovations make it possible to identify specific mutations that are behind specific transitions in limb evolution. Also, as we continue to apply them to more and more extant species, we can expect to gain a fine-grained view of this evolutionary transition that has been so consequential for our species as well.

Enhancers as potential targets for engineering salinity stress tolerance in crop plants

Enhancers represent noncoding regulatory regions of the genome located distantly from their target genes. They regulate gene expression programs in a context-specific manner via interacting with promoters of one or more target genes and are generally associated with transcription factor binding sites and epi(genomic)/chromatin features, such as regions of chromatin accessibility and histone modifications. The enhancers are difficult to identify due to the modularity of their associated features. Although enhancers have been studied extensively in human and animals, only a handful of them has been identified in few plant species till date due to nonavailability of plant-specific experimental and computational approaches for their discovery. Being an important regulatory component of the genome, enhancers represent potential targets for engineering agronomic traits, including salinity stress tolerance in plants. Here, we provide a review of the available experimental and computational approaches along with the associated sequence and chromatin/epigenetic features for the discovery of enhancers in plants. In addition, we provide insights into the challenges and future prospects of enhancer research in plant biology with emphasis on potential applications in engineering salinity stress tolerance in crop plants.

TAD boundary and strength prediction by integrating sequence and epigenetic profile information

Topologically associated domains (TADs) are one of the important higher order chromatin structures with various sizes in the eukaryotic genomes. TAD boundaries, as the flanking regions between adjacent domains, can restrict the interactions of regulatory elements, including enhancers and promoters, and are generally dynamic and variable in different cells. However, the influence of sequence and epigenetic profile-based features in the identification of TAD boundaries is largely unknown. In this work, we proposed a method called pTADS (prediction of TAD boundary and strength), to predict TAD boundaries and boundary strength across multiple cell lines with DNA sequence and epigenetic profile information. The performance was assessed in seven cell lines and three TAD calling methods. The results demonstrate that the TAD boundary can be well predicted by the selected shared features across multiple cell lines. Especially, the model can be transferable to predict the TAD boundary from one cell line to other cell lines. The boundary strength can be characterized by boundary score with good performance. The predicted TAD boundary and TAD boundary strength are further confirmed by three Hi-C contact matrix-based methods across multiple cell lines. The codes and datasets are available at https://github.com/chrom3DEpi/pTADS.

Epigenomic landscape of enhancer elements during Hydra head organizer formation

BACKGROUND

Axis patterning during development is accompanied by large-scale gene expression changes. These are brought about by changes in the histone modifications leading to dynamic alterations in chromatin architecture. The cis regulatory DNA elements also play an important role towards modulating gene expression in a context-dependent manner. Hydra belongs to the phylum Cnidaria where the first asymmetry in the body plan was observed and the oral-aboral axis originated. Wnt signaling has been shown to determine the head organizer function in the basal metazoan Hydra.

RESULTS

To gain insights into the evolution of cis regulatory elements and associated chromatin signatures, we ectopically activated the Wnt signaling pathway in Hydra and monitored the genome-wide alterations in key histone modifications. Motif analysis of putative intergenic enhancer elements from Hydra revealed the conservation of bilaterian cis regulatory elements that play critical roles in development. Differentially regulated enhancer elements were identified upon ectopic activation of Wnt signaling and found to regulate many head organizer specific genes. Enhancer activity of many of the identified cis regulatory elements was confirmed by luciferase reporter assay. Quantitative chromatin immunoprecipitation analysis upon activation of Wnt signaling further confirmed the enrichment of H3K27ac on the enhancer elements of Hv_Wnt5a, Hv_Wnt11 and head organizer genes Hv_Bra1, CnGsc and Hv_Pitx1. Additionally, perturbation of the putative H3K27me3 eraser activity using a specific inhibitor affected the ectopic activation of Wnt signaling indicating the importance of the dynamic changes in the H3K27 modifications towards regulation of the genes involved in the head organizer activity.

CONCLUSIONS

The activation-associated histone marks H3K4me3, H3K27ac and H3K9ac mark chromatin in a similar manner as seen in bilaterians. We identified intergenic cis regulatory elements which harbor sites for key transcription factors involved in developmental processes. Differentially regulated enhancers exhibited motifs for many zinc-finger, T-box and ETS related TFs whose homologs have a head specific expression in Hydra and could be a part of the pioneer TF network in the patterning of the head. The ability to differentially modify the H3K27 residue is critical for the patterning of Hydra axis revealing a dynamic acetylation/methylation switch to regulate gene expression and chromatin architecture.

iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks

BACKGROUND

Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transcription and translation). Having high locational variation and free scattering in 98% of non-encoding genomes, enhancer identification is, therefore, more complicated than other genetic factors. To address this biological issue, several in silico studies have been done to identify and classify enhancer sequences among a myriad of DNA sequences using computational advances. Although recent studies have come up with improved performance, shortfalls in these learning models still remain. To overcome limitations of existing learning models, we introduce iEnhancer-ECNN, an efficient prediction framework using one-hot encoding and k-mers for data transformation and ensembles of convolutional neural networks for model construction, to identify enhancers and classify their strength. The benchmark dataset from Liu et al.'s study was used to develop and evaluate the ensemble models. A comparative analysis between iEnhancer-ECNN and existing state-of-the-art methods was done to fairly assess the model performance.

RESULTS

Our experimental results demonstrates that iEnhancer-ECNN has better performance compared to other state-of-the-art methods using the same dataset. The accuracy of the ensemble model for enhancer identification (layer 1) and enhancer classification (layer 2) are 0.769 and 0.678, respectively. Compared to other related studies, improvements in the Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, and Matthews's correlation coefficient (MCC) of our models are remarkable, especially for the model of layer 2 with about 11.0%, 46.5%, and 65.0%, respectively.

CONCLUSIONS

iEnhancer-ECNN outperforms other previously proposed methods with significant improvement in most of the evaluation metrics. Strong growths in the MCC of both layers are highly meaningful in assuring the stability of our models.

DNA Methylation of Enhancer Elements in Myeloid Neoplasms: Think Outside the Promoters?

Gene regulation through DNA methylation is a well described phenomenon that has a prominent role in physiological and pathological cell-states. This epigenetic modification is usually grouped in regions denominated CpG islands, which frequently co-localize with gene promoters, silencing the transcription of those genes. Recent genome-wide DNA methylation studies have challenged this paradigm, demonstrating that DNA methylation of regulatory regions outside promoters is able to influence cell-type specific gene expression programs under physiologic or pathologic conditions. Coupling genome-wide DNA methylation assays with histone mark annotation has allowed for the identification of specific epigenomic changes that affect enhancer regulatory regions, revealing an additional layer of complexity to the epigenetic regulation of gene expression. In this review, we summarize the novel evidence for the molecular and biological regulation of DNA methylation in enhancer regions and the dynamism of these changes contributing to the fine-tuning of gene expression. We also analyze the contribution of enhancer DNA methylation on the expression of relevant genes in acute myeloid leukemia and chronic myeloproliferative neoplasms. The characterization of the aberrant enhancer DNA methylation provides not only a novel pathogenic mechanism for different tumors but also highlights novel potential therapeutic targets for myeloid derived neoplasms.

iEnhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding

An enhancer is a short (50-1500bp) region of DNA that plays an important role in gene expression and the production of RNA and proteins. Genetic variation in enhancers has been linked to many human diseases, such as cancer, disorder or inflammatory bowel disease. Due to the importance of enhancers in genomics, the classification of enhancers has become a popular area of research in computational biology. Despite the few computational tools employed to address this problem, their resulting performance still requires improvements. In this study, we treat enhancers by the word embeddings, including sub-word information of its biological words, which then serve as features to be fed into a support vector machine algorithm to classify them. We present iEnhancer-5Step, a web server containing two-layer classifiers to identify enhancers and their strength. We are able to attain an independent test accuracy of 79% and 63.5% in the two layers, respectively. Compared to current predictors on the same dataset, our proposed method is able to yield superior performance as compared to the other methods. Moreover, this study provides a basis for further research that can enrich the field of applying natural language processing techniques in biological sequences. iEnhancer-5Step is freely accessible via http://biologydeep.com/fastenc/.

Three-dimensional texture features from intensity and high-order derivative maps for the discrimination between bladder tumors and wall tissues via MRI

PURPOSE

This study aims to determine the three-dimensional (3D) texture features extracted from intensity and high-order derivative maps that could reflect textural differences between bladder tumors and wall tissues, and propose a noninvasive, image-based strategy for bladder tumor differentiation preoperatively.

METHODS

A total of 62 cancerous and 62 wall volumes of interest (VOI) were extracted from T2-weighted MRI datasets of 62 patients with pathologically confirmed bladder cancer. To better reflect heterogeneous distribution of tumor tissues, 3D high-order derivative maps (the gradient and curvature maps) were calculated from each VOI. Then 3D Haralick features based on intensity and high-order derivative maps and Tamura features based on intensity maps were extracted from each VOI. Statistical analysis and recursive feature elimination-based support vector machine classifier (RFE-SVM) was proposed to first select the features with significant differences and then obtain a more predictive and compact feature subset to verify its differentiation performance.

RESULTS

From each VOI, a total of 58 texture features were derived. Among them, 37 features showed significant inter-class differences ([Formula: see text]). With 29 optimal features selected by RFE-SVM, the classification results namely the sensitivity, specificity, accuracy and area under the curve (AUC) of the receiver operating characteristics were 0.9032, 0.8548, 0.8790 and 0.9045, respectively. By using synthetic minority oversampling technique to augment the sample number of each group to 200, the sensitivity, specificity, accuracy an AUC value of the feature selection-based classification were improved to 0.8967, 0.8780, 0.8874 and 0.9416, respectively.

CONCLUSIONS

Our results suggest that 3D texture features derived from intensity and high-order derivative maps can better reflect heterogeneous distribution of cancerous tissues. Texture features optimally selected together with sample augmentation could improve the performance on differentiating bladder carcinomas from wall tissues, suggesting a potential way for tumor noninvasive staging of bladder cancer preoperatively.