Enhancer identification through comparative genomics

A comparative analysis of planarian genomes reveals regulatory conservation in the face of rapid structural divergence

The planarian Schmidtea mediterranea is being studied as a model species for regeneration, but the assembly of planarian genomes remains challenging. Here, we report a high-quality haplotype-phased, chromosome-scale genome assembly of the sexual S2 strain of S. mediterranea and high-quality chromosome-scale assemblies of its three close relatives, S. polychroa, S. nova, and S. lugubris. Using hybrid gene annotations and optimized ATAC-seq and ChIP-seq protocols for regulatory element annotation, we provide valuable genome resources for the planarian research community and a first comparative perspective on planarian genome evolution. Our analyses reveal substantial divergence in protein-coding sequences and regulatory regions but considerable conservation within promoter and enhancer annotations. We also find frequent retrotransposon-associated chromosomal inversions and interchromosomal translocations within the genus Schmidtea and, remarkably, independent and nearly complete losses of ancestral metazoan synteny in Schmidtea and two other flatworm groups. Overall, our results suggest that platyhelminth genomes can evolve without syntenic constraints.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

Background

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues.

Results

Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~ 50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3).

Conclusions

HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues. Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3). HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

Enhancer Recognition: A Transformer Encoder-Based Method with WGAN-GP for Data Augmentation

Enhancers are located upstream or downstream of key deoxyribonucleic acid (DNA) sequences in genes and can adjust the transcription activity of neighboring genes. Identifying enhancers and determining their functions are important for understanding gene regulatory networks and expression regulatory mechanisms. However, traditional enhancer recognition relies on manual feature engineering, which is time-consuming and labor-intensive, making it difficult to perform large-scale recognition analysis. In addition, if the original dataset is too small, there is a risk of overfitting. In recent years, emerging methods, such as deep learning, have provided new insights for enhancing identification. However, these methods also present certain challenges. Deep learning models typically require a large amount of high-quality data, and data acquisition demands considerable time and resources. To address these challenges, in this paper, we propose a data-augmentation method based on generative adversarial networks to solve the problem of small datasets. Moreover, we used regularization methods such as weight decay to improve the generalizability of the model and alleviate overfitting. The Transformer encoder was used as the main component to capture the complex relationships and dependencies in enhancer sequences. The encoding layer was designed based on the principle of k-mers to preserve more information from the original DNA sequence. Compared with existing methods, the proposed approach made significant progress in enhancing the accuracy and strength of enhancer identification and prediction, demonstrating the effectiveness of the proposed method. This paper provides valuable insights for enhancer analysis and is of great significance for understanding gene regulatory mechanisms and studying disease correlations.

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

Understanding the mechanisms of gene expression regulation is crucial in animal breeding. Cis-regulatory DNA sequences, such as enhancers, play a key role in regulating gene expression. Identifying enhancers is challenging, despite the use of experimental techniques and computational methods. Enhancer prediction in the pig genome is particularly significant due to the costliness of high-throughput experimental techniques. The study constructed a high-quality database of pig enhancers by integrating information from multiple sources. A deep learning prediction framework called PorcineAI-enhancer was developed for the prediction of pig enhancers. This framework employs convolutional neural networks for feature extraction and classification. PorcineAI-enhancer showed excellent performance in predicting pig enhancers, validated on an independent test dataset. The model demonstrated reliable prediction capability for unknown enhancer sequences and performed remarkably well on tissue-specific enhancer sequences.The study developed a deep learning prediction framework, PorcineAI-enhancer, for predicting pig enhancers. The model demonstrated significant predictive performance and potential for tissue-specific enhancers. This research provides valuable resources for future studies on gene expression regulation in pigs.

Cis-regulatory landscapes in the evolution and development of the mammalian skull

Extensive morphological variation found in mammals reflects the wide spectrum of their ecological adaptations. The highest morphological diversity is present in the craniofacial region, where geometry is mainly dictated by the bony skull. Mammalian craniofacial development represents complex multistep processes governed by numerous conserved genes that require precise spatio-temporal control. A central question in contemporary evolutionary biology is how a defined set of conserved genes can orchestrate formation of fundamentally different structures, and therefore how morphological variability arises. In principle, differential gene expression patterns during development are the source of morphological variation. With the emergence of multicellular organisms, precise regulation of gene expression in time and space is attributed to cis-regulatory elements. These elements contribute to higher-order chromatin structure and together with trans-acting factors control transcriptional landscapes that underlie intricate morphogenetic processes. Consequently, divergence in cis-regulation is believed to rewire existing gene regulatory networks and form the core of morphological evolution. This review outlines the fundamental principles of the genetic code and genomic regulation interplay during development. Recent work that deepened our comprehension of cis-regulatory element origin, divergence and function is presented here to illustrate the state-of-the-art research that uncovered the principles of morphological novelty. This article is part of the theme issue 'The mammalian skull: development, structure and function'.

Genome-wide identification and characterization of DNA enhancers with a stacked multivariate fusion framework

Enhancers are short non-coding DNA sequences outside of the target promoter regions that can be bound by specific proteins to increase a gene's transcriptional activity, which has a crucial role in the spatiotemporal and quantitative regulation of gene expression. However, enhancers do not have a specific sequence motifs or structures, and their scattered distribution in the genome makes the identification of enhancers from human cell lines particularly challenging. Here we present a novel, stacked multivariate fusion framework called SMFM, which enables a comprehensive identification and analysis of enhancers from regulatory DNA sequences as well as their interpretation. Specifically, to characterize the hierarchical relationships of enhancer sequences, multi-source biological information and dynamic semantic information are fused to represent regulatory DNA enhancer sequences. Then, we implement a deep learning-based sequence network to learn the feature representation of the enhancer sequences comprehensively and to extract the implicit relationships in the dynamic semantic information. Ultimately, an ensemble machine learning classifier is trained based on the refined multi-source features and dynamic implicit relations obtained from the deep learning-based sequence network. Benchmarking experiments demonstrated that SMFM significantly outperforms other existing methods using several evaluation metrics. In addition, an independent test set was used to validate the generalization performance of SMFM by comparing it to other state-of-the-art enhancer identification methods. Moreover, we performed motif analysis based on the contribution scores of different bases of enhancer sequences to the final identification results. Besides, we conducted interpretability analysis of the identified enhancer sequences based on attention weights of EnhancerBERT, a fine-tuned BERT model that provides new insights into exploring the gene semantic information likely to underlie the discovered enhancers in an interpretable manner. Finally, in a human placenta study with 4,562 active distal gene regulatory enhancers, SMFM successfully exposed tissue-related placental development and the differential mechanism, demonstrating the generalizability and stability of our proposed framework.

Enhancer-LSTMAtt: A Bi-LSTM and Attention-Based Deep Learning Method for Enhancer Recognition

Enhancers are short DNA segments that play a key role in biological processes, such as accelerating transcription of target genes. Since the enhancer resides anywhere in a genome sequence, it is difficult to precisely identify enhancers. We presented a bi-directional long-short term memory (Bi-LSTM) and attention-based deep learning method (Enhancer-LSTMAtt) for enhancer recognition. Enhancer-LSTMAtt is an end-to-end deep learning model that consists mainly of deep residual neural network, Bi-LSTM, and feed-forward attention. We extensively compared the Enhancer-LSTMAtt with 19 state-of-the-art methods by 5-fold cross validation, 10-fold cross validation and independent test. Enhancer-LSTMAtt achieved competitive performances, especially in the independent test. We realized Enhancer-LSTMAtt into a user-friendly web application. Enhancer-LSTMAtt is applicable not only to recognizing enhancers, but also to distinguishing strong enhancer from weak enhancers. Enhancer-LSTMAtt is believed to become a promising tool for identifying enhancers.

Epigenetic Regulation of Endothelial Cell Lineages During Zebrafish Development-New Insights From Technical Advances

Epigenetic regulation is integral in orchestrating the spatiotemporal regulation of gene expression which underlies tissue development. The emergence of new tools to assess genome-wide epigenetic modifications has enabled significant advances in the field of vascular biology in zebrafish. Zebrafish represents a powerful model to investigate the activity of cis-regulatory elements in vivo by combining technologies such as ATAC-seq, ChIP-seq and CUT&Tag with the generation of transgenic lines and live imaging to validate the activity of these regulatory elements. Recently, this approach led to the identification and characterization of key enhancers of important vascular genes, such as gata2a, notch1b and dll4. In this review we will discuss how the latest technologies in epigenetics are being used in the zebrafish to determine chromatin states and assess the function of the cis-regulatory sequences that shape the zebrafish vascular network.

Characterization of Mammalian In Vivo Enhancers Using Mouse Transgenesis and CRISPR Genome Editing

Embryonic morphogenesis is strictly dependent on tight spatiotemporal control of developmental gene expression, which is typically achieved through the concerted activity of multiple enhancers driving cell type-specific expression of a target gene. Mammalian genomes are organized in topologically associated domains, providing a preferred environment and framework for interactions between transcriptional enhancers and gene promoters. While epigenomic profiling and three-dimensional chromatin conformation capture have significantly increased the accuracy of identifying enhancers, assessment of subregional enhancer activities via transgenic reporter assays in mice remains the gold standard for assigning enhancer activity in vivo. Once this activity is defined, the ideal method to explore the functional necessity of a transcriptional enhancer and its contribution to target gene dosage and morphological or physiological processes is deletion of the enhancer sequence from the mouse genome. Here we present detailed protocols for efficient introduction of enhancer-reporter transgenes and CRISPR-mediated genomic deletions into the mouse genome, including a step-by-step guide for pronuclear microinjection of fertilized mouse eggs. We provide instructions for the assembly and genomic integration of enhancer-reporter cassettes that have been used for validation of thousands of putative enhancer sequences accessible through the VISTA enhancer browser, including a recently published method for robust site-directed transgenesis at the H11 safe-harbor locus. Together, these methods enable rapid and large-scale assessment of enhancer activities and sequence variants in mice, which is essential to understand mammalian genome function and genetic diseases.

Identification of cell states using super-enhancer RNA

BACKGROUND

A new class of regulatory elements called super-enhancers, comprised of multiple neighboring enhancers, have recently been reported to be the key transcriptional drivers of cellular, developmental, and disease states.

RESULTS

Here, we defined super-enhancer RNAs as highly expressed enhancer RNAs that are transcribed from a cluster of localized genomic regions. Using the cap analysis of gene expression sequencing data from FANTOM5, we systematically explored the enhancer and messenger RNA landscapes in hundreds of different cell types in response to various environments. Applying non-negative matrix factorization (NMF) to super-enhancer RNA profiles, we found that different cell types were well classified. In addition, through the NMF of individual time-course profiles from a single cell-type, super-enhancer RNAs were clustered into several states with progressive patterns. We further investigated the enriched biological functions of the proximal genes involved in each pattern, and found that they were associated with the corresponding developmental process.

CONCLUSIONS

The proposed super-enhancer RNAs can act as a good alternative, without the complicated measurement of histone modifications, for identifying important regulatory elements of cell type specification and identifying dynamic cell states.

Animal-eRNAdb: a comprehensive animal enhancer RNA database

Enhancer RNAs (eRNAs) are a class of non-coding RNAs transcribed from enhancers. As the markers of active enhancers, eRNAs play important roles in gene regulation and are associated with various complex traits and characteristics. With increasing attention to eRNAs, numerous eRNAs have been identified in different human tissues. However, the expression landscape, regulatory network and potential functions of eRNAs in animals have not been fully elucidated. Here, we systematically characterized 185 177 eRNAs from 5085 samples across 10 species by mapping the RNA sequencing data to the regions of known enhancers. To explore their potential functions based on evolutionary conservation, we investigated the sequence similarity of eRNAs among multiple species. In addition, we identified the possible associations between eRNAs and transcription factors (TFs) or nearby genes to decipher their possible regulators and target genes, as well as characterized trait-related eRNAs to explore their potential functions in biological processes. Based on these findings, we further developed Animal-eRNAdb (http://gong_lab.hzau.edu.cn/Animal-eRNAdb/), a user-friendly database for data searching, browsing and downloading. With the comprehensive characterization of eRNAs in various tissues of different species, Animal-eRNAdb may greatly facilitate the exploration of functions and mechanisms of eRNAs.

CRISPR disruption and UK Biobank analysis of a highly conserved polymorphic enhancer suggests a role in male anxiety and ethanol intake

Excessive alcohol intake is associated with 5.9% of global deaths. However, this figure is especially acute in men such that 7.6% of deaths can be attributed to alcohol intake. Previous studies identified a significant interaction between genotypes of the galanin (GAL) gene with anxiety and alcohol abuse in different male populations but were unable to define a mechanism. To address these issues the current study analysed the human UK Biobank cohort and identified a significant interaction (n = 115,865; p = 0.0007) between allelic variation (GG or CA genotypes) in the highly conserved human GAL5.1 enhancer, alcohol intake (AUDIT questionnaire scores) and anxiety in men. Critically, disruption of GAL5.1 in mice using CRISPR genome editing significantly reduced GAL expression in the amygdala and hypothalamus whilst producing a corresponding reduction in ethanol intake in KO mice. Intriguingly, we also found the evidence of reduced anxiety-like behaviour in male GAL5.1KO animals mirroring that seen in humans from our UK Biobank studies. Using bioinformatic analysis and co-transfection studies we further identified the EGR1 transcription factor, that is co-expressed with GAL in amygdala and hypothalamus, as being important in the protein kinase C (PKC) supported activity of the GG genotype of GAL5.1 but less so in the CA genotype. Our unique study uses a novel combination of human association analysis, CRISPR genome editing in mice, animal behavioural analysis and cell culture studies to identify a highly conserved regulatory mechanism linking anxiety and alcohol intake that might contribute to increased susceptibility to anxiety and alcohol abuse in men.

FSHB Transcription is Regulated by a Novel 5' Distal Enhancer With a Fertility-Associated Single Nucleotide Polymorphism

The pituitary gonadotropins, follicle-stimulating hormone (FSH) and luteinizing hormone, signal the gonads to regulate male and female fertility. FSH is critical for female fertility as it regulates oocyte maturation, ovulation, and hormone synthesis. Multiple genome-wide association studies (GWAS) link a 130 Kb locus at 11p14.1, which encompasses the FSH beta-subunit (FSHB) gene, with fertility-related traits that include polycystic ovary syndrome, age of natural menopause, and dizygotic twinning. The most statistically significant single nucleotide polymorphism from several GWAS studies (rs11031006) resides within a highly conserved 450 bp region 26 Kb upstream of the human FSHB gene. Given that sequence conservation suggests an important biological function, we hypothesized that the region could regulate FSHB transcription. In luciferase assays, the conserved region enhanced FSHB transcription and gel shifts identified a binding site for Steroidogenic factor 1 (SF1) contributing to its function. Analysis of mouse pituitary single-cell ATAC-seq demonstrated open chromatin at the conserved region exclusive to a gonadotrope cell-type cluster. Additionally, enhancer-associated histone markers were identified by immunoprecipitation of chromatin from mouse whole pituitary and an immortalized mouse gonadotrope-derived LβT2 cell line at the conserved region. Furthermore, we found that the rs11031006 minor allele upregulated FSHB transcription via increased SF1 binding to the enhancer. All together, these results identify a novel upstream regulator of FSHB transcription and indicate that rs11031006 can modulate FSH levels.

ChIP-Seq Assays from Mammalian Cartilage and Chondrocytes

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a powerful tool to identify binding profiles of transcriptional regulators and chromatin regulators as well as histone modification patterns in a genome-wide manner. ChIP-seq consists of five major steps: (1) preparation of cells and chromatin, (2) ChIP, (3) ChIP-seq library construction, (4) sequencing of ChIP DNA with a next-generation sequencer (NGS), and (5) computational analysis of sequence data. Recent ChIP-seq studies in skeletal tissues enable us to understand the modes of action of key skeletal regulators, functional interaction among the enhancers bound by the regulators, the complex nature of regulatory inputs, and thereby the gene regulatory landscape in skeletal development. Here we describe a ChIP-seq protocol that we have employed in our studies, with particular focus on chromatin preparation and subsequent ChIP in skeletal cells, including chondrocytes.

Evaluation of Whole-Exome Enrichment Solutions: Lessons from the High-End of the Short-Read Sequencing Scale

Whole-exome sequencing has become a popular technique in research and clinical settings, assisting in disease diagnosis and increasing the understanding of disease pathogenesis. In this study, we aimed to compare common enrichment capture solutions available in the market. Peripheral blood-purified DNA samples were enriched with SureSelect^QXT V6 (Agilent) and various Illumina solutions: TruSeq DNA Nano, TruSeq DNA Exome, Nextera DNA Exome, and Illumina DNA Prep with Enrichment, and sequenced on a HiSeq 4000. We found that their percentage of duplicate reads was as much as 2 times higher than previously reported values for the previous HiSeq series. SureSelect^QXT and Illumina DNA Prep with Enrichment showed the best average on-target coverage, which improved when off-target regions were included. At high coverage levels and in shared bases, these two solutions and TruSeq DNA Exome provided three of the best performances. With respect to the number of small variants detected, SureSelect^QXT presented the lowest number of detected variants in target regions. When off-target regions were considered, its ability equalized to other solutions. Our results show SureSelect^QXT and Illumina DNA Prep with Enrichment to be the best enrichment capture solutions.

Perspective: Quality Versus Quantity; Is It Important to Assess the Role of Enhancers in Complex Disease from an In Vivo Perspective?

Sequencing of the human genome has permitted the development of genome-wide association studies (GWAS) to analyze the genetics of a number of complex disorders such as depression, anxiety and substance abuse. Thanks to their ability to analyze huge cohort sizes, these studies have successfully identified thousands of loci associated with a broad spectrum of complex diseases. Disconcertingly, the majority of these GWAS hits occur in non-coding regions of the genome, much of which controls the cell-type-specific expression of genes essential to health. In contrast to gene coding sequences, it is a challenge to understand the function of this non-coding regulatory genome using conventional biochemical techniques in cell lines. The current commentary scrutinizes the field of complex genetics from the standpoint of the large-scale whole-genome functional analysis of the promoters and cis-regulatory elements using chromatin markers. We contrast these large scale quantitative techniques against comparative genomics and in vivo analyses including CRISPR/CAS9 genome editing to determine the functional characteristics of these elements and to understand how polymorphic variation and epigenetic changes within these elements might contribute to complex disease and drug response. Most importantly, we suggest that, although the role of chromatin markers will continue to be important in identifying and characterizing enhancers, more emphasis must be placed on their analysis in relevant in-vivo models that take account of the appropriate cell-type-specific roles of these elements. It is hoped that offering these insights might refocus progress in analyzing the data tsunami of non-coding GWAS and whole-genome sequencing "hits" that threatens to overwhelm progress in the field.

High-Throughput Analysis of Retinal Cis-Regulatory Networks by Massively Parallel Reporter Assays

Inherited retinal degenerations are diverse and debilitating blinding diseases. Genetic tests and exome sequencing have identified mutations in many protein-coding genes associated with such diseases, but causal sequence variants remain to be found in many retinopathy cases. Since 99% of our genome does not code for protein but contains cis-regulatory elements (CREs) that regulate the expression of essential genes, CRE variants might hold the answer for some of these cases. However, identifying functional CREs within the noncoding genome and predicting the pathogenicity of CRE variants pose a significant challenge. Here, we review the development of massively parallel reporter assays in the mouse retina, its use in dissecting retinal cis-regulatory networks, and its potential application for developing therapies.

Functional genetic analysis in a jawless vertebrate, the sea lamprey: insights into the developmental evolution of early vertebrates

Lampreys and hagfishes are the only surviving relicts of an ancient but ecologically dominant group of jawless fishes that evolved in the seas of the Cambrian era over half a billion years ago. Because of their phylogenetic position as the sister group to all other vertebrates (jawed vertebrates), comparisons of embryonic development between jawless and jawed vertebrates offers researchers in the field of evolutionary developmental biology the unique opportunity to address fundamental questions related to the nature of our earliest vertebrate ancestors. Here, we describe how genetic analysis of embryogenesis in the sea lamprey (Petromyzon marinus) has provided insight into the origin and evolution of developmental-genetic programs in vertebrates. We focus on recent work involving CRISPR/Cas9-mediated genome editing to study gene regulatory mechanisms involved in the development and evolution of neural crest cells and new cell types in the vertebrate nervous system, and transient transgenic assays that have been instrumental in dissecting the evolution of cis-regulatory control of gene expression in vertebrates. Finally, we discuss the broad potential for these functional genomic tools to address previously unanswerable questions related to the evolution of genomic regulatory mechanisms as well as issues related to invasive sea lamprey population control.

Enhancer-Driven Gene Expression (EDGE) enables the generation of cell type specific tools for the analysis of neural circuits

As in all circuits, fully understanding how neural circuits operate requires the ability to specifically manipulate individual circuit elements, i.e. particular neuronal cell types. While recent years saw the development of molecular genetic tools allowing one to control and monitor neuronal activity, progress is limited by the ability to express such transgenes specifically enough. This goal is complicated by the fact that we are only beginning to understand how many cell types exist in the mammalian brain. Obtaining neuronal cell type-specific expression requires co-opting the genetic machinery which specifies their striking diversity, typically done by making transgenic animals using promoters expressing in neurons. However, while the vast majority of genes express in the brain, they almost always express in multiple cell types, meaning native promoters are not specific enough. We have recently taken a new approach to increase the specificity of transgene expression based upon identifying the distal cis-regulatory genomic elements (i.e. enhancers) uniquely active in a brain region and combining them with a heterologous minimal promoter. Termed Enhancer-Driven Gene Expression (EDGE), it allows for the generation of transgenic animals targeting the cell types of any brain region with far greater specificity than can be obtained with native promoters. Moreover, their small size allows for the generation of cell-specific viral vectors, conceivably enabling circuit-specific manipulations to any species.

Decoding pluripotency: Genetic screens to interrogate the acquisition, maintenance, and exit of pluripotency

Pluripotent stem cells have the ability to unlimitedly self-renew and differentiate to any somatic cell lineage. A number of systems biology approaches have been used to define this pluripotent state. Complementary to systems level characterization, genetic screens offer a unique avenue to functionally interrogate the pluripotent state and identify the key players in pluripotency acquisition and maintenance, exit of pluripotency, and lineage differentiation. Here we review how genetic screens have helped us decode pluripotency regulation. We will summarize results from RNA interference (RNAi) based screens, discuss recent advances in CRISPR/Cas-based genetic perturbation methods, and how these advances have made it possible to more comprehensively interrogate pluripotency and differentiation through genetic screens. Such investigations will not only provide a better understanding of this unique developmental state, but may enhance our ability to use pluripotent stem cells as an experimental model to study human development and disease progression. Functional interrogation of pluripotency also provides a valuable roadmap for utilizing genetic perturbation to gain systems level understanding of additional cellular states, from later stages of development to pathological disease states. This article is categorized under: Developmental Biology > Stem Cell Biology and Regeneration Developmental Biology > Developmental Processes in Health and Disease Biological Mechanisms > Cell Fates.

ETph: enhancers and their targets in pig and human database

Enhancers, as the genomic non-coding sequences, play a key role in the activation of gene expression. They have been widely identified in the human genome. Pig is an important biomedical model for human health. Few studies have been performed to explore the enhancers in the pig genome. The human enhancer information may be useful to identify enhancers in the pig genome. In addition, the genetic background of pig traits could be useful to annotate human enhancers and diseases. Thus, in order to further study enhancers and their potential roles in human and pig, we developed a public database, ETph (Enhancers and their Targets in pig and human). ETph integrates the information on human enhancers, pig putative enhancers, target genes, pig QTL terms, human diseases, GO terms and the KEGG pathway. A total of 25 182 enhancers were identified in the pig genome using the human homology sequence information. Among them, 6232 high-confidence enhancers were used to build the ETph. ETph provides a convenient platform to search, browse and download data. Moreover, a web-based analytical tool was designed to visualize networks and topology graphs among pig putative enhancers, target genes, pig QTL traits and human diseases. ETph might provide a useful tool for researchers to investigate the genetic background of pig traits and human diseases. ETph is freely accessible at http://klab.sjtu.edu.cn/enhancer/.

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.

Cis-control of Six1 expression in neural crest cells during craniofacial development

BACKGROUND

Six1 is a transcriptional factor that plays an important role in embryonic development. Mouse and chick embryos deficient for Six1 have multiple craniofacial anomalies in the facial bones and cartilages. Multiple Six1 enhancers have been identified, but none of them has been reported to be active in the maxillary and mandibular process.

RESULTS

We studied two Six1 enhancers in the chick neural crest tissues during craniofacial development. We showed that two evolutionarily conserved enhancers, Six1E1 and Six1E2, act synergistically. Neither Six1E1 nor Six1E2 alone can drive enhancer reporter signal in the maxillary or mandibular processes. However, their combination, Six1E, showed robust enhancer activity in these tissues. Similar reporter signal can also be driven by the mouse homolog of Six1E. Mutations of multiple conserved transcriptional factor binding sites altered the enhancer activity of Six1E, especially mutation of the LIM homeobox binding site, dramatically reduced the enhancer activity, implying that the Lhx protein family be an important regulator of Six1 expression.

CONCLUSION

This study, for the first time, described the synergistic activation of two Six1 enhancers in the maxillary and mandibular processes and will facilitate more detailed studies of the regulation of Six1 in craniofacial development.

On the traces of tcf12: Investigation of the gene expression pattern during development and cranial suture patterning in zebrafish (Danio rerio)

The transcription factor 12 (tcf12) is a basic Helix-Loop-Helix protein (bHLH) of the E-protein family, proven to play an important role in developmental processes like neurogenesis, mesoderm formation, and cranial vault development. In humans, mutations in TCF12 lead to craniosynostosis, a congenital birth disorder characterized by the premature fusion of one or several of the cranial sutures. Current research has been primarily focused on functional studies of TCF12, hence the cellular expression profile of this gene during embryonic development and early stages of ossification remains poorly understood. Here we present the establishment and detailed analysis of two transgenic tcf12:EGFP fluorescent zebrafish (Danio rerio) reporter lines. Using these transgenic lines, we analyzed the general spatiotemporal expression pattern of tcf12 during different developmental stages and put emphasis on skeletal development and cranial suture patterning. We identified robust tcf12 promoter-driven EGFP expression in the central nervous system (CNS), the heart, the pronephros, and the somites of zebrafish embryos. Additionally, expression was observed inside the muscles and bones of the viscerocranium in juvenile and adult fish. During cranial vault development, the transgenic fish show a high amount of tcf12 expressing cells at the growth fronts of the ossifying frontal and parietal bones and inside the emerging cranial sutures. Subsequently, we tested the transcriptional activity of three evolutionary conserved non-coding elements (CNEs) located in the tcf12 locus by transient transgenic assays and compared their in vivo activity to the expression pattern determined in the transgenic tcf12:EGFP lines. We could validate two of them as tcf12 enhancer elements driving specific gene expression in the CNS during embryogenesis. Our newly established transgenic lines enhance the understanding of tcf12 gene regulation and open up the possibilities for further functional investigation of these novel tcf12 enhancer elements in zebrafish.

Identification of a 42-bp heart-specific enhancer of the notch1b gene in zebrafish embryos

BACKGROUND

NOTCH1 plays a key role in the differentiation of ventricles, and mutations are strongly associated with both sporadic and familial bicuspid aortic valves. However, few heart-specific enhancers have been identified to date.

RESULTS

In this study, we investigated evolutionary conserved regions (ECRs) that might act as potential enhancers within the region approximately 150-kb upstream and downstream of the NOTCH1 gene. Functional validation revealed that one 127-bp ECR located ~85-kb downstream of the NOTCH1 gene drives green fluorescent protein expression in the zebrafish embryo heart. Transcription factor (TF) prediction and core TF distribution analyses were performed to identify the core region. Dissection of ECR3 was performed to identify the 42-bp sequence, which is sufficient for heart-specific expression. In situ hybridization experiments showed that notch1b is expressed in the heart. Overexpression experiments in cells indicated that NKX2-5 is critical for enhancer activity. Mutation of the NKX-5 binding site significantly decreased reporter gene expression. Next, compared with the commonly used myocardium-labeled zebrafish transgenic strain Tg(cmlc2: mCherry), this 42-bp enhancer-labeled stable line mediated a similar expression pattern but with a smaller core region.

CONCLUSION

This study identified a 42-bp heart-specific enhancer near the NOTCH1 gene and further verified its functional targeting by NKX2-5.

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/.

Pairs of Adjacent Conserved Noncoding Elements Separated by Conserved Genomic Distances Act as Cis-Regulatory Units

Comparative genomic studies have identified thousands of conserved noncoding elements (CNEs) in the mammalian genome, many of which have been reported to exert cis-regulatory activity. We analyzed ∼5,500 pairs of adjacent CNEs in the human genome and found that despite divergence at the nucleotide sequence level, the inter-CNE distances of the pairs are under strong evolutionary constraint, with inter-CNE sequences featuring significantly lower transposon densities than expected. Further, we show that different degrees of conservation of the inter-CNE distance are associated with distinct cis-regulatory functions at the CNEs. Specifically, the CNEs in pairs with conserved and mildly contracted inter-CNE sequences are the most likely to represent active or poised enhancers. In contrast, CNEs in pairs with extremely contracted or expanded inter-CNE sequences are associated with no cis-regulatory activity. Furthermore, we observed that functional CNEs in a pair have very similar epigenetic profiles, hinting at a functional relationship between them. Taken together, our results support the existence of epistatic interactions between adjacent CNEs that are distance-sensitive and disrupted by transposon insertions and deletions, and contribute to our understanding of the selective forces acting on cis-regulatory elements, which are crucial for elucidating the molecular mechanisms underlying adaptive evolution and human genetic diseases.

The Molecular Revolution in Cutaneous Biology: EDC and Locus Control

The epidermal differentiation complex (EDC) locus consists of a cluster of genes important for the terminal differentiation of the epidermis. While early studies identified the functional importance of individual EDC genes, the recognition of the EDC genes as a cluster with its shared biology, homology, and physical linkage was pivotal to later studies that investigated the transcriptional regulation of the locus. Evolutionary conservation of the EDC and the transcriptional activation during epidermal differentiation suggested a cis-regulatory mechanism via conserved noncoding elements or enhancers. This line of pursuit led to the identification of CNE 923, an epidermal-specific enhancer that was found to mediate chromatin remodeling of the EDC in an AP-1 dependent manner. These genomic studies, as well as the advent of high-throughput sequencing and genome engineering techniques, have paved the way for future investigation into enhancer-mediated regulatory networks in cutaneous biology.

Ever-Changing Landscapes: Transcriptional Enhancers in Development and Evolution

A class of cis-regulatory elements, called enhancers, play a central role in orchestrating spatiotemporally precise gene-expression programs during development. Consequently, divergence in enhancer sequence and activity is thought to be an important mediator of inter- and intra-species phenotypic variation. Here, we give an overview of emerging principles of enhancer function, current models of enhancer architecture, genomic substrates from which enhancers emerge during evolution, and the influence of three-dimensional genome organization on long-range gene regulation. We discuss intricate relationships between distinct elements within complex regulatory landscapes and consider their potential impact on specificity and robustness of transcriptional regulation.

An Emerging Regulatory Landscape for Skeletal Development

Skeletal development creates the physical framework that shapes our body and its actions. In the past two decades, genetic studies have provided important insights into the molecular processes at play, including the roles of signaling pathways and transcriptional effectors that coordinate an orderly, progressive emergence and expansion of distinct cartilage and bone cell fates in an invariant temporal and spatial pattern for any given skeletal element within that specific vertebrate species. Genome-scale studies have provided additional layers of understanding, moving from individual genes to the gene regulatory landscape, integrating regulatory information through cis-regulatory modules into cell type-specific gene regulatory programs. This review discusses our current understanding of the transcriptional control of mammalian skeletal development, focusing on recent genome-scale studies.

Dynamic Control of Enhancer Repertoires Drives Lineage and Stage-Specific Transcription during Hematopoiesis

Enhancers are the primary determinants of cell identity, but the regulatory components controlling enhancer turnover during lineage commitment remain largely unknown. Here we compare the enhancer landscape, transcriptional factor occupancy, and transcriptomic changes in human fetal and adult hematopoietic stem/progenitor cells and committed erythroid progenitors. We find that enhancers are modulated pervasively and direct lineage- and stage-specific transcription. GATA2-to-GATA1 switch is prevalent at dynamic enhancers and drives erythroid enhancer commissioning. Examination of lineage-specific enhancers identifies transcription factors and their combinatorial patterns in enhancer turnover. Importantly, by CRISPR/Cas9-mediated genomic editing, we uncover functional hierarchy of constituent enhancers within the SLC25A37 super-enhancer. Despite indistinguishable chromatin features, we reveal through genomic editing the functional diversity of several GATA switch enhancers in which enhancers with opposing functions cooperate to coordinate transcription. Thus, genome-wide enhancer profiling coupled with in situ enhancer editing provide critical insights into the functional complexity of enhancers during development.

EMERGE: a flexible modelling framework to predict genomic regulatory elements from genomic signatures

Regulatory DNA elements, short genomic segments that regulate gene expression, have been implicated in developmental disorders and human disease. Despite this clinical urgency, only a small fraction of the regulatory DNA repertoire has been confirmed through reporter gene assays. The overall success rate of functional validation of candidate regulatory elements is low. Moreover, the number and diversity of datasets from which putative regulatory elements can be identified is large and rapidly increasing. We generated a flexible and user-friendly tool to integrate the information from different types of genomic datasets, e.g. ATAC-seq, ChIP-seq, conservation, aiming to increase the ease and success rate of functional prediction. To this end, we developed the EMERGE program that merges all datasets that the user considers informative and uses a logistic regression framework, based on validated functional elements, to set optimal weights to these datasets. ROC curve analysis shows that a combination of datasets leads to improved prediction of tissue-specific enhancers in human, mouse and Drosophila genomes. Functional assays based on this prediction can be expected to have substantially higher success rates. The resulting integrated signal for prediction of functional elements can be plotted in a build-in genome browser or exported for further analysis.

Enhancer Turnover Is Associated with a Divergent Transcriptional Response to Glucocorticoid in Mouse and Human Macrophages

Phenotypic differences between individuals and species are controlled in part through differences in expression of a relatively conserved set of genes. Genes expressed in the immune system are subject to especially powerful selection. We have investigated the evolution of both gene expression and candidate enhancers in human and mouse macrophages exposed to glucocorticoid (GC), a regulator of innate immunity and an important therapeutic agent. Our analyses revealed a very limited overlap in the repertoire of genes responsive to GC in human and mouse macrophages. Peaks of inducible binding of the GC receptor (GR) detected by chromatin immunoprecipitation-Seq correlated with induction, but not repression, of target genes in both species, occurred at distal regulatory sites not promoters, and were strongly enriched for the consensus GR-binding motif. Turnover of GR binding between mice and humans was associated with gain and loss of the motif. There was no detectable signal of positive selection at species-specific GR binding sites, but clear evidence of purifying selection at the small number of conserved sites. We conclude that enhancer divergence underlies the difference in transcriptional activation after GC treatment between mouse and human macrophages. Only the shared inducible loci show evidence of selection, and therefore these loci may be important for the subset of responses to GC that is shared between species.

Progress and challenges in bioinformatics approaches for enhancer identification

Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.

Handling Permutation in Sequence Comparison: Genome-Wide Enhancer Prediction in Vertebrates by a Novel Non-Linear Alignment Scoring Principle

Enhancers have been described to evolve by permutation without changing function. This has posed the problem of how to predict enhancer elements that are hidden from alignment-based approaches due to the loss of co-linearity. Alignment-free algorithms have been proposed as one possible solution. However, this approach is hampered by several problems inherent to its underlying working principle. Here we present a new approach, which combines the power of alignment and alignment-free techniques into one algorithm. It allows the prediction of enhancers based on the query and target sequence only, no matter whether the regulatory logic is co-linear or reshuffled. To test our novel approach, we employ it for the prediction of enhancers across the evolutionary distance of ~450Myr between human and medaka. We demonstrate its efficacy by subsequent in vivo validation resulting in 82% (9/11) of the predicted medaka regions showing reporter activity. These include five candidates with partially co-linear and four with reshuffled motif patterns. Orthology in flanking genes and conservation of the detected co-linear motifs indicates that those candidates are likely functionally equivalent enhancers. In sum, our results demonstrate that the proposed principle successfully predicts mutated as well as permuted enhancer regions at an encouragingly high rate.

Variation in vertebrate cis-regulatory elements in evolution and disease

Much of the genetic information that drives animal diversity lies within the vast non-coding regions of the genome. Multi-species sequence conservation in non-coding regions of the genome flags important regulatory elements and more recently, techniques that look for functional signatures predicted for regulatory sequences have added to the identification of thousands more. For some time, biologists have argued that changes in cis-regulatory sequences creates the basic genetic framework for evolutionary change. Recent advances support this notion and show that there is extensive genomic variability in non-coding regulatory elements associated with trait variation, speciation and disease.

Analysis of 5' gene regions reveals extraordinary conservation of novel non-coding sequences in a wide range of animals

Background

Phylogenetic footprinting is a comparative method based on the principle that functional sequence elements will acquire fewer mutations over time than non-functional sequences. Successful comparisons of distantly related species will thus yield highly important sequence elements likely to serve fundamental biological roles. RNA regulatory elements are less well understood than those in DNA. In this study we use the emerging model organism Nasonia vitripennis, a parasitic wasp, in a comparative analysis against 12 insect genomes to identify deeply conserved non-coding elements (CNEs) conserved in large groups of insects, with a focus on 5’ UTRs and promoter sequences.

Results

We report the identification of 322 CNEs conserved across a broad range of insect orders. The identified regions are associated with regulatory and developmental genes, and contain short footprints revealing aspects of their likely function in translational regulation. The most ancient regions identified in our analysis were all found to overlap transcribed regions of genes, reflecting stronger conservation of translational regulatory elements than transcriptional elements. Further expanding sequence analyses to non-insect species we also report the discovery of, to our knowledge, the two oldest and most ubiquitous CNE’s yet described in the animal kingdom (700 MYA). These ancient conserved non-coding elements are associated with the two ribosomal stalk genes, RPLP1 and RPLP2, and were very likely functional in some of the earliest animals.

Conclusions

We report the identification of the most deeply conserved CNE’s found to date, and several other deeply conserved elements which are without exception, part of 5’ untranslated regions of transcripts, and occur in a number of key translational regulatory genes, highlighting translational regulation of translational regulators as a conserved feature of insect genomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0499-6) contains supplementary material, which is available to authorized users.

DELTA: A Distal Enhancer Locating Tool Based on AdaBoost Algorithm and Shape Features of Chromatin Modifications

Accurate identification of DNA regulatory elements becomes an urgent need in the post-genomic era. Recent genome-wide chromatin states mapping efforts revealed that DNA elements are associated with characteristic chromatin modification signatures, based on which several approaches have been developed to predict transcriptional enhancers. However, their practical application is limited by incomplete extraction of chromatin features and model inconsistency for predicting enhancers across different cell types. To address these issues, we define a set of non-redundant shape features of histone modifications, which shows high consistency across cell types and can greatly reduce the dimensionality of feature vectors. Integrating shape features with a machine-learning algorithm AdaBoost, we developed an enhancer predicting method, DELTA (Distal Enhancer Locating Tool based on AdaBoost). We show that DELTA significantly outperforms current enhancer prediction methods in prediction accuracy on different datasets and can predict enhancers in one cell type using models trained in other cell types without loss of accuracy. Overall, our study presents a novel framework for accurately identifying enhancers from epigenetic data across multiple cell types.

Regulation of cerebral cortical neurogenesis by the Pax6 transcription factor

Understanding brain development remains a major challenge at the heart of understanding what makes us human. The neocortex, in evolutionary terms the newest part of the cerebral cortex, is the seat of higher cognitive functions. Its normal development requires the production, positioning, and appropriate interconnection of very large numbers of both excitatory and inhibitory neurons. Pax6 is one of a relatively small group of transcription factors that exert high-level control of cortical development, and whose mutation or deletion from developing embryos causes major brain defects and a wide range of neurodevelopmental disorders. Pax6 is very highly conserved between primate and non-primate species, is expressed in a gradient throughout the developing cortex and is essential for normal corticogenesis. Our understanding of Pax6’s functions and the cellular processes that it regulates during mammalian cortical development has significantly advanced in the last decade, owing to the combined application of genetic and biochemical analyses. Here, we review the functional importance of Pax6 in regulating cortical progenitor proliferation, neurogenesis, and formation of cortical layers and highlight important differences between rodents and primates. We also review the pathological effects of PAX6 mutations in human neurodevelopmental disorders. We discuss some aspects of Pax6’s molecular actions including its own complex transcriptional regulation, the distinct molecular functions of its splice variants and some of Pax6’s known direct targets which mediate its actions during cortical development.

The noncoding human genome and the future of personalised medicine

Non-coding cis-regulatory sequences act as the ‘eyes’ of the genome and their role is to perceive, organise and relay cellular communication information to RNA polymerase II at gene promoters. The evolution of these sequences, that include enhancers, silencers, insulators and promoters, has progressed in multicellular organisms to the extent that cis-regulatory sequences make up as much as 10% of the human genome. Parallel evidence suggests that 75% of polymorphisms associated with heritable disease occur within predicted cis-regulatory sequences that effectively alter the ‘perception’ of cis-regulatory sequences or render them blind to cell communication cues. Cis-regulatory sequences also act as major functional targets of epigenetic modification thus representing an important conduit through which changes in DNA-methylation affects disease susceptibility. The objectives of the current review are (1) to describe what has been learned about identifying and characterising cis-regulatory sequences since the sequencing of the human genome; (2) to discuss their role in interpreting cell signalling pathways pathways; and (3) outline how this role may be altered by polymorphisms and epigenetic changes. We argue that the importance of the cis-regulatory genome for the interpretation of cellular communication pathways cannot be overstated and understanding its role in health and disease will be critical for the future development of personalised medicine.

A 'tool box' for deciphering neuronal circuits in the developing chick spinal cord

The genetic dissection of spinal circuits is an essential new means for understanding the neural basis of mammalian behavior. Molecular targeting of specific neuronal populations, a key instrument in the genetic dissection of neuronal circuits in the mouse model, is a complex and time-demanding process. Here we present a circuit-deciphering 'tool box' for fast, reliable and cheap genetic targeting of neuronal circuits in the developing spinal cord of the chick. We demonstrate targeting of motoneurons and spinal interneurons, mapping of axonal trajectories and synaptic targeting in both single and populations of spinal interneurons, and viral vector-mediated labeling of pre-motoneurons. We also demonstrate fluorescent imaging of the activity pattern of defined spinal neurons during rhythmic motor behavior, and assess the role of channel rhodopsin-targeted population of interneurons in rhythmic behavior using specific photoactivation.

Functional analysis of limb transcriptional enhancers in the mouse

Transcriptional enhancers are genomic sequences bound by transcription factors that act together with basal transcriptional machinery to regulate gene transcription. Several high-throughput methods have generated large datasets of tissue-specific enhancer sequences with putative roles in developmental processes. However, few enhancers have been deleted from the genome to determine their roles in development. To understand the roles of two enhancers active in the mouse embryonic limb bud we deleted them from the genome. Although the genes regulated by these enhancers are unknown, they were selected because they were identified in a screen for putative limb bud-specific enhancers associated with p300, an acetyltransferase that participates in protein complexes that promote active transcription, and because the orthologous human enhancers (H1442 and H280) drive distinct lacZ expression patterns in limb buds of embryonic day (E) 11.5 transgenic mice. We show that the orthologous mouse sequences, M1442 and M280, regulate dynamic expression in the developing limb. Although significant transcriptional differences in enhancer-proximal genes in embryonic limb buds accompany the deletion of M1442 and M280 no gross limb malformations during embryonic development were observed, demonstrating that M1442 and M280 are not required for mouse limb development. However, M280 is required for the development and/or maintenance of body size; M280 mice are significantly smaller than controls. M280 also harbors an "ultraconserved" sequence that is identical between human, rat, and mouse. This is the first report of a phenotype resulting from the deletion of an ultraconserved element. These studies highlight the importance of determining enhancer regulatory function by experiments that manipulate them in situ and suggest that some of an enhancer's regulatory capacities may be developmentally tolerated rather than developmentally required.

Reconfiguration of nucleosome-depleted regions at distal regulatory elements accompanies DNA methylation of enhancers and insulators in cancer

It is well established that cancer-associated epigenetic repression occurs concomitant with CpG island hypermethylation and loss of nucleosomes at promoters, but the role of nucleosome occupancy and epigenetic reprogramming at distal regulatory elements in cancer is still poorly understood. Here, we evaluate the scope of global epigenetic alterations at enhancers and insulator elements in prostate and breast cancer cells using simultaneous genome-wide mapping of DNA methylation and nucleosome occupancy (NOMe-seq). We find that the genomic location of nucleosome-depleted regions (NDRs) is mostly cell type specific and preferentially found at enhancers in normal cells. In cancer cells, however, we observe a global reconfiguration of NDRs at distal regulatory elements coupled with a substantial reorganization of the cancer methylome. Aberrant acquisition of nucleosomes at enhancer-associated NDRs is associated with hypermethylation and epigenetic silencing marks, and conversely, loss of nucleosomes with demethylation and epigenetic activation. Remarkably, we show that nucleosomes remain strongly organized and phased at many facultative distal regulatory elements, even in the absence of a NDR as an anchor. Finally, we find that key transcription factor (TF) binding sites also show extensive peripheral nucleosome phasing, suggesting the potential for TFs to organize NDRs genome-wide and contribute to deregulation of cancer epigenomes. Together, our findings suggest that “decommissioning” of NDRs and TFs at distal regulatory elements in cancer cells is accompanied by DNA hypermethylation susceptibility of enhancers and insulator elements, which in turn may contribute to an altered genome-wide architecture and epigenetic deregulation in malignancy.

The most deeply conserved noncoding sequences in plants serve similar functions to those in vertebrates despite large differences in evolutionary rates

In vertebrates, conserved noncoding elements (CNEs) are functionally constrained sequences that can show striking conservation over >400 million years of evolutionary distance and frequently are located megabases away from target developmental genes. Conserved noncoding sequences (CNSs) in plants are much shorter, and it has been difficult to detect conservation among distantly related genomes. In this article, we show not only that CNS sequences can be detected throughout the eudicot clade of flowering plants, but also that a subset of 37 CNSs can be found in all flowering plants (diverging ∼170 million years ago). These CNSs are functionally similar to vertebrate CNEs, being highly associated with transcription factor and development genes and enriched in transcription factor binding sites. Some of the most highly conserved sequences occur in genes encoding RNA binding proteins, particularly the RNA splicing-associated SR genes. Differences in sequence conservation between plants and animals are likely to reflect differences in the biology of the organisms, with plants being much more able to tolerate genomic deletions and whole-genome duplication events due, in part, to their far greater fecundity compared with vertebrates.

Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation

A key finding of the ENCODE project is that the enhancer landscape of mammalian cells undergoes marked alterations during ontogeny. However, the nature and extent of these changes are unclear. As part of the NIH Mouse Regulome Project, we here combined DNaseI hypersensitivity, ChIP-seq, and ChIA-PET technologies to map the promoter-enhancer interactomes of pluripotent ES cells and differentiated B lymphocytes. We confirm that enhancer usage varies widely across tissues. Unexpectedly, we find that this feature extends to broadly transcribed genes, including Myc and Pim1 cell-cycle regulators, which associate with an entirely different set of enhancers in ES and B cells. By means of high-resolution CpG methylomes, genome editing, and digital footprinting, we show that these enhancers recruit lineage-determining factors. Furthermore, we demonstrate that the turning on and off of enhancers during development correlates with promoter activity. We propose that organisms rely on a dynamic enhancer landscape to control basic cellular functions in a tissue-specific manner.