Comparative analysis of regulatory information and circuits across distant species

scNanoSeq-CUT&Tag: a single-cell long-read CUT&Tag sequencing method for efficient chromatin modification profiling within individual cells

Chromatin modifications are fundamental epigenetic marks that determine genome functions, but it remains challenging to profile those of repetitive elements and complex genomic regions. Here, we develop scNanoSeq-CUT&Tag, a streamlined method, by adapting modified cleavage under targets and tagmentation (CUT&Tag) to the nanopore sequencing platform for genome-wide chromatin modification profiling within individual cells. We show that scNanoSeq-CUT&Tag can accurately profile histone marks and transcription factor occupancy patterns at single-cell resolution as well as distinguish different cell types. scNanoSeq-CUT&Tag efficiently maps the allele-specific chromatin modifications and allows analysis of their neighboring region co-occupancy patterns within individual cells. Moreover, scNanoSeq-CUT&Tag can accurately detect chromatin modifications for individual copies of repetitive elements in both human and mouse genomes. Overall, we prove that scNanoSeq-CUT&Tag is a valuable single-cell tool for efficiently profiling histone marks and transcription factor occupancies, especially for previously poorly studied complex genomic regions and blacklist genomic regions.

Comparative analysis of testicular fusion in Spodoptera litura (cutworm) and Bombyx mori (silkworm): Histological and transcriptomic insights

Spodoptera litura commonly known as the cutworm, is among the most destructive lepidopteran pests affecting over 120 plants species. The powerful destructive nature of this lepidopteran is attributable to its high reproductive capacity. The testicular fusion that occurs during metamorphosis from larvae to pupa in S.litura positively influences the reproductive success of the offspring. In contrast, Bombyx mori, the silkworm, retains separate testes throughout its life and does not undergo this fusion process. Microscopic examination reveals that during testicular fusion in S.litura, the peritoneal sheath becomes thinner and more translucent, whereas in B.mori, the analogous region thickens. The outer basement membrane in S.litura exhibits fractures, discontinuity, and uneven thickness accompanied by a significant presence of cellular secretions, large cell size, increased vesicles, liquid droplets, and a proliferation of rough endoplasmic reticulum and mitochondria. In contrast, the testicular peritoneal sheath of B.mori at comparable developmental stage exhibits minimal change. Comparative transcriptomic analysis of the testicular peritoneal sheath reveals a substantial difference in gene expression between the two species. The disparity in differential expressed genes (DEGs) is linked to an enrichment of numerous transcription factors, intracellular signaling pathways involving Ca2+ and GTPase, as well as intracellular protein transport and signaling pathways. Meanwhile, structural proteins including actin, chitin-binding proteins, membrane protein fractions, cell adhesion, extracellular matrix proteins are predominantly identified. Moreover, the study highlights the enrichment of endopeptidases, serine proteases, proteolytic enzymes and matrix metalloproteins, which may play a role in the degradation of the outer membrane. Five transcription factors-Slforkhead, Slproline, Slcyclic, Slsilk, and SlD-ETS were identified, and their expression pattern were confirmed by qRT-PCR. they are candidates for participating in the regulation of testicular fusion. Our findings underscore significant morphological and trancriptomic variation in the testicular peritoneal sheath of S.litura compared to the silkworm, with substantial changes at the transcriptomic level coinciding with testicular fusion. The research provides valuable clues for understanding the complex mechanisms underlying this unique phenomenon in insects.

Identification of Gene Regulatory Networks in B-Cell Progenitor Differentiation and Leukemia

Pro-B- and pre-B-cells are consecutive entities in early B-cell development, representing cells of origin for B-cell precursor acute lymphoid leukemia (BCP-ALL). Normal B-cell differentiation is critically regulated by specific transcription factors (TFs). Accordingly, TF-encoding genes are frequently deregulated or mutated in BCP-ALL. Recently, we described TF-codes which delineate physiological activities of selected groups of TF-encoding genes in hematopoiesis including B-cell development. Here, we exploited these codes to uncover regulatory connections between particular TFs in pro-B- and pre-B-cells via an analysis of developmental TFs encoded by NKL and TALE homeobox genes and by ETS and T-box genes. Comprehensive expression analyses in BCP-ALL cell lines helped identify validated models to study their mutual regulation in vitro. Knockdown and overexpression experiments and subsequent RNA quantification of TF-encoding genes in selected model cell lines revealed activating, inhibitory or absent connections between nine TFs operating in early B-cell development, including HLX, MSX1, IRX1, MEIS1, ETS2, ERG, SPIB, EOMES, and TBX21. In addition, genomic profiling revealed BCP-ALL subtype-specific copy number alterations of ERG at 21q22, while a deletion of the TGFbeta-receptor gene TGFBR2 at 3p24 resulted in an upregulation of EOMES. Finally, we combined the data to uncover gene regulatory networks which control normal differentiation of early B-cells, collectively endorsing more detailed evaluation of BCP-ALL subtypes.

Cactus: A user-friendly and reproducible ATAC-Seq and mRNA-Seq analysis pipeline for data preprocessing, differential analysis, and enrichment analysis

The ever decreasing cost of Next-Generation Sequencing coupled with the emergence of efficient and reproducible analysis pipelines has rendered genomic methods more accessible. However, downstream analyses are basic or missing in most workflows, creating a significant barrier for non-bioinformaticians. To help close this gap, we developed Cactus, an end-to-end pipeline for analyzing ATAC-Seq and mRNA-Seq data, either separately or jointly. Its Nextflow-, container-, and virtual environment-based architecture ensures efficient and reproducible analyses. Cactus preprocesses raw reads, conducts differential analyses between conditions, and performs enrichment analyses in various databases, including DNA-binding motifs, ChIP-Seq binding sites, chromatin states, and ontologies. We demonstrate the utility of Cactus in a multi-modal and multi-species case study as well as by showcasing its unique capabilities as compared to other ATAC-Seq pipelines. In conclusion, Cactus can assist researchers in gaining comprehensive insights from chromatin accessibility and gene expression data in a quick, user-friendly, and reproducible manner.

The Iroquois (Iro/Irx) homeobox genes are conserved Hox targets involved in motor neuron development

The Iroquois (Iro/Irx) homeobox genes encode transcription factors with fundamental roles in animal development. Despite their link to various congenital conditions in humans, our understanding of Iro/Irx gene expression, function, and regulation remains incomplete. Here, we conducted a systematic expression analysis of all six mouse Irx genes in the embryonic spinal cord. We found five Irx genes (Irx1, Irx2, Irx3, Irx5, and Irx6) to be confined mostly to ventral spinal domains, offering new molecular markers for specific groups of post-mitotic motor neurons (MNs). Further, we engineered Irx2, Irx5, and Irx6 mouse mutants and uncovered essential but distinct roles for Irx2 and Irx6 in MN development. Last, we found that the highly conserved regulators of MN development across species, the HOX proteins, directly control Irx gene expression both in mouse and C. elegans MNs, critically expanding the repertoire of HOX target genes in the developing nervous system. Altogether, our study provides important insights into Iro/Irx expression and function in the developing spinal cord, and uncovers an ancient gene regulatory relationship between HOX and Iro/Irx genes.

The ctenophore Mnemiopsis leidyi deploys a rapid injury response dating back to the last common animal ancestor

Regenerative potential is widespread but unevenly distributed across animals. However, our understanding of the molecular mechanisms underlying regenerative processes is limited to a handful of model organisms, restricting robust comparative analyses. Here, we conduct a time course of RNA-seq during whole body regeneration in Mnemiopsis leidyi (Ctenophora) to uncover gene expression changes that correspond with key events during the regenerative timeline of this species. We identified several genes highly enriched in this dataset beginning as early as 10 minutes after surgical bisection including transcription factors in the early timepoints, peptidases in the middle timepoints, and cytoskeletal genes in the later timepoints. We validated the expression of early response transcription factors by whole mount in situ hybridization, showing that these genes exhibited high expression in tissues surrounding the wound site. These genes exhibit a pattern of transient upregulation as seen in a variety of other organisms, suggesting that they may be initiators of an ancient gene regulatory network linking wound healing to the initiation of a regenerative response.

Binding profiles for 954 Drosophila and C. elegans transcription factors reveal tissue specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

The homeodomain transcriptional regulator DVE-1 directs a program for synapse elimination during circuit remodeling

The elimination of synapses during circuit remodeling is critical for brain maturation; however, the molecular mechanisms directing synapse elimination and its timing remain elusive. We show that the transcriptional regulator DVE-1, which shares homology with special AT-rich sequence-binding (SATB) family members previously implicated in human neurodevelopmental disorders, directs the elimination of juvenile synaptic inputs onto remodeling C. elegans GABAergic neurons. Juvenile acetylcholine receptor clusters and apposing presynaptic sites are eliminated during the maturation of wild-type GABAergic neurons but persist into adulthood in dve-1 mutants, producing heightened motor connectivity. DVE-1 localization to GABAergic nuclei is required for synapse elimination, consistent with DVE-1 regulation of transcription. Pathway analysis of putative DVE-1 target genes, proteasome inhibitor, and genetic experiments implicate the ubiquitin-proteasome system in synapse elimination. Together, our findings define a previously unappreciated role for a SATB family member in directing synapse elimination during circuit remodeling, likely through transcriptional regulation of protein degradation processes.

ADAR-mediated regulation of PQM-1 expression in neurons impacts gene expression throughout C. elegans and regulates survival from hypoxia

The ability to alter gene expression programs in response to changes in environmental conditions is central to the ability of an organism to thrive. For most organisms, the nervous system serves as the master regulator in communicating information about the animal's surroundings to other tissues. The information relay centers on signaling pathways that cue transcription factors in a given cell type to execute a specific gene expression program, but also provide a means to signal between tissues. The transcription factor PQM-1 is an important mediator of the insulin signaling pathway contributing to longevity and the stress response as well as impacting survival from hypoxia. Herein, we reveal a novel mechanism for regulating PQM-1 expression specifically in neural cells of larval animals. Our studies reveal that the RNA-binding protein (RBP), ADR-1, binds to pqm-1 mRNA in neural cells. This binding is regulated by the presence of a second RBP, ADR-2, which when absent leads to reduced expression of both pqm-1 and downstream PQM-1 activated genes. Interestingly, we find that neural pqm-1 expression is sufficient to impact gene expression throughout the animal and affect survival from hypoxia, phenotypes that we also observe in adr mutant animals. Together, these studies reveal an important posttranscriptional gene regulatory mechanism in Caenorhabditis elegans that allows the nervous system to sense and respond to environmental conditions to promote organismal survival from hypoxia.

ADARs employ a neural-specific mechanism to regulate PQM-1 expression and survival from hypoxia

The ability to alter gene expression programs in response to changes in environmental conditions is central to the ability of an organism to thrive. For most organisms, the nervous system serves as the master regulator in communicating information about the animal's surroundings to other tissues. The information relay centers on signaling pathways that cue transcription factors in a given cell type to execute a specific gene expression program, but also provide a means to signal between tissues. The transcription factor PQM-1 is an important mediator of the insulin signaling pathway contributing to longevity and the stress response as well as impacting survival from hypoxia. Herein, we reveal a novel mechanism for regulating PQM-1 expression specifically in neural cells of larval animals. Our studies reveal that the RNA binding protein, ADR-1, binds to pqm-1 mRNA in neural cells. This binding is regulated by the presence of a second RNA binding protein, ADR-2, which when absent leads to reduced expression of both pqm-1 and downstream PQM-1 activated genes. Interestingly, we find that neural pqm-1 expression is sufficient to impact gene expression throughout the animal and affect survival from hypoxia; phenotypes that we also observe in adr mutant animals. Together, these studies reveal an important post-transcriptional gene regulatory mechanism that allows the nervous system to sense and respond to environmental conditions to promote organismal survival from hypoxia.

Systematic integration of protein-affecting mutations, gene fusions, and copy number alterations into a comprehensive somatic mutational profile

Somatic mutations occur as random genetic changes in genes through protein-affecting mutations (PAMs), gene fusions, or copy number alterations (CNAs). Mutations of different types can have a similar phenotypic effect (i.e., allelic heterogeneity) and should be integrated into a unified gene mutation profile. We developed OncoMerge to fill this niche of integrating somatic mutations to capture allelic heterogeneity, assign a function to mutations, and overcome known obstacles in cancer genetics. Application of OncoMerge to TCGA Pan-Cancer Atlas increased detection of somatically mutated genes and improved the prediction of the somatic mutation role as either activating or loss of function. Using integrated somatic mutation matrices increased the power to infer gene regulatory networks and uncovered the enrichment of switch-like feedback motifs and delay-inducing feedforward loops. These studies demonstrate that OncoMerge efficiently integrates PAMs, fusions, and CNAs and strengthens downstream analyses linking somatic mutations to cancer phenotypes.

Analysis of the P. lividus sea urchin genome highlights contrasting trends of genomic and regulatory evolution in deuterostomes

Sea urchins are emblematic models in developmental biology and display several characteristics that set them apart from other deuterostomes. To uncover the genomic cues that may underlie these specificities, we generated a chromosome-scale genome assembly for the sea urchin Paracentrotus lividus and an extensive gene expression and epigenetic profiles of its embryonic development. We found that, unlike vertebrates, sea urchins retained ancestral chromosomal linkages but underwent very fast intrachromosomal gene order mixing. We identified a burst of gene duplication in the echinoid lineage and showed that some of these expanded genes have been recruited in novel structures (water vascular system, Aristotle's lantern, and skeletogenic micromere lineage). Finally, we identified gene-regulatory modules conserved between sea urchins and chordates. Our results suggest that gene-regulatory networks controlling development can be conserved despite extensive gene order rearrangement.

ChIP-seq profiling of H3K4me3 and H3K27me3 in an invasive insect, Bactrocera dorsalis

Introduction: While it has been suggested that histone modifications can facilitate animal responses to rapidly changing environments, few studies have profiled whole-genome histone modification patterns in invasive species, leaving the regulatory landscape of histone modifications in invasive species unclear. Methods: Here, we screen genome-wide patterns of two important histone modifications, trimethylated Histone H3 Lysine 4 (H3K4me3) and trimethylated Histone H3 Lysine 27 (H3K27me3), in adult thorax muscles of a notorious invasive pest, the Oriental fruit fly Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), using Chromatin Immunoprecipitation with high-throughput sequencing (ChIP-seq). Results: We identified promoters featured by the occupancy of H3K4me3, H3K27me3 or bivalent histone modifications that were respectively annotated with unique genes key to muscle development and structure maintenance. In addition, we found H3K27me3 occupied the entire body of genes, where the average enrichment was almost constant. Transcriptomic analysis indicated that H3K4me3 is associated with active gene transcription, and H3K27me3 is mostly associated with transcriptional repression. Importantly, we identified genes and putative motifs modified by distinct histone modification patterns that may possibly regulate flight activity. Discussion: These findings provide the first evidence of histone modification signature in B. dorsalis, and will be useful for future studies of epigenetic signature in other invasive insect species.

Transposable elements orchestrate subgenome-convergent and -divergent transcription in common wheat

The success of common wheat as a global staple crop was largely attributed to its genomic diversity and redundancy due to the merge of different genomes, giving rise to the major question how subgenome-divergent and -convergent transcription is mediated and harmonized in a single cell. Here, we create a catalog of genome-wide transcription factor-binding sites (TFBSs) to assemble a common wheat regulatory network on an unprecedented scale. A significant proportion of subgenome-divergent TFBSs are derived from differential expansions of particular transposable elements (TEs) in diploid progenitors, which contribute to subgenome-divergent transcription. Whereas subgenome-convergent transcription is associated with balanced TF binding at loci derived from TE expansions before diploid divergence. These TFBSs have retained in parallel during evolution of each diploid, despite extensive unbalanced turnover of the flanking TEs. Thus, the differential evolutionary selection of paleo- and neo-TEs contribute to subgenome-convergent and -divergent regulation in common wheat, highlighting the influence of TE repertory plasticity on transcriptional plasticity in polyploid.

Intestine-specific removal of DAF-2 nearly doubles lifespan in Caenorhabditis elegans with little fitness cost

Twenty-nine years following the breakthrough discovery that a single-gene mutation of daf-2 doubles Caenorhabditis elegans lifespan, it remains unclear where this insulin/IGF-1 receptor gene is expressed and where it acts to regulate ageing. Using knock-in fluorescent reporters, we determined that daf-2 and its downstream transcription factor daf-16 are expressed ubiquitously. Using tissue-specific targeted protein degradation, we determined that intracellular DAF-2-to-DAF-16 signaling in the intestine plays a major role in lifespan regulation, while that in the hypodermis, neurons, and germline plays a minor role. Notably, intestine-specific loss of DAF-2 activates DAF-16 in and outside the intestine, causes almost no adverse effects on development and reproduction, and extends lifespan by 94% in a way that partly requires non-intestinal DAF-16. Consistent with intestine supplying nutrients to the entire body, evidence from this and other studies suggests that altered metabolism, particularly down-regulation of protein and RNA synthesis, mediates longevity by reduction of insulin/IGF-1 signaling.

Maintenance of neurotransmitter identity by Hox proteins through a homeostatic mechanism

Hox transcription factors play fundamental roles during early patterning, but they are also expressed continuously, from embryonic stages through adulthood, in the nervous system. However, the functional significance of their sustained expression remains unclear. In C. elegans motor neurons (MNs), we find that LIN-39 (Scr/Dfd/Hox4-5) is continuously required during post-embryonic life to maintain neurotransmitter identity, a core element of neuronal function. LIN-39 acts directly to co-regulate genes that define cholinergic identity (e.g., unc-17/VAChT, cho-1/ChT). We further show that LIN-39, MAB-5 (Antp/Hox6-8) and the transcription factor UNC-3 (Collier/Ebf) operate in a positive feedforward loop to ensure continuous and robust expression of cholinergic identity genes. Finally, we identify a two-component design principle for homeostatic control of Hox gene expression in adult MNs: Hox transcriptional autoregulation is counterbalanced by negative UNC-3 feedback. These findings uncover a noncanonical role for Hox proteins during post-embryonic life, critically broadening their functional repertoire from early patterning to the control of neurotransmitter identity.

Transcription factor network analysis identifies REST/NRSF as an intrinsic regulator of CNS regeneration in mice

The inability of neurons to regenerate long axons within the CNS is a major impediment to improving outcome after spinal cord injury, stroke, and other CNS insults. Recent advances have uncovered an intrinsic program that involves coordinate regulation by multiple transcription factors that can be manipulated to enhance growth in the peripheral nervous system. Here, we use a systems genomics approach to characterize regulatory relationships of regeneration-associated transcription factors, identifying RE1-Silencing Transcription Factor (REST; Neuron-Restrictive Silencer Factor, NRSF) as a predicted upstream suppressor of a pro-regenerative gene program associated with axon regeneration in the CNS. We validate our predictions using multiple paradigms, showing that mature mice bearing cell type-specific deletions of REST or expressing dominant-negative mutant REST show improved regeneration of the corticospinal tract and optic nerve after spinal cord injury and optic nerve crush, which is accompanied by upregulation of regeneration-associated genes in cortical motor neurons and retinal ganglion cells, respectively. These analyses identify a role for REST as an upstream suppressor of the intrinsic regenerative program in the CNS and demonstrate the utility of a systems biology approach involving integrative genomics and bio-informatics to prioritize hypotheses relevant to CNS repair.

Development of a 15-Gene Signature Model as a Prognostic Tool in Sex Hormone-Dependent Cancers

Sex hormone dependence is associated with tumor progression and prognosis. Here, we explored the molecular basis of luminal A-like phenotype in sex hormone-dependent cancers. RNA-sequencing data from 8 cancer types were obtained from The Cancer Genome Atlas (TCGA). We investigated the enrichment function of differentially expressed genes (DEGs) in luminal A breast cancer (BRCA). Weighted coexpression network analysis (WGCNA) was used to identify gene modules associated with the luminal A-like phenotype, and we calculated the module's preservation in 8 cancer types. Module hub genes screened using least absolute shrinkage and selection operator (LASSO) were used to construct a gene signature model for the luminal A-like phenotype, and we assessed the model's relationship with prognosis, enriched pathways, and immune infiltration using bioinformatics approaches. Compared to other BRCA subtypes, the enrichment functions of upregulated genes in luminal A BRCA were related to hormone biological processes and receptor activity, and the downregulated genes were associated with the cell cycle and nuclear division. A gene module significantly associated with luminal A BRCA was shared by uterine corpus endometrial carcinoma (UCEC), leading to a similar phenotype. Fifteen hub genes were used to construct a gene signature model for the assessment of the luminal A-like phenotype, and the corrected C-statistics and Brier scores were 0.986 and 0.023, respectively. Calibration plots showed good performance, and decision curve analysis indicated a high net benefit of the model. The 15-gene signature model was associated with better overall survival in BRCA and UCEC and was characterized by downregulation of DNA replication, cell cycle and activated CD4 T cells. In conclusion, our study elucidated that BRCA and UCEC share a similar sex hormone-dependent phenotype and constructed a 15-gene signature model for use as a prognostic tool to quantify the probability of the phenotype.

Transcriptome-wide Cas13 guide RNA design for model organisms and viral RNA pathogens

The recent characterization of RNA-targeting CRISPR nucleases has enabled diverse transcriptome engineering and screening applications that depend crucially on prediction and selection of optimized CRISPR guide RNAs (gRNAs). Previously, we developed a computational model to predict RfxCas13d gRNA activity for all human protein-coding genes. Here, we extend this framework to six model organisms (human, mouse, zebrafish, fly, nematode, and flowering plants) for protein-coding genes and noncoding RNAs (ncRNAs) and also to four RNA virus families (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], HIV-1, H1N1 influenza, and Middle East respiratory syndrome [MERS]). We include experimental validation of predictions by testing knockdown of multiple ncRNAs (MALAT1, HOTAIRM1, Gas5, and Pvt1) in human and mouse cells. We developed a freely available web-based platform (cas13design) with pre-scored gRNAs for transcriptome-wide targeting in several organisms and an interactive design tool to predict optimal gRNAs for custom RNA targets entered by the user. This resource will facilitate CRISPR-Cas13 RNA targeting in model organisms, emerging viral threats to human health.

Multi-scale network targeting: A holistic systems-biology approach to cancer treatment

The vulnerabilities of cancer at the cellular and, recently, with the introduction of immunotherapy, at the tissue level, have been exploited with variable success. Evaluating the cancer system vulnerabilities at the organismic level through analysis of network topology and network dynamics can potentially predict novel anti-cancer drug targets directed at the macroscopic cancer networks. Theoretical work analyzing the properties and the vulnerabilities of the multi-scale network of cancer needs to go hand-in-hand with experimental research that uncovers the biological nature of the relevant networks and reveals new targetable vulnerabilities. It is our hope that attacking cancer on different spatial scales, in a concerted integrated approach, may present opportunities for novel ways to prevent treatment resistance.

Computational biology approaches for mapping transcriptional regulatory networks

Transcriptional Regulatory Networks (TRNs) are mainly responsible for the cell-type- or cell-state-specific expression of gene sets from the same DNA sequence. However, so far there are no precise maps of TRNs available for each cell-type or cell-state, and no ideal tool to map those networks clearly and in full from biological samples. In this review, major approaches and tools to map TRNs from high-throughput data are presented, depending on the type of methods or data used to infer them, and their advantages and limitations are discussed. After summarizing the main principles defining the topology and structure–function relationships in TRNs, an overview of the extensive work done to map TRNs from bulk transcriptomic data will be presented by type of methodological approach. Most recent modellings of TRNs using other types of molecular data or integrating different data types, including single-cell RNA-sequencing and chromatin information, will then be discussed, before briefly concluding with improvements expected to come in the field.

Spatiotemporal Gene Expression Profiling and Network Inference: A Roadmap for Analysis, Visualization, and Key Gene Identification

Gene expression data analysis and the prediction of causal relationships within gene regulatory networks (GRNs) have guided the identification of key regulatory factors and unraveled the dynamic properties of biological systems. However, drawing accurate and unbiased conclusions requires a comprehensive understanding of relevant tools, computational methods, and their workflows. The topics covered in this chapter encompass the entire workflow for GRN inference including: (1) experimental design; (2) RNA sequencing data processing; (3) differentially expressed gene (DEG) selection; (4) clustering prior to inference; (5) network inference techniques; and (6) network visualization and analysis. Moreover, this chapter aims to present a workflow feasible and accessible for plant biologists without a bioinformatics or computer science background. To address this need, TuxNet, a user-friendly graphical user interface that integrates RNA sequencing data analysis with GRN inference, is chosen for the purpose of providing a detailed tutorial.

DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays

Motivation

Mapping distal regulatory elements, such as enhancers, is a cornerstone for elucidating how genetic variations may influence diseases. Previous enhancer-prediction methods have used either unsupervised approaches or supervised methods with limited training data. Moreover, past approaches have implemented enhancer discovery as a binary classification problem without accurate boundary detection, producing low-resolution annotations with superfluous regions and reducing the statistical power for downstream analyses (e.g. causal variant mapping and functional validations). Here, we addressed these challenges via a two-step model called Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays (DECODE). First, we employed direct enhancer-activity readouts from novel functional characterization assays, such as STARR-seq, to train a deep neural network for accurate cell-type-specific enhancer prediction. Second, to improve the annotation resolution, we implemented a weakly supervised object detection framework for enhancer localization with precise boundary detection (to a 10 bp resolution) using Gradient-weighted Class Activation Mapping.

Results

Our DECODE binary classifier outperformed a state-of-the-art enhancer prediction method by 24% in transgenic mouse validation. Furthermore, the object detection framework can condense enhancer annotations to only 13% of their original size, and these compact annotations have significantly higher conservation scores and genome-wide association study variant enrichments than the original predictions. Overall, DECODE is an effective tool for enhancer classification and precise localization.

Availability and implementation

DECODE source code and pre-processing scripts are available at decode.gersteinlab.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types

SUMMARY

Epigenetic modifications reflect key aspects of transcriptional regulation, and many epigenomic datasets have been generated under different biological contexts to provide insights into regulatory processes. However, the technical noise in epigenomic datasets and the many dimensions (features) examined make it challenging to effectively extract biologically meaningful inferences from these datasets. We developed a package that reduces noise while normalizing the epigenomic data by a novel normalization method, followed by integrative dimensional reduction by learning and assigning epigenetic states. This package, called S3V2-IDEAS, can be used to identify epigenetic states for multiple features, or identify discretized signal intensity levels and a master peak list across different cell types for a single feature. We illustrate the outputs and performance of S3V2-IDEAS using 137 epigenomics datasets from the VISION project that provides ValIdated Systematic IntegratiON of epigenomic data in hematopoiesis.

AVAILABILITY AND IMPLEMENTATION

S3V2-IDEAS pipeline is freely available as open source software released under an MIT license at: https://github.com/guanjue/S3V2_IDEAS_ESMP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pathogenic Mechanisms of Somatic Mutation and Genome Mosaicism in Aging

Age-related accumulation of postzygotic DNA mutations results in tissue genetic heterogeneity known as somatic mosaicism. Although implicated in aging as early as the 1950s, somatic mutations in normal tissue have been difficult to study because of their low allele fractions. With the recent emergence of cost-effective high-throughput sequencing down to the single-cell level, enormous progress has been made in our capability to quantitatively analyze somatic mutations in human tissue in relation to aging and disease. Here we first review how recent technological progress has opened up this field, providing the first broad sets of quantitative information on somatic mutations in vivo necessary to gain insight into their possible causal role in human aging and disease. We then propose three major mechanisms that can lead from accumulated de novo mutations across tissues to cell functional loss and human disease.

Establishment and maintenance of motor neuron identity via temporal modularity in terminal selector function

Terminal selectors are transcription factors (TFs) that establish during development and maintain throughout life post-mitotic neuronal identity. We previously showed that UNC-3/Ebf, the terminal selector of C. elegans cholinergic motor neurons (MNs), acts indirectly to prevent alternative neuronal identities (Feng et al., 2020). Here, we globally identify the direct targets of UNC-3. Unexpectedly, we find that the suite of UNC-3 targets in MNs is modified across different life stages, revealing ‘temporal modularity’ in terminal selector function. In all larval and adult stages examined, UNC-3 is required for continuous expression of various protein classes (e.g. receptors, transporters) critical for MN function. However, only in late larvae and adults, UNC-3 is required to maintain expression of MN-specific TFs. Minimal disruption of UNC-3’s temporal modularity via genome engineering affects locomotion. Another C. elegans terminal selector (UNC-30/Pitx) also exhibits temporal modularity, supporting the potential generality of this mechanism for the control of neuronal identity.

Functional Transcription Factor Target Networks Illuminate Control of Epithelial Remodelling

Cell identity is governed by gene expression, regulated by transcription factor (TF) binding at cis-regulatory modules. Decoding the relationship between TF binding patterns and gene regulation is nontrivial, remaining a fundamental limitation in understanding cell decision-making. We developed the NetNC software to predict functionally active regulation of TF targets; demonstrated on nine datasets for the TFs Snail, Twist, and modENCODE Highly Occupied Target (HOT) regions. Snail and Twist are canonical drivers of epithelial to mesenchymal transition (EMT), a cell programme important in development, tumour progression and fibrosis. Predicted "neutral" (non-functional) TF binding always accounted for the majority (50% to 95%) of candidate target genes from statistically significant peaks and HOT regions had higher functional binding than most of the Snail and Twist datasets examined. Our results illuminated conserved gene networks that control epithelial plasticity in development and disease. We identified new gene functions and network modules including crosstalk with notch signalling and regulation of chromatin organisation, evidencing networks that reshape Waddington's epigenetic landscape during epithelial remodelling. Expression of orthologous functional TF targets discriminated breast cancer molecular subtypes and predicted novel tumour biology, with implications for precision medicine. Predicted invasion roles were validated using a tractable cell model, supporting our approach.

Computational identification of cell-specific variable regions in ChIP-seq data

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is used to identify genome-wide DNA regions bound by proteins. Given one ChIP-seq experiment with replicates, binding sites not observed in all the replicates will usually be interpreted as noise and discarded. However, the recent discovery of high-occupancy target (HOT) regions suggests that there are regions where binding of multiple transcription factors can be identified. To investigate ChIP-seq variability, we developed a reproducibility score and a method that identifies cell-specific variable regions in ChIP-seq data by integrating replicated ChIP-seq experiments for multiple protein targets on a particular cell type. Using our method, we found variable regions in human cell lines K562, GM12878, HepG2, MCF-7 and in mouse embryonic stem cells (mESCs). These variable-occupancy target regions (VOTs) are CG dinucleotide rich, and show enrichment at promoters and R-loops. They overlap significantly with HOT regions, but are not blacklisted regions producing non-specific binding ChIP-seq peaks. Furthermore, in mESCs, VOTs are conserved among placental species suggesting that they could have a function important for this taxon. Our method can be useful to point to such regions along the genome in a given cell type of interest, to improve the downstream interpretative analysis before follow-up experiments.

hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets

Transcription factors (TFs) as key regulators play crucial roles in biological processes. The identification of TF–target regulatory relationships is a key step for revealing functions of TFs and their regulations on gene expression. The accumulated data of chromatin immunoprecipitation sequencing (ChIP-seq) provide great opportunities to discover the TF–target regulations across different conditions. In this study, we constructed a database named hTFtarget, which integrated huge human TF target resources (7190 ChIP-seq samples of 659 TFs and high-confidence binding sites of 699 TFs) and epigenetic modification information to predict accurate TF–target regulations. hTFtarget offers the following functions for users to explore TF–target regulations: (1) browse or search general targets of a query TF across datasets; (2) browse TF–target regulations for a query TF in a specific dataset or tissue; (3) search potential TFs for a given target gene or non-coding RNA; (4) investigate co-association between TFs in cell lines; (5) explore potential co-regulations for given target genes or TFs; (6) predict candidate TF binding sites on given DNA sequences; (7) visualize ChIP-seq peaks for different TFs and conditions in a genome browser. hTFtarget provides a comprehensive, reliable and user-friendly resource for exploring human TF–target regulations, which will be very useful for a wide range of users in the TF and gene expression regulation community. hTFtarget is available at http://bioinfo.life.hust.edu.cn/hTFtarget.

Occupancy maps of 208 chromatin-associated proteins in one human cell type

Transcription factors are DNA-binding proteins that have key roles in gene regulation^1,2. Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes^3–6. However, only a minority of the more than 1,600 transcription factors encoded in the human genome has been assayed. Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP–seq) experiments using the human HepG2 cell line for 208 chromatin-associated proteins (CAPs). These comprise 171 transcription factors and 37 transcriptional cofactors and chromatin regulator proteins, and represent nearly one-quarter of CAPs expressed in HepG2 cells. The binding profiles of these CAPs form major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP target. For example, FOX family motifs are enriched in ChIP–seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers. This catalogue reveals high-occupancy target regions at which many CAPs associate, although each contains motifs for only a minority of the numerous associated transcription factors. These analyses provide a more complete overview of the gene regulatory networks that define this cell type, and demonstrate the usefulness of the large-scale production efforts of the ENCODE Consortium.

ChIP–seq and CETCh–seq data are used to analyse binding maps for 208 transcription factors and other chromatin-associated proteins in a single human cell type, providing a comprehensive catalogue of the transcription factor landscape and gene regulatory networks in these cells.

Supervised enhancer prediction with epigenetic pattern recognition and targeted validation

Enhancers are important noncoding elements, but they have been traditionally hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mouse and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription-factor binding patterns at predicted enhancers versus promoters. We demonstrated that these patterns enable the construction of a secondary model effectively discriminating between enhancers and promoters.

Human ZKSCAN3 and Drosophila M1BP are functionally homologous transcription factors in autophagy regulation

Autophagy is an essential cellular process that maintains homeostasis by recycling damaged organelles and nutrients during development and cellular stress. ZKSCAN3 is the sole identified master transcriptional repressor of autophagy in human cell lines. How ZKSCAN3 achieves autophagy repression at the mechanistic or organismal level however still remains to be elucidated. Furthermore, Zkscan3 knockout mice display no discernable autophagy-related phenotypes, suggesting that there may be substantial differences in the regulation of autophagy between normal tissues and tumor cell lines. Here, we demonstrate that vertebrate ZKSCAN3 and Drosophila M1BP are functionally homologous transcription factors in autophagy repression. Expression of ZKSCAN3 in Drosophila prevents premature autophagy onset due to loss of M1BP function and conversely, M1BP expression in human cells can prevent starvation-induced autophagy due to loss of nuclear ZKSCAN3 function. In Drosophila ZKSCAN3 binds genome-wide to sequences targeted by M1BP and transcriptionally regulates the majority of M1BP-controlled genes, demonstrating the evolutionary conservation of the transcriptional repression of autophagy. This study thus  allows the potential for transitioning the mechanisms, gene targets and plethora metabolic processes controlled by M1BP onto ZKSCAN3 and opens up Drosophila as a tool in studying the function of ZKSCAN3 in autophagy and tumourigenesis.

IGAP-integrative genome analysis pipeline reveals new gene regulatory model associated with nonspecific TF-DNA binding affinity

The human genome is regulated in a multi-dimensional way. While biophysical factors like Non-specific Transcription factor Binding Affinity (nTBA) act at DNA sequence level, other factors act above sequence levels such as histone modifications and 3-D chromosomal interactions. This multidimensionality of regulation requires many of these factors for a proper understanding of the regulatory landscape of the human genome. Here, we propose a new biophysical model for estimating nTBA. Integration of nTBA with chromatin modifications and chromosomal interactions, using a new Integrative Genome Analysis Pipeline (IGAP), reveals additive effects of nTBA to regulatory DNA sequences and identifies three types of genomic zones in the human genome (Inactive Genomic Zones, Poised Genomic Zones, and Active Genomic Zones). It also unveils a novel long distance gene regulatory model: chromosomal interactions reduce the physical distance between the high occupancy target (HOT) regions that results in high nTBA to DNA in the area, which in turn attract TFs to such regions with higher binding potential. These findings will help to elucidate the three-dimensional diffusion process that TFs use during their search for the right targets.

A terminal selector prevents a Hox transcriptional switch to safeguard motor neuron identity throughout life

To become and remain functional, individual neuron types must select during development and maintain throughout life their distinct terminal identity features, such as expression of specific neurotransmitter receptors, ion channels and neuropeptides. Here, we report a molecular mechanism that enables cholinergic motor neurons (MNs) in the C. elegans ventral nerve cord to select and maintain their unique terminal identity. This mechanism relies on the dual function of the conserved terminal selector UNC-3 (Collier/Ebf). UNC-3 synergizes with LIN-39 (Scr/Dfd/Hox4-5) to directly co-activate multiple terminal identity traits specific to cholinergic MNs, but also antagonizes LIN-39’s ability to activate terminal features of alternative neuronal identities. Loss of unc-3 causes a switch in the transcriptional targets of LIN-39, thereby alternative, not cholinergic MN-specific, terminal features become activated and locomotion defects occur. The strategy of a terminal selector preventing a transcriptional switch may constitute a general principle for safeguarding neuronal identity throughout life.

Sex biased expression and co-expression networks in development, using the hymenopteran Nasonia vitripennis

Sexual dimorphism requires regulation of gene expression in developing organisms. These developmental differences are caused by differential expression of genes and isoforms. The effect of expressing a gene is also influenced by which other genes are simultaneously expressed (functional interactions). However, few studies have described how these processes change across development. We compare the dynamics of differential expression, isoform switching and functional interactions in the sexual development of the model parasitoid wasp Nasonia vitripennis, a system that permits genome wide analysis of sex bias from early embryos to adults. We find relatively little sex-bias in embryos and larvae at the gene level, but several sub-networks show sex-biased functional interactions in early developmental stages. These networks provide new candidates for hymenopteran sex determination, including histone modification. In contrast, sex-bias in pupae and adults is driven by the differential expression of genes. We observe sex-biased isoform switching consistently across development, but mostly in genes that are already differentially expressed. Finally, we discover that sex-biased networks are enriched by genes specific to the Nasonia clade, and that those genes possess the topological properties of key regulators. These findings suggest that regulators in sex-biased networks evolve more rapidly than regulators of other developmental networks.

HOT or not: examining the basis of high-occupancy target regions

High-occupancy target (HOT) regions are segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and consequently associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solely defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed ‘hyper-ChIPable’ regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers, enrichment of RNA–DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.

GEREDB: Gene expression regulation database curated by mining abstracts from literature

Understanding how genes are expressed and regulated in different biological processes are fundamental and challenging issues. Considerable progress has been made in studying the relationship between the expression and regulation of human genes. However, it is difficult to use these resources productively to analyze gene expression data. GEREDB (www.thua45.cn/geredb) has been developed to facilitate analyses that will provide insights into the regulation of genes that govern specific biological responses. GEREDB is a publicly available, manually curated biological database that stores the data regarding relationships between expression and regulation of human genes. To date, more than 39,000 Links have been contextually annotated by reviewing more than 53,000 abstracts. GEREDB can be searched using the official NCBI gene symbol as a query, and it can be downloaded along with the GEREA software package. GEREDB has the ability to analyze user-supplied gene expression data in a causal analysis oriented manner using the GEREA bioinformatics tool.

Non-coding RNA regulatory networks

It is well established that the vast majority of human RNA transcripts do not encode for proteins and that non-coding RNAs regulate cell physiology and shape cellular functions. A subset of them is involved in gene regulation at different levels, from epigenetic gene silencing to post-transcriptional regulation of mRNA stability. Notably, the aberrant expression of many non-coding RNAs has been associated with aggressive pathologies. Rapid advances in network biology indicates that the robustness of cellular processes is the result of specific properties of biological networks such as scale-free degree distribution and hierarchical modularity, suggesting that regulatory network analyses could provide new insights on gene regulation and dysfunction mechanisms. In this study we present an overview of public repositories where non-coding RNA-regulatory interactions are collected and annotated, we discuss unresolved questions for data integration and we recall existing resources to build and analyse networks.

A map of direct TF-DNA interactions in the human genome

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the most popular assay to identify genomic regions, called ChIP-seq peaks, that are bound in vivo by transcription factors (TFs). These regions are derived from direct TF-DNA interactions, indirect binding of the TF to the DNA (through a co-binding partner), nonspecific binding to the DNA, and noise/bias/artifacts. Delineating the bona fide direct TF-DNA interactions within the ChIP-seq peaks remains challenging. We developed a dedicated software, ChIP-eat, that combines computational TF binding models and ChIP-seq peaks to automatically predict direct TF-DNA interactions. Our work culminated with predicted interactions covering >4% of the human genome, obtained by uniformly processing 1983 ChIP-seq peak data sets from the ReMap database for 232 unique TFs. The predictions were a posteriori assessed using protein binding microarray and ChIP-exo data, and were predominantly found in high quality ChIP-seq peaks. The set of predicted direct TF-DNA interactions suggested that high-occupancy target regions are likely not derived from direct binding of the TFs to the DNA. Our predictions derived co-binding TFs supported by protein-protein interaction data and defined cis-regulatory modules enriched for disease- and trait-associated SNPs. We provide this collection of direct TF-DNA interactions and cis-regulatory modules through the UniBind web-interface (http://unibind.uio.no).

Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant

Gene regulatory networks (GRNs) consist of different molecular interactions that closely work together to establish proper gene expression in time and space. Especially in higher eukaryotes, many questions remain on how these interactions collectively coordinate gene regulation. We study high quality GRNs consisting of undirected protein–protein, genetic and homologous interactions, and directed protein–DNA, regulatory and miRNA–mRNA interactions in the worm Caenorhabditis elegans and the plant Arabidopsis thaliana. Our data-integration framework integrates interactions in composite network motifs, clusters these in biologically relevant, higher-order topological network motif modules, overlays these with gene expression profiles and discovers novel connections between modules and regulators. Similar modules exist in the integrated GRNs of worm and plant. We show how experimental or computational methodologies underlying a certain data type impact network topology. Through phylogenetic decomposition, we found that proteins of worm and plant tend to functionally interact with proteins of a similar age, while at the regulatory level TFs favor same age, but also older target genes. Despite some influence of the duplication mode difference, we also observe at the motif and module level for both species a preference for age homogeneity for undirected and age heterogeneity for directed interactions. This leads to a model where novel genes are added together to the GRNs in a specific biological functional context, regulated by one or more TFs that also target older genes in the GRNs. Overall, we detected topological, functional and evolutionary properties of GRNs that are potentially universal in all species.

Caenorhabditis elegans hub genes that respond to amyloid beta are homologs of genes involved in human Alzheimer's disease

The prominent characteristic of Alzheimer’s disease (AD) is the accumulation of amyloid beta (Abeta) proteins in the form of plaques that cause molecular and cellular alterations in the brain. Due to the paucity of brain samples of early-stage Abeta aggregation, animal models have been developed to study early events in AD. Caenorhabditis elegans is a genetically tractable animal model for AD. Here, we used transcriptomic data, network-based protein-protein interactions and weighted gene co-expression network analysis (WGCNA), to detect modules and their gene ontology in response to Abeta aggregation in C. elegans. Additionally, hub genes and their orthologues in human and mouse were identified to study their relation to AD. We also found several transcription factors (TFs) responding to Abeta accumulation. Our results show that Abeta expression in C. elegans relates to general processes such as molting cycle, locomotion, and larval development plus AD-associated processes, including protein phosphorylation, and G-protein coupled receptor-regulated pathways. We reveal that many hub genes and TFs including ttbk-2, daf-16, and unc-49 have human and mouse orthologues that are directly or potentially associated with AD and neural development. In conclusion, using systems biology we identified important genes and biological processes in C. elegans that respond to Abeta aggregation, which could be used as potential diagnostic or therapeutic targets. In addition, because of evolutionary relationship to AD in human, we suggest that C. elegans is a useful model for studying early molecular events in AD.

The ENCODE Blacklist: Identification of Problematic Regions of the Genome

Functional genomics assays based on high-throughput sequencing greatly expand our ability to understand the genome. Here, we define the ENCODE blacklist- a comprehensive set of regions in the human, mouse, worm, and fly genomes that have anomalous, unstructured, or high signal in next-generation sequencing experiments independent of cell line or experiment. The removal of the ENCODE blacklist is an essential quality measure when analyzing functional genomics data.

FACER: comprehensive molecular and functional characterization of epigenetic chromatin regulators

Epigenetic alterations, a well-recognized cancer hallmark, are driven by chromatin regulators (CRs). However, little is known about the extent of CR deregulation in cancer, and less is known about their common and specialized roles across various cancers. Here, we performed genome-wide analyses and constructed molecular signatures and network profiles of functional CRs in over 10 000 tumors across 33 cancer types. By integration of DNA mutation, genome-wide methylation, transcriptional/post-transcriptional regulation, and protein interaction networks with clinical outcomes, we identified CRs associated with cancer subtypes and clinical prognosis as potential oncogenic drivers. Comparative network analysis revealed principles of CR regulatory specificity and functionality. In addition, we identified common and specific CRs by assessing their prevalence across cancer types. Common CRs tend to be histone modifiers and chromatin remodelers with fundamental roles, whereas specialized CRs are involved in context-dependent functions. Finally, we have made a user-friendly web interface-FACER (Functional Atlas of Chromatin Epigenetic Regulators) available for exploring clinically relevant CRs for the development of CR biomarkers and therapeutic targets. Our integrative analysis reveals specific determinants of CRs across cancer types and presents a resource for investigating disease-associated CRs.

Transcriptional Regulation of Abscission Zones

Precise and timely regulation of organ separation from the parent plant (abscission) is consequential to improvement of crop productivity as it influences both the timing of harvest and fruit quality. Abscission is tightly associated with plant fitness as unwanted organs (petals, sepals, filaments) are shed after fertilization while seeds, fruits, and leaves are cast off as means of reproductive success or in response to abiotic/biotic stresses. Floral organ abscission in Arabidopsis has been a useful model to elucidate the molecular mechanisms that underlie the separation processes, and multiple abscission signals associated with the activation and downstream pathways have been uncovered. Concomitantly, large-scale analyses of omics studies in diverse abscission systems of various plants have added valuable insights into the abscission process. The results suggest that there are common molecular events linked to the biosynthesis of a new extracellular matrix as well as cell wall disassembly. Comparative analysis between Arabidopsis and soybean abscission systems has revealed shared and yet disparate regulatory modules that affect the separation processes. In this review, we discuss our current understanding of the transcriptional regulation of abscission in several different plants that has improved on the previously proposed four-phased model of organ separation.

Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise

In transcriptional regulatory networks (TRNs), a canonical 3-node feed-forward loop (FFL) is hypothesized to evolve to filter out short spurious signals. We test this adaptive hypothesis against a novel null evolutionary model. Our mutational model captures the intrinsically high prevalence of weak affinity transcription factor binding sites. We also capture stochasticity and delays in gene expression that distort external signals and intrinsically generate noise. Functional FFLs evolve readily under selection for the hypothesized function but not in negative controls. Interestingly, a 4-node “diamond” motif also emerges as a short spurious signal filter. The diamond uses expression dynamics rather than path length to provide fast and slow pathways. When there is no idealized external spurious signal to filter out, but only internally generated noise, only the diamond and not the FFL evolves. While our results support the adaptive hypothesis, we also show that non-adaptive factors, including the intrinsic expression dynamics, matter.

Feed‐forward loops (FFLs) can filter out noise, but whether their overrepresentation in GRNs reflects adaptive evolution for this function is debated. Here, the authors develop a null model of regulatory evolution and find that FFLs evolve readily under selection for the noise filtering function.

Hierarchical cooperation of transcription factors from integration analysis of DNA sequences, ChIP-Seq and ChIA-PET data

Background

Chromosomal architecture, which is constituted by chromatin loops, plays an important role in cellular functions. Gene expression and cell identity can be regulated by the chromatin loop, which is formed by proximal or distal enhancers and promoters in linear DNA (1D). Enhancers and promoters are fundamental non-coding elements enriched with transcription factors (TFs) to form chromatin loops. However, the specific cooperation of TFs involved in forming chromatin loops is not fully understood.

Results

Here, we proposed a method for investigating the cooperation of TFs in four cell lines by the integrative analysis of DNA sequences, ChIP-Seq and ChIA-PET data. Results demonstrate that the interaction of enhancers and promoters is a hierarchical and dynamic complex process with cooperative interactions of different TFs synergistically regulating gene expression and chromatin structure. The TF cooperation involved in maintaining and regulating the chromatin loop of cells can be regulated by epigenetic factors, such as other TFs and DNA methylation.

Conclusions

Such cooperation among TFs provides the potential features that can affect chromatin’s 3D architecture in cells. The regulation of chromatin 3D organization and gene expression is a complex process associated with the hierarchical and dynamic prosperities of TFs.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5535-2) contains supplementary material, which is available to authorized users.

CEH-60/PBX and UNC-62/MEIS Coordinate a Metabolic Switch that Supports Reproduction in C. elegans

The molecular basis of how animals integrate metabolic, developmental, and environmental information before committing resources to reproduction is an unresolved issue in developmental biology. In C. elegans, adult animals reallocate fat stores from intestinal cells to the germline via low-density lipoprotein (LDL)-like particles to promote embryogenesis. Here, I demonstrate that two conserved homeodomain transcription factors, CEH-60/PBX and UNC-62/MEIS, coordinate a transcriptional network that supports reproduction while suppressing longevity and stress-response pathways. The CEH-60:UNC-62 heterodimer serves an unanticipated dual function in intestinal nuclei by directly activating the expression of lipoprotein genes while directly repressing stress-responsive genes. Consequently, ceh-60 mutants display fat storage defects, a dramatic lifespan extension, and hyper-activation of innate immunity genes. Finally, CEH-60 associates with PQM-1 at the DAF-16-associated element within the promoters of stress-responsive genes to control gene expression. Thus, CEH-60 governs an elaborate transcriptional network that balances stress responses and longevity against reproduction during developmental transitions.

Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression

Epigenomic signatures from histone marks and transcription factor (TF)-binding sites have been used to annotate putative gene regulatory regions. However, a direct comparison of these diverse annotations is missing, and it is unclear how genetic variation within these annotations affects gene expression. Here, we compare five widely used annotations of active regulatory elements that represent high densities of one or more relevant epigenomic marks-"super" and "typical" (nonsuper) enhancers, stretch enhancers, high-occupancy target (HOT) regions, and broad domains-across the four matched human cell types for which they are available. We observe that stretch and super enhancers cover cell type-specific enhancer "chromatin states," whereas HOT regions and broad domains comprise more ubiquitous promoter states. Expression quantitative trait loci (eQTL) in stretch enhancers have significantly smaller effect sizes compared to those in HOT regions. Strikingly, chromatin accessibility QTL in stretch enhancers have significantly larger effect sizes compared to those in HOT regions. These observations suggest that stretch enhancers could harbor genetically primed chromatin to enable changes in TF binding, possibly to drive cell type-specific responses to environmental stimuli. Our results suggest that current eQTL studies are relatively underpowered or could lack the appropriate environmental context to detect genetic effects in the most cell type-specific "regulatory annotations," which likely contributes to infrequent colocalization of eQTL with genome-wide association study signals.

A De Novo Shape Motif Discovery Algorithm Reveals Preferences of Transcription Factors for DNA Shape Beyond Sequence Motifs

DNA shape adds specificity to sequence motifs but has not been explored systematically outside this context. We hypothesized that DNA-binding proteins (DBPs) preferentially occupy DNA with specific structures ("shape motifs") regardless of whether or not these correspond to high information content sequence motifs. We present ShapeMF, a Gibbs sampling algorithm that identifies de novo shape motifs. Using binding data from hundreds of in vivo and in vitro experiments, we show that most DBPs have shape motifs and can occupy these in the absence of sequence motifs. This "shape-only binding" is common for many DBPs and in regions co-bound by multiple DBPs. When shape and sequence motifs co-occur, they can be overlapping, flanking, or separated by consistent spacing. Finally, DBPs within the same protein family have different shape motifs, explaining their distinct genome-wide occupancy despite having similar sequence motifs. These results suggest that shape motifs not only complement sequence motifs but also facilitate recognition of DNA beyond conventionally defined sequence motifs.