Identifying peaks in *-seq data using shape information

Accurate allocation of multimapped reads enables regulatory element analysis at repeats

Transposable elements (TEs) and other repetitive regions have been shown to contain gene regulatory elements, including transcription factor binding sites. However, regulatory elements harbored by repeats have proven difficult to characterize using short-read sequencing assays such as ChIP-seq or ATAC-seq. Most regulatory genomics analysis pipelines discard "multimapped" reads that align equally well to multiple genomic locations. Because multimapped reads arise predominantly from repeats, current analysis pipelines fail to detect a substantial portion of regulatory events that occur in repetitive regions. To address this shortcoming, we developed Allo, a new approach to allocate multimapped reads in an efficient, accurate, and user-friendly manner. Allo combines probabilistic mapping of multimapped reads with a convolutional neural network that recognizes the read distribution features of potential peaks, offering enhanced accuracy in multimapping read assignment. Allo also provides read-level output in the form of a corrected alignment file, making it compatible with existing regulatory genomics analysis pipelines and downstream peak-finders. In a demonstration application on CTCF ChIP-seq data, we show that Allo results in the discovery of thousands of new CTCF peaks. Many of these peaks contain the expected cognate motif and/or serve as TAD boundaries. We additionally apply Allo to a diverse collection of ENCODE ChIP-seq data sets, resulting in multiple previously unidentified interactions between transcription factors and repetitive element families. Finally, we show that Allo may be particularly beneficial in identifying ChIP-seq peaks at centromeres, near segmentally duplicated genes, and in younger TEs, enabling new regulatory analyses in these regions.

Allo: Accurate allocation of multi-mapped reads enables regulatory element analysis at repeats

Transposable elements (TEs) and other repetitive regions have been shown to contain gene regulatory elements, including transcription factor binding sites. Unfortunately, regulatory elements harbored by repeats have proven difficult to characterize using short-read sequencing assays such as ChIP-seq or ATAC-seq. Most regulatory genomics analysis pipelines discard "multi-mapped" reads that align equally well to multiple genomic locations. Since multi-mapped reads arise predominantly from repeats, current analysis pipelines fail to detect a substantial portion of regulatory events that occur in repetitive regions. To address this shortcoming, we developed Allo, a new approach to allocate multi-mapped reads in an efficient, accurate, and user-friendly manner. Allo combines probabilistic mapping of multi-mapped reads with a convolutional neural network that recognizes the read distribution features of potential peaks, offering enhanced accuracy in multi-mapping read assignment. Allo also provides read-level output in the form of a corrected alignment file, making it compatible with existing regulatory genomics analysis pipelines and downstream peak-finders. In a demonstration application on CTCF ChIP-seq data, we show that Allo results in the discovery of thousands of new CTCF peaks. Many of these peaks contain the expected cognate motif and/or serve as TAD boundaries. We additionally apply Allo to a diverse collection of ENCODE ChIP-seq datasets, resulting in multiple previously unidentified interactions between transcription factors and repetitive element families. Finally, we show that Allo may be particularly effective in identifying ChIP-seq peaks in younger TEs, which hold evolutionary significance due to their emergence during human evolution from primates.

N6-methyladenosine modification of the Aedes aegypti transcriptome and its alteration upon dengue virus infection in Aag2 cell line

The N⁶-methyladenosine (m⁶A) modification of RNA has been reported to affect viral infections. Studies have confirmed the role of m⁶A in replication of several vector-borne flaviviruses, including dengue virus (DENV), in mammalian cells. Here, we explored the role of m⁶A in DENV replication in the mosquito Aedes aegypti Aag2 cell line. We first determined the presence of m⁶A on the RNAs from mosquito cells and using methylated RNA immunoprecipitation and sequencing (MeRIP-Seq) identified m⁶A modification of the mosquito transcriptome and those that changed upon DENV infection. Depletion of m⁶A methyltransferases and the m⁶A binding protein YTHDF3 RNAs decreased the replication of DENV. In particular, we found that the Ae. aegypti ubiquitin carrier protein 9 (Ubc9) is m⁶A modified and its expression increases after DENV infection. Silencing of the gene and ectopic expression of Ubc9 led to reduced and increased DENV replication, respectively. The abundance of Ubc9 mRNA and its stability were reduced with the inhibition of m⁶A modification, implying that m⁶A modification of Ubc9 might enhance expression of the gene. We also show that the genome of DENV is m⁶A modified at five sites in mosquito cells. Altogether, this work reveals the involvement of m⁶A modification in Ae. aegypti-DENV interaction.

Analysis of m⁶A RNA modifications in the mosquito transcriptome and their changes upon dengue virus infection provides insight into the role of epigenetics in regulating viral replication in mosquitoes.

Integration of Count Difference and Curve Similarity in Negative Regulatory Element Detection

Negative regulatory elements (NREs) down-regulate gene expression by inhibiting the activities of promoters or enhancers. The repressing activity of NREs can be measured globally by massively parallel reporter assays (MPRAs). However, most existing algorithms are designed for the statistical detection of positively enriched signals in MPRA datasets. To identify reduced signals in MPRA experiments, we designed a NRE identification program, fast-NR, by integrating the count and graphic features of sequenced reads to detect NREs using datasets generated by experiments of self-transcribing active regulatory region sequencing (STARR-seq). Fast-NR identified hundreds of silencers in human K562 cells that can be validated by independent methods.

Self-organizing maps with variable neighborhoods facilitate learning of chromatin accessibility signal shapes associated with regulatory elements

BACKGROUND

Assigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of these states. However, computational methods to assign chromatin state suffer from the following drawbacks: they typically require data from multiple assays, which may not be practically feasible to obtain, and they depend on peak calling algorithms, which require careful parameterization and often exclude the majority of the genome. To address these drawbacks, we propose a novel learning technique built upon the Self-Organizing Map (SOM), Self-Organizing Map with Variable Neighborhoods (SOM-VN), to learn a set of representative shapes from a single, genome-wide, chromatin accessibility dataset to associate with a chromatin state assignment in which a particular RE is prevalent. These shapes can then be used to assign chromatin state using our workflow.

RESULTS

We validate the performance of the SOM-VN workflow on 14 different samples of varying quality, namely one assay each of A549 and GM12878 cell lines and two each of H1 and HeLa cell lines, primary B-cells, and brain, heart, and stomach tissue. We show that SOM-VN learns shapes that are (1) non-random, (2) associated with known chromatin states, (3) generalizable across sets of chromosomes, and (4) associated with magnitude and multimodality. We compare the accuracy of SOM-VN chromatin states against the Clustering Aggregation Tool (CAGT), an unsupervised method that learns chromatin accessibility signal shapes but does not associate these shapes with REs, and we show that overall precision and recall is increased when learning shapes using SOM-VN as compared to CAGT. We further compare enhancer state assignments from SOM-VN in signals above a set threshold to enhancer state assignments from Predicting Enhancers from ATAC-seq Data (PEAS), a deep learning method that assigns enhancer chromatin states to peaks. We show that the precision-recall area under the curve for the assignment of enhancer states is comparable to PEAS.

CONCLUSIONS

Our work shows that the SOM-VN workflow can learn relationships between REs and chromatin accessibility signal shape, which is an important step toward the goal of assigning and comparing enhancer state across multiple experiments and phenotypic states.

Elucidating the Regulon of a Fur-like Protein in Mycobacterium avium subsp. paratuberculosis (MAP)

Intracellular iron concentration is tightly regulated to maintain cell viability. Iron plays important roles in electron transport, nucleic acid synthesis, and oxidative stress. A Mycobacterium avium subsp. paratuberculosis (MAP)-specific genomic island carries a putative metal transport operon that includes MAP3773c, which encodes a Fur-like protein. Although well characterized as a global regulator of iron homeostasis in multiple bacteria, the function of Fur (ferric uptake regulator) in MAP is unknown as this organism also carries IdeR (iron dependent regulator), a native iron regulatory protein specific to mycobacteria. Computational analysis using PRODORIC identified 23 different pathways involved in respiration, metabolism, and virulence that were likely regulated by MAP3773c. Thus, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) was performed to confirm the putative regulon of MAP3773c (Fur-like protein) in MAP. ChIP-Seq revealed enriched binding to 58 regions by Fur under iron-replete and -deplete conditions, located mostly within open reading frames (ORFs). Three ChIP peaks were identified in genes that are directly related to iron regulation: MAP3638c (hemophore-like protein), MAP3736c (Fur box), and MAP3776c (ABC transporter). Fur box consensus sequence was identified, and binding specificity and dependence on Mn2+ availability was confirmed by a chemiluminescent electrophoresis mobility shift assay (EMSA). The results confirmed that MAP3773c is a Fur ortholog that recognizes a 19 bp DNA sequence motif (Fur box) and it is involved in metal homeostasis. This work provides a regulatory network of MAP Fur binding sites during iron-replete and -deplete conditions, highlighting unique properties of Fur regulon in MAP.

CdbA is a DNA-binding protein and c-di-GMP receptor important for nucleoid organization and segregation in Myxococcus xanthus

Cyclic di-GMP (c-di-GMP) is a second messenger that modulates multiple responses to environmental and cellular signals in bacteria. Here we identify CdbA, a DNA-binding protein of the ribbon-helix-helix family that binds c-di-GMP in Myxococcus xanthus. CdbA is essential for viability, and its depletion causes defects in chromosome organization and segregation leading to a block in cell division. The protein binds to the M. xanthus genome at multiple sites, with moderate sequence specificity; however, its depletion causes only modest changes in transcription. The interactions of CdbA with c-di-GMP and DNA appear to be mutually exclusive and residue substitutions in CdbA regions important for c-di-GMP binding abolish binding to both c-di-GMP and DNA, rendering these protein variants non-functional in vivo. We propose that CdbA acts as a nucleoid-associated protein that contributes to chromosome organization and is modulated by c-di-GMP, thus revealing a link between c-di-GMP signaling and chromosome biology.

The second messenger c-di-GMP modulates multiple responses to environmental and cellular signals in bacteria. Here, Skotnicka et al. identify a protein that binds c-di-GMP and contributes to chromosome organization and segregation in Myxococcus xanthus, with DNA-binding activity regulated by c-di-GMP.

From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.

Building gene regulatory networks from scATAC-seq and scRNA-seq using Linked Self Organizing Maps

Rapid advances in single-cell assays have outpaced methods for analysis of those data types. Different single-cell assays show extensive variation in sensitivity and signal to noise levels. In particular, scATAC-seq generates extremely sparse and noisy datasets. Existing methods developed to analyze this data require cells amenable to pseudo-time analysis or require datasets with drastically different cell-types. We describe a novel approach using self-organizing maps (SOM) to link scATAC-seq regions with scRNA-seq genes that overcomes these challenges and can generate draft regulatory networks. Our SOMatic package generates chromatin and gene expression SOMs separately and combines them using a linking function. We applied SOMatic on a mouse pre-B cell differentiation time-course using controlled Ikaros over-expression to recover gene ontology enrichments, identify motifs in genomic regions showing similar single-cell profiles, and generate a gene regulatory network that both recovers known interactions and predicts new Ikaros targets during the differentiation process. The ability of linked SOMs to detect emergent properties from multiple types of highly-dimensional genomic data with very different signal properties opens new avenues for integrative analysis of heterogeneous data.

A novel LuxR-type solo of Sinorhizobium meliloti, NurR, is regulated by the chromosome replication coordinator, DnaA and activates quorum sensing

The genome of Sinorhizobium meliloti, a model for studying plant-bacteria symbiosis, contains eight genes coding for LuxR-like proteins. Two of these, SinR and ExpR, are essential for quorum sensing (QS). Roles and regulation surrounding the others are mostly unknown. Here, we reveal the DNA recognition sequence and regulon of the LuxR-like protein SMc00877. Unlike ExpR, which uses the long-chain acyl homoserine lactones (AHLs) as inducers, SMc00877 functioned independently of AHLs and was even functional in Escherichia coli. A target of SMc00877 is SinR, the major regulator of AHL production in S. meliloti. Disruption of SMc00877 decreased AHL production. A weaker production of AHLs resulted in smaller microcolonies, starting from single cells, and delayed AHL-dependent regulation. SMc00877 was expressed only in growing cells in the presence of replete nutrients. Therefore, we renamed it NurR (nutrient sensitive LuxR-like regulator). We traced this nutrient-sensitive expression to transcription control by the DNA replication initiation factor, DnaA, which is essential for growth. These results indicate that NurR has a role in modulating the threshold of QS activation according to growth. We propose growth behavior as an additional prerequisite to population density for the activation of QS in S. meliloti.

Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation

The differentiation of self-renewing progenitor cells requires not only the regulation of lineage- and developmental stage–specific genes but also the coordinated adaptation of housekeeping functions from a metabolically active, proliferative state toward quiescence. How metabolic and cell-cycle states are coordinated with the regulation of cell type–specific genes is an important question, because dissociation between differentiation, cell cycle, and metabolic states is a hallmark of cancer. Here, we use a model system to systematically identify key transcriptional regulators of Ikaros-dependent B cell–progenitor differentiation. We find that the coordinated regulation of housekeeping functions and tissue-specific gene expression requires a feedforward circuit whereby Ikaros down-regulates the expression of Myc. Our findings show how coordination between differentiation and housekeeping states can be achieved by interconnected regulators. Similar principles likely coordinate differentiation and housekeeping functions during progenitor cell differentiation in other cell lineages.

The human body is made from billions of cells comprizing many specialized cell types. All of these cells ultimately come from a single fertilized oocyte in a process that has two key features: proliferation, which expands cell numbers, and differentiation, which diversifies cell types. Here, we have examined the transition from proliferation to differentiation using B lymphocytes as an example. We find that the transition from proliferation to differentiation involves changes in the expression of genes, which can be categorized into cell-type–specific genes and broadly expressed “housekeeping” genes. The expression of many housekeeping genes is controlled by the gene regulatory factor Myc, whereas the expression of many B lymphocyte–specific genes is controlled by the Ikaros family of gene regulatory proteins. Myc is repressed by Ikaros, which means that changes in housekeeping and tissue-specific gene expression are coordinated during the transition from proliferation to differentiation.

Identification of new DNA-associated proteins from Waddlia chondrophila

Transcriptional regulation in Chlamydiae is still poorly understood. The absence until recently of genetic tools is the main cause of this gap. We discovered three new potential DNA-associated proteins of Waddlia chondrophila, a Chlamydia-related bacterium, using heparin chromatography coupled to mass spectrometry (Wcw_0377, Wcw_1456, and Wcw_1460). By ChIP-seq analysis, we determined the regulatory landscape of these three proteins and we showed that Wcw_0377 binds all along the genome whereas Wcw_1456 and _1460 possess a wide regulon with a large number of co-regulated genes. Wcw_1456 and Wcw_1460 interact with RpoD (σ⁶⁶), emerging as potential RpoD regulators. On the other hand, Wcw_0377 is able to reach the host nucleus, where it might interact with eukaryotic histones through its putative chromatin-remodelling SWIB/MDM2 domain.

Novel Discovery of LINE-1 in a Korean Individual by a Target Enrichment Method

Long interspersed element-1 (LINE-1 or L1) is an autonomous retrotransposon, which is capable of inserting into a new region of genome. Previous studies have reported that these elements lead to genomic variations and altered functions by affecting gene expression and genetic networks. Mounting evidence strongly indicates that genetic diseases or various cancers can occur as a result of retrotransposition events that involve L1s. Therefore, the development of methodologies to study the structural variations and interpersonal insertion polymorphisms by L1 element-associated changes in an individual genome is invaluable. In this study, we applied a systematic approach to identify human-specific L1s (i.e., L1Hs) through the bioinformatics analysis of high-throughput next-generation sequencing data. We identified 525 candidates that could be inferred to carry non-reference L1Hs in a Korean individual genome (KPGP9). Among them, we randomly selected 40 candidates and validated that approximately 92.5% of non-reference L1Hs were inserted into a KPGP9 genome. In addition, unlike conventional methods, our relatively simple and expedited approach was highly reproducible in confirming the L1 insertions. Taken together, our findings strongly support that the identification of non-reference L1Hs by our novel target enrichment method demonstrates its future application to genomic variation studies on the risk of cancer and genetic disorders.

KSHV encoded ORF59 modulates histone arginine methylation of the viral genome to promote viral reactivation

Kaposi's sarcoma associated herpesvirus (KSHV) persists in a highly-ordered chromatin structure inside latently infected cells with the majority of the viral genome having repressive marks. However, upon reactivation the viral chromatin landscape changes into 'open' chromatin through the involvement of lysine demethylases and methyltransferases. Besides methylation of lysine residues of histone H3, arginine methylation of histone H4 plays an important role in controlling the compactness of the chromatin. Symmetric methylation of histone H4 at arginine 3 (H4R3me2s) negatively affects the methylation of histone H3 at lysine 4 (H3K4me3), an active epigenetic mark deposited on the viral chromatin during reactivation. We identified a novel binding partner to KSHV viral DNA processivity factor, ORF59-a protein arginine methyl transferase 5 (PRMT5). PRMT5 is an arginine methyltransferase that dimethylates arginine 3 (R3) of histone H4 in a symmetric manner, one hallmark of condensed chromatin. Our ChIP-seq data of symmetrically methylated H4 arginine 3 showed a significant decrease in H4R3me2s on the viral genome of reactivated cells as compared to the latent cells. Reduction in arginine methylation correlated with the binding of ORF59 on the viral chromatin and disruption of PRMT5 from its adapter protein, COPR5 (cooperator of PRMT5). Binding of PRMT5 through COPR5 is important for symmetric methylation of H4R3 and the expression of ORF59 competitively reduces the association of PRMT5 with COPR5, leading to a reduction in PRMT5 mediated arginine methylation. This ultimately resulted in a reduced level of symmetrically methylated H4R3 and increased levels of H3K4me3 marks, contributing to the formation of an open chromatin for transcription and DNA replication. Depletion of PRMT5 levels led to a decrease in symmetric methylation and increase in viral gene transcription confirming the role of PRMT5 in viral reactivation. In conclusion, ORF59 modulates histone-modifying enzymes to alter the chromatin structure during lytic reactivation.