Epigenomic Features Research Articles

Deciphering shared attributes of plant long non-coding RNAs through a comparative computational approach

Over the past decade, long non-coding RNA (lncRNA), which lacks protein-coding potential, has emerged as an essential regulator of the genome. The present study examined 13,599 lncRNAs in Arabidopsis thaliana, 11,565 in Oryza sativa, and 32,397 in Zea mays for their characteristic features and explored the associated genomic and epigenomic features. We found lncRNAs were distributed throughout the chromosomes and the Helitron family of transposable elements (TEs) enriched, while the terminal inverted repeat depleted in lncRNA transcribing regions. Our analyses determined that lncRNA transcribing regions show rare or weak signals for most epigenetic marks except for H3K9me2 and cytosine methylation in all three plant species. LncRNAs showed preferential localization in the nucleus and cytoplasm; however, the distribution ratio in the cytoplasm and nucleus varies among the studied plant species. We identified several conserved endogenous target mimic sites in the lncRNAs among the studied plants. We found 233, 301, and 273 unique miRNAs, potentially targeting the lncRNAs of A. thaliana, O. sativa, and Z. mays, respectively. Our study has revealed that miRNAs, which interact with lncRNAs, target genes that are involved in a diverse array of biological and molecular processes. The miRNA-targeted lncRNAs displayed a strong affinity for several transcription factors, including ERF and BBR-BPC, mutually present in all three plants, advocating their conserved functions. Overall, the present study showed that plant lncRNAs exhibit conserved genomic and epigenomic characteristics and potentially govern the growth and development of plants.

Computational methods for analysing multiscale 3D genome organization.

Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.

SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data.

Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.

Prediction of G4 formation in live cells with epigenetic data: a deep learning approach.

G-quadruplexes (G4s) are secondary structures abundant in DNA that may play regulatory roles in cells. Despite the ubiquity of the putative G-quadruplex-forming sequences (PQS) in the human genome, only a small fraction forms G4 structures in cells. Folded G4, histone methylation and chromatin accessibility are all parts of the complex cis regulatory landscape. We propose an approach for prediction ofG4 formation in cells that incorporates epigenetic and chromatin accessibility data. The novel approach termed epiG4NN efficiently predicts cell-specific G4 formation in live cells based on a local epigenomic snapshot. Our results confirm the close relationship between H3K4me3 histone methylation, chromatin accessibility and G4 structure formation. Trained on A549 cell data, epiG4NN was then able to predict G4 formation in HEK293T and K562 cell lines. We observe the dependency of model performance with different epigenetic features on the underlying experimental condition of G4 detection. We expect that this approach will contribute to the systematic understanding of correlations between structural and epigenomic feature landscape.

UNADON: transformer-based model to predict genome-wide chromosome spatial position.

The spatial positioning of chromosomes relative to functional nuclear bodies is intertwined with genome functions such as transcription. However, the sequence patterns and epigenomic features that collectively influence chromatin spatial positioning in a genome-wide manner are not well understood. Here, we develop a new transformer-based deep learning model called UNADON, which predicts the genome-wide cytological distance to a specific type of nuclear body, as measured by TSA-seq, using both sequence features and epigenomic signals. Evaluations of UNADON in four cell lines (K562, H1, HFFc6, HCT116) show high accuracy in predicting chromatin spatial positioning to nuclear bodies when trained on a single cell line. UNADON also performed well in an unseen cell type. Importantly, we reveal potential sequence and epigenomic factors that affect large-scale chromatin compartmentalization in nuclear bodies. Together, UNADON provides new insights into the principles between sequence features and large-scale chromatin spatial localization, which has important implications for understanding nuclear structure and function. The source code of UNADON can be found at https://github.com/ma-compbio/UNADON.

Chromatin structure and context-dependent sequence features control prime editing efficiency.

Prime editing (PE) is a highly versatile CRISPR-Cas9 genome editing technique. The current constructs, however, have variable efficiency and may require laborious experimental optimization. This study presents statistical models for learning the salient epigenomic and sequence features of target sites modulating the editing efficiency and provides guidelines for designing optimal PEs. We found that both regional constitutive heterochromatin and local nucleosome occlusion of target sites impede editing, while position-specific G/C nucleotides in the primer-binding site (PBS) and reverse transcription (RT) template regions of PE guide RNA (pegRNA) yield high editing efficiency, especially for short PBS designs. The presence of G/C nucleotides was most critical immediately 5' to the protospacer adjacent motif (PAM) site for all designs. The effects of different last templated nucleotides were quantified and observed to depend on the length of both PBS and RT templates. Our models found AGG to be the preferred PAM and detected a guanine nucleotide four bases downstream of the PAM to facilitate editing, suggesting a hitherto-unrecognized interaction with Cas9. A neural network interpretation method based on nonextensive statistical mechanics further revealed multi-nucleotide preferences, indicating dependency among several bases across pegRNA. Our work clarifies previous conflicting observations and uncovers context-dependent features important for optimizing PE designs.

Integrated analysis of genome-wide association studies and 3D epigenomic characteristics reveal the BMP2 gene regulating loin muscle depth in Yorkshire pigs.

The lack of integrated analysis of genome-wide association studies (GWAS) and 3D epigenomics restricts a deep understanding of the genetic mechanisms of meat-related traits. With the application of techniques as ChIP-seq and Hi-C, the annotations of cis-regulatory elements in the pig genome have been established, which offers a new opportunity to elucidate the genetic mechanisms and identify major genetic variants and candidate genes that are significantly associated with important economic traits. Among these traits, loin muscle depth (LMD) is an important one as it impacts the lean meat content. In this study, we integrated cis-regulatory elements and genome-wide association studies (GWAS) to identify candidate genes and genetic variants regulating LMD. Five single nucleotide polymorphisms (SNPs) located on porcine chromosome 17 were significantly associated with LMD in Yorkshire pigs. A 10 kb quantitative trait locus (QTL) was identified as a candidate functional genomic region through the integration of linkage disequilibrium and linkage analysis (LDLA) and high-throughput chromosome conformation capture (Hi-C) analysis. The BMP2 gene was identified as a candidate gene for LMD based on the integrated results of GWAS, Hi-C meta-analysis, and cis-regulatory element data. The identified QTL region was further verified through target region sequencing. Furthermore, through using dual-luciferase assays and electrophoretic mobility shift assays (EMSA), two SNPs, including SNP rs321846600, located in the enhancer region, and SNP rs1111440035, located in the promoter region, were identified as candidate SNPs that may be functionally related to the LMD. Based on the results of GWAS, Hi-C, and cis-regulatory elements, the BMP2 gene was identified as an important candidate gene regulating variation in LMD. The SNPs rs321846600 and rs1111440035 were identified as candidate SNPs that are functionally related to the LMD of Yorkshire pigs. Our results shed light on the advantages of integrating GWAS with 3D epigenomics in identifying candidate genes for quantitative traits. This study is a pioneering work for the identification of candidate genes and related genetic variants regulating one key production trait (LMD) in pigs by integrating genome-wide association studies and 3D epigenomics.

PyMEGABASE: Predicting Cell-Type-Specific Structural Annotations of Chromosomes Using the Epigenome

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

Abstract B012: Genomic and epigenomic drivers of double-negative metastatic prostate cancer

Abstract Systemic targeted therapy in prostate cancer is primarily focused on ablating androgen receptor (AR) signaling. Androgen deprivation therapy and second-generation AR-targeted therapy selectively favor the development of treatment-resistant subtypes of metastatic castration-resistant prostate cancer (mCRPC), defined by whether the tumor expresses either AR or neuroendocrine (NE) markers. Among the subtypes of mCRPC, the molecular drivers of double-negative (AR-/NE-) mCRPC are poorly defined. In this study, we comprehensively characterize genomic and epigenomic features of treatment-emergent mCRPC subtypes in 210 tumors by integrating matched RNA sequencing, whole-genome sequencing, and whole-genome bisulfite sequencing. We show that AR-/NE- tumors exhibit a clinically and molecularly distinct phenotype. Patients with AR-/NE- mCRPC tumors have the shortest survival, and these tumors preferentially harbor amplification of the chromatin remodeler CHD7 and loss of PTEN. We demonstrate that methylation changes in CHD7 candidate enhancers are linked to elevated CHD7 expression in AR-/NE+ tumors. Moreover, we use genome-wide methylation analysis to nominate the Krüppel-like factor gene KLF5 as a driver of the AR-/NE- phenotype and link its activity to loss of the tumor suppressor RB1. These observations reveal the aggressiveness of the AR-/NE- tumors and elucidate genomic and epigenomic drivers of mCRPC subtypes, which may facilitate the identification of novel therapeutic targets in this highly aggressive disease. Citation Format: Arian Lundberg, Meng Zhang, Rahul R. Aggarwal, Haolong Li, Li Zhang, Adam Foye, Martin Sjöström, Jonathan Chou, Kevin Chang, Thaidy Moreno-Rodriguez, Raunak Shrestha, Avi Baskin, Xiaolin Zhu, Alana S. Weinstein, Noah Younger, Joshi J. Alumkal, Tomasz M. Beer, Kim N. Chi, Christopher P. Evans, Martin Gleave, Primo N. Lara, Robert E. Reiter, Matthew B. Rettig, Owen N. Witte, Alexander W. Wyatt, Felix Y. Feng, Eric J. Small, David A. Quigley. Genomic and epigenomic drivers of double-negative metastatic prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B012.

Abstract A009: Distinct activity of androgen receptor splice variants in promoting prostate cancer metastasis

Abstract Introduction: Constitutively active androgen receptor splice variant 7 (AR-V7) correlates with the adaptation to androgen receptor signaling inhibition treatment in prostate cancer (PCa) patients. Despite intensive studies of AR-V7, it is still unclear how the distinct genomic and epigenomic characteristics of AR-V7-dependent cistrome and transcriptome are distinct from full-length AR (AR-FL) and whether AR-V7 may play a role in promoting the metastatic progression of castration-resistant PCa (CRPC). Experiments: To accurately compare the activity of AR-V7 with AR-FL, we generated lentiviral stable cell lines with inducible overexpression of AR-V7 or AR-FL using AR-V7 negative LNCaP and C4-2 cell lines. We assessed the in vivo impact of AR-V7 or AR-FL expression on PCa metastasis by injecting cells in zebrafish embryos and the tibias of castrated male mice. ChIP-seq analyses of AR-V7, AR-FL, FOXA1, and H3K27ac, ATAC-seq analysis, and RNA-seq analysis were conducted in to characterize the global cistrome and transcriptome activity of AR-V7 in comparison with AR-FL. In addition, we also examined how a posttranslational modification, Ser81 phosphorylation, affects AR-V7 activity by generating an S81A mutant of AR-V7 and using S81-phosphorylation inhibitors. Results: Our in vivo study revealed that overexpressed-AR-V7, but not AR-FL, strongly promotes tumor cell invasion into blood vessels and induces osteoblastic bone lesions. Through integrated ChIP-, ATAC- and RNA-seq analysis, we determined that AR-V7 has a “pioneer factor-like” ability to bind to androgen-responsive elements (AREs) located at compact chromatin regions and activates the enhancers by increasing the chromatin accessibility. This mechanism leads to a unique AR-V7-regulated transcriptional program that is completely independent of AR-FL activity and is highly enriched for genes mediating epithelial-mesenchymal transition and metastatic functions. We then identified a subset of AR-V7-specific targets with significant overexpression in CRPC tumor samples and associated with poor clinical outcomes. In particular, we found that SOX9, a critical metastasis driver gene, was a direct target and downstream effector of AR-V7, and its protein expression was dramatically upregulated at AR-V7-induced bone lesions. Furthermore, we found that the pro-metastasis function of AR-V7 can be enhanced by Ser81 phosphorylation through chromatin-binding-independent mechanisms, and that targeting this phosphorylation by CDK9 inhibitors can block AR-V7-induced SOX9 expression and impair AR-V7-mediated metastasis function. Conclusion: Our study provides novel molecular insights into the role of AR splice variants in driving the metastatic progression of CRPC. In specific, these data have demonstrated the distinctive transcriptional program of AR-V7 from AR-FL, identified critical AR-V7 targets, and determined the function of Ser81 phosphorylation on AR-V7. Our data also suggest a new therapeutic strategy to target AR-V7-induced metastasis cascade in CRPC by using CDK9 inhibitor treatment. Citation Format: Maryam Labaf, Dong Han, Yawei Zhao, Jude Owiredu, Songqi Zhang, Kavita Venkataramani, Jocelyn S. Steinfeld, Wanting Han, Muqing Li, Mingyu Liu, Zifeng Wang, Anna Besschetnova, Susan C. Patalano-Salsman, Jill A. Macoska, Xin Yuan, Steven P. Balk, Stephen R. Plymate, Shuai Gao, Kellee R. Siegfried-Harris, Ruihua Liu, Gabrielle Foxa, Mary M. Stangis, Piotr J. Czernik, Bart Williams, Kourosh Zarringhalam, Xiaohong Li, Changmeng Cai. Distinct activity of androgen receptor splice variants in promoting prostate cancer metastasis [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A009.

MATRIX plasma-in-plasma contrived samples assessment and detection of MRD using the Personalis NeXT Personal assay.

e15056 Background: Detection of circulating tumor DNA (ctDNA) has been shown to correlate with clinical outcome of oncology patients. Molecular residual disease (MRD) profiling by ctDNA is being rapidly deployed. Current tumor-informed MRD tests assess a relatively small number of personalised variants, placing limits on their detection sensitivity and ultimately leading to false-negative results due to insufficient assay limit of detection (LOD). Here we report a performance evaluation of the Personalis NeXT Personal tumor-informed MRD assay, using a novel design for contrived samples that are highly commutable to clinical samples, enabling robust assessment of these emerging MRD assays. Methods: Our novel samples were built from commercially acquired matched tumor and plasma samples, across different indications. The cancer plasma was diluted into a background of healthy donor plasma to create the 72 plasma-in-plasma samples in each study (total of 144). Personalis performed WGS on the matched solid tumor and normal samples from each patient. ~1800 somatic variants were selected for each patient. A personalized panel was designed and used to enrich for the selected targets in the individual plasma samples. An aggregated positive variant score was evaluated to determine the presence of ctDNA in each plasma sample. Results: MATRIX 1 panels averaged 1863 variants (range: 1818 to 1888) selected for MRD tracking. With 152 clinically relevant variants and additional assay components, an average of 2206 variants were assessed per patient. MATRIX 2 panels averaged 1836 variants (range: 1819 to 1867) selected for MRD tracking. With 2130 clinically relevant variants they averaged 4094 variants assessed per patient. In the MATRIX 1 study, tumor signal was detected in all analyzed samples, including 9 samples at 0.002% tumor plasma dilution, with an assay sensitivity of 100%. The MATRIX 2 study showed tumor signal detected in 14 of 16 samples at 0.001% tumor plasma dilution. The 2 false negatives were reported at the 0.001% tumor plasma dilution. Thus, the assay sensitivity was 87.5% at the lowest dilution (0.001%) and 96.8% overall. Conclusions: The MATRIX plasma-in-plasma approach is a robust option for assessing the sensitivity of MRD assays to low levels of ctDNA. This approach addresses all parts of an MRD assay for both the plasma and tumor/normal tissues, and is the closest thing to real clinical samples while allowing direct interrogation of sensitivity. Additionally, it allows assessment of any genomic or epigenomic biological feature. The Personalis NeXT Personal assay shows ultra-high sensitivity with reproducible data down to the 1-3 PPM range, and expansion of the personalized panel fixed clinical content allows tracking of more driver and resistance mutations with no impact to the MRD sensitivity.

The impact of local genomic properties on the evolutionary fate of genes.

Functionally indispensable genes are likely to be retained and otherwise to be lost during evolution. This evolutionary fate of a gene can also be affected by factors independent of gene dispensability, including the mutability of genomic positions, but such features have not been examined well. To uncover the genomic features associated with gene loss, we investigated the characteristics of genomic regions where genes have been independently lost in multiple lineages. With a comprehensive scan of gene phylogenies of vertebrates with a careful inspection of evolutionary gene losses, we identified 813 human genes whose orthologs were lost in multiple mammalian lineages: designated 'elusive genes.' These elusive genes were located in genomic regions with rapid nucleotide substitution, high GC content, and high gene density. A comparison of the orthologous regions of such elusive genes across vertebrates revealed that these features had been established before the radiation of the extant vertebrates approximately 500 million years ago. The association of human elusive genes with transcriptomic and epigenomic characteristics illuminated that the genomic regions containing such genes were subject to repressive transcriptional regulation. Thus, the heterogeneous genomic features driving gene fates toward loss have been in place and may sometimes have relaxed the functional indispensability of such genes. This study sheds light on the complex interplay between gene function and local genomic properties in shaping gene evolution that has persisted since the vertebrate ancestor.

The MMP-2 histone H3 N-terminal tail protease is selectively targeted to the transcription start sites of active genes

BackgroundProteolysis of the histone H3 N-terminal tail (H3NT) is an evolutionarily conserved epigenomic feature of nearly all eukaryotes, generating a cleaved H3 product that is retained in ~ 5–10% of the genome. Although H3NT proteolysis within chromatin was first reported over 60 years ago, the genomic sites targeted for H3NT proteolysis and the impact of this histone modification on chromatin structure and function remain largely unknown. The goal of this study was to identify the specific regions targeted for H3NT proteolysis and investigate the consequence of H3NT “clipping” on local histone post-translational modification (PTM) dynamics.ResultsLeveraging recent findings that matrix metalloproteinase 2 (MMP-2) functions as the principal nuclear H3NT protease in the human U2OS osteosarcoma cell line, a ChIP-Seq approach was used to map MMP-2 localization genome wide. The results indicate that MMP-2 is selectively targeted to the transcription start sites (TSSs) of protein coding genes, primarily at the + 1 nucleosome. MMP-2 localization was exclusive to highly expressed genes, further supporting a functional role for H3NT proteolysis in transcriptional regulation. MMP-2 dependent H3NT proteolysis at the TSSs of these genes resulted in a > twofold reduction of activation-associated histone H3 PTMs, including H3K4me3, H3K9ac and H3K18ac. One of genes requiring MMP-2 mediated H3NT proteolysis for proficient expression was the lysosomal cathepsin B protease (CTSB), which we discovered functions as a secondary nuclear H3NT protease in U2OS cells.ConclusionsThis study revealed that the MMP-2 H3NT protease is selectively targeted to the TSSs of active protein coding genes in U2OS cells. The resulting H3NT proteolysis directly alters local histone H3 PTM patterns at TSSs, which likely functions to regulate transcription. MMP-2 mediated H3NT proteolysis directly activates CTSB, a secondary H3NT protease that generates additional cleaved H3 products within chromatin.

Forkhead box protein D2 suppresses colorectal cancer by reprogramming enhancer interactions.

Somatic stem cells contribute to normal tissue homeostasis, and their epigenomic features play an important role in regulating tissue identities or developing disease states. Enhancers are one of the key players controlling chromatin context-specific gene expression in a spatial and temporal manner while maintaining tissue homeostasis, and their dysregulation leads to tumorigenesis. Here, epigenomic and transcriptomic analyses reveal that forkhead box protein D2 (FOXD2) is a hub for the gene regulatory network exclusive to large intestinal stem cells, and its overexpression plays a significant role in colon cancer regression. FOXD2 is positioned at the closed chromatin and facilitates mixed-lineage leukemia protein-4 (MLL4/KMT2D) binding to deposit H3K4 monomethylation. De novo FOXD2-mediated chromatin interactions rewire the regulation of p53-responsive genes and induction of apoptosis. Taken together, our findings illustrate the novel mechanistic details of FOXD2 in suppressing colorectal cancer growth and suggest its function as a chromatin-tuning factor and a potential therapeutic target for colorectal cancer.

Chicken Erythrocyte: Epigenomic Regulation of Gene Activity.

The chicken genome is one-third the size of the human genome and has a similarity of sixty percent when it comes to gene content. Harboring similar genome sequences, chickens' gene arrangement is closer to the human genomic organization than it is to rodents. Chickens have been used as model organisms to study evolution, epigenome, and diseases. The chicken nucleated erythrocyte's physiological function is to carry oxygen to the tissues and remove carbon dioxide. The erythrocyte also supports the innate immune response in protecting the chicken from pathogens. Among the highly studied aspects in the field of epigenetics are modifications of DNA, histones, and their variants. In understanding the organization of transcriptionally active chromatin, studies on the chicken nucleated erythrocyte have been important. Through the application of a variety of epigenomic approaches, we and others have determined the chromatin structure of expressed/poised genes involved in the physiological functions of the erythrocyte. As the chicken erythrocyte has a nucleus and is readily isolated from the animal, the chicken erythrocyte epigenome has been studied as a biomarker of an animal's long-term exposure to stress. In this review, epigenomic features that allow erythroid gene expression in a highly repressive chromatin background are presented.

Genomic and transcriptomic features between primary and paired metastatic fumarate hydratase–deficient renal cell carcinoma

BackgroundFumarate hydratase–deficient renal cell carcinoma (FH-RCC) is a rare highly aggressive subtype of kidney cancer for which the distinct genomic, transcriptomic, and evolutionary relationships between metastatic and primary lesions are still unclear.MethodsIn this study, whole-exome, RNA-seq, and DNA methylation sequencing were performed on primary-metastatic paired specimens from 19 FH-RCC cases, including 23 primary and 35 matched metastatic lesions. Phylogenetic and clonal evolutionary analyses were used to investigate the evolutionary characteristics of FH-RCC. Transcriptomic analyses, immunohistochemistry, and multiple immunofluorescence experiments were performed to identify the tumor microenvironmental features of metastatic lesions.ResultsPaired primary and metastatic lesions generally showed similar characteristics of tumor mutation burden, tumor neoantigen burden, microsatellite instability score, CNV burden, and genome instability index. Notably, we identified an FH-mutated founding MRCA (the most recent common ancestor) clone that dominated the early evolutionary trajectories in FH-RCC. Although both primary and metastatic lesions manifested high immunogenicity, metastatic lesions exhibited higher enrichment of T effector cells and immune-related chemokines, together with upregulation of PD-L1, TIGIT, and BTLA. In addition, we found that concurrent NF2 mutation may be associated with bone metastasis and upregulation of cell cycle signature in metastatic lesions. Furthermore, although in FH-RCC metastatic lesions in general shared similar CpG island methylator phenotype with primary lesions, we found metastatic lesions displaying hypomethylated chemokine and immune checkpoints related genomic loci.ConclusionsOverall, our study demonstrated the genomic, epigenomic, and transcriptomic features of metastatic lesions in FH-RCC and revealed their early evolutionary trajectory. These results provided multi-omics evidence portraying the progression of FH-RCC.

Comparing genomic and epigenomic features across species using the WashU Comparative Epigenome Browser.

Genome browsers have become an intuitive and critical tool to visualize and analyze genomic features and data. Conventional genome browsers display data/annotations on a single reference genome/assembly; there are also genomic alignment viewer/browsers that help users visualize alignment, mismatch, and rearrangement between syntenic regions. However, there is a growing need for a comparative epigenome browser that can display genomic and epigenomic data sets across different species and enable users to compare them between syntenic regions. Here, we present the WashU Comparative Epigenome Browser. It allows users to load functional genomic data sets/annotations mapped to different genomes and display them over syntenic regions simultaneously. The browser also displays genetic differences between the genomes from single-nucleotide variants (SNVs) to structural variants (SVs) to visualize the association between epigenomic differences and genetic differences. Instead of anchoring all data sets to the reference genome coordinates, it creates independent coordinates of different genome assemblies to faithfully present features and data mapped to different genomes. It uses a simple, intuitive genome-align track to illustrate the syntenic relationship between different species. It extends the widely used WashU Epigenome Browser infrastructure and can be expanded to support multiple species. This new browser function will greatly facilitate comparative genomic/epigenomic research, as well as support the recent growing needs to directly compare and benchmark the T2T CHM13 assembly and other human genome assemblies.

Patterns, mechanisms, and consequences of homoeologous exchange in allopolyploid angiosperms: A genomic and epigenomic perspective.

Allopolyploids result from hybridization between different evolutionary lineages coupled with genome doubling. Homoeologous chromosomes (chromosomes with common shared ancestry) may undergo recombination immediately after allopolyploid formation and continue over successive generations. The outcome of this meiotic pairing behavior is dynamic and complex. Homoeologous exchanges (HEs) may lead to the formation of unbalanced gametes, reduced fertility, and selective disadvantage. In contrast, HEs could act as sources of novel evolutionary substrates, shifting the relative dosage of parental gene copies, generating novel phenotypic diversity, and helping the establishment of neo-allopolyploids. However, HE patterns vary among lineages, across generations, and even within individual genomes and chromosomes. The causes and consequences of this variation are not fully understood, though interest in this evolutionary phenomenon has increased in the last decade. Recent technological advances show promise in uncovering the mechanistic basis of HEs. Here, we describe recent observations of the common patterns among allopolyploid angiosperm lineages, underlying genomic and epigenomic features, and consequences of HEs. We identify critical research gaps and discuss future directions with far-reaching implications in understanding allopolyploid evolution and applying them to the development of important phenotypic traits of polyploid crops.

Breaking the Mold: Epigenetics and Genomics Approaches Addressing Novel Treatments and Chemoresponse in TGCT Patients.

Testicular germ-cell tumors (TGCT) have been widely recognized for their outstanding survival rates, commonly attributed to their high sensitivity to cisplatin-based therapies. Despite this, a subset of patients develops cisplatin resistance, for whom additional therapeutic options are unsuccessful, and ~20% of them will die from disease progression at an early age. Several efforts have been made trying to find the molecular bases of cisplatin resistance. However, this phenomenon is still not fully understood, which has limited the development of efficient biomarkers and precision medicine approaches as an alternative that could improve the clinical outcomes of these patients. With the aim of providing an integrative landscape, we review the most recent genomic and epigenomic features attributed to chemoresponse in TGCT patients, highlighting how we can seek to combat cisplatin resistance through the same mechanisms by which TGCTs are particularly hypersensitive to therapy. In this regard, we explore ongoing treatment directions for resistant TGCT and novel targets to guide future clinical trials. Through our exploration of recent findings, we conclude that epidrugs are promising treatments that could help to restore cisplatin sensitivity in resistant tumors, shedding light on potential avenues for better prognosis for the benefit of the patients.

Predicting enhancer-promoter interaction based on epigenomic signals.

Introduction: The physical interactions between enhancers and promoters are often involved in gene transcriptional regulation. High tissue-specific enhancer-promoter interactions (EPIs) are responsible for the differential expression of genes. Experimental methods are time-consuming and labor-intensive in measuring EPIs. An alternative approach, machine learning, has been widely used to predict EPIs. However, most existing machine learning methods require a large number of functional genomic and epigenomic features as input, which limits the application to different cell lines. Methods: In this paper, we developed a random forest model, HARD (H3K27ac, ATAC-seq, RAD21, and Distance), to predict EPI using only four types of features. Results: Independent tests on a benchmark dataset showed that HARD outperforms other models with the fewest features. Discussion: Our results revealed that chromatin accessibility and the binding of cohesin are important for cell-line-specific EPIs. Furthermore, we trained the HARD model in the GM12878 cell line and performed testing in the HeLa cell line. The cross-cell-lines prediction also performs well, suggesting it has the potential to be applied to other cell lines.