Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines.

Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies.

DG-Affinity: predicting antigen-antibody affinity with language models from sequences.

BACKGROUND: Antibody-mediated immune responses play a crucial role in the immune defense of human body. The evolution of bioengineering has led the progress of antibody-derived drugs, showing promising efficacy in cancer and autoimmune disease therapy. A critical step of this development process is obtaining the affinity between antibodies and their binding antigens. RESULTS: In this study, we introduce a novel sequence-based antigen-antibody affinity prediction method, named DG-Affinity. DG-Affinity uses deep neural networks to efficiently and accurately predict the affinity between antibodies and antigens from sequences, without the need for structural information. The sequences of both the antigen and the antibody are first transformed into embedding vectors by two pre-trained language models, then these embeddings are concatenated into an ConvNeXt framework with a regression task. The results demonstrate the superiority of DG-Affinity over the existing structure-based prediction methods and the sequence-based tools, achieving a Pearson's correlation of over 0.65 on an independent test dataset. CONCLUSIONS: Compared to the baseline methods, DG-Affinity achieves the best performance and can advance the development of antibody design. It is freely available as an easy-to-use web server at https://www.digitalgeneai.tech/solution/affinity .

Mammalian splicing divergence is shaped by drift, buffering in trans, and a scaling law.

Alternative splicing is ubiquitous, but the mechanisms underlying its pattern of evolutionary divergence across mammalian tissues are still underexplored. Here, we investigated the cis-regulatory divergences and their relationship with tissue-dependent trans-regulation in multiple tissues of an F1 hybrid between two mouse species. Large splicing changes between tissues are highly conserved and likely reflect functional tissue-dependent regulation. In particular, micro-exons frequently exhibit this pattern with high inclusion levels in the brain. Cis-divergence of splicing appears to be largely non-adaptive. Although divergence is in general associated with higher densities of sequence variants in regulatory regions, events with high usage of the dominant isoform apparently tolerate more mutations, explaining why their exon sequences are highly conserved but their intronic splicing site flanking regions are not. Moreover, we demonstrate that non-adaptive mutations are often masked in tissues where accurate splicing likely is more important, and experimentally attribute such buffering effect to trans-regulatory splicing efficiency.

Systematic Analysis of Monoallelic Gene Expression and Chromatin Accessibility Across Multiple Tissues in Hybrid Mice.

In diploid eukaryotic organisms, both alleles of each autosomal gene are usually assumed to be simultaneously expressed at similar levels. However, some genes can be expressed preferentially or strictly from a single allele, a process known as monoallelic expression. Classic monoallelic expression of X-chromosome-linked genes, olfactory receptor genes and developmentally imprinted genes is the result of epigenetic modifications. Genetic-origin-dependent monoallelic expression, however, is caused by cis-regulatory differences between the alleles. There is a paucity of systematic study to investigate these phenomena across multiple tissues, and the mechanisms underlying such monoallelic expression are not yet fully understood. Here we provide a detailed portrait of monoallelic gene expression across multiple tissues/cell lines in a hybrid mouse cross between the Mus musculus strain C57BL/6J and the Mus spretus strain SPRET/EiJ. We observed pervasive tissue-dependent allele-specific gene expression: in total, 1,839 genes exhibited monoallelic expression in at least one tissue, and 410 genes in at least two tissues. Among these 88 are monoallelic genes with different active alleles between tissues, probably representing genetic-origin-dependent monoallelic expression. We also identified six autosomal monoallelic genes with the active allele being identical in all eight tissues, which are likely novel candidates of imprinted genes. To depict the underlying regulatory mechanisms at the chromatin layer, we performed ATAC-seq in two different cell lines derived from the F1 mouse. Consistent with the global expression pattern, cell-type dependent monoallelic peaks were found, and a higher proportion of C57BL/6J-active peaks were observed in both cell types, implying possible species-specific regulation. Finally, only a small part of monoallelic gene expression could be explained by allelic differences in chromatin organization in promoter regions, suggesting that other distal elements may play important roles in shaping the patterns of allelic gene expression across tissues.

CASB: a concanavalin A-based sample barcoding strategy for single-cell sequencing.

Sample multiplexing facilitates single-cell sequencing by reducing costs, revealing subtle difference between similar samples, and identifying artifacts such as cell doublets. However, universal and cost-effective strategies are rather limited. Here, we reported a concanavalin A-based sample barcoding strategy (CASB), which could be followed by both single-cell mRNA and ATAC (assay for transposase-accessible chromatin) sequencing techniques. The method involves minimal sample processing, thereby preserving intact transcriptomic or epigenomic patterns. We demonstrated its high labeling efficiency, high accuracy in assigning cells/nuclei to samples regardless of cell type and genetic background, and high sensitivity in detecting doublets by three applications: 1) CASB followed by scRNA-seq to track the transcriptomic dynamics of a cancer cell line perturbed by multiple drugs, which revealed compound-specific heterogeneous response; 2) CASB together with both snATAC-seq and scRNA-seq to illustrate the IFN-γ-mediated dynamic changes on epigenome and transcriptome profile, which identified the transcription factor underlying heterogeneous IFN-γ response; and 3) combinatorial indexing by CASB, which demonstrated its high scalability.

CIGAR-seq, a CRISPR/Cas-based method for unbiased screening of novel mRNA modification regulators.

Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6 A and m5 C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high-throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR-seq). Using CIGAR-seq, we discovered NSUN6 as a novel mRNA m5 C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non-overlapping subsets of mRNA m5 C sites and together contributed to almost all the m5 C modification in mRNA. Finally, using m1 A as an example, we demonstrated that CIGAR-seq can be easily adapted for identifying regulators of other mRNA modification.

Integrative multi-omics analysis of a colon cancer cell line with heterogeneous Wnt activity revealed RUNX2 as an epigenetic regulator of EMT.

Epithelial-mesenchymal transition (EMT) program, which facilitates tumor metastasis, stemness and therapy resistance, is a reversible biological process that is largely orchestrated at the epigenetic level under the regulation of different cell signaling pathways. EMT state is often heterogeneous within individual tumors, though the epigenetic drivers underlying such heterogeneity remain elusive. In colon cancer, hyperactivation of the Wnt/ß-catenin signaling not only drives tumor initiation, but also promotes metastasis in late stage by promoting EMT program. However, it is unknown whether the intratumorally heterogeneous Wnt activity could directly drive EMT heterogeneity, and, if so, what are the underlying epigenetic driver(s). Here, by analyzing a phenotypically and molecularly heterogeneous colon cancer cell line using single-cell RNA sequencing, we identified two distinct cell populations with positively correlated Wnt activity and EMT state. Integrative multi-omics analysis of these two cell populations revealed RUNX2 as a critical transcription factor epigenetically driving the EMT heterogeneity. Both in vitro and in vivo genetic perturbation assays validated the EMT-enhancing effect of RUNX2, which remodeled chromatin landscape and activated a panel of EMT-associated genes through binding to their promoters and/or potential enhancers. Finally, by exploring the clinical data, we showed that RUNX2 expression is positively correlated with metastasis development and poor survival of colon cancer patients, as well as patients afflicted with other types of cancer. Taken together, our work revealed RUNX2 as a new EMT-promoting epigenetic regulator in colon cancer, which may potentially serve as a prognostic marker for tumor metastasis.

Pan-tissue analysis of allelic alternative polyadenylation suggests widespread functional regulation.

Alternative polyadenylation (APA) is a major layer of gene regulation. However, it has recently been argued that most APA represents molecular noise. To clarify their functional relevance and evolution, we quantified allele-specific APA patterns in multiple tissues from an F1 hybrid mouse. We found a clearly negative correlation between gene expression and APA diversity for the 2,866 genes (24.9%) with a dominant polyadenylation site (PAS) usage above or equal to 90%, suggesting that their other PASs represent molecular errors. Among the remaining genes with multiple PASs, 3,971 genes (34.5%) express two or more isoforms with potentially functional importance. Interestingly, the genes with potentially functional minor PASs specific to neuronal tissues often express two APA isoforms with distinct subcellular localizations. Furthermore, our analysis of cis-APA divergence shows its pattern across tissues is distinct from that of gene expression. Finally, we demonstrate that the relative usage of alternative PASs is not only affected by their cis-regulatory elements, but also by potential coupling between transcriptional and APA regulation as well as competition kinetics between alternative sites.

A novel cytogenetic method to image chromatin interactions at subkilobase resolution: Tn5 transposase-based fluorescence in situ hybridization.

There is an increasing interest in understanding how three-dimensional organization of the genome is regulated. Different strategies have been used to identify genome-wide chromatin interactions. However, owing to current limitations in resolving genomic contacts, visualization and validation of these genomic loci at subkilobase resolution remain unsolved to date. Here, we describe Tn5 transposase-based fluorescence in situ hybridization (Tn5-FISH), a polymerase chain reaction-based, cost-effective imaging method, which can colocalize the genomic loci at subkilobase resolution, dissect genome architecture, and verify chromatin interactions detected by chromatin configuration capture-derived methods. To validate this method, short-range interactions in the keratin-encoding gene (KRT) locus in the topologically associated domain were imaged by triple-color Tn5-FISH, indicating that Tn5-FISH is very useful to verify short-range chromatin interactions inside the contact domain and TAD. Therefore, Tn5-FISH can be a powerful molecular tool for clinical detection of cytogenetic changes in numerous genetic diseases such as cancers.

Full-length transcriptome reconstruction reveals a large diversity of RNA and protein isoforms in rat hippocampus.

Gene annotation is a critical resource in genomics research. Many computational approaches have been developed to assemble transcriptomes based on high-throughput short-read sequencing, however, only with limited accuracy. Here, we combine next-generation and third-generation sequencing to reconstruct a full-length transcriptome in the rat hippocampus, which is further validated using independent 5´ and 3´-end profiling approaches. In total, we detect 28,268 full-length transcripts (FLTs), covering 6,380 RefSeq genes and 849 unannotated loci. Based on these FLTs, we discover co-occurring alternative RNA processing events. Integrating with polysome profiling and ribosome footprinting data, we predict isoform-specific translational status and reconstruct an open reading frame (ORF)-eome. Notably, a high proportion of the predicted ORFs are validated by mass spectrometry-based proteomics. Moreover, we identify isoforms with subcellular localization pattern in neurons. Collectively, our data advance our knowledge of RNA and protein isoform diversity in the rat brain and provide a rich resource for functional studies.

HiCDB: a sensitive and robust method for detecting contact domain boundaries.

Contact domains are closely linked to gene regulation and lineage commitment, while current understanding of contact domains and their boundaries is still limited. Here, we present a novel method HiCDB, which is constructively based on local relative insulation metric and multi-scale aggregation approach to detect contact domain boundaries (CDBs) on Hi-C maps. Compared with other 'state-of-art' methods, HiCDB shows improved sensitivity and specificity in determining CDBs at various Hi-C resolutions. The superiority of HiCDB enabled us to study the epigenetic features of detected CDBs and showed enrichment of architectural proteins and cell-type-specific transcription factor binding sites at CDBs. The further comparison of GM12878 and IMR90 Hi-C datasets suggested that cell-type-specific CDBs are marked by active regulatory signals and correlate with activation of nearby cell identity genes.

Alterations of specific chromatin conformation affect ATRA-induced leukemia cell differentiation.

Chromatin conformation plays a key role in regulating gene expression and controlling cell differentiation. However, the whole-genome chromatin conformation changes that occur during leukemia cell differentiation are poorly understood. Here, we characterized the changes in chromatin conformation, histone states, chromatin accessibility, and gene expression using an all-trans retinoic acid (ATRA)-induced HL-60 cell differentiation model. The results showed that the boundaries of topological associated domains (TADs) were stable during differentiation; however, the chromatin conformations within several specific TADs were obviously changed. By combining H3K4me3, H3K27ac, and Hi-C signals, we annotated the differential gene-regulatory chromatin interactions upon ATRA induction. The gains and losses of the gene-regulatory chromatin interactions are significantly correlated with gene expression and chromatin accessibility. Finally, we found that the loss of GATA2 expression and DNA binding are crucial for the differentiation process, and changes in the chromatin structure around the GATA2 regulate its expression upon ATRA induction. This study provided both statistical insights and experimental details regarding the relationship between chromatin conformation changes and transcription regulation during leukemia cell differentiation, and the results suggested that the chromatin conformation is a new type of potential drug target for cancer therapy.

BL-Hi-C is an efficient and sensitive approach for capturing structural and regulatory chromatin interactions.

In human cells, DNA is hierarchically organized and assembled with histones and DNA-binding proteins in three dimensions. Chromatin interactions play important roles in genome architecture and gene regulation, including robustness in the developmental stages and flexibility during the cell cycle. Here we propose in situ Hi-C method named Bridge Linker-Hi-C (BL-Hi-C) for capturing structural and regulatory chromatin interactions by restriction enzyme targeting and two-step proximity ligation. This method improves the sensitivity and specificity of active chromatin loop detection and can reveal the regulatory enhancer-promoter architecture better than conventional methods at a lower sequencing depth and with a simpler protocol. We demonstrate its utility with two well-studied developmental loci: the beta-globin and HOXC cluster regions.

ChIA-PET2: a versatile and flexible pipeline for ChIA-PET data analysis.

ChIA-PET2 is a versatile and flexible pipeline for analyzing different types of ChIA-PET data from raw sequencing reads to chromatin loops. ChIA-PET2 integrates all steps required for ChIA-PET data analysis, including linker trimming, read alignment, duplicate removal, peak calling and chromatin loop calling. It supports different kinds of ChIA-PET data generated from different ChIA-PET protocols and also provides quality controls for different steps of ChIA-PET analysis. In addition, ChIA-PET2 can use phased genotype data to call allele-specific chromatin interactions. We applied ChIA-PET2 to different ChIA-PET datasets, demonstrating its significantly improved performance as well as its ability to easily process ChIA-PET raw data. ChIA-PET2 is available at https://github.com/GuipengLi/ChIA-PET2.

3CPET: finding co-factor complexes from ChIA-PET data using a hierarchical Dirichlet process.

Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies. 3CPET does so by combining data from ChIA-PET, transcription factor binding sites, and protein interactions. 3CPET results show biologically significant and accurate predictions when validated against experimental and simulation data.

ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

UNLABELLED: Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID. AVAILABILITY: ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be obtained upon request.