DOT1L complex regulates transcriptional initiation in human erythroleukemic cells.

DOT1L, the only H3K79 methyltransferase in human cells and a homolog of the yeast Dot1, normally forms a complex with AF10, AF17, and ENL or AF9, is dysregulated in most cases of mixed-lineage leukemia (MLLr), and has been believed to regulate transcriptional elongation on the basis of its colocalization with RNA polymerase II (Pol II), the sharing of subunits (AF9 and ENL) between the DOT1L and super elongation complexes, and the distribution of H3K79 methylation on both promoters and transcribed regions of active genes. Here we show that DOT1L depletion in erythroleukemic cells reduces its global occupancy without affecting the traveling ratio or the elongation rate (assessed by 4sUDRB-seq) of Pol II, suggesting that DOT1L does not play a major role in elongation in these cells. In contrast, analyses of transcription initiation factor binding reveal that DOT1L and ENL depletions each result in reduced TATA binding protein (TBP) occupancies on thousands of genes. More importantly, DOT1L and ENL depletions concomitantly reduce TBP and Pol II occupancies on a significant fraction of direct (DOT1L-bound) target genes, indicating a role for the DOT1L complex in transcription initiation. Mechanistically, proteomic and biochemical studies suggest that the DOT1L complex may regulate transcriptional initiation by facilitating the recruitment or stabilization of transcription factor IID, likely in a monoubiquitinated H2B (H2Bub1)-enhanced manner. Additional studies show that DOT1L enhances H2Bub1 levels by limiting recruitment of the Spt-Ada-Gcn5-acetyltransferase (SAGA) complex. These results advance our understanding of roles of the DOT1L complex in transcriptional regulation and have important implications for MLLr leukemias.

Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing.

Understanding of intratumor heterogeneity (ITH) among different non-small cell lung cancer (NSCLC) subtypes is necessary. Whether circulating tumor DNA (ctDNA) profile could represent these ITH is still an open question. We performed 181 multi-region tumor tissues sequencing and matched ctDNA sequencing from 32 operative NSCLC to compare ITH among different NSCLC subtypes, including EGFR-mutant lung adenocarcinoma (LUAD), KRAS-mutant LUAD, EGFR&KRAS-wild-type LUAD, and lung squamous cell carcinoma (LUSC), and examine potential value of ctDNA for ITH analysis. ITH is evaluated by ITH index (ITHi). If the somatic genetic alteration is shared by all the tissue regions, it is defined as trunk mutation. Otherwise, it is called branch mutation. The ITHi will be higher, if the tumor has less trunk mutations. We found EGFR-mutant LUAD showed significantly higher ITHi than KRAS-mutant LUAD/wild-type LUAD (P = 0.03) and numerically higher ITH than LUSC. For trunk mutations, driver mutations were identified at a higher proportion than passenger mutations (60% vs. 40%, P = 0.0023) in overall, especially in EGFR-mutant LUAD (86% vs. 14%, P = 0.0004), while it was opposite in KRAS-mutant LUAD (40% vs. 60%, P = 0.18). For branch mutations, the proportions of driver mutations and passenger mutations were similar for each NSCLC subtype. ctDNA analysis showed unsatisfactory detections of tumor-derived trunk and branch mutations (43% vs. 23%, P = 4.53e-6) among all NSCLC subtypes. In summary, EGFR-mutant LUAD has the highest ITH than other NSCLC subtypes, offering further understanding of tumorigenesis mechanisms among different NSCLC subtypes. Besides, ctDNA maybe not an appropriate method to reflect ITH.

Extensive ceRNA-ceRNA interaction networks mediated by miRNAs regulate development in multiple rhesus tissues.

Crosstalk between RNAs mediated by shared microRNAs (miRNAs) represents a novel layer of gene regulation, which plays important roles in development. In this study, we analyzed time series expression data for coding genes and long non-coding RNAs (lncRNAs) to identify thousands of interactions among competitive endogenous RNAs (ceRNAs) in four rhesus tissues. The ceRNAs exhibited dynamic expression and regulatory patterns during each tissue development process, which suggests that ceRNAs might work synergistically during different developmental stages or tissues to control specific functions. In addition, lncRNAs exhibit higher specificity as ceRNAs than coding-genes and their functions were predicted based on their competitive coding-gene partners to discover their important developmental roles. In addition to the specificity of tissue development, functional analyses demonstrated that the combined effects of multiple ceRNAs can have major impacts on general developmental and metabolic processes in multiple tissues, especially transcription-related functions where competitive interactions. Moreover, ceRNA interactions could sequentially and/or synergistically mediate the crosstalk among different signaling pathways during brain development. Analyzing ceRNA interactions during the development of multiple tissues will provideinsights in the regulation of normal development and the dysregulation of key mechanisms during pathogenesis.

tRNA m1A modification regulate HSC maintenance and self-renewal via mTORC1 signaling.

Haematopoietic stem cells (HSCs) possess unique physiological adaptations to sustain blood cell production and cope with stress responses throughout life. To maintain these adaptations, HSCs rely on maintaining a tightly controlled protein translation rate. However, the mechanism of how HSCs regulate protein translation remains to be fully elucidated. In this study, we investigate the role of transfer RNA (tRNA) m1A58 'writer' proteins TRMT6 and TRMT61A in regulating HSCs function. Trmt6 deletion promoted HSC proliferation through aberrant activation of mTORC1 signaling. TRMT6-deficient HSCs exhibited an impaired self-renewal ability in competitive transplantation assay. Mechanistically, single cell RNA-seq analysis reveals that the mTORC1 signaling pathway is highly upregulated in HSC-enriched cell populations after Trmt6 deletion. m1A-tRNA-seq and Western blot analysis suggest that TRMT6 promotes methylation modification of specific tRNA and expression of TSC1, fine-tuning mTORC1 signaling levels. Furthermore, Pharmacological inhibition of the mTORC1 pathway rescued functional defect in TRMT6-deficient HSCs. To our knowledge, this study is the first to elucidate a mechanism by which TRMT6-TRMT61A complex-mediated tRNA-m1A58 modification regulates HSC homeostasis.

Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies.

As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.

Causal relationship between circulating immune cells and the risk of type 2 diabetes: a Mendelian randomization study.

Objectives: Though type 2 diabetes (T2D) has been known as a metabolic disease caused by multiple factors, the etiology remains insufficiently understood. Here, we aimed to figure out whether circulating immune cell profiles causally impact T2D liability. Methods: We applied one genome-wide association study (GWAS) summary statistics of blood traits in 563,085 participants from the Blood Cell Consortium and another GWAS of flow cytometric profile of lymphocyte subsets comprising 3,757 Sardinians to identify genetically predicted blood immune cells. We also obtained GWAS summary statistics in 898,130 individuals from the DIAGRAM Consortium to evaluate genetically predicted T2D. We primarily used inverse variance weighted (IVW) and weighted median methods to perform Mendelian randomization analyses and sensitivity analyses to evaluate heterogeneity and pleiotropy. Results: For circulating blood leukocyte and its subpopulations, the increase of genetically predicted circulating monocyte count was causally correlated with a higher risk of T2D [odds ratio (OR) = 1.06, 95% confidence interval (CI) = 1.02-1.10, p = 0.0048]. For lymphocyte subsets, CD8+ T cell and CD4+ CD8dim T cell count were identified with causal effect on T2D susceptibility (CD8+ T cell: OR = 1.09, 95% CI = 1.03-1.17, p = 0.0053; CD4+ CD8dim T cell: OR = 1.04, 95% CI = 1.01-1.08, p = 0.0070). No pleiotropy was determined. Conclusions: These findings demonstrated that higher circulating monocyte and T-lymphocyte subpopulation predicted increased T2D susceptibility, which confirmed the immunity predisposition for T2D. Our results may have the potential to provide new therapeutic targets for the diagnosis and treatment of T2D.

Tox4 regulates transcriptional elongation and reinitiation during murine T cell development.

HMG protein Tox4 is a regulator of PP1 phosphatases with unknown function in development. Here we show that Tox4 conditional knockout in mice reduces thymic cellularity, partially blocks T cell development, and decreases ratio of CD8 to CD4 through decreasing proliferation and increasing apoptosis of CD8 cells. In addition, single-cell RNA-seq discovered that Tox4 loss also impairs proliferation of the fast-proliferating double positive (DP) blast population within DP cells in part due to downregulation of genes critical for proliferation, notably Cdk1. Moreover, genes with high and low expression level are more dependent on Tox4 than genes with medium expression level. Mechanistically, Tox4 may facilitate transcriptional reinitiation and restrict elongation in a dephosphorylation-dependent manner, a mechanism that is conserved between mouse and human. These results provide insights into the role of TOX4 in development and establish it as an evolutionarily conserved regulator of transcriptional elongation and reinitiation.

TOX4 facilitates promoter-proximal pausing and C-terminal domain dephosphorylation of RNA polymerase II in human cells.

TOX4 is one of the regulatory factors of PP1 phosphatases with poorly understood functions. Here we show that chromatin occupancy pattern of TOX4 resembles that of RNA polymerase II (Pol II), and its loss increases cellular level of C-terminal domain (CTD) phosphorylated Pol II but mainly decreases Pol II occupancy on promoters. In addition, elongation rate analyses by 4sUDRB-seq suggest that TOX4 restricts pause release and early elongation but promotes late elongation. Moreover, TT-seq analyses indicate that TOX4 loss mainly decreases transcriptional output. Mechanistically, TOX4 may restrict pause release through facilitating CTD serine 2 and DSIF dephosphorylation, and promote Pol II recycling and reinitiation through facilitating CTD serines 2 and 5 dephosphorylation. Furthermore, among the PP1 phosphatases, TOX4 preferentially binds PP1α and is capable of facilitating Pol II CTD dephosphorylation in vitro. These results lay the foundation for a better understanding of the role of TOX4 in transcriptional regulation.

Integrative analysis reveals clinically relevant molecular fingerprints in pancreatic cancer.

Pancreatic cancer is a highly aggressive cancer with an exceedingly low rate of response to treatments, which calls for comprehensive molecular characterization of pancreatic cancer cell lines (PCCLs). We screened multi-layer molecular data of 36 PCCLs, including gene mutation, gene expression, microRNA (miRNA) expression, and protein profiles. Our comparative analysis of genomic mutations found that PCCLs recapitulated genomic alterations of the primary tumor and suggested potential therapeutic strategies for clinical interventions. The panel of 36 PCCLs was classified into 2 subgroups based on transcriptomic mRNA expression, wherein the C1 subgroup was characterized with differentiation, whereas C2 cell lines were featured with immunity, angiogenesis, epidermis, and proliferation. Transcriptomic classification was further recapitulated by miRNA and protein expression. Additionally, the differential proteins between C1 and C2 subgroups were prominently involved in epidermal growth factor receptor (EGFR) signaling, phosphatidylinositol 3-kinase (PI3K) signaling, and mitogen-activated protein kinase (MAPK) signaling pathways. Tumor samples from different subgroups exhibited distinct infiltration of CD4 naive cells and monocytes. Remarkably, patients in subgroups C1 showed longer survival, whereas those in C2 had worse clinical outcome. Further integrative analysis revealed that temozolomide and NVP-TAE684 showed higher sensitivity in the C1 subgroup, whereas the C2 cell lines were more sensitive to SR1001 and SRT-1720. Our results also showed that PCCLs with mutations in CDKN2A, TP53, and SMAD4 were more sensitive to certain anti-cancer drugs. Our integrative analysis identified molecular features of pancreatic cancer that were associated with clinical significance and drug sensitivity, providing potentially effective strategies for precision treatments of patients with pancreatic cancer.

Diverged Preferences towards Sustainable Development Goals? A Comparison between Academia and the Communication Industry.

To understand how the sustainable development goals (SDGs) are involved and cited in different fields, the current study aimed to explore the key SDGs and SDG-pairs from the viewpoints of academia and the media. The academic publications with SDG(s)-related keywords in the Scopus database and the entry videos of the "2018 SDG Lions" were collected and analyzed through content and network analysis. It was found that SDG 3 and SDG 10 shared the highest preferences in both industries, but apparent gaps happened to SDG 5. The tied frequencies of the possible SDG pairs were also examined, and SDG 3-10 was identified taking the lead in both industries. Network analysis using degree centrality as the vital parameter demonstrated that SDG 8 and SDG 5 has strong connections with several SDGs for the academia and the media, respectively. The SDG-2-6-7 combination or "water-energy-food" nexus was also found the most frequent combination of three SDGs in the academia. Overall, SDG 3 can be treated as a unifying theme when seeking to acquire evidence-based knowledge for integrated implementation of the SDGs. Important implications for policy-making of the SDGs were also discussed.

The correlations of tumor mutational burden among single-region tissue, multi-region tissues and blood in non-small cell lung cancer.

High-level tissue tumor mutational burden (tTMB) or blood TMB (bTMB) are associated with better response of immunotherapy in non-small cell lung cancer (NSCLC) patients. However, the correlations of single-region tTMB, multi-region tTMB and bTMB remain to be determined. Moreover, whether intratumor heterogeneity (ITH) has impact on TMB should be clarified. We collected multi-region tumor tissues with matched blood from 32 operative NSCLC and evaluated single-region tTMB, multi-region tTMB and bTMB through a 1021-gene panel sequencing. TMB of > 9 mutations/Mb was classified as high. Besides, we used tTMB fold-change to evaluate the influence of the enrolled region number on tTMB. We found both of single-region tTMB and bTMB showed strong correlations with multi-region tTMB, while the former correlated better (Pearson r = 0.94, P = 2E-84; Pearson r = 0.47, P = 0.0067). It showed extremely high specificity (100%) but low sensitivity (43%) when using bTMB to define TMB-high patients, while most false-negative predictions were in early-stage patients. Compared to single region, we found significantly enhanced tTMB fold-change if taking multi-regions for consideration. However, it showed insignificant tTMB fold-change increase if the included regions' number more than three. Moreover, ITH-high patients had significantly higher tTMB fold-change compared with ITH-low patients (2.32 vs. 1.02, P = 8.879e-05). The conversion rate of tTMB level (tTMB-low to tTMB-high) was numerically higher in ITH-high group than that in ITH-low group (16.67% vs. 3.84%). In summary, single-region tTMB has stronger correlation with multi-region tTMB compared with bTMB. ITH has an impact on tTMB, especially in high-level ITH patients.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/.

Identification of module biomarkers from the dysregulated ceRNA-ceRNA interaction network in lung adenocarcinoma.

Competitive endogenous RNA (ceRNA) represents a novel layer of gene regulation that plays important roles in the physiology and development of diseases such as cancer and its dysregulation could contribute to cancer pathogenesis. Here, we have proposed a computational method to systematically identify genome-wide dysregulated ceRNA-ceRNA interactions by integrating microRNA regulation with expression profiles in cancer and normal tissues by RNA sequencing, as well as considering the details of how the behavior of ceRNAs has changed. These gain or loss dysregulations further assemble into a dysregulated ceRNA-ceRNA network; lncRNAs and pseudogenes are also considered. After applying the method to lung adenocarcinoma, we found that most dysregulations are connected together and formed a lung adenocarcinoma dysregulated ceRNA-ceRNA network (LDCCNet). Our analyses found that ceRNA pairs with gain regulations have consistent expression in cancer, otherwise for loss regulation, it is not necessary. Moreover, ceRNAs with more significant gain regulations (gain ceRNAs) undergo stronger regulation in cancer; thus their expression is more likely to decrease in cancer, while the expression of loss ceRNAs displays a rising trend. Additionally, we found that gain and loss ceRNAs as topological key nodes are implicated in the development of cancer. Finally, dysregulated ceRNA modules were identified, which are significantly enriched with known lung cancer microRNAs. We further found that several modules have the power as diagnostic biomarkers even in three independent datasets. For example, the module with lncRNA RP11-457M11.2 as a center is involved in the epithelial cell morphogenesis process and provides the average AUC values of 0.95. Our study about LDCCNet opens up the possibility of a new biological mechanism in cancer that could serve as a biomarker for diagnosis.

Functional dissection of virus-human crosstalk mediated by miRNAs based on the VmiReg database.

Recently, a number of viruses have been shown to encode microRNAs (miRNAs), and they play important roles in several biological processes, enhancing the intricacies of the virus-host crosstalk. However, systematically deciphering the characteristics of crosstalk mediated by viral and human miRNAs has been hampered by the lack of high-confidence targets. Here, a user-friendly platform is developed to provide experimentally validated and predicted target genes of viral miRNAs as well as their functions, named VmiReg. To explore the virus-human crosstalk meditated by miRNAs, validated human cellular targets of viral and cellular miRNAs are analyzed. As a result, target genes of viral miRNAs are prone to be silenced by human miRNAs. Two kinds of targets have globally significantly high functional similarities and are more often found simultaneously in many important biological functions, even in disease genes, particularly cancer genes, and essential genes. In addition, viral and human miRNA targets are in close proximity within the protein-protein interaction network, indicating frequent communication via physical interactions to participate in the same functions. Finally, multiple dense modules intuitively exhibit crosstalk between viral and cellular miRNAs. Furthermore, most co-regulated genes tend to be in important locations of modules. The lymphoma-related module is one of the typical examples. Our study suggests that the functional importance of cellular genes targeted by viral miRNAs and the intricate virus-host crosstalk mediated by miRNAs may be performed via the sharing of target genes or physical interactions, providing a new direction in further researching the roles of miRNAs in infection.

Integrating analysis reveals microRNA-mediated pathway crosstalk among Crohn's disease, ulcerative colitis and colorectal cancer.

Inflammatory bowel disease (IBD), which can increase the risk of colorectal cancer (CRC), includes two primary subtypes, ulcerative colitis (UC) and Crohn's disease (CD). Although several individual genes involved in inflammation or cancer characterization have been identified, it is still difficult to elucidate functional relationship details between the molecules underlying pathogenesis at the system level. The global effect of miRNAs on genes or their involved functions is also poorly understood. We first integrated genome-wide gene expression profiles and biological pathway information to explore the underlying associations among UC, CD and CRC at the function and gene level. After identifying the pathways regulated by miRNAs, a global map of miRNA-mediated pathway crosstalk shared by the three diseases was further constructed to vertically explain the links of three level alterations. The three types of diseases have close associations with each other at the levels of function, gene and miRNA regulation. Several key biological pathways are involved in the three diseases, related to the immune system and inflammation, metabolism, or cell proliferation and apoptosis etc. Moreover, miRNAs exhibit dominant effects on multiple pathways. It is worth noting that UC shows relatively close associations with CD and CRC at the three levels. Finally, the miRNAs could mediate the crosstalk within or between pathways. For example, hsa-miR-125b, hsa-miR-335 and hsa-miR-155 mediated the crosstalk between three metabolic pathways. The crosstalk within the Toll-like receptor signaling pathway could be mediated by hsa-miR-124, hsa-miR-146a and hsa-mir-221/222. Our results make sense for the prevention and treatment of intestinal-related chronic inflammation or cancer.

Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

BACKGROUND: DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. RESULTS: In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. CONCLUSIONS: We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.