Integrative analyses shed new light on human ribosomal protein gene regulation

Identifying Reproducible Transcription Regulator Coexpression Patterns with Single Cell Transcriptomics

The proliferation of single cell transcriptomics has potentiated our ability to unveil patterns that reflect dynamic cellular processes, rather than cell type compositional effects that emerge from bulk tissue samples. In this study, we leverage a broad collection of single cell RNA-seq data to identify the gene partners whose expression is most coordinated with each human and mouse transcription regulator (TR). We assembled 120 human and 103 mouse scRNA-seq datasets from the literature (>28 million cells), constructing a single cell coexpression network for each. We aimed to understand the consistency of TR coexpression profiles across a broad sampling of biological contexts, rather than examine the preservation of context-specific signals. Our workflow therefore explicitly prioritizes the patterns that are most reproducible across cell types. Towards this goal, we characterize the similarity of each TR's coexpression within and across species. We create single cell coexpression rankings for each TR, demonstrating that this aggregated information recovers literature curated targets on par with ChIP-seq data. We then combine the coexpression and ChIP-seq information to identify candidate regulatory interactions supported across methods and species. Finally, we highlight interactions for the important neural TR ASCL1 to demonstrate how our compiled information can be adopted for community use.

Canopy Homolog 2 contributes to liver oncogenesis by promoting unfolded protein response-dependent destabilization of tumor protein P53

BACKGROUD AND AIMS

Abnormalities in the tumor protein P53 (p53) gene and overexpression of mouse double minute 2 homolog (MDM2), a negative regulator of p53, are commonly observed in cancers. p53 destabilization is regulated by endoplasmic reticulum (ER) stress and unfolded protein response (UPR) in cancer. However, the mechanisms remain enigmatic. Canopy homolog 2 (CNPY2) is a key UPR initiator that primarily involved in ER stress and is highly expressed in the liver, but its functional role in regulating liver carcinogenesis is poorly understood. Therefore, we aimed to investigate the role of CNPY2 in hepartocarcinogenesis through URP-dependent p53 destabilization.

APPROACH AND RESULTS

Here, we showed that CNPY2 expression is up-regulated in HCC and negatively correlated with survival rate in liver cancer patients. Deletion of Cnpy2 obliterates diethylnitrosamine (DEN)-induced HCC in mice. Mechanistic studies demonstrated that CNPY2 binds and prevents ribosome proteins from inhibiting MDM2 and enhances the UPR activity of protein kinase RNA-like endoplasmic reticulum kinase and inositol-requiring transmembrane kinase endoribonuclease-1α, leading to p53 destabilization and cell-cycle progression. In addition, transcriptome analyses uncovered that CNPY2 is also required for DEN-induced expression of oncogenes, including c-Jun and fibroblast growth factor 21. Intratumoral injection of nanoparticle-based CRISPR single-guide RNA/CRISPR-associated protein 9 mRNA against Cnpy2 has antitumor effects in HCC.

CONCLUSIONS

These findings demonstrate that CNPY2 is crucial for liver oncogenesis through UPR-dependent repression of p53 and activation of oncogenes, providing insights into the design of a therapeutic target for HCC.

A systematic study of HIF1A cofactors in hypoxic cancer cells

Hypoxia inducible factor 1 alpha (HIF1A) is a transcription factor (TF) that forms highly structural and functional protein-protein interactions with other TFs to promote gene expression in hypoxic cancer cells. However, despite the importance of these TF-TF interactions, we still lack a comprehensive view of many of the TF cofactors involved and how they cooperate. In this study, we systematically studied HIF1A cofactors in eight cancer cell lines using the computational motif mining tool, SIOMICS, and discovered 201 potential HIF1A cofactors, which included 21 of the 29 known HIF1A cofactors in public databases. These 201 cofactors were statistically and biologically significant, with 19 of the top 37 cofactors in our study directly validated in the literature. The remaining 18 were novel cofactors. These discovered cofactors can be essential to HIF1A's regulatory functions and may lead to the discovery of new therapeutic targets in cancer treatment.

A revisit to universal single-copy genes in bacterial genomes

Universal single-copy genes (USCGs) are widely used for species classification and taxonomic profiling. Despite many studies on USCGs, our understanding of USCGs in bacterial genomes might be out of date, especially how different the USCGs are in different studies, how well a set of USCGs can distinguish two bacterial species, whether USCGs can separate different strains of a bacterial species, to name a few. To fill the void, we studied USCGs in the most updated complete bacterial genomes. We showed that different USCG sets are quite different while coming from highly similar functional categories. We also found that although USCGs occur once in almost all bacterial genomes, each USCG does occur multiple times in certain genomes. We demonstrated that USCGs are reliable markers to distinguish different species while they cannot distinguish different strains of most bacterial species. Our study sheds new light on the usage and limitations of USCGs, which will facilitate their applications in evolutionary, phylogenomic, and metagenomic studies.

Drp1 regulates transcription of ribosomal protein genes in embryonic hearts

Mitochondrial dysfunction causes severe congenital cardiac abnormalities and prenatal/neonatal lethality. The lack of sufficient knowledge regarding how mitochondrial abnormalities affect cardiogenesis poses a major barrier for the development of clinical applications that target mitochondrial deficiency-induced inborn cardiomyopathies. Mitochondrial morphology, which is regulated by fission and fusion, plays a key role in determining mitochondrial activity. Dnm1l encodes a dynamin-related GTPase, Drp1, which is required for mitochondrial fission. To investigate the role of Drp1 in cardiogenesis during the embryonic metabolic shift period, we specifically inactivated Dnm1l in second heart field-derived structures. Mutant cardiomyocytes in the right ventricle (RV) displayed severe defects in mitochondrial morphology, ultrastructure and activity. These defects caused increased cell death, decreased cell survival, disorganized cardiomyocytes and embryonic lethality. By characterizing this model, we reveal an AMPK-SIRT7-GABPB axis that relays the reduced cellular energy level to decrease transcription of ribosomal protein genes in cardiomyocytes. We therefore provide the first genetic evidence in mouse that Drp1 is essential for RV development. Our research provides further mechanistic insight into how mitochondrial dysfunction causes pathological molecular and cellular alterations during cardiogenesis.

A systematic study of motif pairs that may facilitate enhancer-promoter interactions

Pairs of interacting transcription factors (TFs) have previously been shown to bind to enhancers and promoters and contribute to their physical interactions. However, to date, we have limited knowledge about such TF pairs. To fill this void, we systematically studied the co-occurrence of TF-binding motifs in interacting enhancer-promoter (EP) pairs in seven human cell lines. We discovered 423 motif pairs that significantly co-occur in enhancers and promoters of interacting EP pairs. We demonstrated that these motif pairs are biologically meaningful and significantly enriched with motif pairs of known interacting TF pairs. We also showed that the identified motif pairs facilitated the discovery of the interacting EP pairs. The developed pipeline, EPmotifPair, together with the predicted motifs and motif pairs, is available at https://doi.org/10.6084/m9.figshare.14192000. Our study provides a comprehensive list of motif pairs that may contribute to EP physical interactions, which facilitate generating meaningful hypotheses for experimental validation.

NFAT-dependent and -independent exhaustion circuits program maternal CD8 T cell hypofunction in pregnancy

Pregnancy is a common immunization event, but the molecular mechanisms and immunological consequences provoked by pregnancy remain largely unknown. We used mouse models and human transplant registry data to reveal that pregnancy induced exhausted CD8 T cells (Preg-TEX), which associated with prolonged allograft survival. Maternal CD8 T cells shared features of exhaustion with CD8 T cells from cancer and chronic infection, including transcriptional down-regulation of ribosomal proteins and up-regulation of TOX and inhibitory receptors. Similar to other models of T cell exhaustion, NFAT-dependent elements of the exhaustion program were induced by fetal antigen in pregnancy, whereas NFAT-independent elements did not require fetal antigen. Despite using conserved molecular circuitry, Preg-TEX cells differed from TEX cells in chronic viral infection with respect to magnitude and dependency of T cell hypofunction on NFAT-independent signals. Altogether, these data reveal the molecular mechanisms and clinical consequences of maternal CD8 T cell hypofunction and identify pregnancy as a previously unappreciated context in which T cell exhaustion may occur.

Comprehensive comparison of sample preparation workflows for proteomics

Mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining deep and accurate protein identification. Here, to obtain an optimal sample preparation workflow...

ZNF423 modulates the AMP-activated protein kinase pathway and metformin response in a single nucleotide polymorphisms, estrogen and selective estrogen receptor modulator dependent fashion

OBJECTIVES

We previously discovered that the single nucleotide polymorphisms (SNP) rs9940645 in the ZNF423 gene regulate ZNF423 expression and serve as a potential biomarker for response to selective estrogen receptor modulators (SERMs). Here we explored pathways involved in ZNF423-mediated SERMs response and drugs that potentially sensitize SERMs.

METHODS

RNA sequencing and label-free quantitative proteomics were performed to identify genes and pathways that are regulated by ZNF423 and the ZNF423 SNP. Both cultured cells and mouse xenograft models with different ZNF423 SNP genotypes were used to study the cellular responses to metformin.

RESULTS

We identified ribosome and AMP-activated protein kinase (AMPK) signaling as potential pathways regulated by ZNF423 or ZNF423 rs9940645 SNP. Moreover, using clustered regularly interspaced short palindromic repeats/Cas9-engineered ZR75-1 breast cancer cells with different ZNF423 SNP genotypes, striking differences in cellular responses to metformin, either alone or in the combination of tamoxifen, were observed in both cell culture and the mouse xenograft model.

CONCLUSIONS

We found that AMPK signaling is modulated by the ZNF423 rs9940645 SNP in estrogen and SERM-dependent fashion. The ZNF423 rs9940645 SNP affects metformin response in breast cancer and could be a potential biomarker for tailoring the metformin treatment.

Antagonising Chromatin Remodelling Activities in the Regulation of Mammalian Ribosomal Transcription

Ribosomal transcription constitutes the major energy consuming process in cells and is regulated in response to proliferation, differentiation and metabolic conditions by several signalling pathways. These act on the transcription machinery but also on chromatin factors and ncRNA. The many ribosomal gene repeats are organised in a number of different chromatin states; active, poised, pseudosilent and repressed gene repeats. Some of these chromatin states are unique to the 47rRNA gene repeat and do not occur at other locations in the genome, such as the active state organised with the HMG protein UBF whereas other chromatin state are nucleosomal, harbouring both active and inactive histone marks. The number of repeats in a certain state varies on developmental stage and cell type; embryonic cells have more rRNA gene repeats organised in an open chromatin state, which is replaced by heterochromatin during differentiation, establishing different states depending on cell type. The 47S rRNA gene transcription is regulated in different ways depending on stimulus and chromatin state of individual gene repeats. This review will discuss the present knowledge about factors involved, such as chromatin remodelling factors NuRD, NoRC, CSB, B-WICH, histone modifying enzymes and histone chaperones, in altering gene expression and switching chromatin states in proliferation, differentiation, metabolic changes and stress responses.

Interpretation of deep learning in genomics and epigenomics

Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies towards understanding the underlying molecular and cellular mechanisms. Deep neural networks (DNNs) have recently gained popularity in various types of genomic and epigenomic studies due to their capabilities in utilizing large-scale high-throughput bioinformatics data and achieving high accuracy in predictions and classifications. However, DNNs are often challenged by their potential to explain the predictions due to their black-box nature. In this review, we present current development in the model interpretation of DNNs, focusing on their applications in genomics and epigenomics. We first describe state-of-the-art DNN interpretation methods in representative machine learning fields. We then summarize the DNN interpretation methods in recent studies on genomics and epigenomics, focusing on current data- and computing-intensive topics such as sequence motif identification, genetic variations, gene expression, chromatin interactions and non-coding RNAs. We also present the biological discoveries that resulted from these interpretation methods. We finally discuss the advantages and limitations of current interpretation approaches in the context of genomic and epigenomic studies. Contact:xiaoman@mail.ucf.edu, haihu@cs.ucf.edu.

An intriguing characteristic of enhancer-promoter interactions

Background

It is still challenging to predict interacting enhancer-promoter pairs (IEPs), partially because of our limited understanding of their characteristics. To understand IEPs better, here we studied the IEPs in nine cell lines and nine primary cell types.

Results

By measuring the bipartite clustering coefficient of the graphs constructed from these experimentally supported IEPs, we observed that one enhancer is likely to interact with either none or all of the target genes of another enhancer. This observation implies that enhancers form clusters, and every enhancer in the same cluster synchronously interact with almost every member of a set of genes and only this set of genes. We perceived that an enhancer can be up to two megabase pairs away from other enhancers in the same cluster. We also noticed that although a fraction of these clusters of enhancers do overlap with super-enhancers, the majority of the enhancer clusters are different from the known super-enhancers.

Conclusions

Our study showed a new characteristic of IEPs, which may shed new light on distal gene regulation and the identification of IEPs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-021-07440-5).

Regulation of ribosomal protein genes: An ordered anarchy

Ribosomal protein genes are among the most highly expressed genes in most cell types. Their products are generally essential for ribosome synthesis, which is the cornerstone for cell growth and proliferation. Many cellular resources are dedicated to producing ribosomal proteins and thus this process needs to be regulated in ways that carefully balance the supply of nascent ribosomal proteins with the demand for new ribosomes. Ribosomal protein genes have classically been viewed as a uniform interconnected regulon regulated in eukaryotic cells by target of rapamycin and protein kinase A pathway in response to changes in growth conditions and/or cellular status. However, recent literature depicts a more complex picture in which the amount of ribosomal proteins produced varies between genes in response to two overlapping regulatory circuits. The first includes the classical general ribosome‐producing program and the second is a gene‐specific feature responsible for fine‐tuning the amount of ribosomal proteins produced from each individual ribosomal gene. Unlike the general pathway that is mainly controlled at the level of transcription and translation, this specific regulation of ribosomal protein genes is largely achieved through changes in pre‐mRNA splicing efficiency and mRNA stability. By combining general and specific regulation, the cell can coordinate ribosome production, while allowing functional specialization and diversity. Here we review the many ways ribosomal protein genes are regulated, with special focus on the emerging role of posttranscriptional regulatory events in fine‐tuning the expression of ribosomal protein genes and its role in controlling the potential variation in ribosome functions.

This article is categorized under:

Translation > Ribosome Biogenesis

Translation > Ribosome Structure/Function

Translation > Translation Regulation

Ubiquitin ligases and medulloblastoma: genetic markers of the four consensus subgroups identified through transcriptome datasets

The ubiquitin proteasome system regulates key cellular processes in normal and in cancer cells. Herein, we review published data on the role of ubiquitin ligases in the four major subgroups of medulloblastoma (MB). While conventional literature serves as an initial source of information on cellular pathways in MB, large publicly available datasets of gene expression can be used to add information not previously identified in the literature. By analysing the publicly available Cavalli dataset, we show that increased expression of ZNRF3 characterizes the WNT subgroup of MB. The ZNRF3 gene codes for an E3 ligase associated with WNT receptors. Loss of a copy of chromosome 6 in a subtype of the WNT group was associated with decreased expression of the gene encoding the E3 ligase RNF146. While the E3 ligase SMURF regulates SHH receptors, increased expression of the gene encoding the Cullin Ring E3 adaptor PPP2R2C was statistically a better genetic marker of the SHH group. Genes whose expression was statistically strongly related to Group 3 included the E3 ligase gene TRIM58, and the gene for the E3 ligase adaptor, PPP2R2B. Group 4 MB was associated with expression of genes encoding several E3 ligases and E3 ligase adaptors involved in ribosome biogenesis. Increased expression of the genes encoding the E3 ligase adaptors and transcription repressors ZBTB18 and ZBTB38 were also noted in subgroup 4. These data suggest that several E3 ligases and their adaptors should be investigated as therapeutic targets for subgroup specific MB brain tumors.

High-resolution analysis of differential gene expression during skeletal muscle atrophy and programmed cell death

Skeletal muscles can undergo atrophy and/or programmed cell death (PCD) during development or in response to a wide range of insults, including immobility, cachexia, and spinal cord injury. However, the protracted nature of atrophy and the presence of multiple cell types within the tissue complicate molecular analyses. One model that does not suffer from these limitations is the intersegmental muscle (ISM) of the tobacco hawkmoth Manduca sexta. Three days before the adult eclosion (emergence) at the end of metamorphosis, the ISMs initiate a nonpathological program of atrophy that results in a 40% loss of mass. The ISMs then generate the eclosion behavior and initiate a nonapoptotic PCD during the next 30 h. We have performed a comprehensive transcriptomics analysis of all mRNAs and microRNAs throughout ISM development to better understand the molecular mechanisms that mediate atrophy and death. Atrophy involves enhanced protein catabolism and reduced expression of the genes involved in respiration, adhesion, and the contractile apparatus. In contrast, PCD involves the induction of numerous proteases, DNA methylases, membrane transporters, ribosomes, and anaerobic metabolism. These changes in gene expression are largely repressed when insects are injected with the insect steroid hormone 20-hydroxyecdysone, which delays death. The expression of the death-associated proteins may be greatly enhanced by reductions in specific microRNAs that function to repress translation. This study not only provides fundamental new insights into basic developmental processes, it may also represent a powerful resource for identifying potential diagnostic markers and molecular targets for therapeutic intervention.

EPIP: a novel approach for condition-specific enhancer-promoter interaction prediction

MOTIVATION

The identification of enhancer-promoter interactions (EPIs), especially condition-specific ones, is important for the study of gene transcriptional regulation. Existing experimental approaches for EPI identification are still expensive, and available computational methods either do not consider or have low performance in predicting condition-specific EPIs.

RESULTS

We developed a novel computational method called EPIP to reliably predict EPIs, especially condition-specific ones. EPIP is capable of predicting interactions in samples with limited data as well as in samples with abundant data. Tested on more than eight cell lines, EPIP reliably identifies EPIs, with an average area under the receiver operating characteristic curve of 0.95 and an average area under the precision-recall curve of 0.73. Tested on condition-specific EPIPs, EPIP correctly identified 99.26% of them. Compared with two recently developed methods, EPIP outperforms them with a better accuracy.

AVAILABILITY AND IMPLEMENTATION

The EPIP tool is freely available at http://www.cs.ucf.edu/˜xiaoman/EPIP/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Untangling the effects of cellular composition on coexpression analysis

Coexpression analysis is widely used for inferring regulatory networks, predicting gene function, and interpretation of transcriptome profiling studies, based on methods such as clustering. The majority of such studies use data collected from bulk tissue, where the effects of cellular composition present a potential confound. However, the impact of composition on coexpression analysis has not been studied in detail. Here, we examine this issue for the case of human RNA analysis. Focusing on brain tissue, we found that, for most genes, differences in expression levels across cell types account for a large fraction of the variance of their measured RNA levels (median R 2 = 0.68). We then show that genes that have similar expression patterns across cell types will have correlated RNA levels in bulk tissue, due to the effect of variation in cellular composition. We demonstrate that much of the coexpression and the formation of coexpression clusters can be attributed to this effect for both brain and blood transcriptomes. For brain, we further show how this composition-induced coexpression masks underlying intra-cell-type coexpression observed in single-cell data. An attempt to correct for composition yielded mixed results. Our conclusion is that the dominant coexpression signal in brain, blood, and, likely, other complex tissues can be attributed to cellular compositional effects, rather than intra-cell-type regulatory relationships. These results have implications for the relevance and interpretation of coexpression analysis.

Shared distal regulatory regions may contribute to the coordinated expression of human ribosomal protein genes

To identify the potential distal regulatory regions of human ribosomal protein genes (RPGs) and to understand their characteristics, we studied the chromatin interactions in seven cell lines and four primary cell types. We identified 22,797 putative regulatory regions that directly or indirectly interact with human RPG promoters. A large proportion of these regions are only present in one cell line or one cell type, implying that RPGs may be differentially regulated across experimental conditions. We also noticed that groups of RPGs, which are the same groups across cell lines and cell types, share common regulatory regions. These shared regulatory regions by RPGs may contribute to their coordinated regulation. By studying the overrepresented motifs in the identified regulatory regions, we showed that there are about two dozen motifs in these regions shared across cell lines and cell types. Our study shed new light on the coordinated transcriptional regulation of human RPGs.

Divergent effects of translation termination factor eRF3A and nonsense-mediated mRNA decay factor UPF1 on the expression of uORF carrying mRNAs and ribosome protein genes

In addition to its role in translation termination, eRF3A has been implicated in the nonsense-mediated mRNA decay (NMD) pathway through its interaction with UPF1. NMD is a RNA quality control mechanism, which detects and degrades aberrant mRNAs as well as some normal transcripts including those that harbour upstream open reading frames in their 5ʹ leader sequence. In this study, we used RNA-sequencing and ribosome profiling to perform a genome wide analysis of the effect of either eRF3A or UPF1 depletion in human cells. Our bioinformatics analyses allow to delineate the features of the transcripts controlled by eRF3A and UPF1 and to compare the effect of each of these factors on gene expression. We find that eRF3A and UPF1 have very different impacts on the human transcriptome, less than 250 transcripts being targeted by both factors. We show that eRF3A depletion globally derepresses the expression of mRNAs containing translated uORFs while UPF1 knockdown derepresses only the mRNAs harbouring uORFs with an AUG codon in an optimal context for translation initiation. Finally, we also find that eRF3A and UPF1 have opposite effects on ribosome protein gene expression. Together, our results provide important elements for understanding the impact of translation termination and NMD on the human transcriptome and reveal novel determinants of ribosome biogenesis regulation.