Expression Of Gene Pairs Research Articles

Pairwise analysis of gene expression for oral squamous cell carcinoma via a large-scale transcriptome integration.

Among all cancers occurring in the head and neck region, oral squamous cell carcinoma (OSCC) is the most common oral malignant tumours characterized by its aggressiveness and metastasis. The development of transcriptomics technology has greatly facilitated the diagnosis of various cancers. However, identifying genetic biomarkers is limited by data from a single batch of OSCC samples, and integrating analysis across different platforms remains a great challenge. In this study, we integrated five OSCC transcriptome datasets using an innovative strategy capable of mitigating batch effect, and extracting information from different datasets based on changes in the relative expression of gene pairs. By leveraging a machine learning method, we developed a prediction model including 27 differential gene pairs (DGPs) to discriminate OSCC from control samples, achieving an area under the receiver operating characteristic curve (AUC) of 0.8987 for the training set. Moreover, the model demonstrated commendable performance in four external validation sets, with AUCs of 0.9926, 0.9688, 0.8052 and 0.8565, respectively. Subsequently, a prognostic model was constructed based on six key gene pairs through univariate and multivariate Cox regression analysis. The AUCs of the model at 1-year and 3-year overall survival time prediction were 0.717 and 0.779 in an independent dataset. Our result demonstrates the effectiveness of this new method of integrating data and identifying DGPs. Using DGPs can significantly improve the performance of both diagnostic and prognostic models.

SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network.

The rise of single-cell RNA sequencing (scRNA-seq) technology presents new opportunities for constructing detailed cell type-specific gene regulatory networks (GRNs) to study cell heterogeneity. However, challenges caused by noises, technical errors, and dropout phenomena in scRNA-seq data pose significant obstacles to GRN inference, making the design of accurate GRN inference algorithms still essential. The recent growth of both single-cell and spatial transcriptomic sequencing data enables the development of supervised deep learning methods to infer GRNs on these diverse single-cell datasets. In this study, we introduce a novel deep learning framework based on shared factor neighborhood and integrated neural network (SFINN) for inferring potential interactions and causalities between transcription factors and target genes from single-cell and spatial transcriptomic data. SFINN utilizes shared factor neighborhood to construct cellular neighborhood network based on gene expression data and additionally integrates cellular network generated from spatial location information. Subsequently, the cell adjacency matrix and gene pair expression are fed into an integrated neural network framework consisting of a graph convolutional neural network and a fully-connected neural network to determine whether the genes interact. Performance evaluation in the tasks of gene interaction and causality prediction against the existing GRN reconstruction algorithms demonstrates the usability and competitiveness of SFINN across different kinds of data. SFINN can be applied to infer GRNs from conventional single-cell sequencing data and spatial transcriptomic data. SFINN can be accessed at GitHub: https://github.com/JGuan-lab/SFINN.

A Bidirectional Non-Coding RNA Promoter Mediates Long-Range Gene Expression Regulation.

Recent evidence suggests that human gene promoters display gene expression regulatory mechanisms beyond the typical single gene local transcription modulation. In mammalian genomes, genes with an associated bidirectional promoter are abundant; bidirectional promoter architecture serves as a regulatory hub for a gene pair expression. However, it has been suggested that its contribution to transcriptional regulation might exceed local transcription initiation modulation. Despite their abundance, the functional consequences of bidirectional promoter architecture remain largely unexplored. This work studies the long-range gene expression regulatory role of a long non-coding RNA gene promoter using chromosome conformation capture methods. We found that this particular bidirectional promoter contributes to distal gene expression regulation in a target-specific manner by establishing promoter-promoter interactions. In particular, we validated that the promoter-promoter interactions of this regulatory element with the promoter of distal gene BBX contribute to modulating the transcription rate of this gene; removing the bidirectional promoter from its genomic context leads to a rearrangement of BBX promoter-enhancer interactions and to increased gene expression. Moreover, long-range regulatory functionality is not directly dependent on its associated non-coding gene pair expression levels.

Integrated analysis reveals the dysfunction of intercellular communication and metabolic signals in dilated cardiomyopathy

AimsDilated cardiomyopathy refers to a heart muscle condition characterized by structural and functional irregularities in the myocardium that are not related to ischemia. Due to diverse etiologies such as genetic mutations, infections, and exposure to toxins, dilated cardiomyopathy can lead to substantial morbidity and mortality despite advances in the management of heart failure in dilated cardiomyopathy patients. We sought to analyze the characteristics of cell-cell communication and the metabolic signaling pathways in dilated cardiomyopathy. Methods and resultsThe single-nucleus sequencing data of left ventricle samples were acquired from two donor datasets and two dilated cardiomyopathy datasets. Three dilated cardiomyopathy bulk-sequencing datasets were included to determine the shared dilated cardiomyopathy-specific alterations in differentially expressed genes and signaling pathways. Using “CellChat,” we analyzed intercellular communication to grasp how cell clusters interact and to map out the impaired signaling pathways in both donor and dilated cardiomyopathy conditions. Gene set enrichment analysis was applied to compare the metabolic signaling before and after dilated cardiomyopathy. We showcased how cell clusters exhibited abnormal cell-to-cell signaling transduction and how each cell type displayed dysfunctional metabolic signaling pathways through the integration of various datasets. The crucial ligand-receptor signaling contributing to outgoing or incoming signaling of dilated cardiomyopathy was identified in a cell-type dependent way, and the cell-specific metabolic alterations in glucose, lipid and amino acid were determined. The expression of gene pairs in BMP and NOTCH signal, as well as the gene expression in the arginine metabolism was validated. ConclusionsWe reveal the key signals and metabolic pathways for dilated cardiomyopathy adaptation and maintenance, providing potential targets for dilated cardiomyopathy interference.

DNA methylation role in subgenome expression dominance of Juglans regia and its wild relative J. mandshurica.

Subgenome expression dominance plays a crucial role in the environmental adaptation of polyploids. However, the epigenetic molecular mechanism underlying this process has not been thoroughly investigated, particularly in perennial woody plants. Persian walnut (Juglans regia) and its wild relative, Manchurian walnut (Juglans mandshurica), are woody plants of great economic importance and are both paleopolyploids that have undergone whole-genome duplication events. In this study, we explored the characteristics of subgenome expression dominance in these 2 Juglans species and examined its epigenetic basis. We divided their genomes into dominant subgenome (DS) and submissive subgenome (SS) and found that the DS-specific genes might play critical roles in biotic stress response or pathogen defense. We comprehensively elucidated the characteristics of biased gene expression, asymmetric DNA methylation, transposable elements (TEs), and alternative splicing (AS) events of homoeologous gene pairs between subgenomes. The results showed that biased expression genes (BEGs) in 2 Juglans species were mainly related to external stimuli response, while non-BEGs were related to complexes that might be involved in signal transduction. DS genes had higher expression and more AS events while having less DNA methylation and TEs than homoeologous genes from the SS in the 2 Juglans species. Further studies showed that DNA methylation might contribute to the biased expression of gene pairs by modifying LTR/TIR/nonTIR TEs and improving the AS efficiency of corresponding precursor mRNAs in a particular context. Our study contributes to understanding the epigenetic basis of subgenome expression dominance and the environmental adaptation of perennial woody plants.

Dosage-sensitivity shapes how genes transcriptionally respond to allopolyploidy and homoeologous exchange in resynthesized Brassica napus.

The gene balance hypothesis proposes that selection acts on the dosage (i.e. copy number) of genes within dosage-sensitive portions of networks, pathways, and protein complexes to maintain balanced stoichiometry of interacting proteins, because perturbations to stoichiometric balance can result in reduced fitness. This selection has been called dosage balance selection. Dosage balance selection is also hypothesized to constrain expression responses to dosage changes, making dosage-sensitive genes (those encoding members of interacting proteins) experience more similar expression changes. In allopolyploids, where whole-genome duplication involves hybridization of diverged lineages, organisms often experience homoeologous exchanges that recombine, duplicate, and delete homoeologous regions of the genome and alter the expression of homoeologous gene pairs. Although the gene balance hypothesis makes predictions about the expression response to homoeologous exchanges, they have not been empirically tested. We used genomic and transcriptomic data from 6 resynthesized, isogenic Brassica napus lines over 10 generations to identify homoeologous exchanges, analyzed expression responses, and tested for patterns of genomic imbalance. Groups of dosage-sensitive genes had less variable expression responses to homoeologous exchanges than dosage-insensitive genes, a sign that their relative dosage is constrained. This difference was absent for homoeologous pairs whose expression was biased toward the B. napus A subgenome. Finally, the expression response to homoeologous exchanges was more variable than the response to whole-genome duplication, suggesting homoeologous exchanges create genomic imbalance. These findings expand our knowledge of the impact of dosage balance selection on genome evolution and potentially connect patterns in polyploid genomes over time, from homoeolog expression bias to duplicate gene retention.

Homoeolog gene expression analysis reveals novel expression biases in upland hybrid cotton under intraspecific hybridization.

Hybridization is useful to enhance the yield potential of agronomic crops in the world. Cotton has genome doubling due to the allotetraploid process and hybridization in coordination with duplicated genome can produce more yield and adaptability. Therefore, the expression of homoeologous gene pairs between hybrids and inbred parents is vital to characterize the genetic source of heterosis in cotton. Investigation results of homoeolog gene pairs between two contrasting hybrids and their respective inbred parents identified 36853 homoeolog genes in hybrids. It was observed both high and low hybrids had similar trends in homoeolog gene expression patterns in each tissue under study. An average of 96% of homoeolog genes had no biased expression and their expressions were derived from the equal contribution of both parents. Besides, very few homoeolog genes (an average of 1%) showed no biased or novel expression in both hybrids. The functional analysis described secondary metabolic pathways had a majority of novel biased homoeolog genes in hybrids. These results contribute preliminary knowledge about how hybridization affects expression patterns of homoeolog gene pairs in upland cotton hybrids. Our study also highlights the functional genomics of metabolic genes to explore the genetic mechanism of heterosis in cotton.

RN7SK small nuclear RNA controls bidirectional transcription of highly expressed gene pairs in skin

Pausing of RNA polymerase II (Pol II) close to promoters is a common regulatory step in RNA synthesis, and is coordinated by a ribonucleoprotein complex scaffolded by the noncoding RNA RN7SK. The function of RN7SK-regulated gene transcription in adult tissue homoeostasis is currently unknown. Here, we deplete RN7SK during mouse and human epidermal stem cell differentiation. Unexpectedly, loss of this small nuclear RNA specifically reduces transcription of numerous cell cycle regulators leading to cell cycle exit and differentiation. Mechanistically, we show that RN7SK is required for efficient transcription of highly expressed gene pairs with bidirectional promoters, which in the epidermis co-regulated cell cycle and chromosome organization. The reduction in transcription involves impaired splicing and RNA decay, but occurs in the absence of chromatin remodelling at promoters and putative enhancers. Thus, RN7SK is directly required for efficient Pol II transcription of highly transcribed bidirectional gene pairs, and thereby exerts tissue-specific functions, such as maintaining a cycling cell population in the epidermis.

Asymmetric epigenetic modification and homoeolog expression bias in the establishment and evolution of allopolyploid Brassica napus.

This study explores how allopolyploidization reshapes the biased expression and asymmetric epigenetic modification of homoeologous gene pairs, and examines the regulation types and epigenetic basis of expression bias. We analyzed the gene expression and four epigenetic modifications (DNA methylation, H3K4me3, H3K27me3 and H3K27ac) of 29976 homoeologous gene pairs in resynthesized, natural allopolyploid Brassica napus and an in silico 'hybrid'. We comprehensively elucidated the biased gene expression, asymmetric epigenetic modifications and the generational transmission characteristics of these homoeologous gene pairs in B.napus. We analyzed cis/trans effects and the epigenetic basis of homoeolog expression bias. There was a significant positive correlation between two active histone modifications and biased gene expression. We revealed that parental legacy was the dominant principle in the remodeling of homoeolog expression bias and asymmetric epigenetic modifications in B.napus, and further clarified that this depends on whether there were differences in the expression/epigenetic modifications of gene pairs in parents/progenitors. The maternal genome was dominant in the homoeolog expression bias of resynthesized B.napus, and this phenomenon was attenuated in natural B.napus. Furthermore, cis rather than trans effects were dominant when epigenetic modifications potentially affected biased expression of gene pairs in B.napus.

COTAN: scRNA-seq data analysis based on gene co-expression.

Estimating the co-expression of cell identity factors in single-cell is crucial. Due to the low efficiency of scRNA-seq methodologies, sensitive computational approaches are critical to accurately infer transcription profiles in a cell population. We introduce COTAN, a statistical and computational method, to analyze the co-expression of gene pairs at single cell level, providing the foundation for single-cell gene interactome analysis. The basic idea is studying the zero UMI counts’ distribution instead of focusing on positive counts; this is done with a generalized contingency tables framework. COTAN can assess the correlated or anti-correlated expression of gene pairs, providing a new correlation index with an approximate p-value for the associated test of independence. COTAN can evaluate whether single genes are differentially expressed, scoring them with a newly defined global differentiation index. Similarly to correlation network analysis, it provides ways to plot and cluster genes according to their co-expression pattern with other genes, effectively helping the study of gene interactions, becoming a new tool to identify cell-identity markers. We assayed COTAN on two neural development datasets with very promising results. COTAN is an R package that complements the traditional single cell RNA-seq analysis and it is available at https://github.com/seriph78/COTAN.

Individualized prognostic signature for pancreatic carcinoma validated by integrating immune-related gene pairs (IRGPs)

ABSTRACT Increasingly attention is being given to immune molecules in pancreatic cancer. The purpose of this study was to understand the potential clinical application of immune-regulated genes (IRGs) in the stratification of prognosis and to facilitate the development of personalized prognostic information for pancreatic cancer patients. We systematically used public data to comprehensively analyze immune-regulated gene pair (IRGP) expression profiles and clinical data. In our study, IRGP signature was identified to predict the overall survival (OS) of pancreatic cancer patients. We suggested that immune genes are enriched in different risk groups. In the high-risk group, M1 macrophages and resting NK cells were significantly enriched, while the percentages of naïve B cells, resting dendritic cells, CD8 T cells and regulatory T cells (Tregs) were significantly higher in the low-risk group, and we verified these results with immunohistochemical experiments. Gene ontology (GO) analysis confirmed that the IRGP index (IRGPI) signature genes in the cohort were mostly party to sensory perception of a chemical stimulus and the adaptive immune response. The identification of these pathways provides a basis for studying the molecular mechanisms of IRGPI signaling to predict the prognosis of pancreatic cancer. Our study effectively constructed a robust IRGP signature with prognostic value for pancreatic cancer, presenting a conceivable method for deciding on a preoperative treatment.

Characterization of pathways involved in colorectal cancer using real-time RT-PCR gene expression data.

Efforts to explore biomarkers and biological pathways involved in the disease are needed to improve colorectal cancer (CRC) diagnosis and alternative treatments. The fourth common malignancy in the world is colorectal cancer. The over-all burden is predicted to rise by 2030. In the current study, nine genes were selected. Previously, a panel of genes by Agendia, a classifier of robust gene expression (ColoPrint), was determined to significantly improve the prognostic accuracy of pathologic factors in stage II and III colorectal cancer patients. Five genes, including Ppara, Mctp1, Pyroxd1, Il2r, and Cyfip2, from this panel and four other genes which were not in this panel but were cited abundantly in the literature were selected. Then, expression levels of the selected genes in CRC tissue were compared with levels in adjacent normal tissue. To identify the pathways involved in CRC, gene set enrichment analysis was subsequently performed. Furthermore, to illustrate the relationship between genes in this disease, the cross-shaped co-expression pattern and gene regulatory network were determined using computational methods. This research found that the pairs of genes: {IL2R, CYFIP2}, {FOXM1, PPARA}, {MCTP1, CTSC}, and {PYROXD1, CYF1P2} are functionally related. Furthermore, two differentially expressed gene pairs ({FOXM1, PPARA} and {IL2R, CYFIP2}) are involved in the vascular endothelial growth factor receptor signaling pathway and the purine ribonucleoside diphosphate metabolic process, respectively. This research found that the combination of computational analysis and laboratory data provided the opportunity to better characterize the relation between central colorectal cancer genes as well as possible pathways involved in the colorectal cancer.

Homoeolog expression bias and expression level dominance (ELD) in four tissues of natural allotetraploid Brassica napus

BackgroundAllopolyploidy is widespread in angiosperms, and they can coordinate two or more different genomes through genetic and epigenetic modifications to exhibit stronger vigor and adaptability. To explore the changes in homologous gene expression patterns in the natural allotetraploid Brassica napus (AnAnCnCn) relative to its two diploid progenitors, B. rapa (ArAr) and B. oleracea (CoCo), after approximately 7500 years of domestication, the global gene pair expression patterns in four major tissues (stems, leaves, flowers and siliques) of these three species were analyzed using an RNA sequencing approach.ResultsThe results showed that the ‘transcriptomic shock’ phenomenon was alleviated in natural B. napus after approximately 7500 years of natural domestication, and most differentially expressed genes (DEGs) in B. napus were downregulated relative to those in its two diploid progenitors. The KEGG analysis indicated that three pathways related to photosynthesis were enriched in both comparison groups (AnAnCnCn vs ArAr and AnAnCnCn vs CoCo), and these pathways were all downregulated in four tissues of B. napus. In addition, homoeolog expression bias and expression level dominance (ELD) in B. napus were thoroughly studied through analysis of expression levels of 27,609 B. rapa-B. oleracea orthologous gene pairs. The overwhelming majority of gene pairs (an average of 86.7%) in B. napus maintained their expression pattern in two diploid progenitors, and approximately 78.1% of the gene pairs showed expression bias with a preference toward the A subgenome. Overall, an average of 48, 29.7 and 22.3% homologous gene pairs exhibited additive expression, ELD and transgressive expression in B. napus, respectively. The ELD bias varies from tissue to tissue; specifically, more gene pairs in stems and siliques showed ELD-A, whereas the opposite was observed in leaves and flowers. More transgressive upregulation, rather than downregulation, was observed in gene pairs of B. napus.ConclusionsIn general, these results may provide a comprehensive understanding of the changes in homologous gene expression patterns in natural B. napus after approximately 7500 years of evolution and domestication and may enhance our understanding of allopolyploidy.

Sleep- and time of day-linked RNA transcript expression in wild-type and IL1 receptor accessory protein-null mice.

Sleep regulation involves interleukin-1β (IL1) family members, TNF, and circadian clock genes. Previously, we characterized spontaneous sleep and sleep after 8 h of sleep deprivation (SD) ending at zeitgeber time (ZT)4 and ZT16 in wild-type (WT) and IL1 receptor accessory protein (AcP)- and brain-specific AcP (AcPb)-knockout (KO) mice. Here, we applied quantitative reverse transcriptase polymerase chain reaction and Spearman gene pair expression correlation methods to characterize IL1, IL1 receptor 1 (IL1R1), AcP, AcPb, Period 1 (Per1), Clock, adenosine deaminase (Ada), peptidoglycan recognition protein 1 (Pglyrp1), and TNF mRNA expressions under conditions with distinct sleep phenotypes. In WT mice, IL1, IL1R1, AcP, Ada, and Clock mRNAs were higher at ZT4 (mid-sleep period) than at ZT16. mRNA expressions differed substantially in AcP and AcPb KO mice at those times. After SD ending at ZT4, only WT mice had a non-rapid eye movement sleep (NREMS) rebound, and AcPb and IL1R1 mRNA increases were unique to WT mice. In AcPb KO mice, which have spontaneous high EEG slow wave power, AcP and Pglyrp1 mRNAs were elevated relative to WT mice at ZT4. At ZT4, the AcPb KO - WT Spearman correlation difference networks showed high positive correlations between IL1R1 and IL1, Per1, and Clock and high negative correlations between TNF and Pglyrp1 and Ada. At ZT16, the WT mice gene pair expression network was mostly negative, whereas in AcP KO mice, which have substantially more rapid eye movement sleep than WT mice, it was all positive. We conclude that gene pair expression correlations depend on the presence of AcP and AcPb.NEW & NOTEWORTHY Spearman gene pair expression correlations depend upon the presence or absence of interleukin-1 receptor accessory protein and upon sleep phenotype.

Characterization of bidirectional gene pairs in The Cancer Genome Atlas (TCGA) dataset

The “bidirectional gene pair” indicates a particular head-to-head gene organization in which transcription start sites of two genes are located on opposite strands of genomic DNA within a region of one kb. Despite bidirectional gene pairs are well characterized, little is known about their expression profiles and regulation features in tumorigenesis. We used RNA-seq data from The Cancer Genome Atlas (TCGA) dataset for a systematic analysis of the expression profiles of bidirectional gene pairs in 13 cancer datasets. Gene pairs on the opposite strand with transcription end site distance within one kb or on the same strand with the distance of two genes between 1–10 kb and gene pairs comprising two randomly chosen genes were used as control gene pairs (CG1, CG2, and random). We identified and characterized up-/down-regulated genes by comparing the expression level between tumors and adjacent normal tissues in 13 TCGA datasets. There were no consistently significant difference in the percentage of up-/down-regulated genes between bidirectional and control/random genes in most of TCGA datasets. However, the percentage of bidirectional gene pairs comprising two up- or two down-regulated genes was significantly higher than gene pairs from CG1/2 in 12/11 analyzed TCGA datasets and the random gene pairs in all 13 TCGA datasets. Then we identified the methylation correlated bidirectional genes to explore the regulatory mechanism of bidirectional genes. Like the differentially expressed gene pairs, the bidirectional genes in a pair were significantly prone to be both hypo- or hyper-methylation correlated genes in 12/13 TCGA datasets when comparing to the CG2/random gene pairs despite no significant difference between the percentages of hypo-/hyper-methylation correlated genes in bidirectional and CG2/random genes in most of TCGA datasets. Finally, we explored the correlation between bidirectional genes and patient’s survival, identifying prognostic bidirectional genes and prognostic bidirectional gene pairs in each TCGA dataset. Remarkably, we found a group of prognostic bidirectional gene pairs in which the combination of two protein coding genes with different expression level correlated with different survival prognosis in survival analysis for OS. The percentage of these gene pairs in bidirectional gene pair were significantly higher than the gene pairs in controls in COAD datasets and lower in none of 13 TCGA datasets.

Clustering analysis to identify key genes associated with motor neuron excitability following spinal cord injury

Purpose: As a neurodegenerative disease, spinal cord injury can lead to the loss of autonomic function, muscle function, or sensation. This study is designed to identify the key genes implicated in the excitability of motor neurons following spinal cord injury.Materials and methods: The GSE19701 dataset was obtained from Gene Expression Omnibus. It includes a total of 31 motor neurons after spinal cord injury (samples at day 0, 2, 7, 21 and 60 following injury). After the data were preprocessed by the Robust Multi-array Average method, soft clustering analysis was conducted by the Fuzzy C-Means method in the Mfuzz package to identify the differentially expressed genes. Afterward, the differentially expressed genes were analyzed with enrichment analysis using the DAVID online tool. Based on Cytoscape software, a protein-protein interaction network was constructed and then module analysis was carried out. Furthermore, miRNA-differentially expressed gene pairs were downloaded from the miRWalk2.0 database and the miRNA regulatory network was visualized by Cytoscape software.Results: We found 218 upregulated genes and 526 downregulated genes. In the protein-protein interaction network, Uba3, Sumo1, and Pik3ca had higher scores, and Uba3 interacted with Sumo1. Among the eight modules identified from the protein–protein interaction network, module 1 and 8 were significantly enriched in pathways related to degenerative diseases of the nervous system. Additionally, Pdcd4 was targeted by miR-21 in the miRNA regulatory network.Conclusion: Uba3, Sumo1, Pik3ca and miR-21 targeting Pdcd4 might be responsible for the excitability of motor neurons after spinal cord injury.

PRR11 and SKA2 gene pair is overexpressed and regulated by p53 in breast cancer

Our previous study found that two novel cancer-related genes, PRR11 and SKA2, constituted a classic gene pair that was regulated by p53 and NF-Y in lung cancer. However, their role and regulatory mechanism in breast cancer remain elusive. In this study, we found that the expression levels of PRR11 and SKA2 were upregulated and have a negative prognotic value in breast cancer. Loss-of-function experiments showed that RNAi-mediated knockdown of PRR11 and/or SKA2 inhibited proliferation, migration, and invasion of breast cancer cells. Mechanistic experiments revealed that knockdown of PRR11 and/or SKA2 caused dysregulation of several downstream genes, including CDK6, TPM3, and USP12, etc. Luciferase reporter assays demonstrated that wild type p53 significantly repressed the PRR11-SKA2 bidirectional promoter activity, but not NF-Y. Interestingly, NF-Y was only essential for and correlated with the expression of PRR11, but not SKA2. Consistently, adriamycin-induced (ADR) activation of endogenous p53 also caused significant repression of the PRR11 and SKA2 gene pair expression. Notably, breast cancer patients with lower expression levels of either PRR11 or SKA2, along with wild type p53, exhibited better disease-free survival compared to others with p53 mutations and/or higher expression levels of either PRR11 or SKA2. Collectively, our study indicates that the PRR11 and SKA2 transcription unit might be an oncogenic contributor and might serve as a novel diagnostic and therapeutic target in breast cancer.

Profiling of patient-specific myocytes identifies altered gene expression in the ophthalmoplegic subphenotype of myasthenia gravis

BackgroundWhile extraocular muscles are affected early in myasthenia gravis (MG), but respond to treatment, we observe a high incidence of treatment-resistant ophthalmoplegia (OP-MG) among MG subjects with African genetic ancestry. Previously, using whole exome sequencing, we reported potentially functional variants which associated with OP-MG. The aim of this study was to profile the expression of genes harbouring the OP-MG associated variants using patient-derived subphenotype-specific ‘myocyte’ cultures.MethodsFrom well-characterised MG patients we developed the ‘myocyte’ culture models by transdifferentiating dermal fibroblasts using an adenovirus expressing MyoD. These myocyte cultures were treated with homologous acetylcholine receptor antibody-positive myasthenic sera to induce muscle transcripts in response to an MG stimulus. Gene expression in myocytes derived from OP-MG (n = 10) and control MG subjects (MG without ophthalmoplegia; n = 6) was quantified using a custom qPCR array profiling 93 potentially relevant genes which included the putative OP-MG susceptibility genes and other previously reported genes of interest in MG and experimental autoimmune myasthenia gravis (EAMG).ResultsOP-MG myocytes compared to control MG myocytes showed altered expression of four OP-MG susceptibility genes (PPP6R2, CANX, FAM136A and FAM69A) as well as several MG and EAMG genes (p < 0.05). A correlation matrix of gene pair expression levels revealed that 15% of gene pairs were strongly correlated in OP-MG samples (r > 0.78, p < 0.01), but not in control MG samples. OP-MG susceptibility genes and MG-associated genes accounted for the top three significantly correlated gene pairs (r ≥ 0.98, p < 1 × 10− 6) reflecting crosstalk between OP-MG and myasthenia pathways, which was not evident in control MG cells. The genes with altered expression dynamics between the two subphenotypes included those with a known role in gangliosphingolipid biosynthesis, mitochondrial metabolism and the IGF1-signalling pathway.ConclusionUsing a surrogate cell culture model our findings suggest that muscle gene expression and co-expression differ between OP-MG and control MG individuals. These findings implicate pathways not previously considered in extraocular muscle involvement in myasthenia gravis and will inform future studies.

Homoeolog expression bias and expression level dominance in resynthesized allopolyploid Brassica napus

BackgroundAllopolyploids require rapid genetic and epigenetic modifications to reconcile two or more sets of divergent genomes. To better understand the fate of duplicate genes following genomic mergers and doubling during allopolyploid formation, in this study, we explored the global gene expression patterns in resynthesized allotetraploid Brassica napus (AACC) and its diploid parents B. rapa (AA) and B. oleracea (CC) using RNA sequencing of leaf transcriptomes.ResultsWe found that allopolyploid B. napus formation was accompanied by extensive changes (approximately one-third of the expressed genes) in the parental gene expression patterns (‘transcriptome shock’). Interestingly, the majority (85%) of differentially expressed genes (DEGs) were downregulated in the allotetraploid. Moreover, the homoeolog expression bias (relative contribution of homoeologs to the transcriptome) and expression level dominance (total expression level of both homoeologs) were thoroughly investigated by monitoring the expression of 23,766 B. oleracea-B. rapa orthologous gene pairs. Approximately 36.5% of the expressed gene pairs displayed expression bias with a slight preference toward the A-genome. In addition, 39.6, 4.9 and 9.0% of the expressed gene pairs exhibited expression level dominance (ELD), additivity expression and transgressive expression, respectively. The genome-wide ELD was also biased toward the A-genome in the resynthesized B. napus. To explain the ELD phenomenon, we compared the individual homoeolog expression levels relative to those of the diploid parents and found that ELD in the direction of the higher-expression parent can be explained by the downregulation of homoeologs from the dominant parent or upregulation of homoeologs from the nondominant parent; however, ELD in the direction of the lower-expression parent can be explained only by the downregulation of the nondominant parent or both homoeologs. Furthermore, Gene Ontology (GO) enrichment analysis suggested that the alteration in the gene expression patterns could be a prominent cause of the phenotypic variation between the newly formed B. napus and its parental species.ConclusionsCollectively, our data provide insight into the rapid repatterning of gene expression at the beginning of Brassica allopolyploidization and enhance our knowledge of allopolyploidization processes.

Estrogen Protects Neurotransmission Transcriptome During Status Epilepticus

Women with epilepsy commonly have premature onset of menopause. The decrease in estrogen levels is associated with increased occurrence of neurodegenerative processes and cognitive decline. Previously, we found that estradiol (E2) replacement in ovariectomized (OVX) female rats significantly reduced the seizure-related damage in the sensitive hilar region of hippocampal dentate gyrus (DG). However, the complex mechanisms by which E2 empowers the genomic fabrics of neurotransmission to resist damaging effects of status epilepticus (SE) are still unclear. We determined the protective effects of the estradiol replacement against kainic acid-induced SE-associated transcriptomic alterations in the DG of OVX rats. Without E2 replacement, SE altered expression of 44% of the DG genes. SE affected all major functional pathways, including apoptosis (61%), Alzheimer's disease (47%), cell cycle (59%), long-term potentiation (62%), and depression (55%), as well as synaptic vesicle cycle (62%), glutamatergic (53%), GABAergic (49%), cholinergic (52%), dopaminergic (55%), and serotonergic (49%) neurotransmission. However, in rats with E2 replacement the percentage of significantly affected genes after SE was reduced to the average 11% (from 8% for apoptosis to 32% for GABAergic synapse). Interestingly, while SE down-regulated most of the synaptic receptor genes in oil-injected females it had little effect on these receptors after E2-replacement. Our novel Pathway Protection analysis indicated that the E2-replacement prevented SE-related damage from 50% for GABA to 75% for dopaminergic transmission. The 15% synergistic expression between genes involved in estrogen signaling (ESG) and neurotransmission explains why low E2 levels result in down-regulation of neurotransmission. Interestingly, in animals with E2-replacement, SE switched 131 synergistically expressed ESG-neurotransmission gene pairs into antagonistically expressed gene pairs. Thus, the ESG pathway acts like a buffer against SE-induced alteration of neurotransmission that may contribute to the E2-mediated maintenance of brain function after the SE injury in postmenopausal women. We also show that the long-term potentiation is lost in OVX rats following SE but not in those with E2 replacement. The electrophysiological findings in OVX female rats with SE are corroborated by the high percentage of long-term potentiation regulated genes (62%) in oil-injected while only 13% of genes were regulated following SE in E2-replaced rats.