Genome-wide Co-expression Analysis Research Articles

IMMU-59. AN IMMUNOSUPPRESSIVE PROGRAM ENCOMPASSING MULTIPLE IMMUNE CELL TYPES IN GBM TYPIFIED BY NOVEL MARKER LRRC25 ASSOCIATED WITH TYROBP SIGNALING

Abstract Immunosuppression in glioblastoma is a powerful impediment to effective immunotherapy. We used maximal tumor sampling and genome-wide coexpression analysis of RNA sequencing, on 69 samples from 8 patients, to identify a module of 270 genes marked by LRRC25, determined by top fidelity score, that covaries with many immunosuppressive molecules. An immunosuppressive module was independently derived from an expanded cohort of 319 samples from 28 GBM also marked by LRRC25 by top fidelity score. Within the gene module, we observed strong co-variation of markers for monocytes, neutrophils, and NK cells with LRRC25. In published single-cell RNA-seq from glioma, we determined that LRRC25 is expressed by neutrophils and myeloid cells while absent from NK-cells. LRRC25 is also constitutively expressed in monocytes and neutrophils while being upregulated by microglia and DCs in the tumor core and necrotic regions. In addition to covariation with multiple cell-type specific markers we also discovered that LRRC25 expression is tightly associated with several members of the TYROBP causal signaling network in microglia. Thus, LRRC25 may play a novel role in TYROBP signaling which may, in turn, represent a novel mechanism of NK cell and neutrophil immunosuppression in glioma. We confirmed LRRC25 RNA expression in patient samples by RNAscope co-stained with an anti-CD163 antibody indicating myeloid expression, as well as tumor cell expression determined by histopathology. Although LRRC25 is known to mediate IFN and NFKb signaling in myeloid cells in-vitro, its function in glioma remains understudied. While significant efforts have focused on mechanisms of myeloid to T-cell immunosuppression, less focus has been given to mechanisms of myeloid to NK-cell and neutrophil immunosuppression, despite the fact they exist at levels comparable to T-cells in the tumor microenvironment. This work will be followed up with antibody validation as well as genetic manipulation of LRRC25 in-vitro and in-vivo.

EPCO-33. OMICON: A CLOUD PLATFORM FOR FAIR RESEARCH ON GENE COEXPRESSION NETWORKS IN NORMAL HUMAN BRAIN AND BRAIN TUMORS

Abstract Genome-wide coexpression analysis of bulk human brain samples is a powerful approach for identifying highly reproducible transcriptional signatures of cell types and cell states, since it can survey huge numbers of individuals, cells, and transcripts. However, it is difficult to optimize gene coexpression network construction, compare gene coexpression modules from independent datasets, or even locate gene expression datasets with similar attributes. To address these challenges, we have developed the OMICON platform (theomicon.ucsf.edu) to promote FAIR (Findable, Accessible, Interoperable, Reusable) research practices involving human brain gene coexpression networks. OMICON contains structured gene expression data for >17K bulk human brain samples (~10K normal and ~7K malignant glioma), which were collected from diverse public repositories and consortia (e.g., GEO, TCGA, CGGA, CPTAC, REMBRANDT, IvyGAP, GTEx, NABEC, the Allen Institute). To promote interoperability, we have standardized metadata for hundreds of dataset and sample attributes, including single-nucleotide and copy-number mutations. For each dataset, we have used the FindModules R function to construct dozens of gene coexpression networks by iterating over module detection parameters. These efforts have identified ~100K gene coexpression modules, which have been extensively characterized via enrichment analysis with thousands of curated gene sets. All datasets, metadata, gene coexpression networks, enrichment results, and analysis steps can be browsed with an interactive workflow visualization tool, which promotes accessibility, reusability, and reproducibility by maintaining complete data provenance with unique identifiers. To promote findability, we have built an advanced search engine to identify datasets, samples, modules, and more, by filtering standardized metadata (e.g., find gene coexpression modules in human glioblastoma datasets that are significantly enriched with markers of T-cells). A detailed description of OMICON’s functionality is described on our Help page: theomicon.ucsf.edu/home/help. Through this functionality, OMICON seeks to build community and focus therapeutic efforts around reproducible analyses of transcriptional variation in normal human brain and brain tumors.

Dampened Regulatory Circuitry of TEAD1/ITGA1/ITGA2 Promotes TGFβ1 Signaling to Orchestrate Prostate Cancer Progression.

The extracellular matrix (ECM) undergoes substantial changes during prostate cancer (PCa) progression, thereby regulating PCa growth and invasion. Herein, a meta-analysis of multiple PCa cohorts is performed which revealed that downregulation or genomic loss of ITGA1 and ITGA2 integrin genes is associated with tumor progression and worse prognosis. Genomic deletion of both ITGA1 and ITGA2 activated epithelial-to-mesenchymal transition (EMT) in benign prostate epithelial cells, thereby enhancing their invasive potential in vitro and converting them into tumorigenic cells in vivo. Mechanistically, EMT is induced by enhanced secretion and autocrine activation of TGFβ1 and nuclear targeting of YAP1. An unbiased genome-wide co-expression analysis of large PCa cohort datasets identified the transcription factor TEAD1 as a key regulator of ITGA1 and ITGA2 expression in PCa cells while TEAD1 loss phenocopied the dual loss of α1- and α2-integrins in vitro and in vivo. Remarkably, clinical data analysis revealed that TEAD1 downregulation or genomic loss is associated with aggressive PCa and together with low ITGA1 and ITGA2 expression synergistically impacted PCa prognosis and progression. This study thus demonstrated that loss of α1- and α2-integrins, either via deletion/inactivation of the ITGA1/ITGA2 locus or via loss of TEAD1, contributes to PCa progression by inducing TGFβ1-driven EMT.

Investigating the prognostic and predictive value of the type II cystatin genes in gastric cancer

BackgroundAccumulating evidence indicates that type II cystatin (CST) genes play a pivotal role in several tumor pathological processes, thereby affecting all stages of tumorigenesis and tumor development. However, the prognostic and predictive value of type II CST genes in GC has not yet been investigated.MethodsThe present study evaluated the expression and prognostic value of type II CST genes in GC by using The Cancer Genome Atlas (TCGA) database and the Kaplan–Meier plotter (KM plotter) online database. The type II CST genes related to the prognosis of GC were then screened out. We then validated the expression and prognostic value of these genes by immunohistochemistry. We also used Database for Annotation, Visualization, and Integrated Discovery (DAVID), Gene Multiple Association Network Integration Algorithm (GeneMANIA), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), nomogram, genome-wide co-expression analysis, and other bioinformatics tools to analyze the value of type II CST genes in GC and the underlying mechanism.ResultsThe data from the TCGA database and the KM plotter online database showed that high expression of CST2 and CST4 was associated with the overall survival (OS) of patients with GC. The immunohistochemical expression analysis showed that patients with high expression of CST4 in GC tissues have a shorter OS than those with low expression of CST4 (HR = 1.85,95%CI: 1.13–3.03, P = 0.015). Multivariate Cox regression analysis confirmed that the high expression level of CST4 was an independent prognostic risk factor for OS.ConclusionsOur findings suggest that CST4 could serve as a tumor marker that affects the prognosis of GC and could be considered as a potential therapeutic target for GC.

Extensive germline-somatic interplay contributes to prostate cancer progression through HNF1B co-option of TMPRSS2-ERG

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

Genome-Wide Identification and Co-Expression Analysis of ARF and IAA Family Genes in Euscaphis konishii: Potential Regulators of Triterpenoids and Anthocyanin Biosynthesis.

Euscaphis konishii is an evergreen plant that is widely planted as an industrial crop in Southern China. It produces red fruits with abundant secondary metabolites, giving E. konishii high medicinal and ornamental value. Auxin signaling mediated by members of the AUXIN RESPONSE FACTOR (ARF) and auxin/indole-3-acetic acid (Aux/IAA) protein families plays important roles during plant growth and development. Aux/IAA and ARF genes have been described in many plants but have not yet been described in E. konishii. In this study, we identified 34 EkIAA and 29 EkARF proteins encoded by the E. konishii genome through database searching using HMMER. We also performed a bioinformatic characterization of EkIAA and EkARF genes, including their phylogenetic relationships, gene structures, chromosomal distribution, and cis-element analysis, as well as conserved motifs in the proteins. Our results suggest that EkIAA and EkARF genes have been relatively conserved over evolutionary history. Furthermore, we conducted expression and co-expression analyses of EkIAA and EkARF genes in leaves, branches, and fruits, which identified a subset of seven EkARF genes as potential regulators of triterpenoids and anthocyanin biosynthesis. RT-qPCR, yeast one-hybrid, and transient expression analyses showed that EkARF5.1 can directly interact with auxin response elements and regulate downstream gene expression. Our results may pave the way to elucidating the function of EkIAA and EkARF gene families in E. konishii, laying a foundation for further research on high-yielding industrial products and E. konishii breeding.

Genome-wide identification and co-expression analysis of GDSL genes related to suberin formation during fruit russeting in pear

Glycine-aspartic acid‑serine-leucine (GDSL) type lipases/esterases genes play critical roles in plant development and are related to the responses to abiotic and biotic stress. However, little is known about the GDSL family in pear (Pyrus spp.). Studies have shown GDSL-domain proteins play key roles in suberin deposition. Suberin deposition in the fruit epidermis, also called russeting, is an important defect that negatively affects consumer's appeal in some fruit species, such as pear, apple and grapevine. Fruit russeting is mainly associated with cuticle microcracking and suberin accumulation in the inner part of the epidermal cell walls. To gain insight into the role of the GDSL gene family in suberin deposition and russet development in pear, we performed a genome-wide characterization of the GDSL family, including their identification, chromosomal localization, phylogenetic relationships, and expression patterns, in different tissues/organs in pear. One hundred and thirteen GDSL-type lipases/esterases genes were identified in the pear genome, and a phylogenetic analysis revealed that GDSL family can be classified into four distinct groups. Thirty GDSL genes were co-expressed with five homolog pear genes of three well-known suberin biosynthesis Arabidopsis genes (AtGPAT5, AtASFT, and AtCYP86B1) in the transcriptional co-expression network during pear fruit development. Among the 30 co-expressed GDSL genes, twelve genes were further analyzed by quantitative Real-time PCR, and the results showed the expression levels of the 12 genes were different between the russet exocarp and green exocarp of sand pear at different fruit development stages. Our study provides a detailed overview of the GDSL gene family and lays the foundation for future functional characterization of GDSL genes in P. bretschneideri.

Identification and validation of signal recognition particle 14 as a prognostic biomarker predicting overall survival in patients with acute myeloid leukemia

BackgroundThis study aimed to determine and verify the prognostic value and potential functional mechanism of signal recognition particle 14 (SRP14) in acute myeloid leukemia (AML) using a genome-wide expression profile dataset.MethodsWe obtained an AML genome-wide expression profile dataset and clinical prognostic data from The Cancer Genome Atlas (TCGA) and GSE12417 databases, and explored the prognostic value and functional mechanism of SRP14 in AML using survival analysis and various online tools.ResultsSurvival analysis showed that AML patients with high SRP14 expression had poorer overall survival than patients with low SRP14 expression. Time-dependent receiver operating characteristic curves indicated that SRP14 had good accuracy for predicting the prognosis in patients with AML. Genome-wide co-expression analysis suggested that SRP14 may play a role in AML by participating in the regulation of biological processes and signaling pathways, such as cell cycle, cell adhesion, mitogen-activated protein kinase, tumor necrosis factor, T cell receptor, DNA damage response, and nuclear factor-kappa B (NF-κB) signaling. Gene set enrichment analysis indicated that SRP14 was significantly enriched in biological processes and signaling pathways including regulation of hematopoietic progenitor cell differentiation and stem cell differentiation, intrinsic apoptotic signaling pathway by p53 class mediator, interleukin-1, T cell mediated cytotoxicity, and NF-κB-inducing kinase/NF-κB signaling. Using the TCGA AML dataset, we also identified four drugs (phenazone, benzydamine, cinnarizine, antazoline) that may serve as SRP14-targeted drugs in AML.ConclusionThe current results revealed that high SRP14 expression was significantly related to a poor prognosis and may serve as a prognostic biomarker in patients with AML.

UXT antisense RNA 1 sever as a novel prognostic long non-coding RNA in early stage pancreatic ductal adenocarcinoma patients after receiving pancreaticoduodenectomy.

Objective: The principal objective of this project was to investigate the prognostic value of UXT antisense RNA 1 (UXT-AS1) in pancreatic ductal adenocarcinoma (PDAC), as well as its biological function mechanisms and the screening of targeted drugs using The Cancer Genome Atlas (TCGA) PDAC genome-wide RNA sequencing (RNA-seq) dataset.Methods: We used TCGA 112 early stage PDAC patients to screen the prognostic value of UXT-AS1. Biological functions and mechanisms of UXT-AS1 were investigated by co-expression analysis, differentially expressed genes (DEGs) and gene set enrichment analysis, while targeted drug screening was investigated by connectivity Map (CMap).Results: By analyzing the dataset from TCGA cohort, we found that UXT-AS1 was significantly up-regulated in pancreatic cancer tissues. Multivariate survival analysis demonstrated that PDAC patients with high UXT-AS1 expression had an unfavourable prognosis (adjusted P=0.033, HR=1.830, 95%CI=1.051-3.188). Genome-wide co-expression analysis and gene set enrichment analysis suggested that UXT-AS1 may act as a pivotal part in PDAC by participating in nuclear factor kappa beta, regulation of tumor necrosis factor, cell adhesion, T cell receptor signaling pathway, and numerous immune-related biological processes and signaling pathways. Functional enrichment analysis of DEGs between high- and low-UXT-AS1 expression groups suggested that these DEGs were significant enriched in B cell receptor complex, response to drug chemical carcinogenesis and drug metabolism-cytochrome P450. CMap analysis revealed that quipazine and terazosin may be targeted drugs for UXT-AS1 in PDAC.Conclusion: Our current study has identified UXT-AS1 as a novel biomarker for the prognosis of early stage PDAC. We also clarified its biological functional mechanisms and identified two targeted drugs of UXT-AS1 in PDAC.

Prognostic value of Glypican family genes in early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy and possible mechanisms

BackgroundThis study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).MethodsA total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis.ResultsIn TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway.ConclusionGPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.

Identification and verification of the prognostic value of the glutathione S-transferase Mu genes in gastric cancer.

Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancer types in the world. Novel prognostic biomarkers are required to predict the progression of GC. Glutathione S-transferase Mu (GSTM) belongs to a family of phase II enzymes that have been implicated in a number of cancer types. However, the prognostic value of the GSTM genes has not been previously investigated in GC. The Cancer Genome Atlas (TCGA) was used to evaluate mRNA expression levels of GSTMs in GC tissue samples. Overall survival (OS) rates, hazard ratios (HRs) and 95% CIs were calculated using the Cox logistic regression model and Kaplan-Meier (KM) analysis was performed. In addition, the KM plotter online database was used to validate mRNA expression and the prognostic value of GSMT family members in patients with GC. To predict the function of GSTM genes in these patients, several bioinformatics tools, including the Database for Annotation, Visualization and Integrated Discovery, gene multiple association network integration algorithm, Search Tool for the Retrieval of Interacting Genes/Proteins, Gene Set Enrichment Analysis (GSEA), nomogram and genome-wide co-expression analysis were used. In the present study, high expression of GSTM5 was indicated to be strongly associated with lower OS in patients with GC, according to the TCGA and KM plotter online databases (HR=1.47, 95% CI: 1.06-2.04, P=0.021; and HR=1.69, 95% CI: 1.42-2.01, P=1.6×10−9, respectively). The results from the GSEA and genome-wide co-expression analysis indicated that GSTM5 expression associated with several biological process terms, including ‘adhesion’, ‘angiogenesis’, ‘apoptotic process’, ‘cell growth’, ‘proliferation’, ‘migration’, ‘Hedgehog signaling’, ‘MAPK signaling’ and the ‘TGF-β signaling pathway’. In conclusion, the present results indicated that GSTM5 may serve as a biomarker for GC prognosis and may be a potential therapeutic target for GC.

Co-expression Networks Identify DHX15 RNA Helicase as a B Cell Regulatory Factor.

Genome-wide co-expression analysis is often used for annotating novel gene functions from high-dimensional data. Here, we developed an R package with a Shiny visualization app that creates immuno-networks from RNAseq data using a combination of Weighted Gene Co-expression Network Analysis (WGCNA), xCell immune cell signatures, and Bayesian Network Learning. Using a large publicly available RNAseq dataset we generated a Gene Module-Immune Cell (GMIC) network that predicted causal relationships between DEAH-box RNA helicase (DHX)15 and genes associated with humoral immunity, suggesting that DHX15 may regulate B cell fate. Deletion of DHX15 in mouse B cells led to impaired lymphocyte development, reduced peripheral B cell numbers, and dysregulated expression of genes linked to antibody-mediated immune responses similar to the genes predicted by the GMIC network. Moreover, antigen immunization of mice demonstrated that optimal primary IgG1 responses required DHX15. Intrinsic expression of DHX15 was necessary for proliferation and survival of activated of B cells. Altogether, these results support the use of co-expression networks to elucidate fundamental biological processes.

Prognostic value of Kinesin-4 family genes mRNA expression in early-stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy.

BackgroundThe aim of this study was to investigate the potential prognostic value of Kinesin‐4 family genes mRNA expression in early‐stage pancreatic ductal adenocarcinoma (PDAC) patients after pancreaticoduodenectomy.MethodsKaplan‐Meier survival analysis method with log‐rank test and Cox proportional hazards regression analysis were performed to figure out the association between Kinesin‐4 family genes expression and PDAC patients overall survival time. Joint‐effect survival analysis and stratified survival analysis were carried out to assess the prognosis prediction value of prognosis‐related gene. Nomogram was constructed for the individualized prognosis prediction. In addition, we had used the gene set enrichment analysis and genome‐wide co‐expression analysis to further explore the potential mechanism.Results KIF21A expression level was significantly associated with PDAC patient clinical prognosis outcome and patient with a high expression of KIF21A would have a shorter overall survival time. The prognosis prediction significance of KIF21A was well validated by the joint‐effect survival analysis, stratified survival analysis, and nomogram. Meanwhile, the gene set enrichment analysis and genome‐wide co‐expression analysis revealed that KIF21A might involve in DNA damage and repair, transcription and translation process, post‐translation protein modification, cell cycle, carcinogensis genes and pathways.ConclusionsOur current research demonstrated that KIF21A could serve as a potential prognostic biomarker for patient with early‐stage PDAC after pancreaticoduodenectomy.

A comprehensive study on genome-wide coexpression network of KHDRBS1/Sam68 reveals its cancer and patient-specific association

Human KHDRBS1/Sam68 is an oncogenic splicing factor involved in signal transduction and pre-mRNA splicing. We explored the molecular mechanism of KHDRBS1 to be a prognostic marker in four different cancers. Within specific cancer, including kidney renal papillary cell carcinoma (KIRP), lung adenocarcinoma (LUAD), acute myeloid leukemia (LAML), and ovarian cancer (OV), KHDRBS1 expression is heterogeneous and patient specific. In KIRP and LUAD, higher expression of KHDRBS1 affects the patient survival, but not in LAML and OV. Genome-wide coexpression analysis reveals genes and transcripts which are coexpressed with KHDRBS1 in KIRP and LUAD, form the functional modules which are majorly involved in cancer-specific events. However, in case of LAML and OV, such modules are absent. Irrespective of the higher expression of KHDRBS1, the significant divergence of its biological roles and prognostic value is due to its cancer-specific interaction partners and correlation networks. We conclude that rewiring of KHDRBS1 interactions in cancer is directly associated with patient prognosis.

Diagnostic and prognostic values of the mRNA expression of excision repair cross-complementation enzymes in hepatitis B virus-related hepatocellular carcinoma.

BackgroundThe current study aims at using the whole genome expression profile chips for systematically investigating the diagnostic and prognostic values of excision repair cross-complementation (ERCC) genes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).Materials and methodsWhole genome expression profile chips were obtained from the GSE14520. The receiver-operating characteristic (ROC) curve, survival analysis, and nomogram were used to investigate the diagnostic and prognostic values of ERCC genes. Investigation of the potential function of ERCC8 was carried out by gene set enrichment analysis (GSEA) and genome-wide coexpression analysis.ResultsROC analysis suggests that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated and may have potential to distinguish between HBV-related HCC tumor and paracancerous tissues (area under the curve of ROC ranged from 0.623 to 0.744). Survival analysis demonstrated that high ERCC8 expression was associated with a significantly decreased risk of recurrence (adjusted P=0.021; HR=0.643; 95% CI=0.442–0.937) and death (adjusted P=0.049; HR=0.631; 95% CI=0.399–0.998) in HBV-related HCC. Then, we also developed two nomograms for the HBV-related HCC individualized prognosis predictions. GSEA suggests that the high expression of ERCC8 may have involvement in the energy metabolism biological processes. As the genome-wide coexpression analysis and functional assessment of ERCC8 suggest, those coexpressed genes were significantly enriched in multiple biological processes of DNA damage and repair.ConclusionThe present study indicates that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated between HBV-related HCC tumor and paracancerous tissues and that the mRNA expression of ERCC8 may serve as a potential biomarker for the HBV-related HCC prognosis.

Characterization of the ZmbHLH122 transcription factor and its potential collaborators in maize male reproduction

OsEAT1 (DTD), a stamen-specific bHLH transcription factor, is a master regulator in rice male reproduction. To elucidate its functional mechanism in maize male reproduction, the maize orthologue ZmbHLH122 of OsEAT1 was isolated in this study. Sequence analysis revealed that the ZmbHLH122 coding sequence consists of 1422 bp which encode a protein of 473 amino acids. Bioinformatic analysis confirmed that ZmbHLH122 belongs to the bHLH TF family. The subcellular localization of ZmbHLH122-eGFP in rice protoplasts showed that ZmbHLH122 is a nuclear-localized protein. Yeast one-hybrid assays demonstrated that ZmbHLH122 exhibits weak transactivation ability. Genome-wide coexpression analysis identified 751 potential collaborators of ZmbHLH122, most of which are highly expressed in maize anthers and tassels, and sequence alignment analysis revealed that 43 coexpressed genes are homologous to Arabidopsis male fertility-related genes. Expression pattern analysis confirmed that ZmbHLH122 and its potential collaborators Ms23 (ZmbHLH16), ZmbHLH51, ZmbHLH66 (Ms32) and ZmMYB74 are preferentially expressed in the maize male reproductive organs, especially those at the uninucleate and early binucleate stages. Yeast two-hybrid assays revealed that ZmMYB74 directly interacts with two maize stamen development regulators, Ms23 (ZmbHLH16) and ZmbHLH51, and indirectly collaborates with ZmbHLH122. Our study lays the foundation for further understanding of the ZmbHLH122 molecular function in maize male reproduction.

Combinatorial Regulation of Stilbene Synthase Genes by WRKY and MYB Transcription Factors in Grapevine (Vitis vinifera L.).

Stilbene synthase (STS) is the key enzyme leading to the biosynthesis of resveratrol. Recently we reported two R2R3-MYB transcription factor (TF) genes that regulate the stilbene biosynthetic pathway in grapevine: VviMYB14 and VviMYB15. These genes are strongly co-expressed with STS genes under a range of stress and developmental conditions, in agreement with the specific activation of STS promoters by these TFs. Genome-wide gene co-expression analysis using two separate transcriptome compendia based on microarray and RNA sequencing data revealed that WRKY TFs were the top TF family correlated with STS genes. On the basis of correlation frequency, four WRKY genes, namely VviWRKY03, VviWRKY24, VviWRKY43 and VviWRKY53, were further shortlisted and functionally validated. Expression analyses under both unstressed and stressed conditions, together with promoter-luciferase reporter assays, suggested different hierarchies for these TFs in the regulation of the stilbene biosynthetic pathway. In particular, VviWRKY24 seems to act as a singular effector in the activation of the VviSTS29 promoter, while VviWRKY03 acts through a combinatorial effect with VviMYB14, suggesting that these two regulators may interact at the protein level as previously reported in other species.

Genome-wide identification and characterization of the RIO atypical kinase family in plants.

Members of the right open reading frame (RIO) atypical kinase family are present in all three domains of life. In eukaryotes, three subfamilies have been identified: RIO1, RIO2, and RIO3. Studies have shown that the yeast and human RIO1 and RIO2 kinases are essential for the biogenesis of small ribosomal subunits. Thus far, RIO3 has been found only in multicellular eukaryotes. In this study, we systematically identified members of the RIO gene family in 37 species representing the major evolutionary lineages in Viridiplantae. A total of 84 RIO genes were identified; among them, 41 were classified as RIO1 and 43 as RIO2. However, no RIO3 gene was found in any of the species examined. Phylogenetic trees constructed for plant RIO1 and RIO2 proteins were generally congruent with the species phylogeny. Subcellular localization analyses showed that the plant RIO proteins were localized mainly in the nucleus and/or cytoplasm. Expression profile analysis of rice, maize, and Arabidopsis RIO genes in different tissues revealed similar expression patterns between RIO1 and RIO2 genes, and their expression levels were high in certain tissues. In addition, the expressions of plant RIO genes were regulated by two drugs: mycophenolic acid and actinomycin D. Function prediction using genome-wide coexpression analysis revealed that most plant RIO genes may be involved in ribosome biogenesis. Our results will be useful for the evolutionary analysis of the ancient RIO kinase family and provide a basis for further functional characterization of RIO genes in plants.

The Brugada Syndrome Susceptibility Gene HEY2 Modulates Cardiac Transmural Ion Channel Patterning and Electrical Heterogeneity.

Genome-wide association studies previously identified an association of rs9388451 at chromosome 6q22.3 (near HEY2) with Brugada syndrome. The causal gene and underlying mechanism remain unresolved. We used an integrative approach entailing transcriptomic studies in human hearts and electrophysiological studies in Hey2+/- (Hey2 heterozygous knockout) mice to dissect the underpinnings of the 6q22.31 association with Brugada syndrome. We queried expression quantitative trait locus data acquired in 190 human left ventricular samples from the genotype-tissue expression consortium for cis-expression quantitative trait locus effects of rs9388451, which revealed an association between Brugada syndrome risk allele dosage and HEY2 expression (β=+0.159; P=0.0036). In the same transcriptomic data, we conducted genome-wide coexpression analysis for HEY2, which uncovered KCNIP2, encoding the β-subunit of the channel underlying the transient outward current (Ito), as the transcript most robustly correlating with HEY2 expression (β=+1.47; P=2×10-34). Transcript abundance of Hey2 and the Ito subunits Kcnip2 and Kcnd2, assessed by quantitative reverse transcription-polymerase chain reaction, was higher in subepicardium versus subendocardium in both left and right ventricles, with lower levels in Hey2+/- mice compared with wild type. Surface ECG measurements showed less prominent J waves in Hey2+/- mice compared with wild-type. In wild-type mice, patch-clamp electrophysiological studies on cardiomyocytes from right ventricle demonstrated a shorter action potential duration and a lower Vmax in subepicardium compared with subendocardium cardiomyocytes, which was paralleled by a higher Ito and a lower sodium current (INa) density in subepicardium versus subendocardium. These transmural differences were diminished in Hey2+/- mice because of changes in subepicardial cardiomyocytes. This study uncovers a role of HEY2 in the normal transmural electrophysiological gradient in the ventricle and provides compelling evidence that genetic variation at 6q22.31 (rs9388451) is associated with Brugada syndrome through a HEY2-dependent alteration of ion channel expression across the cardiac ventricular wall.

SSGA and MSGA: two seed-growing algorithms for constructing collaborative subnetworks

The establishment of a collaborative network of transcription factors (TFs) followed by decomposition and then construction of subnetworks is an effective way to obtain sets of collaborative TFs; each set controls a biological process or a complex trait. We previously developed eight gene association methods for genome-wide coexpression analysis between each TF and all other genomic genes and then constructing collaborative networks of TFs but only one algorithm, called Triple-Link Algorithm, for building collaborative subnetworks. In this study, we developed two more algorithms, Single Seed-Growing Algorithm (SSGA) and Multi-Seed Growing Algorithm (MSGA), for building collaborative subnetworks of TFs by identifying the fully-linked triple-node seeds from a decomposed collaborative network and then growing them into subnetworks with two different strategies. The subnetworks built from the three algorithms described above were comparatively appraised in terms of both functional cohesion and intra-subnetwork association strengths versus inter-subnetwork association strengths. We concluded that SSGA and MSGA, which performed more systemic comparisons and analyses of edge weights and network connectivity during subnetwork construction processes, yielded more functional and cohesive subnetworks than Triple-Link Algorithm. Together, these three algorithms provide alternate approaches for acquiring subnetworks of collaborative TFs. We also presented a framework to outline how to use these three algorithms to obtain collaborative TF sets governing biological processes or complex traits.