scholarly journals Discovering and Constructing ceRNA-miRNA-Target Gene Regulatory Networks during Anther Development in Maize

2019 ◽  
Vol 20 (14) ◽  
pp. 3480 ◽  
Author(s):  
Ziwen Li ◽  
Xueli An ◽  
Taotao Zhu ◽  
Tingwei Yan ◽  
Suowei Wu ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Gene ◽  
Target Genes ◽  
Anther Development ◽  
Small Rna Sequencing ◽  
Mirna Target Gene ◽  
Gene Pairs ◽  
Gene Regulatory

The “competing endogenous RNA (ceRNA) hypothesis” has recently been proposed for a new type of gene regulatory model in many organisms. Anther development is a crucial biological process in plant reproduction, and its gene regulatory network (GRN) has been gradually revealed during the past two decades. However, it is still unknown whether ceRNAs contribute to anther development and sexual reproduction in plants. We performed RNA and small RNA sequencing of anther tissues sampled at three developmental stages in two maize lines. A total of 28,233 stably transcribed loci, 61 known and 51 potentially novel microRNAs (miRNAs) were identified from the transcriptomes. Predicted ceRNAs and target genes were found to conserve in sequences of recognition sites where their corresponding miRNAs bound. We then reconstructed 79 ceRNA-miRNA-target gene regulatory networks consisting of 51 known miRNAs, 28 potentially novel miRNAs, 619 ceRNA-miRNA pairs, and 869 miRNA-target gene pairs. More than half of the regulation pairs showed significant negative correlations at transcriptional levels. Several well-studied miRNA-target gene pairs associated with plant flower development were located in some networks, including miR156-SPL, miR159-MYB, miR160-ARF, miR164-NAC, miR172-AP2, and miR319-TCP pairs. Six target genes in the networks were found to be orthologs of functionally confirmed genes participating in anther development in plants. Our results provide an insight that the ceRNA-miRNA-target gene regulatory networks likely contribute to anther development in maize. Further functional studies on a number of ceRNAs, miRNAs, and target genes will facilitate our deep understanding on mechanisms of anther development and sexual plants reproduction.

scholarly journals DNA methylation and gene expression profiles to identify childhood atopic asthma associated genes

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rui Chen ◽  
Li-Zhen Piao ◽  
Ling Liu ◽  
Xiao-Fei Zhang
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Mirna Target ◽  
Target Gene ◽  
Atopic Asthma ◽  
Mirna Target Gene ◽  
Kegg Pathways ◽  
Gene Regulatory

Abstract Background Asthma is a chronic inflammatory disorder of the airways involving many different factors. This study aimed to screen for the critical genes using DNA methylation/CpGs and miRNAs involved in childhood atopic asthma. Methods DNA methylation and gene expression data (Access Numbers GSE40732 and GSE40576) were downloaded from the Gene Expression Omnibus database. Each set contains 194 peripheral blood mononuclear cell (PBMC) samples of 97 children with atopic asthma and 97 control children. Differentially expressed genes (DEGs) with DNA methylation changes were identified. Pearson correlation analysis was used to select genes with an opposite direction of expression and differences in methylation levels, and then Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Protein–protein interaction network and miRNA–target gene regulatory networks were then constructed. Finally, important genes related to asthma were screened. Results A total of 130 critical DEGs with DNA methylation changes were screened from children with atopic asthma and compared with control samples from healthy children. GO and KEGG pathway enrichment analysis found that critical genes were primarily related to 24 GO terms and 10 KEGG pathways. In the miRNA–target gene regulatory networks, 9 KEGG pathways were identified. Analysis of the miRNA–target gene network noted an overlapping KEGG signaling pathway, hsa04060: cytokine-cytokine receptor interaction, in which the gene CCL2, directly related to asthma, was involved. This gene is targeted by eight asthma related miRNAs (hsa-miR-206, hsa-miR-19a, hsa-miR-9,hsa-miR-22, hsa-miR-33b, hsa-miR-122, hsa-miR-1, and hsa-miR-23b). The genes IL2RG and CCl4 were also involved in this pathway. Conclusions The present study provides a novel insight into the underlying molecular mechanism of childhood atopic asthma.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals Integrated Analysis of MicroRNA (miRNA) and mRNA Profiles Reveals Reduced Correlation between MicroRNA and Target Gene in Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xingsong Li ◽  
Xiaokang Yu ◽  
Yuting He ◽  
Yuhuan Meng ◽  
Jinsheng Liang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Mirna Target ◽  
Target Gene ◽  
Target Genes ◽  
Integrated Analysis ◽  
Cancer Type ◽  
Gene Pairs ◽  
Cancer Types

Background. Accumulating evidences demonstrated that microRNA-target gene pairs were closely related to tumorigenesis and development. However, the correlation between miRNA and target gene was insufficiently understood, especially its changes between tumor and normal tissues. Objectives. The aim of this study was to evaluate the changes of correlation of miRNAs-target pairs between normal and tumor. Materials and Methods. 5680 mRNA and 5740 miRNA expression profiles of 11 major human cancers were downloaded from the Cancer Genome Atlas (TCGA). The 11 cancer types were bladder urothelial carcinoma, breast invasive carcinoma, head and neck squamous cell carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, stomach adenocarcinoma, and thyroid carcinoma. For each cancer type, we firstly obtained differentially expressed miRNAs (DEMs) and genes (DEGs) in tumor and then acquired critical miRNA-target gene pairs by combining DEMs, DEGs and two experimentally validated miRNA-target interaction databases, miRTarBase and miRecords. We collected samples with both miRNA and mRNA expression values and performed a correlation analysis by Pearson method for miRNA-target pairs in normal and tumor, respectively. Results. We totally got 4743 critical miRNA-target pairs across 11 cancer types, and 4572 of them showed weaker correlation in tumor than in normal. The average correlation coefficients of miRNA-target pairs were different greatly between normal (-0.38 ~ -0.61) and tumor (-0.04 ~ -0.26) for 11 cancer type. The pan-cancer network, which consisted of 108 edges connecting 35 miRNAs and 89 target genes, showed the interactions of pairs appeared in multicancers. Conclusions. This comprehensive analysis revealed that correlation between miRNAs and target genes was greatly reduced in tumor and these critical pairs we got were involved in cellular adhesion, proliferation, and migration. Our research could provide opportunities for investigating cancer molecular regulatory mechanism and seeking therapeutic targets.

Study on the Function of miRNA-155 Target Using Bioinformatics Methods

2013 ◽  
Vol 709 ◽  
pp. 858-861
Author(s):  
De Ming Han ◽  
Zi Jun Shen ◽  
Li Hui Zhao
Keyword(s):  
Protein Expression ◽  
Mirna Target ◽  
Target Gene ◽  
Target Genes ◽  
Gene Prediction ◽  
Diagnosis And Treatment ◽  
Transcriptional Level ◽  
Mirna Target Gene ◽  
Non Coding Rnas

MicroRNAs are small non-coding RNAs that act at the post-transcriptional level, regulating protein expression by repressing translation or destabilizing mRNA target. We searched information about miR-155 in miRBase. Target genes of miR-155 are predicted by four miRNA target gene prediction softwares. The result shows that miR-155 was involved in proliferation, differentiation and apoptosis. These results can contribute to further study on the role of microRNA in diagnosis and treatment of cancer.

MicroRNA profiling reveals dysregulated microRNAs and their target gene regulatory networks in cemento-ossifying fibroma

2017 ◽  
Vol 47 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Thaís dos Santos Fontes Pereira ◽  
João Artur Ricieri Brito ◽  
André Luiz Sena Guimarães ◽  
Carolina Cavaliéri Gomes ◽  
Júlio Cesar Tanos de Lacerda ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Gene ◽  
Ossifying Fibroma ◽  
Microrna Profiling ◽  
Gene Regulatory

scholarly journals AGENT: the Arabidopsis Gene Regulatory Network Tool for Exploring and Analyzing GRNs

2021 ◽  
Author(s):  
Vincent Lau ◽  
Rachel Woo ◽  
Bruno Pereira ◽  
Asher Pasha ◽  
Eddi Esteban ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Gene Network ◽  
Regulatory Networks ◽  
Target Genes ◽  
Ad Hoc ◽  
Arabidopsis Gene ◽  
Nitrate Signaling ◽  
Multi Level ◽  
Gene Regulatory

AbstractGene regulatory networks (GRNs) are complex networks that capture multi-level regulatory events between one or more regulatory macromolecules, such as transcription factors (TFs), and their target genes. Advancements in screening technologies such as enhanced yeast-one-hybrid screens have allowed for high throughput determination of GRNs. However, visualization of GRNs in Arabidopsis has been limited to ad hoc networks and are not interactive. Here, we describe the Arabidopsis GEne Network Tool (AGENT) that houses curated GRNs and provides tools to visualize and explore them. AGENT features include expression overlays, subnetwork motif scanning, and network analysis. We show how to use AGENT’s multiple built-in tools to identify key genes that are involved in flowering and seed development along with identifying temporal multi-TF control of a key transporter in nitrate signaling. AGENT can be accessed at https://bar.utoronto.ca/AGENT.

scholarly journals Association of Extracellular Signal-Regulated Kinase Genes With Myopia: A Longitudinal Study of Chinese Children

2021 ◽  
Vol 12 ◽  
Author(s):  
Haishao Xiao ◽  
Shudan Lin ◽  
Dandan Jiang ◽  
Yaoyao Lin ◽  
Linjie Liu ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Gene Network ◽  
Mirna Target ◽  
Target Gene ◽  
Target Genes ◽  
Chinese Children ◽  
Indirect Interaction ◽  
Mirna Target Gene ◽  
Extracellular Signal Regulated Kinase ◽  
Extracellular Signal

Graphical AbstractThe genes in the miRNA-target gene network represent the intersection of the target genes and the genes from String that had direct or indirect interaction relationships with significant genes.

scholarly journals Evolution of Mendelian Dominance in Gene Regulatory Networks Associated With Phenotypic Robustness

2021 ◽  
Author(s):  
Kenji Okubo ◽  
Kunihiko Kaneko
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Classical Case ◽  
Mendelian Inheritance ◽  
Degree Of Dominance ◽  
Gene Expression Dynamics ◽  
Phenotypic Robustness ◽  
Robustness To Noise ◽  
Gene Regulatory

Abstract Background: Mendelian inheritance is a fundamental law of genetics. Considering two alleles in a diploid, a phenotype of a heterotype is dominated by a particular homotype according to the law of dominance. This picture is usually based on simple genotype-phenotype mapping in which one gene regulates one phenotype. However, in reality, some interactions between genes can result in deviation from Mendelian dominance. Result: Here, by using the numerical evolution of diploid gene regulatory networks (GRNs), we discuss whether Mendelian dominance evolves beyond the classical case of one-to-one genotype-phenotype mapping. We examine whether complex genotype-phenotype mapping can achieve Mendelian dominance through the evolution of the GRN with interacting genes. Specifically, we extend the GRN model to a diploid case, in which two GRN matrices are added to give gene expression dynamics, and simulate evolution with meiosis and recombination. Our results reveal that Mendelian dominance evolves even under complex genotype-phenotype mapping. This dominance is achieved via a group of genotypes that differ from each other but have a common phenotype given by the expression of target genes. Calculating the degree of dominance shows that it increases through the evolution, correlating closely with the decrease in phenotypic fluctuations and the increase in robustness to initial noise. This evolution of Mendelian dominance is associated with phenotypic robustness against meiosis-induced genome mixing, whereas sexual recombination arising from the mixing of chromosomes from the parents further enhances dominance and robustness. Owing to this dominance, the robustness to genetic differences increases, while the optimal fitness is sustained up to a large difference between the two genomes. Conclusion: Mendelian dominance is achieved by groups of genotypes that are associated with the increase in phenotypic robustness to noise.

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