P.1.003 Gene networks and blood biomarkers of methamphetamine-associated psychosis: a preliminary integrative RNA-Seq report

2016 ◽  
Vol 26 ◽  
pp. S4-S5
Author(s):  
M.S. Breen ◽  
A. Uhlmann ◽  
C. Nday ◽  
S. Glatt ◽  
A. Metsalpu ◽  
...  
Keyword(s):  
Gene Networks ◽  
Rna Seq ◽  
Blood Biomarkers

scholarly journals OsMYB80 Regulates Anther Development and Pollen Fertility by Targeting Multiple Biological Pathways

2020 ◽  
Vol 61 (5) ◽  
pp. 988-1004 ◽  
Author(s):  
Xiaoying Pan ◽  
Wei Yan ◽  
Zhenyi Chang ◽  
Yingchao Xu ◽  
Ming Luo ◽  
...  
Keyword(s):  
Pollen Development ◽  
Male Fertility ◽  
Gene Networks ◽  
Affinity Purification ◽  
Anther Development ◽  
Rna Seq ◽  
Male Sterile ◽  
New Information ◽  
Gel Shift Assay

Abstract Pollen development is critical to the reproductive success of flowering plants, but how it is regulated is not well understood. Here, we isolated two allelic male-sterile mutants of OsMYB80 and investigated how OsMYB80 regulates male fertility in rice. OsMYB80 was barely expressed in tissues other than anthers, where it initiated the expression during meiosis, reached the peak at the tetrad-releasing stage and then quickly declined afterward. The osmyb80 mutants exhibited premature tapetum cell death, lack of Ubisch bodies, no exine and microspore degeneration. To understand how OsMYB80 regulates anther development, RNA-seq analysis was conducted to identify genes differentially regulated by OsMYB80 in rice anthers. In addition, DNA affinity purification sequencing (DAP-seq) analysis was performed to identify DNA fragments interacting with OsMYB80 in vitro. Overlap of the genes identified by RNA-seq and DAP-seq revealed 188 genes that were differentially regulated by OsMYB80 and also carried an OsMYB80-interacting DNA element in the promoter. Ten of these promoter elements were randomly selected for gel shift assay and yeast one-hybrid assay, and all showed OsMYB80 binding. The 10 promoters also showed OsMYB80-dependent induction when co-expressed in rice protoplast. Functional annotation of the 188 genes suggested that OsMYB80 regulates male fertility by directly targeting multiple biological processes. The identification of these genes significantly enriched the gene networks governing anther development and provided much new information for the understanding of pollen development and male fertility.

scholarly journals Integrative genome-wide analysis reveals the role of WIP proteins in inhibition of growth and development

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Maria Victoria Gomez Roldan ◽  
Farhaj Izhaq ◽  
Marion Verdenaud ◽  
John Eleblu ◽  
Aimen Haraghi ◽  
...  
Keyword(s):  
Gene Networks ◽  
Growth Arrest ◽  
Reproductive Organs ◽  
Stress Signaling ◽  
Rna Seq ◽  
Genome Wide Analysis ◽  
Inhibition Of Growth ◽  
Genome Wide ◽  
Male Flowers

AbstractIn cucurbits, CmWIP1 is a master gene controlling sex determination. To bring new insight in the function of CmWIP1, we investigated two Arabidopsis WIP transcription factors, AtWIP1/TT1 and AtWIP2/NTT. Using an inducible system we showed that WIPs are powerful inhibitor of growth and inducer of cell death. Using ChIP-seq and RNA-seq we revealed that most of the up-regulated genes bound by WIPs display a W-box motif, associated with stress signaling. In contrast, the down-regulated genes contain a GAGA motif, a known target of polycomb repressive complex. To validate the role of WIP proteins in inhibition of growth, we expressed AtWIP1/TT1 in carpel primordia and obtained male flowers, mimicking CmWIP1 function in melon. Using other promoters, we further demonstrated that WIPs can trigger growth arrest of both vegetative and reproductive organs. Our data supports an evolutionary conserved role of WIPs in recruiting gene networks controlling growth and adaptation to stress.

scholarly journals Satellite Cell Depletion Disrupts Transcriptional Coordination and Muscle Adaptation to Exercise

Function ◽  
2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Davis A Englund ◽  
Vandré C Figueiredo ◽  
Cory M Dungan ◽  
Kevin A Murach ◽  
Bailey D Peck ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Satellite Cell ◽  
Satellite Cells ◽  
Gene Networks ◽  
Wheel Running ◽  
Skeletal Muscle Regeneration ◽  
Rna Seq ◽  
Muscle Adaptation ◽  
Hypertrophic Growth ◽  
Adaptation To Exercise

Abstract Satellite cells are required for postnatal development, skeletal muscle regeneration across the lifespan, and skeletal muscle hypertrophy prior to maturity. Our group has aimed to address whether satellite cells are required for hypertrophic growth in mature skeletal muscle. Here, we generated a comprehensive characterization and transcriptome-wide profiling of skeletal muscle during adaptation to exercise in the presence or absence of satellite cells in order to identify distinct phenotypes and gene networks influenced by satellite cell content. We administered vehicle or tamoxifen to adult Pax7-DTA mice and subjected them to progressive weighted wheel running (PoWeR). We then performed immunohistochemical analysis and whole-muscle RNA-seq of vehicle (SC+) and tamoxifen-treated (SC−) mice. Further, we performed single myonuclear RNA-seq to provide detailed information on how satellite cell fusion affects myonuclear transcription. We show that while skeletal muscle can mount a robust hypertrophic response to PoWeR in the absence of satellite cells, growth, and adaptation are ultimately blunted. Transcriptional profiling reveals several gene networks key to muscle adaptation are altered in the absence of satellite cells.

scholarly journals Comprehensive genomic profiling in diabetic nephropathy reveals the predominance of proinflammatory pathways

2013 ◽  
Vol 45 (16) ◽  
pp. 710-719 ◽  
Author(s):  
K. J. Kelly ◽  
Yunlong Liu ◽  
Jizhong Zhang ◽  
Chirayu Goswami ◽  
Hai Lin ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Systems Biology ◽  
Gene Networks ◽  
Inflammatory Cells ◽  
Rna Seq ◽  
Cycle Arrest ◽  
Comprehensive Genomic Profiling ◽  
Novel Therapeutic Strategies ◽  
Stage Renal Disease ◽  
End Stage

Despite advances in the treatment of diabetic nephropathy (DN), currently available therapies have not prevented the epidemic of progressive chronic kidney disease (CKD). The morbidity of CKD, and the inexorable increase in the prevalence of end-stage renal disease, demands more effective approaches to prevent and treat progressive CKD. We undertook next-generation sequencing in a rat model of diabetic nephropathy to study in depth the pathogenic alterations involved in DN with progressive CKD. We employed the obese, diabetic ZS rat, a model that develops diabetic nephropathy, characterized by progressive CKD, inflammation, and fibrosis, the hallmarks of human disease. We then used RNA-seq to examine the combined effects of renal cells and infiltrating inflammatory cells acting as a pathophysiological unit. The comprehensive systems biology analysis of progressive CKD revealed multiple interactions of altered genes that were integrated into morbid networks. These pathological gene assemblies lead to renal inflammation and promote apoptosis and cell cycle arrest in progressive CKD. Moreover, in what is clearly a major therapeutic challenge, multiple and redundant pathways were found to be linked to renal fibrosis, a major cause of kidney loss. We conclude that systems biology applied to progressive CKD in DN can be used to develop novel therapeutic strategies directed to restore critical anomalies in affected gene networks.

scholarly journals SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples

2014 ◽  
Vol 42 (15) ◽  
pp. e121-e121 ◽  
Author(s):  
Hari Krishna Yalamanchili ◽  
Zhaoyuan Li ◽  
Panwen Wang ◽  
Maria P. Wong ◽  
Jianfeng Yao ◽  
...  
Keyword(s):  
Sample Size ◽  
Gene Networks ◽  
Simulated Data ◽  
Exon Array ◽  
R Package ◽  
Mapk Signaling ◽  
Rna Seq ◽  
Gene Expressions ◽  
Exon Level ◽  
Splicing Isoforms

Abstract Conventionally, overall gene expressions from microarrays are used to infer gene networks, but it is challenging to account splicing isoforms. High-throughput RNA Sequencing has made splice variant profiling practical. However, its true merit in quantifying splicing isoforms and isoform-specific exon expressions is not well explored in inferring gene networks. This study demonstrates SpliceNet, a method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large dimensional trace. It goes beyond differentially expressed genes and infers splicing isoform network changes between normal and diseased samples. It eases the sample size bottleneck; evaluations on simulated data and lung cancer-specific ERBB2 and MAPK signaling pathways, with varying number of samples, evince the merit in handling high exon to sample size ratio datasets. Inferred network rewiring of well established Bcl-x and EGFR centered networks from lung adenocarcinoma expression data is in good agreement with literature. Gene level evaluations demonstrate a substantial performance of SpliceNet over canonical correlation analysis, a method that is currently applied to exon level RNA-Seq data. SpliceNet can also be applied to exon array data. SpliceNet is distributed as an R package available at http://www.jjwanglab.org/SpliceNet.

scholarly journals Transcriptome Analysis in Domesticated Species: Challenges and Strategies

2015 ◽  
Vol 9S4 ◽  
pp. BBI.S29334 ◽  
Author(s):  
Jessica P. Hekman ◽  
Jennifer L Johnson ◽  
Anna V. Kukekova
Keyword(s):  
Complex Traits ◽  
Gene Networks ◽  
Association Studies ◽  
Cultural Value ◽  
Genomic Research ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Rna Seq ◽  
Genome Wide ◽  
Genome Assemblies

Domesticated species occupy a special place in the human world due to their economic and cultural value. In the era of genomic research, domesticated species provide unique advantages for investigation of diseases and complex phenotypes. RNA sequencing, or RNA-seq, has recently emerged as a new approach for studying transcriptional activity of the whole genome, changing the focus from individual genes to gene networks. RNA-seq analysis in domesticated species may complement genome-wide association studies of complex traits with economic importance or direct relevance to biomedical research. However, RNA-seq studies are more challenging in domesticated species than in model organisms. These challenges are at least in part associated with the lack of quality genome assemblies for some domesticated species and the absence of genome assemblies for others. In this review, we discuss strategies for analyzing RNA-seq data, focusing particularly on questions and examples relevant to domesticated species.

scholarly journals Genomic Modules and Intramodular Network Convergency of Susceptibility and Resilience in Multimodeled Stress in Male Mice

2021 ◽  
Author(s):  
Jordan Marrocco ◽  
Salvatore G Caradonna ◽  
Tie-Yuan Zhang ◽  
Nicholas O'Toole ◽  
Mo-Jun Shen ◽  
...  
Keyword(s):  
Construct Validity ◽  
Gene Networks ◽  
Anxiety And Depression ◽  
Rna Seq ◽  
Data Set ◽  
Genomic Signatures ◽  
Medical Standards ◽  
Gene Coding ◽  
Chronic Social Defeat Stress ◽  
Response To Stress

The multifactorial etiology of stress-related disorders is a challenge in developing synchronized medical standards for treatment and diagnosis. It is largely unknown whether there exists molecular convergence in preclinical models of stress generated using disparate construct validity. Using RNA-sequencing (RNA-seq), we investigated the genomic signatures in the ventral hippocampus, which mostly regulates affective behavior, in mouse models that recapitulate the hallmarks of anxiety and depression. Chronic oral corticosterone (CORT), a model that causes a blunted endocrine response to stress, induced anxiety- and depression-like behavior in wildtype mice and mice heterozygous for the gene coding for brain-derived neurotrophic factor (BDNF) Val66Met, a variant associated with genetic susceptibility to stress. In a separate set of mice, chronic social defeat stress led to a susceptible or a resilient population, whose proportion was dependent on housing conditions, standard housing or enriched environment. A rank-rank-hypergeometric (RRHO) analysis of the RNA-seq data set across models demonstrated that in mice treated with CORT and susceptible mice raised in standard housing differentially expressed genes (DEGs) converged toward gene networks involved in similar biological functions. Weighted gene co-expression analysis generated 54 unique modules of interconnected gene hubs, two of which included a combination of all experimental groups and were significantly enriched in DEGs, whose function was consistent with that predicted in the RRHO GO analysis. This multimodel approach showed transcriptional synchrony between models of stress with hormonal, environmental or genetic construct validity shedding light on common genomic drivers that embody the multifaceted nature of stress-related disorders.

scholarly journals Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing

2020 ◽  
Author(s):  
Ruoyu Zhang ◽  
Gurinder S. Atwal ◽  
Wei Keat Lim
Keyword(s):  
Single Cell ◽  
Gene Networks ◽  
Immune Cell ◽  
Data Preprocessing ◽  
Rna Seq ◽  
Imputation Methods ◽  
Individual Gene ◽  
Gene Associations ◽  
Cell Modules ◽  
Noise Regularization

AbstractWith the rapid advancement of single-cell RNA-seq (scRNA-seq) technology, many data preprocessing methods have been proposed to address numerous systematic errors and technical variabilities inherent in this technology. While these methods have been demonstrated to be effective in recovering individual gene expression, the suitability to the inference of gene-gene associations and subsequent gene networks reconstruction have not been systemically investigated. In this study, we benchmarked five representative scRNA-seq normalization/imputation methods on human cell atlas bone marrow data with respect to their impact on inferred gene-gene associations. Our results suggested that a considerable amount of spurious correlations was introduced during the data preprocessing steps due to over-smoothing of the raw data. We proposed a model-agnostic noise regularization method that can effectively eliminate the correlation artifacts. The noise regularized gene-gene correlations were further used to reconstruct gene co-expression network and successfully revealed several known immune cell modules.

scholarly journals Integrative lncRNA landscape reveals lncRNA-coding gene networks in the secondary cell wall biosynthesis pathway of moso bamboo (Phyllostachys edulis)

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiongliang Wang ◽  
Yinguang Hou ◽  
Yu Wang ◽  
Hansheng Zhao
Keyword(s):  
Cell Wall ◽  
Gene Networks ◽  
Secondary Cell Wall ◽  
Gene Families ◽  
Molecular Study ◽  
Moso Bamboo ◽  
Rna Seq ◽  
Machine Learning Approach ◽  
Flavonoids Biosynthesis

Abstract Background LncRNAs are extensively involved in plant biological processes. However, the lack of a comprehensive lncRNA landscape in moso bamboo has hindered the molecular study of lncRNAs. Moreover, the role of lncRNAs in secondary cell wall (SCW) biosynthesis of moso bamboo is elusive. Results For comprehensively identifying lncRNA throughout moso bamboo genome, we collected 231 RNA-Seq datasets, 1 Iso-Seq dataset, and 1 full-length cDNA dataset. We used a machine learning approach to improve the pipeline of lncRNA identification and functional annotation based on previous studies and identified 37,009 lncRNAs in moso bamboo. Then, we established a network of potential lncRNA-coding gene for SCW biosynthesis and identified SCW-related lncRNAs. We also proposed that a mechanism exists in bamboo to direct phenylpropanoid intermediates to lignin or flavonoids biosynthesis through the PAL/4CL/C4H genes. In addition, we identified 4 flavonoids and 1 lignin-preferred genes in the PAL/4CL/C4H gene families, which gained implications in molecular breeding. Conclusions We provided a comprehensive landscape of lncRNAs in moso bamboo. Through analyses, we identified SCW-related lncRNAs and improved our understanding of lignin and flavonoids biosynthesis.

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