scholarly journals Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data

2019 ◽  
Author(s):  
Amit Blumberg ◽  
Yixin Zhao ◽  
Yi-Fei Huang ◽  
Noah Dukler ◽  
Edward J. Rice ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Rna Splicing ◽  
Structural Equation ◽  
Rna Stability ◽  
Estimation Method ◽  
Equation Model ◽  
Rna Seq ◽  
Simple Method ◽  
Systematic Analysis ◽  
Genome Wide

AbstractThe rate at which RNA molecules decay is a key determinant of cellular RNA concentrations, yet current approaches for measuring RNA half-lives are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On and sequencing (PRO-seq) and RNA sequencing (RNA-seq). Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding, DNA methylation, and G+C-richness are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1-binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations.

scholarly journals Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Amit Blumberg ◽  
Yixin Zhao ◽  
Yi-Fei Huang ◽  
Noah Dukler ◽  
Edward J. Rice ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Structural Equation ◽  
Dynamic Equilibrium ◽  
Rna Stability ◽  
Estimation Method ◽  
Decay Rates ◽  
Rna Decay ◽  
Rna Seq ◽  
Simple Method ◽  
Genome Wide

Abstract Background The concentrations of distinct types of RNA in cells result from a dynamic equilibrium between RNA synthesis and decay. Despite the critical importance of RNA decay rates, current approaches for measuring them are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here, we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On sequencing (PRO-seq) and RNA sequencing (RNA-seq). Results Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding and DNA methylation are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1 binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability. Conclusion We introduce an approach for estimating the relative half-lives of individual RNAs. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations.

scholarly journals Distinct regulation of hippocampal neuroplasticity and ciliary genes by corticosteroid receptors

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Karen R. Mifsud ◽  
Clare L. M. Kennedy ◽  
Silvia Salatino ◽  
Eshita Sharma ◽  
Emily M. Price ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Glucocorticoid Receptors ◽  
Acute Stress ◽  
Circadian Variation ◽  
Rna Seq ◽  
Physiological Regulation ◽  
Behavioural Adaptation ◽  
Neuronal Progenitor ◽  
Genome Wide ◽  
Transcriptional Changes

AbstractGlucocorticoid hormones (GCs) — acting through hippocampal mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) — are critical to physiological regulation and behavioural adaptation. We conducted genome-wide MR and GR ChIP-seq and Ribo-Zero RNA-seq studies on rat hippocampus to elucidate MR- and GR-regulated genes under circadian variation or acute stress. In a subset of genes, these physiological conditions resulted in enhanced MR and/or GR binding to DNA sequences and associated transcriptional changes. Binding of MR at a substantial number of sites however remained unchanged. MR and GR binding occur at overlapping as well as distinct loci. Moreover, although the GC response element (GRE) was the predominant motif, the transcription factor recognition site composition within MR and GR binding peaks show marked differences. Pathway analysis uncovered that MR and GR regulate a substantial number of genes involved in synaptic/neuro-plasticity, cell morphology and development, behavior, and neuropsychiatric disorders. We find that MR, not GR, is the predominant receptor binding to >50 ciliary genes; and that MR function is linked to neuronal differentiation and ciliogenesis in human fetal neuronal progenitor cells. These results show that hippocampal MRs and GRs constitutively and dynamically regulate genomic activities underpinning neuronal plasticity and behavioral adaptation to changing environments.

scholarly journals Empirical Analysis in the Relationship Between the Consumption and Economic Growth Based on the Structural Equation Model

2016 ◽  
Vol 4 (5) ◽  
pp. 419-427
Author(s):  
Erxin Zhang ◽  
Wancai Yang
Keyword(s):  
Economic Growth ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Equation Model ◽  
Positive Effects ◽  
Structure Equation Model ◽  
The Relationship ◽  
Maximum Likelihood Estimation Method

AbstractThis paper constructs the relationship between consumption and economic growth by a structure equation model and uses the provincial panel data of 29 provinces (municipalities, autonomous regions) from 1992 to 2010 in China, using maximum likelihood estimation method to analyze empirically the relationship between the consumption and economic growth in China. The result shows that the path coefficients between consumptions and economic growth are all positive, that suggests the consumption has significant positive effects on the economic growth. Also in this paper, it gives a new try to use a structural equation model to research the relationship between consumption and economic growth.

Heritability and GWAS Analyses of Acne in Australian Adolescent Twins

2017 ◽  
Vol 20 (6) ◽  
pp. 541-549 ◽  
Author(s):  
Angela Mina-Vargas ◽  
Lucía Colodro-Conde ◽  
Katrina Grasby ◽  
Gu Zhu ◽  
Scott Gordon ◽  
...  
Keyword(s):  
Structural Equation ◽  
Genome Wide Association Study ◽  
Acne Vulgaris ◽  
Monozygotic Twins ◽  
Twin Studies ◽  
Equation Model ◽  
Genome Wide ◽  
A Genome ◽  
Parsimonious Model ◽  
Three Body

Acne vulgaris is a skin disease with a multifactorial and complex pathology. While several twin studies have estimated that acne has a heritability of up to 80%, the genomic elements responsible for the origin and pathology of acne are still undiscovered. Here we performed a twin-based structural equation model, using available data on acne severity for an Australian sample of 4,491 twins and their siblings aged from 10 to 24. This study extends by a factor of 3 an earlier analysis of the genetic factors of acne. Acne severity was rated by nurses on a 4-point scale (1 = absent to 4 = severe) on up to three body sites (face, back, chest) and on up to three occasions (age 12, 14, and 16). The phenotype that we analyzed was the most severe rating at any site or age. The polychoric correlation for monozygotic twins was higher (rMZ = 0.86, 95% CI [0.81, 0.90]) than for dizygotic twins (rDZ = 0.42, 95% CI [0.35, 0.47]). A model that includes additive genetic effects and unique environmental effects was the most parsimonious model to explain the genetic variance of acne severity, and the estimated heritability was 0.85 (95% CI [0.82, 0.87]). We then conducted a genome-wide analysis including an additional 271 siblings — for a total of 4,762 individuals. A genome-wide association study (GWAS) scan did not detect loci associated with the severity of acne at the threshold of 5E-08 but suggestive association was found for three SNPs: rs10515088 locus 5q13.1 (p = 3.9E-07), rs12738078 locus 1p35.5 (p = 6.7E-07), and rs117943429 locus 18q21.2 (p = 9.1E-07). The 5q13.1 locus is close to PIK3R1, a gene that has a potential regulatory effect on sebocyte differentiation.

scholarly journals DeeReCT-TSS: A novel meta-learning-based method annotates TSS in multiple cell types based on DNA sequences and RNA-seq data

2021 ◽  
Author(s):  
Juexiao Zhou ◽  
Bin Zhang ◽  
Haoyang Li ◽  
Longxi Zhou ◽  
Zhongxiao Li ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Cell Types ◽  
Rna Seq ◽  
Sources Of Information ◽  
Genome Wide ◽  
A Genome ◽  
Meta Learning ◽  
Multiple Cell ◽  
Different Cell Types ◽  
Genome Scale

The accurate annotation of TSSs and their usage is critical for the mechanistic understanding of gene regulation under different biological contexts. To fulfill this, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner. Various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these tools have drastic false positive predictions when applied on the genome-scale. Here, we present DeeReCT-TSS, a deep-learning-based method that is capable of TSSs identification across the whole genome based on DNA sequences and conventional RNA-seq data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous transcription start site (TSS) annotation on 10 cell types, which enables the identification of cell-type-specific TSS. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets from the ENCODE project by correlating our predicted TSSs with experimentally defined TSS chromatin states.

scholarly journals Eksplorasi Keterkaitan antara Citra Destinasi, Personalitas Destinasi dan Niat Berkunjung Kembali ke Destinasi Wisata

2019 ◽  
Vol 7 (2) ◽  
pp. 105
Author(s):  
Heri Setiawan ◽  
Jusmawi Bustan ◽  
Abd. Hamid ◽  
Ummasyroh Ummasyroh
Keyword(s):  
Maximum Likelihood ◽  
Linear Relationship ◽  
Structural Equation ◽  
Estimation Method ◽  
Equation Model ◽  
Destination Image ◽  
Ml Estimation ◽  
Tourist Destinations ◽  
Tourism Destinations ◽  
The Relationship

Most countries try to develop tourism destinations with a variety of strategies to be able to compete with other destinations. This study is designed to explore the relationship between destination image, destination personality, and intention to re-visit tourists to tourism destinations. The approach used in this study is a quantitative approach to the design of causality research. The research sample is domestic tourists who have visited tourist destinations in Palembang such as Benteng Kuto Besak, Jaka Baring Sport City, Kemaro Island, Kambang Iwak Park, Punti Kayu Park, Siguntang Park, Taman Purbakala Sriwijaya totaling 192 respondents. The structural equation model is used to test the model developed using the maximum likelihood (ML) estimation method using AMOS 22.0. The results of the study explained that there is a linear relationship between destination images and destination personalities. There is no linear relationship between the destination images with the intention to visiting again. Then, there is a linear relationship between personalities of the destination with the intention of visiting again.

scholarly journals Comprehensive network analysis reveals alternative splicing-related lncRNAs in hepatocellular carcinoma

2019 ◽  
Author(s):  
Junqing Wang ◽  
Yixin Chen ◽  
Keli Xu ◽  
Yin-yuan Mo ◽  
Yunyun Zhou
Keyword(s):  
Hepatocellular Carcinoma ◽  
Alternative Splicing ◽  
Rna Splicing ◽  
Normal Liver ◽  
Splicing Factors ◽  
Primary Concern ◽  
Rna Seq ◽  
Genome Wide ◽  
Tumorigenesis And Progression ◽  
Extensive Collection

AbstractA number of recent studies have highlighted the findings that certain lncRNAs are associated with alternative splicing (AS) in tumorigenesis and progression. Although existing work showed the importance of linking certain misregulations of RNA splicing with lncRNAs, a primary concern is the lack of genome-wide comprehensive analysis for their associations.We analyzed an extensive collection of RNA-seq data, quantified 198,619 isoform expressions, and found systematic isoform usage changes between hepatocellular carcinoma (HCC) and normal liver tissue. We identified a total of 1375 splicing switched isoforms and further analyzed their biological functions.To predict which lncRNAs are associated with these AS genes, we integrated the co-expression networks and epigenetic interaction networks collected from text mining and database searching, linking lncRNA modulators such as splicing factors, transcript factors, and miRNAs with their targeted AS genes in HCC. To model the heterogeneous networks in a single framework, we developed a multi-graphic random walk (RWMG) network method to prioritize the lncRNAs associated with AS in HCC. RWMG showed a good performace evaluated by ROC curve based on cross-validation and bootstrapping strategy.As a summary, we identified 31 AS-related lncRNAs including MALAT1 and HOXA11-AS, which have been reported before, as well as some novel lncRNAs such as DNM1P35, HAND2-AS1, and DLX6-AS1. Survival analysis further confirmed the clinical significance of identified lncRNAs.

scholarly journals Metabolic labeling of RNAs uncovers hidden features and dynamics of the Arabidopsis thaliana transcriptome

2019 ◽  
Author(s):  
Emese Xochitl Szabo ◽  
Philipp Reichert ◽  
Marie-Kristin Lehniger ◽  
Marilena Ohmer ◽  
Marcella de Francisco Amorim ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Transcriptome Analysis ◽  
Rna Processing ◽  
Rna Synthesis ◽  
Rna Stability ◽  
Metabolic Labeling ◽  
Rna Seq ◽  
Genome Wide ◽  
Stability Measurement ◽  
Chemical Inhibition

AbstractTranscriptome analysis by RNA sequencing (RNA-seq) has become an indispensable core research tool in modern plant biology. Virtually all RNA-seq studies provide a snapshot of the steady-state transcriptome, which contains valuable information about RNA populations at a given time, but lacks information about the dynamics of RNA synthesis and degradation. Only a few specialized sequencing techniques, such as global run-on sequencing (GRO-seq), have been applied in plants and provide information about RNA synthesis rates. Here, we demonstrate that RNA labeling with a modified, non-toxic uridine analog, 5-ethynyl uridine (5-EU), in Arabidopsis thaliana seedlings provides insight into the dynamic nature of a plant transcriptome. Pulse-labeling with 5-EU allowed the detection and analysis of nascent and unstable RNAs, of RNA processing intermediates generated by splicing, and of chloroplast RNAs. We also conducted pulse-chase experiments with 5-EU, which allowed us to determine RNA stabilities without the need for chemical inhibition of transcription using compounds such as actinomycin and cordycepin. Genome-wide analysis of RNA stabilities by 5-EU pulse-chase experiments revealed that this inhibitor-free RNA stability measurement results in RNA half-lives much shorter than those reported after chemical inhibition of transcription. In summary, our results show that the Arabidopsis nascent transcriptome contains unstable RNAs and RNA processing intermediates, and suggest that half-lives of plant RNAs are largely overestimated. Our results lay the ground for an easy and affordable nascent transcriptome analysis and inhibitor-free analysis of RNA stabilities in plants.

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