scholarly journals BaRTv2: A highly resolved barley reference transcriptome for accurate transcript-specific RNA-seq quantification

2021 ◽  
Author(s):  
Max Coulter ◽  
Juan Carlos Entizne ◽  
Wenbin Guo ◽  
Micha Bayer ◽  
Ronja Wonneberger ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Spring Barley ◽  
Transcript Level ◽  
Rna Seq ◽  
Reference Transcriptome ◽  
Reference Transcript ◽  
Precise Quantification ◽  
Transcript Diversity ◽  
Post Transcriptional Regulation ◽  
Splice Junctions

Accurate characterization of splice junctions as well as transcription start and end sites in reference transcriptomes allows precise quantification of transcripts from RNA-seq data and enable detailed investigations of transcriptional and post-transcriptional regulation. Using novel computational methods and a combination of PacBio Iso-seq and Illumina short read sequences from 20 diverse tissues and conditions, we generated a comprehensive and highly resolved barley reference transcript dataset (RTD) from the European 2-row spring barley cultivar Barke (BaRTv2.18). Stringent and thorough filtering was carried out to maintain the quality and accuracy of the splice junctions and transcript start and end sites. BaRTv2.18 shows increased transcript diversity and completeness compared to an earlier version, BaRTv1.0. The accuracy of transcript level quantification, splice junctions and transcript start and end sites has been validated extensively using parallel technologies and analysis, including high resolution RT PCR and 5 prime RACE. BaRTv2.18 contains 39,434 genes and 148,260 transcripts, representing the most comprehensive and resolved reference transcriptome in barley to date. It provides an important and high-quality resource for advanced transcriptomic analyses, including both transcriptional and post-transcriptional regulation, with exceptional resolution and precision.

scholarly journals Erratum: Analysis of intronic and exonic reads in RNA-seq data characterizes transcriptional and post-transcriptional regulation

2016 ◽  
Vol 34 (2) ◽  
pp. 210-210 ◽  
Author(s):  
Dimos Gaidatzis ◽  
Lukas Burger ◽  
Maria Florescu ◽  
Michael B Stadler
Keyword(s):  
Transcriptional Regulation ◽  
Rna Seq ◽  
Post Transcriptional Regulation

scholarly journals RNA-seq reveals post-transcriptional regulation ofDrosophilainsulin-like peptidedilp8and the neuropeptide-like precursorNplp2by the exoribonuclease Pacman/XRN1

2015 ◽  
Vol 44 (1) ◽  
pp. 267-280 ◽  
Author(s):  
Christopher I. Jones ◽  
Amy L. Pashler ◽  
Benjamin P. Towler ◽  
Sophie R. Robinson ◽  
Sarah F. Newbury
Keyword(s):  
Transcriptional Regulation ◽  
Rna Seq ◽  
Post Transcriptional Regulation

scholarly journals Analysis of intronic and exonic reads in RNA-seq data characterizes transcriptional and post-transcriptional regulation

2015 ◽  
Vol 33 (7) ◽  
pp. 722-729 ◽  
Author(s):  
Dimos Gaidatzis ◽  
Lukas Burger ◽  
Maria Florescu ◽  
Michael B Stadler
Keyword(s):  
Transcriptional Regulation ◽  
Rna Seq ◽  
Post Transcriptional Regulation

scholarly journals Assessment of mapping strategies for determining the 5□-end of mRNAs and long-noncoding RNAs with short read sequences

2020 ◽  
Author(s):  
Shuhei Noguchi ◽  
Hideya Kawaji ◽  
Takeya Kasukawa
Keyword(s):  
Genome Mapping ◽  
Rna Seq ◽  
Reference Transcriptome ◽  
Transcription Start Sites ◽  
Mapping Software ◽  
Genome Wide ◽  
Biological Interpretation ◽  
Exon Junctions ◽  
Cap Analysis ◽  
Splice Junctions

AbstractBackgroundGenome mapping is an essential step in data processing for transcriptome analysis, and many previous studies have evaluated various methods and strategies for mapping RNA-seq data. Cap Analysis of Gene Expression (CAGE) is a sequencing-based protocol particularly designed to capture the 5□-ends of transcripts for quantitatively measuring the expression levels of transcription start sites genome-wide. Because CAGE analysis can also predict the activities of promoters and enhancers, this protocol has been an essential tool in studies of transcriptional regulation. Typically, the same mapping software is used to align both RNA-seq data and CAGE reads to a reference genome, but which mapping software and options are most appropriate for mapping the 5□-end sequence reads obtained through CAGE has not previously been evaluated systematically.ResultsHere we assessed various strategies for aligning CAGE reads, particularly ∼50-bp sequences, with the human genome by using the HISAT2, LAST, and STAR programs both with and without a reference transcriptome. One of the major inconsistencies among the tested strategies involves alignments to pseudogenes and parent genes: some of the strategies prioritized alignments with pseudogenes even when the read could be aligned with coding genes with fewer mismatches. Another inconsistency concerned the detection of exon-exon junctions. These preferences depended on the program applied and whether a reference transcriptome was included. Overall, the choice of strategy yielded different mapping results for approximately 2% of all promoters.ConclusionsAlthough the various alignment strategies produced very similar results overall, we noted several important and measurable differences. In particular, using the reference transcriptome in STAR yielded alignments with the fewest mismatches. In addition, the inconsistencies among the strategies were especially noticeable regarding alignments to pseudogenes and novel splice junctions. Our results indicate that the choice of alignment strategy is important because it might affect the biological interpretation of the data.

scholarly journals Genetic variants associated mRNA stability in lung

2021 ◽  
Author(s):  
Jian-Rong Li ◽  
Mabel Tang ◽  
Yafang Li ◽  
Christopher I Amos ◽  
Chao Cheng
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Mrna Stability ◽  
Genetic Variants ◽  
Binding Sites ◽  
Molecular Mechanisms ◽  
Rna Binding ◽  
Rna Seq ◽  
Post Transcriptional Regulation ◽  
Gene Expression Levels

AbstractExpression quantitative trait loci (eQTLs) analyses have been widely used to identify genetic variants associated with gene expression levels to understand what molecular mechanisms underlie genetic traits. The resultant eQTLs might affect the expression of associated genes through transcriptional or post-transcriptional regulation. In this study, we attempt to distinguish these two types of regulation by identifying genetic variants associated with mRNA stability of genes (stQTLs). Specifically, we computationally inferred mRNA stability of genes based on RNA-seq data and performed association analysis to identify stQTLs. Using the Genotype-Tissue Expression (GTEx) lung RNA-Seq data, we identified a total of 142,801 stQTLs for 3,942 genes and 186,132 eQTLs for 4,751 genes from 15,122,700 genetic variants for 13,476 genes, respectively. Interesting, our results indicated that stQTLs were enriched in the CDS and 3’UTR regions, while eQTLs are enriched in the CDS, 3’UTR, 5’UTR, and upstream regions. We also found that stQTLs are more likely than eQTLs to overlap with RNA binding protein (RBP) and microRNA (miRNA) binding sites. Our analyses demonstrate that simultaneous identification of stQTLs and eQTLs can provide more mechanistic insight on the association between genetic variants and gene expression levels.Author SummaryIn the past decade, many studies have identified genetic variants associated with gene expression level (eQTLs) in different phenotypes, including tissues and diseases. Gene expression is the result of cooperation between transcriptional regulation, such as transcriptional activity, and post-transcriptional regulation, such as mRNA stability. Here, we present a computational framework that take advantage of recently developed methods to estimate mRNA stability from RNA-Seq, which is widely used to estimate gene expression, and then to identify genetic variants associated with mRNA stability (stQTLs) in lung tissue. Compared to eQTLs, we found that genetic variants that affects mRNA stability are more significantly located in the CDS and 3’UTR regions, which are known to interact with RNA-binding proteins (RBPs) or microRNAs to regulate stability. In addition, stQTLs are significantly more likely to overlap the binding sites of RBPs. We show that the six RBPs that most significantly bind to stQTLs are all known to regulate mRNA stability. This pipeline of simultaneously identifying eQTLs and stQTLs using only RNA-Seq data can provide higher resolution than traditional eQTLs study to better understand the molecular mechanisms of genetic variants on the regulation of gene expression.

Abstract 401: Functional Impact Of Rbfox1c In Cardiac Pathological Remodeling Through Targeted Mrna Stability Regulation

2021 ◽  
Vol 129 (Suppl_1) ◽  
Author(s):  
Chen Gao ◽  
Zhaojun Xiong ◽  
Jianfang Liu ◽  
Nancy Cao ◽  
Tomohiro Yokota ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Rna Splicing ◽  
Cardiac Fibrosis ◽  
Rna Binding ◽  
Rna Degradation ◽  
Mouse Heart ◽  
Rna Seq ◽  
Intact Mouse ◽  
Post Transcriptional Regulation

Post-transcriptional regulation plays a key role in transcriptome reprogramming during cardiac pathogenesis. In previous studies, we have identified that cardiac enriched RNA-binding protein, RBFox1 plays key role in cardiac hypertrophy through mRNA alternative splicing regulation in nuclei. However, RBFox1 gene also generates a cytosolic isoform (RBFox1c), suggesting additional functions of post-transcriptional regulation in heart. In adult heart, RBFox1c mRNA constituted ~ 40% of total RBFox1 level but was significantly repressed in pressure-overloaded failing mouse heart. Using CRISPR-Cas9 technology, we have established an isoform specific RBFox1c-cKO mouse. At baseline inactivation of RBFox1c led to decreased cardiac function along with induction of cardiac fibrosis. RBFox1c-cKO mice also showed macrophages infiltration into myocardium post 7days MI. In contrast, restoration of RBFox1c expression in adult intact hearts significantly reduced cardiac fibrosis post stress. RNA-seq analyses in RBFox1c expressing cardiomyocytes showed that RBFox1c specifically suppressed the expression of pro-inflammatory genes. Secondly, CLIP-Seq analysis and targeted RNA-IP showed that RBFox1c could directly interact with inflammatory pathway mRNAs. These results suggested the inflammatory mRNAs are direct downstream targets regulated by RBFox1c. Using both in vitro cultured cardiomyocytes and intact mouse hearts, we demonstrated that expression of RBFox1c reduces pro-inflammatory mRNA expression at baseline and upon hypertrophy stimulation. Lastly, we characterized the interactome of RBFox1c through proteomic analysis and found RBFox1c specifically interacted with a component of the RNA NMD machinery-Upf1. RBFox1c interaction with Upf1 in cardiomyocytes was diminished upon hypertrophic stress. Furthermore, by inactivation of Upf1 via siRNA, we demonstrated that RBFox1c mediated repression of proinflammatory genes was Upf1 dependent.RBFox1 regulates cardiac transcriptome reprogramming in two post-transcriptional processes via distinct isoforms. While the RBFox1n regulates RNA splicing, the RBFox1c functions through targeted mRNA repression of proinflammatory genes by recruitment of Upf1 mediated RNA degradation.

43-OR: Post-transcriptional Regulation of Slc16a1 mRNA Is Essential for Maintaining Normal ß-Cell Function

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 43-OR
Author(s):  
DINA MOSTAFA ◽  
AKINORI TAKAHASHI ◽  
TADASHI YAMAMOTO
Keyword(s):  
Transcriptional Regulation ◽  
Cell Function ◽  
Post Transcriptional Regulation
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