scholarly journals RiboPlotR: a Visualization Tool for Periodic Ribo-seq Reads

2021 ◽  
Author(s):  
Hsin-Yen Larry Wu ◽  
Polly Yingshan Hsu
Keyword(s):  
Mrna Translation ◽  
Regulatory Mechanisms ◽  
Untranslated Regions ◽  
Data Display ◽  
Rna Seq ◽  
Genome Wide ◽  
Non Coding Rnas ◽  
Splice Junctions ◽  
Small Orfs ◽  
Reading Frames

Abstract Background: Ribo-seq has revolutionized the study of genome-wide mRNA translation. High-quality Ribo-seq data display strong 3-nucleotide (nt) periodicity, which corresponds to translating ribosomes deciphering three nts at a time. While 3-nt periodicity has been widely used to study novel translation events such as upstream ORFs in 5’ untranslated regions and small ORFs in presumed non-coding RNAs, tools that allow the visualization of these events remain underdeveloped.Results: RiboPlotR is a visualization package written in R that presents both RNA-seq coverage and Ribo-seq reads in genomic coordinates for all annotated transcript isoforms of a gene. Specifically, for individual isoform models, RiboPlotR plots Ribo-seq data related to splice junctions and presents the reads for all three reading frames in three different colors. Moreover, RiboPlotR shows Ribo-seq reads in upstream ORFs, 5' and 3' untranslated regions and introns, which is critical for observing new translation events and identifying potential regulatory mechanisms.Conclusions: RiboPlotR is freely available (https://github.com/hsinyenwu/RiboPlotR and https://sourceforge.net/projects/riboplotr/) and allows the visualization of translated features identified in Ribo-seq data.

scholarly journals RiboPlotR: a visualization tool for periodic Ribo-seq reads

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Hsin-Yen Larry Wu ◽  
Polly Yingshan Hsu
Keyword(s):  
Mrna Translation ◽  
Untranslated Regions ◽  
Rna Seq ◽  
Color Coding ◽  
Link Type ◽  
Genome Wide ◽  
Non Coding Rnas ◽  
Gene Structures ◽  
Small Orfs ◽  
Reading Frames

Abstract Background Ribo-seq has revolutionized the study of genome-wide mRNA translation. High-quality Ribo-seq data display strong 3-nucleotide (nt) periodicity, which corresponds to translating ribosomes deciphering three nts at a time. While 3-nt periodicity has been widely used to study novel translation events such as upstream ORFs in 5′ untranslated regions and small ORFs in presumed non-coding RNAs, tools that allow the visualization of these events remain underdeveloped. Results RiboPlotR is a visualization package written in R that presents both RNA-seq coverage and Ribo-seq reads in genomic coordinates for all annotated transcript isoforms of a gene. Specifically, for individual isoform models, RiboPlotR plots Ribo-seq data in the context of gene structures, including 5′ and 3′ untranslated regions and introns, and it presents the reads for all three reading frames in three different colors. The inclusion of gene structures and color-coding the reading frames facilitate observing new translation events and identifying potential regulatory mechanisms. Conclusions RiboPlotR is freely available (https://github.com/hsinyenwu/RiboPlotR and https://sourceforge.net/projects/riboplotr/) and allows the visualization of translated features identified in Ribo-seq data.

scholarly journals Visualizing the periodic Ribo-seq reads with RiboPlotR

2019 ◽  
Author(s):  
Hsin-Yen Larry Wu ◽  
Polly Yingshan Hsu
Keyword(s):  
Mrna Translation ◽  
Open Reading Frames ◽  
Untranslated Regions ◽  
Rna Seq ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Non Coding Rnas ◽  
Reading Frames ◽  
Small Open Reading Frames

ABSTRACTBackgroundRibo-seq has revolutionized the study of mRNA translation in a genome-wide scale. High-quality Ribo-seq data display strong 3-nucleotide (nt) periodicity, which corresponds to translating ribosomes decipher three nucleotides each time. While the 3-nt periodicity has been widely used to study novel translation events and identify small open reading frames on presumed non-coding RNAs, tools which allow the visualization of those events remain underdeveloped.FindingsRiboPlotR is a visualization package written in R that presents both RNA-seq coverage and Ribo-seq reads for all annotated transcript isoforms in a context of a given gene. In particular, RiboPlotR plots Ribo-seq reads mapped in three reading frames using three colors for one isoform model at a time. Moreover, RiboPlotR shows Ribo-seq reads on upstream ORFs, 5’ and 3’ untranslated regions and introns, which is critical for observing new translation events and potential regulatory mechanisms.ConclusionsRiboPlotR is freely available (https://github.com/hsinyenwu/RiboPlotR) and allows the visualization of the translating features in Ribo-seq data.

scholarly journals Genome-wide analysis of long non-coding RNAs (lncRNAs) in two contrasting soybean genotypes subjected to phosphate starvation

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jinyu Zhang ◽  
Huanqing Xu ◽  
Yuming Yang ◽  
Xiangqian Zhang ◽  
Zhongwen Huang ◽  
...  
Keyword(s):  
Growth And Yield ◽  
Biological Processes ◽  
Rna Seq ◽  
Plant Growth And Development ◽  
P Deficiency ◽  
Genome Wide ◽  
Low Phosphorus ◽  
Soybean Genotypes ◽  
Non Coding Rnas ◽  
Sensitive Genotype

Abstract Background Phosphorus (P) is essential for plant growth and development, and low-phosphorus (LP) stress is a major factor limiting the growth and yield of soybean. Long noncoding RNAs (lncRNAs) have recently been reported to be key regulators in the responses of plants to stress conditions, but the mechanism through which LP stress mediates the biogenesis of lncRNAs in soybean remains unclear. Results In this study, to explore the response mechanisms of lncRNAs to LP stress, we used the roots of two representative soybean genotypes that present opposite responses to P deficiency, namely, a P-sensitive genotype (Bogao) and a P-tolerant genotype (NN94156), for the construction of RNA sequencing (RNA-seq) libraries. In total, 4,166 novel lncRNAs, including 525 differentially expressed (DE) lncRNAs, were identified from the two genotypes at different P levels. GO and KEGG analyses indicated that numerous DE lncRNAs might be involved in diverse biological processes related to phosphate, such as lipid metabolic processes, catalytic activity, cell membrane formation, signal transduction, and nitrogen fixation. Moreover, lncRNA-mRNA-miRNA and lncRNA-mRNA networks were constructed, and the results identified several promising lncRNAs that might be highly valuable for further analysis of the mechanism underlying the response of soybean to LP stress. Conclusions These results revealed that LP stress can significantly alter the genome-wide profiles of lncRNAs, particularly those of the P-sensitive genotype Bogao. Our findings increase the understanding of and provide new insights into the function of lncRNAs in the responses of soybean to P stress.

scholarly journals Improved ribosome-footprint and mRNA measurements provide insights into dynamics and regulation of yeast translation

2015 ◽  
Author(s):  
David E Weinberg ◽  
Premal Shah ◽  
Stephen W Eichhorn ◽  
Jeffrey A Hussmann ◽  
Joshua B Plotkin ◽  
...  
Keyword(s):  
Translational Control ◽  
Nucleotide Composition ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Untranslated Regions ◽  
Coding Regions ◽  
Genome Wide ◽  
Upstream Open Reading Frames ◽  
Improved Methods ◽  
Reading Frames

Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a 10-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5′- untranslated regions. Collectively, our results reveal key features of translational control in yeast and provide a framework for executing and interpreting ribosome- profiling studies.

scholarly journals Emerging Roles of Estrogen-Regulated Enhancer and Long Non-Coding RNAs

2020 ◽  
Vol 21 (10) ◽  
pp. 3711
Author(s):  
Melina J. Sedano ◽  
Alana L. Harrison ◽  
Mina Zilaie ◽  
Chandrima Das ◽  
Ramesh Choudhari ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Expression Patterns ◽  
Biological Significance ◽  
Rna Seq ◽  
Biological Functions ◽  
Protein Coding ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Non Coding Rnas

Genome-wide RNA sequencing has shown that only a small fraction of the human genome is transcribed into protein-coding mRNAs. While once thought to be “junk” DNA, recent findings indicate that the rest of the genome encodes many types of non-coding RNA molecules with a myriad of functions still being determined. Among the non-coding RNAs, long non-coding RNAs (lncRNA) and enhancer RNAs (eRNA) are found to be most copious. While their exact biological functions and mechanisms of action are currently unknown, technologies such as next-generation RNA sequencing (RNA-seq) and global nuclear run-on sequencing (GRO-seq) have begun deciphering their expression patterns and biological significance. In addition to their identification, it has been shown that the expression of long non-coding RNAs and enhancer RNAs can vary due to spatial, temporal, developmental, or hormonal variations. In this review, we explore newly reported information on estrogen-regulated eRNAs and lncRNAs and their associated biological functions to help outline their markedly prominent roles in estrogen-dependent signaling.

scholarly journals Genome-wide identification of novel long non-coding RNAs and their possible roles in hypoxic zebrafish brain

2020 ◽  
Author(s):  
Bodhisattwa Banerjee ◽  
Debaprasad Koner ◽  
David Karasik ◽  
Nirmalendu Saha
Keyword(s):  
Target Genes ◽  
Neuronal Development ◽  
Rna Seq ◽  
Master Regulators ◽  
Expression Studies ◽  
Genome Wide ◽  
Development And Differentiation ◽  
Non Coding Rnas ◽  
Differentiation Pathways ◽  
Syntenic Regions

AbstractLong non-coding RNAs (lncRNAs) are the master regulators of numerous biological processes. Hypoxia causes oxidative stress with severe and detrimental effects on brain function and acts as a critical initiating factor in the pathogenesis of Alzheimer’s disease (AD). From the RNA-Seq in the forebrain (Fb), midbrain (Mb), and hindbrain (Hb) regions of hypoxic and normoxic zebrafish, we identified novel lncRNAs, whose potential cis targets showed involvement in neuronal development and differentiation pathways. Under hypoxia, several lncRNAs and mRNAs were differentially expressed. Co-expression studies indicated that the Fb and Hb regions’ potential lncRNA target genes were involved in the AD pathogenesis. In contrast, those in Mb (cry1b, per1a, cipca) were responsible for regulating circadian rhythm. We identified specific lncRNAs present in the syntenic regions between zebrafish and humans, possibly functionally conserved. We thus identified several conserved lncRNAs as the probable regulators of AD genes (adrb3b, cav1, stat3, bace2, apoeb, psen1, s100b).

scholarly journals Genome-wide analysis reveals a switch in the translational program upon oocyte meiotic resumption

2019 ◽  
Author(s):  
Xuan G. Luong ◽  
Enrico Maria Daldello ◽  
Gabriel Rajkovic ◽  
Cai-Rong Yang ◽  
Marco Conti
Keyword(s):  
Mrna Translation ◽  
Messenger Rnas ◽  
Rna Seq ◽  
Genome Wide Analysis ◽  
Meiotic Progression ◽  
Maternal Mrna ◽  
Highly Active ◽  
Genome Wide ◽  
Molecular Machinery ◽  
Maternal Mrnas

SummaryDuring oocyte maturation, changes in gene expression depend exclusively on translation and degradation of maternal mRNAs rather than transcription. Execution of this translation program is essential for assembling the molecular machinery required for meiotic progression, fertilization, and embryo development. With the present study, we used a RiboTag/RNA-Seq approach to explore the timing of maternal mRNA translation in quiescent oocytes as well as in oocytes progressing through the first meiotic division. This genome-wide analysis reveals a global switch in maternal mRNA translation coinciding with oocyte re-entry into the meiotic cell cycle. Messenger RNAs whose translation is highly active in quiescent oocytes invariably become repressed during meiotic re-entry, whereas transcripts repressed in quiescent oocytes become activated. Experimentally, we have defined the exact timing of the switch, the repressive function of CPE elements, and identified a novel role for CPEB1 in maintaining constitutive translation of a large group of maternal mRNAs during maturation.

scholarly journals Genome-wide analysis of long non-coding RNAs (lncRNAs) in two contrasting soybean genotypes subjected to phosphate starvation

2021 ◽  
Author(s):  
jinyu zhang ◽  
Huanqing Xu ◽  
Yuming Yang ◽  
Xiangqian Zhang ◽  
Zhongwen Huang ◽  
...  
Keyword(s):  
Growth And Yield ◽  
Biological Processes ◽  
Rna Seq ◽  
Plant Growth And Development ◽  
P Deficiency ◽  
Genome Wide ◽  
Low Phosphorus ◽  
Soybean Genotypes ◽  
Non Coding Rnas ◽  
Sensitive Genotype

Abstract Background: Phosphorus (P) is essential for plant growth and development, and low-phosphorus (LP) stress is a major factor limiting the growth and yield of soybean. Long noncoding RNAs (lncRNAs) have recently been reported to be key regulators in the responses of plants to stress conditions, but the mechanism through which LP stress mediates the biogenesis of lncRNAs in soybean remains unclear.Results: In this study, to explore the response mechanisms of lncRNAs to LP stress, we used the roots of two representative soybean genotypes that present opposite responses to P deficiency, namely, a P-sensitive genotype (Bogao) and a P-tolerant genotype (NN94156), for the construction of RNA sequencing (RNA-seq) libraries. In total, 4,166 novel lncRNAs, including 525 differentially expressed (DE) lncRNAs, were identified from the two genotypes at different P levels. GO and KEGG analyses indicated that numerous DE lncRNAs might be involved in diverse biological processes related to phosphate, such as lipid metabolic processes, catalytic activity, cell membrane formation, signal transduction, and nitrogen fixation. Moreover, lncRNA-mRNA-miRNA and lncRNA-mRNA networks were constructed, and the results identified several promising lncRNAs that might be highly valuable for further analysis of the mechanism underlying the response of soybean to LP stress.Conclusions: These results revealed that LP stress can significantly alter the genome-wide profiles of lncRNAs, particularly those of the P-sensitive genotype Bogao. Our findings increase the understanding of and provide new insights into the function of lncRNAs in the responses of soybean to P stress.

scholarly journals Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data

2020 ◽  
Vol 49 (D1) ◽  
pp. D1251-D1258
Author(s):  
Yue Gao ◽  
Shipeng Shang ◽  
Shuang Guo ◽  
Xin Li ◽  
Hanxiao Zhou ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Regulatory Mechanisms ◽  
Circular Rnas ◽  
Rna Seq ◽  
Biological Functions ◽  
Cancer Subtypes ◽  
Web Tools ◽  
Online Tools ◽  
Non Coding Rnas ◽  
Mesenchymal Transformation

Abstract An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

2020 ◽  
Author(s):  
A T Vivek ◽  
Shailesh Kumar
Keyword(s):  
Computational Methods ◽  
High Throughput ◽  
Rna Seq ◽  
Physiological Mechanisms ◽  
Software Packages ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Plant Transcriptome ◽  
Non Coding Rnas

Abstract Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

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