scholarly journals Stable intronic sequence RNAs (sisRNAs) are selected regions in introns with distinct properties

2020 ◽  
Author(s):  
Jing Jin ◽  
Ximiao He ◽  
Elena M Silva
Keyword(s):  
Transcription Factors ◽  
Noncoding Rna ◽  
Biological Function ◽  
Gene Expression Regulation ◽  
Average Length ◽  
Oocyte Nucleus ◽  
Sequencing Data ◽  
Intronic Sequence ◽  
Zygotic Transcription ◽  
Synchronous Cell

Abstract Background: Stable introns and intronic fragments make up the largest population of RNA in the oocyte nucleus of the frog Xenopus tropicalis. These stable intronic sequence RNAs (sisRNAs) persist through the onset of zygotic transcription when synchronous cell division has ended and the developing embryo consists of approximately 8000 cells. Despite their abundance, the sequence properties and biological function of sisRNAs are just beginning to be understood. Results: To characterize this population of noncoding RNA, we identified all of the sisRNAs in the X. tropicalis oocyte nucleus using published high-throughput RNA sequencing data. Our analysis revealed that sisRNAs, have an average length of ~360 bps, are widely expressed from genes with multiple introns, and are derived from specific regions of introns that are GC and TG rich, while CpG poor. They are enriched in introns at both ends of transcripts but preferentially at the 3’ end. The consensus binding sites of specific transcription factors such as Stat3 are enriched in sisRNAs, suggesting an association between sisRNAs and transcription factors involved in early development. Evolutionary conservation analysis of sisRNA sequences in seven vertebrate genomes indicates that sisRNAs are as conserved as other parts of introns, but much less conserved than exons. Conclusion: In total, our results indicate sisRNAs are selected intron regions with distinct properties, supporting a biological function in gene expression regulation.

scholarly journals Stable intronic sequence RNAs (sisRNAs) are selected regions in introns with distinct properties

2019 ◽  
Author(s):  
Jing Jin ◽  
Ximiao He ◽  
Elena M Silva
Keyword(s):  
Transcription Factors ◽  
Noncoding Rna ◽  
Biological Function ◽  
Gene Expression Regulation ◽  
Average Length ◽  
Oocyte Nucleus ◽  
Sequencing Data ◽  
Intronic Sequence ◽  
Zygotic Transcription ◽  
Synchronous Cell

Abstract Stable introns and intronic fragments make up the largest population of RNA in the oocyte nucleus of the frog Xenopus tropicalis . These stable intronic sequence RNAs (sisRNAs) persist through the onset of zygotic transcription when synchronous cell division has ended and the developing embryo consists of approximately 8000 cells. Despite their abundance, the sequence properties and biological function of sisRNAs are just beginning to be understood. To characterize this population of noncoding RNA, we identified all of the sisRNAs in the X. tropicalis oocyte nucleus using the published high-throughput RNA sequencing data. Our analysis revealed that sisRNAs, have an average length of ~360 bps, are widely expressed from genes with multiple introns, and are derived from specific regions of introns that are GC and TG rich, while CpG poor. They are enriched in introns at both ends of transcripts but preferentially at the 3’ end. The consensus binding sites of specific transcription factors such as Stat3 are enriched in sisRNAs, suggesting an association between sisRNAs and transcription factors involved in early development. Evolutionary conservation analysis of sisRNA sequences in seven vertebrate genomes indicates that sisRNAs are as conserved as other parts of introns, but much less conserved than exons. In total, our results indicate sisRNAs are selected intron regions with distinct properties, supporting a biological function in gene expression regulation.

scholarly journals Stable intronic sequence RNAs (sisRNAs) are selected regions in introns with distinct properties

2020 ◽  
Author(s):  
Jing Jin ◽  
Ximiao He ◽  
Elena M Silva
Keyword(s):  
Transcription Factors ◽  
Noncoding Rna ◽  
Gene Expression Regulation ◽  
Average Length ◽  
Oocyte Nucleus ◽  
Sequencing Data ◽  
Intronic Sequence ◽  
Conservation Analysis ◽  
Zygotic Transcription ◽  
Synchronous Cell

Abstract Background: Stable introns and intronic fragments make up the largest population of RNA in the oocyte nucleus of the frog Xenopus tropicalis. These stable intronic sequence RNAs (sisRNAs) persist through the onset of zygotic transcription when synchronous cell division has ended and the developing embryo consists of approximately 8000 cells. Despite their abundance, the sequence properties and biological function of sisRNAs are just beginning to be understood. Results: To characterize this population of noncoding RNA, we identified all of the sisRNAs in the X. tropicalis oocyte nucleus using published high-throughput RNA sequencing data. Our analysis revealed that sisRNAs, have an average length of ~360 bps, are widely expressed from genes with multiple introns, and are derived from specific regions of introns that are GC and TG rich, while CpG poor. They are enriched in introns at both ends of transcripts but preferentially at the 3’ end. The consensus binding sites of specific transcription factors such as Stat3 are enriched in sisRNAs, suggesting an association between sisRNAs and transcription factors involved in early development. Evolutionary conservation analysis of sisRNA sequences in seven vertebrate genomes indicates that sisRNAs are as conserved as other parts of introns, but much less conserved than exons. Conclusion: In total, our results indicate sisRNAs are selected intron regions with distinct properties, and may play a role in gene expression regulation.

scholarly journals Stable intronic sequence RNAs (sisRNAs) are selected regions in introns with distinct properties

2020 ◽  
Author(s):  
Jing Jin ◽  
Ximiao He ◽  
Elena M Silva
Keyword(s):  
Transcription Factors ◽  
Noncoding Rna ◽  
Gene Expression Regulation ◽  
Average Length ◽  
Oocyte Nucleus ◽  
Sequencing Data ◽  
Intronic Sequence ◽  
Conservation Analysis ◽  
Zygotic Transcription ◽  
Synchronous Cell

Abstract Background: Stable introns and intronic fragments make up the largest population of RNA in the oocyte nucleus of the frog Xenopus tropicalis . These stable intronic sequence RNAs (sisRNAs) persist through the onset of zygotic transcription when synchronous cell division has ended and the developing embryo consists of approximately 8000 cells. Despite their abundance, the sequence properties and biological function of sisRNAs are just beginning to be understood. Results: To characterize this population of noncoding RNA, we identified all of the sisRNAs in the X. tropicalis oocyte nucleus using published high-throughput RNA sequencing data. Our analysis revealed that sisRNAs, have an average length of ~360 bps, are widely expressed from genes with multiple introns, and are derived from specific regions of introns that are GC and TG rich, while CpG poor. They are enriched in introns at both ends of transcripts but preferentially at the 3’ end. The consensus binding sites of specific transcription factors such as Stat3 are enriched in sisRNAs, suggesting an association between sisRNAs and transcription factors involved in early development. Evolutionary conservation analysis of sisRNA sequences in seven vertebrate genomes indicates that sisRNAs are as conserved as other parts of introns, but much less conserved than exons. Conclusion: In total, our results indicate sisRNAs are selected intron regions with distinct properties, and may play a role in gene expression regulation .

scholarly journals Stable intronic sequence RNA (sisRNA), a new class of noncoding RNA from the oocyte nucleus of Xenopus tropicalis

2012 ◽  
Vol 26 (22) ◽  
pp. 2550-2559 ◽  
Author(s):  
E. J. Gardner ◽  
Z. F. Nizami ◽  
C. C. Talbot ◽  
J. G. Gall
Keyword(s):  
Noncoding Rna ◽  
Xenopus Tropicalis ◽  
Oocyte Nucleus ◽  
Intronic Sequence ◽  
New Class

scholarly journals Classifying gastric cancer using FLORA reveals clinically relevant molecular subtypes and highlights LINC01614 as a biomarker for patient prognosis

Oncogene ◽  
2021 ◽  
Author(s):  
Yiyun Chen ◽  
Wing Yin Cheng ◽  
Hongyu Shi ◽  
Shengshuo Huang ◽  
Huarong Chen ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Noncoding Rna ◽  
Molecular Subtype ◽  
Sequencing Data ◽  
Cell Growth And Migration ◽  
Protein Coding ◽  
Over Expression ◽  
And Migration ◽  
Patient Prognosis ◽  
Subtype 3

AbstractMolecular-based classifications of gastric cancer (GC) were recently proposed, but few of them robustly predict clinical outcomes. While mutation and expression signature of protein-coding genes were used in previous molecular subtyping methods, the noncoding genome in GC remains largely unexplored. Here, we developed the fast long-noncoding RNA analysis (FLORA) method to study RNA sequencing data of GC cases, and prioritized tumor-specific long-noncoding RNAs (lncRNAs) by integrating clinical and multi-omic data. We uncovered 1235 tumor-specific lncRNAs, based on which three subtypes were identified. The lncRNA-based subtype 3 (L3) represented a subgroup of intestinal GC with worse survival, characterized by prevalent TP53 mutations, chromatin instability, hypomethylation, and over-expression of oncogenic lncRNAs. In contrast, the lncRNA-based subtype 1 (L1) has the best survival outcome, while LINC01614 expression further segregated a subgroup of L1 cases with worse survival and increased chance of developing distal metastasis. We demonstrated that LINC01614 over-expression is an independent prognostic factor in L1 and network-based functional prediction implicated its relevance to cell migration. Over-expression and CRISPR-Cas9-guided knockout experiments further validated the functions of LINC01614 in promoting GC cell growth and migration. Altogether, we proposed a lncRNA-based molecular subtype of GC that robustly predicts patient survival and validated LINC01614 as an oncogenic lncRNA that promotes GC proliferation and migration.

scholarly journals Transcriptome analysis of two contrasting genotypes of pearl millet to gain insight into heat stress responses

2020 ◽  
Author(s):  
Albert Maibam ◽  
Sunil Nigombam ◽  
Harinder Vishwakarma ◽  
Showkat Ahmad Lone ◽  
Kishor Gaikwad ◽  
...  
Keyword(s):  
Heat Stress ◽  
Pearl Millet ◽  
Stress Responses ◽  
Simple Sequence Repeats ◽  
Pennisetum Glaucum ◽  
Average Length ◽  
Gc Content ◽  
Functional Markers ◽  
Sequencing Data ◽  
Simple Sequence

Abstract Background Pennisetum glaucum (L.) R. Br. is mainly grown in arid and semi-arid regions. Being naturally tolerant to various adverse condtitions, it is a good biological resource for deciphering the molecular basis of abiotic stresses such as heat stress in plants but limited studies have been carried out till date to this effect. Here, we performed RNA-sequencing from the leaf of two contrasting genotypes of pearl millet (841-B and PPMI-69) subjected to heat stress (42 °C for 6 h). Results Over 274 million high quality reads with an average length of 150 nt were generated. Assembly was carried out using trinity, obtaining 47,310 unigenes having an average length of 1254 nucleotides, N50 length of 1853 nucleotides and GC content of 53.11%. Blastx resulted in annotation of 35,628 unigenes and functional classification showed 15,950 unigenes designated to 51 Gene Ontology terms, 13,786 unigenes allocated to 23 Clusters of Orthologous Groups and 4,255 unigenes distributed into 132 functional KEGG pathways. 12,976 simple sequence repeats were identified from 10,294 unigenes for the development of functional markers. A total of 3,05,759 SNPs were observed in the transcriptome data. Out of 2,301 differentially expressed genes, 10 potential candidates genes were selected based on log2 fold change and adjusted p-value parameters for their differential gene expression by qRT-PCR. Conclusions The dynamic expression changes in two genotypes of P. glaucum reflect transcriptome regulation of signaling pathways in heat stress response. In order to develop genetic markers, 12,976 simple sequence repeats (SSRs) were identified. The sequencing data generated in this study shall serve as an important resource for further research in the area of crop biotechnology.

scholarly journals The Long Noncoding RNA Differential Expression in Peripheral Blood Leukocyte from Schizophrenia Patients by RNA Sequencing

2020 ◽  
Author(s):  
Jie Wu ◽  
Zijun Liu ◽  
Yunqiao Zhang ◽  
Zhaowei Teng ◽  
Xu You ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Correlation Coefficient ◽  
Peripheral Blood ◽  
Noncoding Rna ◽  
Clinical Symptoms ◽  
Function Analysis ◽  
Hierarchical Classification ◽  
Peripheral Blood Leukocyte ◽  
Protein Coding ◽  
Functional Sites

Abstract Background: The diagnosis of schizophrenia (SCZ) depends on the evaluation of clinical symptoms, and there is no objective biomarker. Surveys have found that long non-coding RNA (lncRNA) may be affected in the pathogenesis of SCZ. There are also different genes in the expression of peripheral blood (PBL) in SCZ patients.Methods: We profiled transcriptome analysis of PBL in 50 patients with schizophrenia and 50 controls without psychiatric diagnoses, reconstructed PBL transcriptome information using RNA-seq, predicted lncRNA-mRNA interaction via “RNAplex”, a hierarchical classification-Spielman correlation coefficient approach was used to analyze the correlation between lncRNA and protein-coding gene expression among samples, and used systematic bioinformatics methods (Go/Pathway) to perform lncRNA functional annotation and qPCR experimental verification. Predicting functional sites for sequences using the database PROSITE, NCBI, UCSC, JASPAR.Results: We screened 94 lncRNA and 1179 mRNA differential expressions in PBL, of which 46 new lncRNAs were identified for the first time. Enrichment into lncRNA involves biological processes and signaling pathways related to the neutrophil activation involved in immune response. According to Spearman correlation coefficient analysis, 81 lncRNA and 410 mRNA have expression correlation (p<0.01 and |r|≥0.4), QPCR in independent samples verified that the core node of the lncRNA-mRNA co-expression network IL1RAP-TCONS_00138311 variable shear is indeed highly expressed in SCZ patients, 2^-△△Ct is 0.56, the area under the ROC curve is 0.924. The top four ranked transcription factors were predicted to be HSF1, HSF2, HSF4, and FOXA1.Conclusions: Combined with sequence function analysis, it showed that the transcription factors FOXA1, HSF1, HSF2, HSF4, etc. may mediate the activation of IL1B-induced NF-kβ pathway and other inflammatory pathways through the regulation of IL1RAP alternative splicing transcripts TCONS_00138311, thereby participating in the pathogenesis of SCZ. We propose that the frequency of Differential lncRNA in peripheral blood could be used as novel biomarker for distinguishing SCZ from health.

scholarly journals A machine learning-based framework for modeling transcription elongation

2021 ◽  
Vol 118 (6) ◽  
pp. e2007450118
Author(s):  
Peiyuan Feng ◽  
An Xiao ◽  
Meng Fang ◽  
Fangping Wan ◽  
Shuya Li ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
High Throughput Sequencing ◽  
Gene Expression Regulation ◽  
Transcription Elongation ◽  
Transcriptional Elongation ◽  
Sequencing Data ◽  
Pol Ii ◽  
High Throughput Sequencing Data ◽  
Pol Ii Pausing ◽  
Elongation Process

RNA polymerase II (Pol II) generally pauses at certain positions along gene bodies, thereby interrupting the transcription elongation process, which is often coupled with various important biological functions, such as precursor mRNA splicing and gene expression regulation. Characterizing the transcriptional elongation dynamics can thus help us understand many essential biological processes in eukaryotic cells. However, experimentally measuring Pol II elongation rates is generally time and resource consuming. We developed PEPMAN (polymerase II elongation pausing modeling through attention-based deep neural network), a deep learning-based model that accurately predicts Pol II pausing sites based on the native elongating transcript sequencing (NET-seq) data. Through fully taking advantage of the attention mechanism, PEPMAN is able to decipher important sequence features underlying Pol II pausing. More importantly, we demonstrated that the analyses of the PEPMAN-predicted results around various types of alternative splicing sites can provide useful clues into understanding the cotranscriptional splicing events. In addition, associating the PEPMAN prediction results with different epigenetic features can help reveal important factors related to the transcription elongation process. All these results demonstrated that PEPMAN can provide a useful and effective tool for modeling transcription elongation and understanding the related biological factors from available high-throughput sequencing data.

scholarly journals Pluripotency factors select gene expression repertoire at Zygotic Genome Activation

2020 ◽  
Author(s):  
Meijiang Gao ◽  
Marina Veil ◽  
Marcus Rosenblatt ◽  
Anna Gebhard ◽  
Helge Hass ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Early Gene ◽  
Zebrafish Embryos ◽  
Fate Specification ◽  
Pluripotency Factors ◽  
Zygotic Transcription ◽  
Simultaneous Loss ◽  
Genome Activation ◽  
Zygotic Genome

AbstractAwakening of zygotic transcription in animal embryos relies on maternal pioneer transcription factors. The interplay of global and specific functions of these proteins remains poorly understood. Here, we analyzed nucleosome positioning, H3K27 acetylation, transcription, and gastrulation rates in zebrafish embryos lacking pluripotency factors Pou5f3 and Sox19b. We show that the bulk transcriptional onset does not require Sox19b and Pou5f3, but is sensitive to their balance. Pou5f3 docks H3K27ac on the enhancers of genes involved in gastrulation and ventral fate specification. Sox19b facilitates Pou5f3 access to one-third of these enhancers. The genes regulating mesendodermal and dorsal fates are primed for activation independently on Pou5f3 and Sox19b. Strikingly, the loss of either factor results in activation of silent enhancers; simultaneous loss of both leads to premature expression of differentiation genes. Our results uncover how independent activities of maternal Pou5f3 and Sox19b add up or antagonize to determine the early gene expression repertoire.

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