Long Noncoding RNA Derived from LncRNA–mRNA Co-expression Networks Modulates the Locust Phase Change

AbstractLong noncoding RNAs (lncRNAs) regulate various biological processes from gene expression to animal behavior. Although protein-coding genes, microRNAs, and neuropeptides play important roles in the regulation of phenotypic plasticity in migratory locust, empirical studies on the function of lncRNAs in the process remain limited. Here, we applied high-throughput RNA-seq to characterize the expression patterns of lncRNAs and mRNAs in the time course of the locust phase change. LncRNAs displayed more rapid response at the early stages of the time-course treatments than mRNA expression. Functional annotations demonstrated that early changed lncRNAs employed different pathways in isolation and crowding processes to cope up with the changes in population density. Finally, two overlapping hub lncRNA loci in the crowding and isolation networks were screened to be functionally verified. Experimental validation indicated that LNC1010057 could act as a potential regulator to modulate the locust phase change. This work offers new insights into the mechanism underlying the locust phase change and expands the scope of lncRNA functions in animal behavior.

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PLncDB V2.0: a comprehensive encyclopedia of plant long noncoding RNAs

Nucleic Acids Research ◽

10.1093/nar/gkaa910 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D1489-D1495 ◽

Cited By ~ 1

Author(s):

Jingjing Jin ◽

Peng Lu ◽

Yalong Xu ◽

Zefeng Li ◽

Shizhou Yu ◽

...

Keyword(s):

Noncoding Rna ◽

Regulatory Networks ◽

Expression Patterns ◽

Noncoding Rnas ◽

Long Noncoding Rnas ◽

Data Driven ◽

Rna Seq ◽

Protein Coding ◽

User Friendly ◽

Coding Potential

Abstract Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides with little or no protein coding potential. The expanding list of lncRNAs and accumulating evidence of their functions in plants have necessitated the creation of a comprehensive database for lncRNA research. However, currently available plant lncRNA databases have some deficiencies, including the lack of lncRNA data from some model plants, uneven annotation standards, a lack of visualization for expression patterns, and the absence of epigenetic information. To overcome these problems, we upgraded our Plant Long noncoding RNA Database (PLncDB, http://plncdb.tobaccodb.org/), which was based on a uniform annotation pipeline. PLncDB V2.0 currently contains 1 246 372 lncRNAs for 80 plant species based on 13 834 RNA-Seq datasets, integrating lncRNA information from four other resources including EVLncRNAs, RNAcentral and etc. Expression patterns and epigenetic signals can be visualized using multiple tools (JBrowse, eFP Browser and EPexplorer). Targets and regulatory networks for lncRNAs are also provided for function exploration. In addition, PLncDB V2.0 is hierarchical and user-friendly and has five built-in search engines. We believe PLncDB V2.0 is useful for the plant lncRNA community and data mining studies and provides a comprehensive resource for data-driven lncRNA research in plants.

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

International Journal of Molecular Sciences ◽

10.3390/ijms21103711 ◽

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.

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Differential Expression Analysis Using A Model-Based Gene Clustering Algorithm for RNA-Seq Data

10.21203/rs.3.rs-86123/v1 ◽

2020 ◽

Author(s):

Takayuki Osabe ◽

Kentaro Shimizu ◽

Koji Kadota

Keyword(s):

Differential Expression ◽

Time Course ◽

Clustering Algorithm ◽

Expression Patterns ◽

Differential Expression Analysis ◽

Real Data ◽

Gene Clustering ◽

Rna Seq ◽

Model Based ◽

Group Data

Abstract Background RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering is used to classify DEGs with similar expression patterns for the subsequent analyses of data from experiments such as time-courses or multi-group comparisons. However, gene clustering has rarely been used for analyzing simple two-group data or differential expression (DE). In this study, we report a model-based clustering algorithm, MBCluster.Seq, that can be implemented using an R package for DE analysis.Results The input data originally used by MBCluster.Seq is DEGs, and the proposed method (called MBCdeg) uses all genes for the analysis. The method uses posterior probabilities of genes assigned to a cluster displaying non-DEG pattern for overall gene ranking. We compared the performance of MBCdeg with conventional R packages such as edgeR, DESeq2, and TCC that are specialized for DE analysis using simulated and real data. Our results showed that MBCdeg outperformed other methods when the proportion of DEG was less than 50%. However, the DEG identification using MBCdeg was less consistent than with conventional methods. We compared the effects of different normalization algorithms using MBCdeg, and performed an analysis using MBCdeg in combination with a robust normalization algorithm (called DEGES) that was not implemented in MBCluster.Seq. The new analysis method showed greater stability than using the original MBCdeg with the default normalization algorithm.Conclusions MBCdeg with DEGES normalization can be used in the identification of DEGs when the PDEG is relatively low. As the method is based on gene clustering, the DE result includes information on which expression pattern the gene belongs to. The new method may be useful for the analysis of time-course and multi-group data, where the classification of expression patterns is often required.

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The long noncoding RNA FRILAIR regulates strawberry fruit ripening by functioning as a noncanonical target mimic

PLoS Genetics ◽

10.1371/journal.pgen.1009461 ◽

2021 ◽

Vol 17 (3) ◽

pp. e1009461

Author(s):

Yajun Tang ◽

Zhipeng Qu ◽

Jiajun Lei ◽

Reqing He ◽

David L. Adelson ◽

...

Keyword(s):

Fruit Ripening ◽

Noncoding Rna ◽

Expression Patterns ◽

Noncoding Rnas ◽

Mrna Levels ◽

Strawberry Fruit ◽

Rna Seq ◽

Fruit Maturation ◽

Temporal Expression ◽

Strawberry Fruit Ripening

Long noncoding RNAs (lncRNAs) are emerging as important regulators in plant development, but few of them have been functionally characterized in fruit ripening. Here, we have identified 25,613 lncRNAs from strawberry ripening fruits based on RNA-seq data from poly(A)-depleted libraries and rRNA-depleted libraries, most of which exhibited distinct temporal expression patterns. A novel lncRNA, FRILAIR harbours the miR397 binding site that is highly conserved in diverse strawberry species. FRILAIR overexpression promoted fruit maturation in the Falandi strawberry, which was consistent with the finding from knocking down miR397, which can guide the mRNA cleavage of both FRILAIR and LAC11a (encoding a putative laccase-11-like protein). Moreover, LAC11a mRNA levels were increased in both FRILAIR overexpressing and miR397 knockdown fruits, and accelerated fruit maturation was also found in LAC11a overexpressing fruits. Overall, our study demonstrates that FRILAIR can act as a noncanonical target mimic of miR397 to modulate the expression of LAC11a in the strawberry fruit ripening process.

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Assessment of CircRNA Expression Profiles and Potential Functions in Brown Adipogenesis

Frontiers in Genetics ◽

10.3389/fgene.2021.769690 ◽

2021 ◽

Vol 12 ◽

Author(s):

Pengpeng Zhang ◽

Mingxuan Sheng ◽

Chunyu Du ◽

Zhe Chao ◽

Haixia Xu ◽

...

Keyword(s):

Binding Sites ◽

Expression Profiles ◽

Expression Patterns ◽

Potential Functions ◽

Rna Seq ◽

Specific Expression ◽

Protein Coding ◽

Multiple Binding Sites ◽

Brown Adipose ◽

Brown Adipogenesis

Brown adipose tissue (BAT) is specialized for energy expenditure, thus a better understanding of the regulators influencing BAT development could provide novel strategies to defense obesity. Many protein-coding genes, miRNAs, and lncRNAs have been investigated in BAT development, however, the expression patterns and functions of circRNA in brown adipogenesis have not been reported yet. This study determined the circRNA expression profiles across brown adipogenesis (proliferation, early differentiated, and fully differentiated stages) by RNA-seq. We identified 3,869 circRNAs and 36.9% of them were novel. We found the biogenesis of circRNA was significantly related to linear mRNA transcription, meanwhile, almost 70% of circRNAs were generated by alternative back-splicing. Next, we examined the cell-specific and differentiation stage-specific expression of circRNAs. Compared to white adipocytes, nearly 30% of them were specifically expressed in brown adipocytes. Further, time-series expression analysis showed circRNAs were dynamically expressed, and 117 differential expression circRNAs (DECs) in brown adipogenesis were identified, with 77 upregulated and 40 downregulated. Experimental validation showed the identified circRNAs could be successfully amplified and the expression levels detected by RNA-seq were reliable. For the potential functions of the circRNAs, GO analysis suggested that the decreased circRNAs were enriched in cell proliferation terms, while the increased circRNAs were enriched in development and thermogenic terms. Bioinformatics predictions showed that DECs contained numerous binding sites of functional miRNAs. More interestingly, most of the circRNAs contained multiple binding sites for the same miRNA, indicating that they may facilitate functions by acting as microRNA sponges. Collectively, we characterized the circRNA expression profiles during brown adipogenesis and provide numerous novel circRNAs candidates for future brown adipogenesis regulating studies.

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RNA-Seq Implies Divergent Regulation Patterns of LincRNA on Spermatogenesis and Testis Growth in Goats

Animals ◽

10.3390/ani11030625 ◽

2021 ◽

Vol 11 (3) ◽

pp. 625

Author(s):

Dongdong Bo ◽

Xunping Jiang ◽

Guiqiong Liu ◽

Ruixue Hu ◽

Yuqing Chong

Keyword(s):

Target Genes ◽

Expression Patterns ◽

Testicular Development ◽

Related Protein ◽

Rna Seq ◽

Down Regulation ◽

Protein Coding ◽

Protein Coding Genes ◽

Regulation Of Growth ◽

Fresh Insight

Long intergenic non-coding RNAs (lincRNAs) regulate testicular development by acting on protein-coding genes. However, little is known about whether lincRNAs and protein-coding genes exhibit the same expression pattern in the same phase of postnatal testicular development in goats. Therefore, this study aimed to demonstrate the expression patterns and roles of lincRNAs during the postnatal development of the goat testis. Herein, the testes of Yiling goats with average ages of 0, 30, 60, 90, 120, 150, and 180 days postnatal (DP) were used for RNA-seq. In total, 20,269 lincRNAs were identified, including 16,931 novel lincRNAs. We identified seven time-specifically diverse lincRNA modules and six mRNA modules by weighted gene co-expression network analysis (WGCNA). Interestingly, the down-regulation of growth-related lincRNAs was nearly one month earlier than the up-regulation of spermatogenesis-related lincRNAs, while the down-regulation of growth-related protein-coding genes and the correspondent up-regulation of spermatogenesis-related protein-coding genes occurred at the same age. Then, potential lincRNA target genes were predicted. Moreover, the co-expression network of lincRNAs demonstrated that ENSCHIT00000000777, ENSCHIT00000002069, and ENSCHIT00000005076 were the key lincRNAs in the process of testis development. Our study discovered the divergent regulation patterns of lincRNA on spermatogenesis and testis growth, providing a fresh insight into age-biased changes in lincRNA expression in the goat testis.

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SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions

10.1101/046110 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ning Leng ◽

Li-Fang Chu ◽

Jeea Choi ◽

Christina Kendziorski ◽

James A. Thomson ◽

...

Keyword(s):

Single Cell ◽

Cell Fate ◽

Empirical Bayes ◽

Time Course ◽

Expression Patterns ◽

R Package ◽

Embryonic Cell ◽

Rna Seq ◽

Cell Fate Decisions ◽

Probability Estimates

AbstractMotivationWith the development of single cell RNA-seq (scRNA-seq) technology, scRNA-seq experiments with ordered conditions (e.g. time-course) are becoming common. Methods developed for analyzing ordered bulk RNA-seq experiments are not applicable to scRNA-seq, since their distributional assumptions are often violated by additional heterogeneities prevalent in scRNA-seq. Here we present SC-Pattern - an empirical Bayes model to characterize genes with expression changes in ordered scRNA-seq experiments. SCPattern utilizes the non-parametrical Kolmogorov-Smirnov statistic, thus it has the flexibility to identify genes with a wide variety of types of changes. Additionally, the Bayes framework allows SCPattern to classify genes into expression patterns with probability estimates.ResultsSimulation results show that SCPattern is well powered for identifying genes with expression changes while the false discovery rate is well controlled. SCPattern is also able to accurately classify these dynamic genes into directional expression patterns. Applied to a scRNA-seq time course dataset studying human embryonic cell differentiation, SCPattern detected a group of important genes that are involved in mesendoderm and definitive endoderm cell fate decisions, positional patterning, and cell cycle.Availability and ImplementationThe SCPattern is implemented as an R package along with a user-friendly graphical interface, which are available at:https://github.com/lengning/SCPatternContact:[email protected]

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Comparison of characteristics of long noncoding RNA in Hanwoo according to sex

Asian-Australasian Journal of Animal Sciences ◽

10.5713/ajas.18.0533 ◽

2020 ◽

Vol 33 (5) ◽

pp. 696-703

Author(s):

Jae-Young Choi ◽

KyeongHye Won ◽

Seungwoo Son ◽

Donghyun Shin ◽

Jae-Don Oh

Keyword(s):

Long Noncoding Rna ◽

Noncoding Rna ◽

Skeletal Muscles ◽

Expression Patterns ◽

Differentially Expressed ◽

Physiological Mechanisms ◽

Protein Coding ◽

Future Studies ◽

Hanwoo Cattle

Objective: Cattle were some of the first animals domesticated by humans for the production of milk, meat, etc. Long noncoding RNA (lncRNA) is defined as longer than 200 bp in non-protein coding transcripts. lncRNA is known to function in regulating gene expression and is currently being studied in a variety of livestock including cattle. The purpose of this study is to analyze the characteristics of lncRNA according to sex in Hanwoo cattle.Methods: This study was conducted using the skeletal muscles of 9 Hanwoo cattle include bulls, steers and cows. RNA was extracted from skeletal muscle of Hanwoo. Sequencing was conducted using Illumina HiSeq2000 and mapped to the Bovine Taurus genome. The expression levels of lncRNAs were measured by DEGseq and quantitative trait loci (QTL) data base was used to identify QTLs associated with lncRNA. The python script was used to match the nearby genesResults: In this study, the expression patterns of transcripts of bulls, steers and cows were identified. And we identified significantly differentially expressed lncRNAs in bulls, steers and cows. In addition, characteristics of lncRNA which express differentially in muscles according to the sex of Hanwoo were identified. As a result, we found differentially expressed lncRNAs according to sex were related to shear force and body weight.Conclusion: This study was classified and characterized lncRNA which differentially expressed by sex in Hanwoo cattle. We believe that the characterization of lncRNA by sex of Hanwoo will be helpful for future studies of the physiological mechanisms of Hanwoo cattle.

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Comparative genomics of muskmelon reveals a potential role for retrotransposons in the modification of gene expression

Communications Biology ◽

10.1038/s42003-020-01172-0 ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Ryoichi Yano ◽

Tohru Ariizumi ◽

Satoko Nonaka ◽

Yoichi Kawazu ◽

Silin Zhong ◽

...

Keyword(s):

Gene Expression ◽

Fruit Ripening ◽

Expression Patterns ◽

Rna Seq ◽

Protein Coding ◽

Genome Wide ◽

Oxford Nanopore ◽

Melon Genome ◽

Number Variation ◽

Genome Assemblies

AbstractMelon exhibits substantial natural variation especially in fruit ripening physiology, including both climacteric (ethylene-producing) and non-climacteric types. However, genomic mechanisms underlying such variation are not yet fully understood. Here, we report an Oxford Nanopore-based high-grade genome reference in the semi-climacteric cultivar Harukei-3 (378 Mb + 33,829 protein-coding genes), with an update of tissue-wide RNA-seq atlas in the Melonet-DB database. Comparison between Harukei-3 and DHL92, the first published melon genome, enabled identification of 24,758 one-to-one orthologue gene pairs, whereas others were candidates of copy number variation or presence/absence polymorphisms (PAPs). Further comparison based on 10 melon genome assemblies identified genome-wide PAPs of 415 retrotransposon Gag-like sequences. Of these, 160 showed fruit ripening-inducible expression, with 59.4% of the neighboring genes showing similar expression patterns (r > 0.8). Our results suggest that retrotransposons contributed to the modification of gene expression during diversification of melon genomes, and may affect fruit ripening-inducible gene expression.

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The Transcriptome of Verticillium dahliae Responds Differentially Depending on the Disease Susceptibility Level of the Olive (Olea europaea L.) Cultivar

Genes ◽

10.3390/genes10040251 ◽

2019 ◽

Vol 10 (4) ◽

pp. 251 ◽

Cited By ~ 10

Author(s):

Jaime Jiménez-Ruiz ◽

María de la O Leyva-Pérez ◽

Carmen Gómez-Lama Cabanás ◽

Juan B. Barroso ◽

Francisco Luque ◽

...

Keyword(s):

Verticillium Dahliae ◽

Time Course ◽

Expression Patterns ◽

Differential Susceptibility ◽

Rna Seq ◽

Niche Adaptation ◽

Olive Cultivars ◽

Olive Trees ◽

Cultivar Susceptibility ◽

Comparative Transcriptomic Analysis

Among biotic constraints affecting olive trees cultivation worldwide, the soil-borne fungus Verticillium dahliae is considered one of the most serious threats. Olive cultivars display differential susceptibility to the disease, but our knowledge on the pathogen’s responses when infecting varieties differing in susceptibility is scarce. A comparative transcriptomic analysis (RNA-seq) was conducted in olive cultivars Picual (susceptible) and Frantoio (tolerant). RNA samples originated from roots during the first two weeks after inoculation with V. dahliae defoliating (D) pathotype. Verticillium dahliae mRNA amount was overwhelmingly higher in roots of the susceptible cultivar, indicating that proliferation of pathogen biomass is favored in ‘Picual’. A significant larger number of V. dahliae unigenes (11 fold) were only induced in this cultivar. Seven clusters of differentially expressed genes (DEG) were identified according to time-course expression patterns. Unigenes potentially coding for niche-adaptation, pathogenicity, virulence and microsclerotia development were induced in ‘Picual’, while in ‘Frantoio’ expression remained negligible or null. Verticillium dahliae D pathotype transcriptome responses are qualitatively and quantitatively different, and depend on cultivar susceptibility level. The much larger V. dahliae biomass found in ‘Picual’ roots is a consequence of both host and pathogen DEG explaining, to a large extent, the higher aggressiveness exerted over this cultivar.

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