scholarly journals Integrated analysis of long non-coding RNAs and mRNAs reveals the regulatory network of maize seedling root responding to salt stress

BMC Genomics ◽  
2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Peng Liu ◽  
Yinchao Zhang ◽  
Chaoying Zou ◽  
Cong Yang ◽  
Guangtang Pan ◽  
...  
Keyword(s):  
Salt Stress ◽  
Salt Tolerance ◽  
Inbred Lines ◽  
Maize Seedling ◽  
Integrated Analysis ◽  
Regulatory Pathway ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Non Coding Rnas ◽  
Whole Transcriptome

Abstract Background Long non-coding RNAs (lncRNAs) play important roles in response to abiotic stresses in plants, by acting as cis- or trans-acting regulators of protein-coding genes. As a widely cultivated crop worldwide, maize is sensitive to salt stress particularly at the seedling stage. However, it is unclear how the expressions of protein-coding genes are affected by non-coding RNAs in maize responding to salt tolerance. Results The whole transcriptome sequencing was employed to investigate the differential lncRNAs and target transcripts responding to salt stress between two maize inbred lines with contrasting salt tolerance. We developed a flexible, user-friendly, and modular RNA analysis workflow, which facilitated the identification of lncRNAs and novel mRNAs from whole transcriptome data. Using the workflow, 12,817 lncRNAs and 8,320 novel mRNAs in maize seedling roots were identified and characterized. A total of 742 lncRNAs and 7,835 mRNAs were identified as salt stress-responsive transcripts. Moreover, we obtained 41 cis- and 81 trans-target mRNA for 88 of the lncRNAs. Among these target transcripts, 11 belonged to 7 transcription factor (TF) families including bHLH, C2H2, Hap3/NF-YB, HAS, MYB, WD40, and WRKY. The above 8,577 salt stress-responsive transcripts were further classified into 28 modules by weighted gene co-expression network analysis. In the salt-tolerant module, we constructed an interaction network containing 79 nodes and 3081 edges, which included 5 lncRNAs, 18 TFs and 56 functional transcripts (FTs). As a trans-acting regulator, the lncRNA MSTRG.8888.1 affected the expressions of some salt tolerance-relative FTs, including protein-serine/threonine phosphatase 2C and galactinol synthase 1, by regulating the expression of the bHLH TF. Conclusions The contrasting genetic backgrounds of the two inbred lines generated considerable variations in the expression abundance of lncRNAs and protein-coding transcripts. In the co-expression networks responding to salt stress, some TFs were targeted by the lncRNAs, which further regulated the salt tolerance-related functional transcripts. We constructed a regulatory pathway of maize seedlings to salt stress, which was mediated by the hub lncRNA MSTRG.8888.1 and participated by the bHLH TF and its downstream target transcripts. Future work will be focused on the functional revelation of the regulatory pathway.

scholarly journals Integrated analysis of differentially expressed genes and construction of a competing endogenous RNA network in human Huntington neural progenitor cells

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiaoping Tan ◽  
Yang Liu ◽  
Taiming Zhang ◽  
Shuyan Cong
Keyword(s):  
Transcription Factors ◽  
Progenitor Cells ◽  
Neural Progenitor Cells ◽  
Integrated Analysis ◽  
Ppi Network ◽  
Competing Endogenous Rna ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Cerna Network ◽  
Non Coding Rnas

Abstract Background Huntington's disease (HD) is one of the most common polyglutamine disorders, leading to progressive dyskinesia, cognitive impairment, and neuropsychological problems. Besides the dysregulation of many protein-coding genes in HD, previous studies have revealed a variety of non-coding RNAs that are also dysregulated in HD, including several long non-coding RNAs (lncRNAs). However, an integrated analysis of differentially expressed (DE) genes based on a competing endogenous RNA (ceRNA) network is still currently lacking. Methods In this study, we have systematically analyzed the gene expression profile data of neural progenitor cells (NPCs) derived from patients with HD and controls (healthy controls and the isogenic controls of HD patient cell lines corrected using a CRISPR-Cas9 approach at the HTT locus) to screen out DE mRNAs and DE lncRNAs and create a ceRNA network. To learn more about the possible functions of lncRNAs in the ceRNA regulatory network in HD, we conducted a functional analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) and established a protein–protein interaction (PPI) network for mRNAs interacting with these lncRNAs. Results We identified 490 DE mRNAs and 94 DE lncRNAs, respectively. Of these, 189 mRNAs and 20 lncRNAs were applied to create a ceRNA network. The results showed that the function of DE lncRNAs mainly correlated with transcriptional regulation as demonstrated by GO analysis. Also, KEGG enrichment analysis showed these lncRNAs were involved in tumor necrosis factor, calcium, Wnt, and NF-kappa B signaling pathways. Interestingly, the PPI network revealed that a variety of transcription factors in the ceRNA network interacted with each other, suggesting such lncRNAs may regulate transcription in HD by controlling the expression of such protein-coding genes, especially transcription factors. Conclusions Our research provides new clues for uncovering the mechanisms of lncRNAs in HD and can be used as the focus for further investigation.

scholarly journals Integrated Analysis of Differentially Expressed Genes and Construction of a Competing Endogenous RNA Network in Human Huntington Neural Progenitor Cells

2020 ◽  
Author(s):  
Xiaoping Tan ◽  
Shuyan Cong ◽  
Yang Liu ◽  
Taiming Zhang
Keyword(s):  
Transcription Factors ◽  
Progenitor Cells ◽  
Neural Progenitor Cells ◽  
Integrated Analysis ◽  
Ppi Network ◽  
Competing Endogenous Rna ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Cerna Network ◽  
Non Coding Rnas

Abstract Background Huntington's disease (HD) is one of the most common polyglutamine disorders, leading to progressive dyskinesia, cognitive impairment, and neuropsychological problems. Besides the dysregulation of many protein-coding genes in HD, previous studies have revealed a variety of non-coding RNAs that are dysregulated in HD, including several long non-coding RNAs (lncRNAs). However, an integrated analysis of differentially expressed (DE) genes based on a competing endogenous RNA (ceRNA) network is still currently lacking. Results Here, we have systematically analyzed the gene expression profile data of neural progenitor cells (NPCs) derived from patients with HD and controls (healthy controls and the isogenic controls of HD patient cell lines corrected using CRISPR-Cas9 approach at the HTT locus, and we identified 490 DE mRNAs and 94 DE lncRNAs, respectively. Of these, 189 mRNAs and 20 lncRNAs were applied to create a ceRNA network. To learn more about the possible functions of lncRNAs in the ceRNA regulatory network in HD, we conducted a functional analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) and established a protein-protein interaction (PPI) network for mRNAs interacting with these lncRNAs. It is suggested that the function of DE lncRNAs mainly correlated with transcriptional regulation demonstrated by GO analysis. Also, KEGG enrichment analysis showed these lncRNAs were involved in tumor necrosis factor, calcium, Wnt, and NF-kappa B signaling pathways. Interestingly, the PPI network revealed that a variety of transcription factors in the ceRNA network interacted with each other, suggesting such lncRNAs may regulate transcription in HD by controlling the expression of such protein-coding genes, especially transcription factors. Conclusions Our research provides new clues for uncovering the mechanism of lncRNAs in HD and can be used as the focus for further investigation.

scholarly journals Co‐regulation of long non‐coding RNAs and protein‐coding genes during cell quiescence

2021 ◽  
Vol 35 (S1) ◽  
Author(s):  
Hilary Coller ◽  
Huiling Huang ◽  
Mithun Mitra ◽  
Kaiser Atai ◽  
Kirthana Sarathy
Keyword(s):  
Protein Coding ◽  
Protein Coding Genes ◽  
Cell Quiescence ◽  
Non Coding Rnas

scholarly journals DNA methylation patterns of protein-coding genes and long non-coding RNAs in males with schizophrenia

2015 ◽  
Vol 12 (5) ◽  
pp. 6568-6576 ◽  
Author(s):  
QI LIAO ◽  
YUNLIANG WANG ◽  
JIA CHENG ◽  
DONGJUN DAI ◽  
XINGYU ZHOU ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Non Coding Rnas ◽  
Methylation Patterns

Expression changes in protein-coding genes and long non-coding RNAs in denatured dermis following thermal injury

Burns ◽  
2020 ◽  
Vol 46 (5) ◽  
pp. 1128-1135 ◽  
Author(s):  
Wenchang Yu ◽  
Zaiwen Guo ◽  
Pengfei Liang ◽  
Bimei Jiang ◽  
Le Guo ◽  
...  
Keyword(s):  
Thermal Injury ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Non Coding Rnas

scholarly journals Continuous salt stress-induced long non-coding RNAs and DNA methylation patterns in soybean roots

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Rui Chen ◽  
Ming Li ◽  
Huiyuan Zhang ◽  
Lijin Duan ◽  
Xianjun Sun ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Salt Stress ◽  
Bioinformatic Analysis ◽  
Protein Coding ◽  
Reduced Representation ◽  
Soybean Seedlings ◽  
A Genome ◽  
Whole Transcriptome Sequencing ◽  
Soybean Roots ◽  
Non Coding Rnas

Abstract Background Environmental stimuli can activate a series of physiological and biochemical responses in plants accompanied by extensive transcriptional reprogramming. Long non-coding RNAs (lncRNAs), as versatile regulators, control gene expression in multiple ways and participate in the adaptation to biotic and abiotic stresses. Results In this study, soybean seedlings were continuously cultured for 15 days with high salinity solutions started from seed germination. Strand-specific whole transcriptome sequencing and stringent bioinformatic analysis led to the identification of 3030 long intergenic non-coding RNAs (lincRNAs) and 275 natural antisense transcripts (lncNATs) in soybean roots. In contrast to mRNAs, newly identified lncRNAs exhibited less exons, similar AU content to UTRs, even distribution across the genome and low evolutionary conservation. Remarkably, more than 75% of discovered lncRNAs that were activated or up-regulated by continuous salt stress mainly targeted proteins with binding and catalytic activities. Furthermore, two DNA methylation maps with single-base resolution were generated by using reduced representation bisulfite sequencing, offering a genome-wide perspective and important clues for epigenetic regulation of stress-associated lncRNAs and protein-coding genes. Conclusions Taken together, our findings systematically demonstrated the characteristics of continuous salt stress-induced lncRNAs and extended the knowledge of corresponding methylation profiling, providing valuable evidence for a better understanding of how plants cope with long-term salt stress circumstances.

scholarly journals LncExpDB: an expression database of human long non-coding RNAs

2020 ◽  
Vol 49 (D1) ◽  
pp. D962-D968 ◽  
Author(s):  
Zhao Li ◽  
Lin Liu ◽  
Shuai Jiang ◽  
Qianpeng Li ◽  
Changrui Feng ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Biological Functions ◽  
Protein Coding ◽  
Web Interfaces ◽  
Functional Studies ◽  
Protein Coding Genes ◽  
Genes Expression ◽  
Wide Range ◽  
Non Coding Rnas ◽  
User Friendly

Abstract Expression profiles of long non-coding RNAs (lncRNAs) across diverse biological conditions provide significant insights into their biological functions, interacting targets as well as transcriptional reliability. However, there lacks a comprehensive resource that systematically characterizes the expression landscape of human lncRNAs by integrating their expression profiles across a wide range of biological conditions. Here, we present LncExpDB (https://bigd.big.ac.cn/lncexpdb), an expression database of human lncRNAs that is devoted to providing comprehensive expression profiles of lncRNA genes, exploring their expression features and capacities, identifying featured genes with potentially important functions, and building interactions with protein-coding genes across various biological contexts/conditions. Based on comprehensive integration and stringent curation, LncExpDB currently houses expression profiles of 101 293 high-quality human lncRNA genes derived from 1977 samples of 337 biological conditions across nine biological contexts. Consequently, LncExpDB estimates lncRNA genes’ expression reliability and capacities, identifies 25 191 featured genes, and further obtains 28 443 865 lncRNA-mRNA interactions. Moreover, user-friendly web interfaces enable interactive visualization of expression profiles across various conditions and easy exploration of featured lncRNAs and their interacting partners in specific contexts. Collectively, LncExpDB features comprehensive integration and curation of lncRNA expression profiles and thus will serve as a fundamental resource for functional studies on human lncRNAs.

The dark matter rises: the expanding world of regulatory RNAs

2013 ◽  
Vol 54 ◽  
pp. 1-16 ◽  
Author(s):  
Michael B. Clark ◽  
Anupma Choudhary ◽  
Martin A. Smith ◽  
Ryan J. Taft ◽  
John S. Mattick
Keyword(s):  
Phenotypic Diversity ◽  
Rapid Progress ◽  
Major Area ◽  
Protein Coding ◽  
Diverse Range ◽  
Protein Coding Genes ◽  
Evolutionary Innovation ◽  
Non Coding Rnas ◽  
Cellular Pathways ◽  
Regulatory Rnas

The ability to sequence genomes and characterize their products has begun to reveal the central role for regulatory RNAs in biology, especially in complex organisms. It is now evident that the human genome contains not only protein-coding genes, but also tens of thousands of non–protein coding genes that express small and long ncRNAs (non-coding RNAs). Rapid progress in characterizing these ncRNAs has identified a diverse range of subclasses, which vary widely in size, sequence and mechanism-of-action, but share a common functional theme of regulating gene expression. ncRNAs play a crucial role in many cellular pathways, including the differentiation and development of cells and organs and, when mis-regulated, in a number of diseases. Increasing evidence suggests that these RNAs are a major area of evolutionary innovation and play an important role in determining phenotypic diversity in animals.

scholarly journals The integration of activity in saline environments: problems and perspectives

2013 ◽  
Vol 40 (9) ◽  
pp. 759 ◽  
Author(s):  
John M. Cheeseman
Keyword(s):  
Salt Stress ◽  
Salt Tolerance ◽  
Stress Responses ◽  
Growth And Development ◽  
Optimal Solution ◽  
Life Cycles ◽  
Saline Environments ◽  
Lethal Shock ◽  
Whole Transcriptome Analysis ◽  
Whole Transcriptome

The successful integration of activity in saline environments requires flexibility of responses at all levels, from genes to life cycles. Because plants are complex systems, there is no ‘best’ or ‘optimal’ solution and with respect to salt, glycophytes and halophytes are only the ends of a continuum of responses and possibilities. In this review, I briefly examine seven major aspects of plant function and their responses to salinity including transporters, secondary stresses, carbon acquisition and allocation, water and transpiration, growth and development, reproduction, and cytosolic function and ‘integrity’. I conclude that new approaches are needed to move towards understanding either organismal integration or ‘salt tolerance’, especially cessation of protocols dependent on sudden, often lethal, shock treatments and the embracing of systems level resources. Some of the tools needed to understand the integration of activity and even ‘salt stress’ are already in hand, such as those for whole-transcriptome analysis. Others, ranging from discovery studies of the nature of the cytosol to expanded tool kits for proteomic, metabolomic and epigenomic studies, still need to be further developed. After resurrecting the distinction between applied stress and the resultant strain and noting that with respect to salinity, the strain is manifest in changes at all -omic levels, I conclude that it should be possible to model and quantify stress responses.

Sign in / Sign up

Export Citation Format

Share Document