scholarly journals Genome-Wide Identification and Characterization of Fusarium circinatum-Responsive lncRNAs in Pinus radiata

2021 ◽  
Author(s):  
Cristina Zamora-Ballesteros ◽  
Jorge Martin-Garcia ◽  
Aroa Suarez-Vega ◽  
Julio Diez
Keyword(s):  
Cell Wall ◽  
Pinus Radiata ◽  
Target Genes ◽  
Early Stage ◽  
Gc Content ◽  
Fusarium Circinatum ◽  
Protein Coding ◽  
Biotic Stresses ◽  
Non Coding Rnas

One of the most promising strategies of Pine Pitch Canker (PPC) management is the use of reproductive plant material resistant to the disease. Understanding the complexity of plant transcriptome that underlies the defence to the causal agent Fusarium circinatum, would greatly facilitate the development of an accurate breeding program. Long non-coding RNAs (lncRNAs) are emerging as important transcriptional regulators under biotic stresses in plants. However, to date, characterization of lncRNAs in conifer trees has not been reported. In this study, transcriptomic identification of lncRNAs was carried out using strand-specific paired-end RNA sequencing, from Pinus radiata samples inoculated with F. circinatum at an early stage of infection. Overall, 13,312 lncRNAs were predicted through a bioinformatics approach, including long intergenic non-coding RNAs (92.3%), antisense lncRNAs (3.3%) and intronic lncRNAs (2.9%). Compared with protein-coding RNAs, pine lncRNAs are shorter, have lower expression, lower GC content and harbour fewer and shorter exons. A total of 164 differentially expressed (DE) lncRNAs were identified in response to F. circinatum infection in the inoculated versus mock-inoculated P. radiata seedlings. The predicted cis-regulated target genes of these pathogen-responsive lncRNAs were related to defence mechanisms such as kinase activity, phytohormone regulation, and cell wall reinforcement. Co-expression network analysis of DE lncRNAs, DE protein-coding RNAs and lncRNA target genes also indicated a potential network regulating pectinesterase activity and cell wall remodelling. This study presents the first analysis of conifer lncRNAs involved in the regulation of defence network and provides the basis for future functional characterizations of lncRNAs in relation to pine defence responses against F. circinatum.

scholarly journals Identification and in Silico Characterization of Novel and Conserved MicroRNAs in Methyl Jasmonate-Stimulated Scots Pine (Pinus sylvestris L.) Needles

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 384
Author(s):  
Baiba Krivmane ◽  
Ilze Šņepste ◽  
Vilnis Šķipars ◽  
Igor Yakovlev ◽  
Carl Gunnar Fossdal ◽  
...  
Keyword(s):  
Methyl Jasmonate ◽  
Scots Pine ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Stem Loop ◽  
Protein Coding ◽  
Stem Loop Structure ◽  
In Silico Characterization ◽  
Potential Precursor

MicroRNAs (miRNAs) are non-protein coding RNAs of ~20–24 nucleotides in length that play an important role in many biological and metabolic processes, including the regulation of gene expression, plant growth and developmental processes, as well as responses to stress and pathogens. The aim of this study was to identify and characterize novel and conserved microRNAs expressed in methyl jasmonate-treated Scots pine needles. In addition, potential precursor sequences and target genes of the identified miRNAs were determined by alignment to the Pinus unigene set. Potential precursor sequences were identified using the miRAtool, conserved miRNA precursors were also tested for the ability to form the required stem-loop structure, and the minimal folding free energy indexes were calculated. By comparison with miRBase, 4975 annotated sequences were identified and assigned to 173 miRNA groups, belonging to a total of 60 conserved miRNA families. A total of 1029 potential novel miRNAs, grouped into 34 families were found, and 46 predicted precursor sequences were identified. A total of 136 potential target genes targeted by 28 families were identified. The majority of previously reported highly conserved plant miRNAs were identified in this study, as well as some conserved miRNAs previously reported to be monocot specific. No conserved dicot-specific miRNAs were identified. A number of potential gymnosperm or conifer specific miRNAs were found, shared among a range of conifer species.

scholarly journals Genome-Wide Identification and Characterization of Long Non-Coding RNAs in Peanut

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 536 ◽  
Author(s):  
Xiaobo Zhao ◽  
Liming Gan ◽  
Caixia Yan ◽  
Chunjuan Li ◽  
Quanxi Sun ◽  
...  
Keyword(s):  
Large Scale ◽  
Target Genes ◽  
Sequencing Data ◽  
Regulatory Processes ◽  
Genome Wide ◽  
Non Coding Rnas ◽  
Identification And Characterization ◽  
Lower Expression ◽  
Weighted Correlation

Long non-coding RNAs (lncRNAs) are involved in various regulatory processes although they do not encode protein. Presently, there is little information regarding the identification of lncRNAs in peanut (Arachis hypogaea Linn.). In this study, 50,873 lncRNAs of peanut were identified from large-scale published RNA sequencing data that belonged to 124 samples involving 15 different tissues. The average lengths of lncRNA and mRNA were 4335 bp and 954 bp, respectively. Compared to the mRNAs, the lncRNAs were shorter, with fewer exons and lower expression levels. The 4713 co-expression lncRNAs (expressed in all samples) were used to construct co-expression networks by using the weighted correlation network analysis (WGCNA). LncRNAs correlating with the growth and development of different peanut tissues were obtained, and target genes for 386 hub lncRNAs of all lncRNAs co-expressions were predicted. Taken together, these findings can provide a comprehensive identification of lncRNAs in peanut.

scholarly journals Characterization and identification of long non-coding RNAs based on feature relationship

2018 ◽  
Author(s):  
Guangyu Wang ◽  
Hongyan Yin ◽  
Boyang Li ◽  
Chunlei Yu ◽  
Fan Wang ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
Large Scale ◽  
Gc Content ◽  
Training Data ◽  
Significant Advance ◽  
Protein Coding ◽  
Reading Frame ◽  
Wide Range ◽  
Non Coding Rnas ◽  
Computational Identification

ABSTRACTThe significance of long non-coding RNAs (lncRNAs) in many biological processes and diseases has gained intense interests over the past several years. However, computational identification of lncRNAs in a wide range of species remains challenging; it requires prior knowledge of well-established sequences and annotations or species-specific training data, but the reality is that only a limited number of species have high-quality sequences and annotations. Here we first characterize lncRNAs by contrast to protein-coding RNAs based on feature relationship and find that the feature relationship between ORF (open reading frame) length and GC content presents universally substantial divergence in lncRNAs and protein-coding RNAs, as observed in a broad variety of species. Based on the feature relationship, accordingly, we further present LGC, a novel algorithm for identifying lncRNAs that is able to accurately distinguish lncRNAs from protein-coding RNAs in a cross-species manner without any prior knowledge. As validated on large-scale empirical datasets, comparative results show that LGC outperforms existing algorithms by achieving higher accuracy, well-balanced sensitivity and specificity, and is robustly effective (>90% accuracy) in discriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals. To our knowledge, this study, for the first time, differentially characterizes lncRNAs and protein-coding RNAs based on feature relationship, which is further applied in computational identification of lncRNAs. Taken together, our study represents a significant advance in characterization and identification of lncRNAs and LGC thus bears broad potential utility for computational analysis of lncRNAs in a wide range of species.

scholarly journals Genome-wide DNA methylome analysis reveals novel epigenetically dysregulated non-coding RNAs in human breast cancer

2014 ◽  
Author(s):  
Yongsheng Li ◽  
Yunpeng Zhang ◽  
Shengli Li ◽  
Jianping Lu ◽  
Juan Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Human Breast Cancer ◽  
Target Genes ◽  
Cpg Islands ◽  
Aberrant Methylation ◽  
Breast Cancers ◽  
Human Breast ◽  
Protein Coding ◽  
Methylome Analysis ◽  
Non Coding Rnas

The development of human breast cancer is driven by changes in the genetic and epigenetic landscape of the cell. Despite growing appreciation of the importance of epigenetics in breast cancers, our knowledge of epigenetic alterations of non-coding RNAs (ncRNAs) in breast cancers remains limited. Here, we explored the epigenetic patterns of ncRNAs in breast cancers via a sequencing-based comparative methylome analysis, mainly focusing on two most popular ncRNA biotypes, long non-coding RNAs (lncRNAs) and miRNAs. Besides global hypomethylation and extensive CpG islands (CGIs) hypermethylation, we observed widely aberrant methylation in the promoters of ncRNAs, which was higher than that of protein-coding genes. Specifically, intergenic ncRNAs were observed to contribute a large slice of the aberrantly methylated ncRNA promoters. Moreover, we summarized five patterns of ncRNA promoter aberrant methylation in the context of genomic CGIs, where aberrant methylation occurred not only on the CGIs, but also flanking regions and CGI sparse promoters. Integration with transcriptional datasets, we found that the ncRNA promoter methylation events were associated with transcriptional changes. Furthermore, a panel of ncRNAs were identified as biomarkers that were able to discriminate between disease phenotypes (AUCs>0.90). Finally, the potential functions for aberrantly methylated ncRNAs were predicted based on similar patterns, adjacency and/or target genes, highlighting that ncRNAs and coding genes coordinately mediated pathways dysregulation in the development and progression of breast cancers. This study presents the aberrant methylation patterns of ncRNAs, which will be a highly valuable resource for investigations at understanding epigenetic regulation of breast cancers.

Simultaneous silencing of two target genes using virus-induced gene silencing technology in Nicotiana benthamiana

2019 ◽  
Vol 74 (5-6) ◽  
pp. 151-159
Author(s):  
Feng Zhu ◽  
Yanping Che ◽  
Fei Xu ◽  
Yangkai Zhou ◽  
Kun Qian ◽  
...  
Keyword(s):  
Gene Silencing ◽  
Nicotiana Benthamiana ◽  
Target Genes ◽  
Function Analysis ◽  
Tobacco Rattle Virus ◽  
Pcr Analysis ◽  
Virus Induced Gene Silencing ◽  
Biotic Stresses ◽  
Overlap Extension

Abstract Virus-induced gene silencing (VIGS) is an effective strategy for rapid gene function analysis. It is well established that the NAC transcription factor and salicylic acid (SA) signal pathway play essential roles in response to biotic stresses. However, simultaneous silencing of two target genes using VIGS in plants has been rarely reported. Therefore, in this report, we performed VIGS to silence simultaneously the SA-binding protein 2 (NbSABP2) and NbNAC1 in Nicotiana benthamiana to investigate the gene silencing efficiency of simultaneous silencing of two genes. We first cloned the full-length NbNAC1 gene, and the characterization of NbNAC1 was also analysed. Overlap extension polymerase chain reaction (PCR) analysis showed that the combination of NbSABP2 and NbNAC1 was successfully amplified. Bacteria liquid PCR confirmed that the combination of NbSABP2 and NbNAC1 was successfully inserted into the tobacco rattle virus vector. The results showed that the leaves from the NbSABP2 and NbNAC1 gene-silenced plants collapsed slightly, with browning at the base of petiole or veina. Quantitative real-time PCR results showed that the expression of NbSABP2 and NbNAC1 were significantly reduced in 12 days post silenced plants after tobacco rattle virus infiltration compared with the control plants. Overall, our results suggest that VIGS can be used to silence simultaneously two target genes.

scholarly journals Systematic and computational identification of Androctonus crassicauda long non-coding RNAs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Salabi ◽  
Hedieh Jafari ◽  
Shahrokh Navidpour ◽  
Ayeh Sadat Sadr
Keyword(s):  
Gc Content ◽  
Sequencing Data ◽  
Closely Related Species ◽  
Protein Coding ◽  
Model Animal ◽  
Lower Protein ◽  
Non Coding Rnas ◽  
Reference Genomes ◽  
Per Gene

AbstractThe potential function of long non-coding RNAs in regulating neighbor protein-coding genes has attracted scientists’ attention. Despite the important role of lncRNAs in biological processes, a limited number of studies focus on non-model animal lncRNAs. In this study, we used a stringent step-by-step filtering pipeline and machine learning-based tools to identify the specific Androctonus crassicauda lncRNAs and analyze the features of predicted scorpion lncRNAs. 13,401 lncRNAs were detected using pipeline in A. crassicauda transcriptome. The blast results indicated that the majority of these lncRNAs sequences (12,642) have no identifiable orthologs even in closely related species and those considered as novel lncRNAs. Compared to lncRNA prediction tools indicated that our pipeline is a helpful approach to distinguish protein-coding and non-coding transcripts from RNA sequencing data of species without reference genomes. Moreover, analyzing lncRNA characteristics in A. crassicauda uncovered that lower protein-coding potential, lower GC content, shorter transcript length, and less number of isoform per gene are outstanding features of A. crassicauda lncRNAs transcripts.

scholarly journals Discovery Function Labels Based On Numerical Features Of MicroRNA Found In Plant

2019 ◽  
Author(s):  
Rongsheng Zhu ◽  
Jinglu Liu ◽  
Dawei Xin ◽  
Zhanguo Zhang ◽  
Zhenbang Hu ◽  
...  
Keyword(s):  
Target Genes ◽  
Biological Function ◽  
Biological Process ◽  
Gc Content ◽  
Mrna Translation ◽  
Non Coding Rnas ◽  
The Difference ◽  
Post Transcriptional Regulation ◽  
Go Terms ◽  
Perl Program

AbstractMicroRNAs(miRNAs),are a class of small endogenous non-coding RNAs that play Important post-transcriptional regulation role by degrading targeted mRNAs or repressing mRNA translation. We screened 84 miRNAs belonging to 21 conserved family from 4014 miRNAs in miRBase database which distributed in 47 plant species. Of the predicted 274 target genes,42 GO terms were found in the Gene Ontology. With the 135 numerical features which extracted by perl program, the difference significantly result of ANOVA (P<0.001) and multiple comparison show that the function labels G…,GC content and Helix in biological process, cellular component and biological function, respectively. Our result have suggested a potential connection between numerical features of miRNAs and the function of target genes of miRNAs.

scholarly journals Characterization of the complete chloroplast genome sequence of Vitis vinifera ‘Guifeimeigui’

2021 ◽  
pp. 001-003
Author(s):  
Liu Li ◽  
Yang Yang ◽  
Li Xiujie ◽  
Li Bo
Keyword(s):  
Vitis Vinifera ◽  
Gc Content ◽  
Single Copy ◽  
Protein Coding ◽  
Complete Chloroplast Genome ◽  
Chloroplast Genome Sequence ◽  
Cp Genome ◽  
Eurasian Species ◽  
Rna Genes

Vitis vinifera ‘Guifeimeigui’ is a diploid table grape, a Eurasian species. This research first reported the complete chloroplast (cp) genome of Vitis vinifera ‘Guifeimeigui’. The size of the complete cp genome is 160,928 bp and its GC content is 37.38%, including a pair of inverted repeats (26,353 bp each) separated by large (89,150 bp) and small (19,072 bp) single-copy regions. It encodes 85 genes, including 40 protein coding genes, 37 transfer RNA genes (tRNA), and 8 ribosomal RNA genes (rRNA). The Maximum Likelihood (ML) phylogenetic tree demonstrated that Vitis vinifera ‘Guifeimeigui’ is close to Vitis vinifera.

scholarly journals Genome-wide identification of long non-coding RNAs in the gravid ectoparasite Varroa destructor

2020 ◽  
Author(s):  
Zheguang Lin ◽  
Yibing Liu ◽  
Xiaomei Chen ◽  
Cong Han ◽  
Wei Wang ◽  
...  
Keyword(s):  
Varroa Destructor ◽  
High Throughput Sequencing ◽  
Target Genes ◽  
Protein Coding ◽  
Genome Wide ◽  
Genomic Studies ◽  
Genetic Information Processing ◽  
Non Coding Rnas ◽  
Environmental Responses ◽  
Living Organisms

AbstractLong non-coding RNAs (lncRNAs) emerge as critical regulators with various biological functions in living organisms. However, to date, no systematic characterization of lncRNAs has been investigated in the ectoparasitic mite Varroa destructor, the most severe biotic threat to honey bees worldwide. Here, we performed an initial genome-wide identification of lncRNAs in V. destructor via high-throughput sequencing technology and reported, for the first time, the transcriptomic landscape of lncRNAs in the devastating parasite. By means of a lncRNA identification pipeline, 6,645 novel lncRNA transcripts, encoded by 3,897 gene loci, were identified, including 2,066 sense lncRNAs, 2,772 lincRNAs, and 1,807 lncNATs. Compared with protein-coding mRNAs, V. destructor lncRNAs are shorter in terms of full length, as well as of the ORF length, contain less exons, and express at lower level. GO term and KEGG pathway enrichment analyses of the lncRNA target genes demonstrated that these predicted lncRNAs are likely to play key roles in cellular processes, genetic information processing and environmental responses. To our knowledge, this is the first catalog of lncRNA profile in the parasitiformes species, providing a valuable resource for genetic and genomic studies. Understanding the characteristics and features of lncRNAs in V. destructor would promote sustainable pest control.

scholarly journals PHASIS: A computational suite for de novo discovery and characterization of phased, siRNA-generating loci and their miRNA triggers

2017 ◽  
Author(s):  
Atul Kakrana ◽  
Pingchuan Li ◽  
Parth Patel ◽  
Reza Hammond ◽  
Deepti Anand ◽  
...  
Keyword(s):  
De Novo ◽  
Sequencing Data ◽  
Protein Coding ◽  
Secondary Sirnas ◽  
Integrated Methods ◽  
Non Coding Rnas

AbstractPhased, secondary siRNAs (phasiRNAs) are found widely in plants, from protein-coding transcripts and long, non-coding RNAs; animal piRNAs are also phased. Integrated methods characterizing “PHAS” loci are unavailable, and existing methods are quite limited and inefficient in handling large volumes of sequencing data. The PHASIS suite described here provides complete tools for the computational characterization of PHAS loci, with an emphasis on plants, in which these loci are numerous. Benchmarked comparisons demonstrate that PHASIS is sensitive, highly scalable and fast. Importantly, PHASIS eliminates the requirement of a sequenced genome and PARE/degradome data for discovery of phasiRNAs and their miRNA triggers.

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