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 Genome-wide identification and characterization of long non-coding RNAs responsive to Dickeya zeae in rice

RSC Advances ◽  
2018 ◽  
Vol 8 (60) ◽  
pp. 34408-34417 ◽  
Author(s):  
Wen Qi Li ◽  
Yu Lin Jia ◽  
Feng Quan Liu ◽  
Fang Quan Wang ◽  
Fang Jun Fan ◽  
...  
Keyword(s):  
Stress Responses ◽  
Critical Role ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Epigenetic Regulator ◽  
Non Coding Rnas ◽  
Growth Development ◽  
Long Non Coding Rna ◽  
Identification And Characterization

Plant long non-coding RNA (lncRNA) is a type of newly emerging epigenetic regulator playing a critical role in plant growth, development, and biotic stress responses.

scholarly journals Genome-wide characterization of coding and non-coding RNAs in the ovary of honeybee workers and queens

Apidologie ◽  
2020 ◽  
Vol 51 (5) ◽  
pp. 777-792
Author(s):  
Xiao Chen ◽  
Wei Shi
Keyword(s):  
Egg Laying ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Competing Endogenous Rna ◽  
Genome Wide ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Virgin Queens ◽  
Potential Interactions

Abstract Adult honeybee queens and workers drastically differ in ovary state and ovary size. However, this reproductive bias is only partially understood from the view of a single RNA type. In this study, we predicted 10,271 mRNAs, 7235 lncRNAs, 11,794 circRNAs, and 164 miRNAs in the ovary of honeybee workers through bioinformatics. Combining RNA sequencing data of honeybee virgin queens, 4385 mRNAs, 2390 lncRNAs, 5602 circRNAs, and 75 miRNAs were differentially expressed in workers compared with virgins. Compared with egg-laying queens, 6536 mRNAs, 3130 lncRNAs, 5751 circRNAs, and 81 miRNAs were differentially expressed in workers. Further, functional annotation revealed that neural regulation was closely related to ovary state. Moreover, the potential interactions among circRNAs, miRNAs, lncRNAs, and mRNAs revealed that vitellogenin, ecdysone-induced protein 74, ame_circ_0001176, and ame_circ_0001243 might play critical roles in the competing endogenous RNA network. These findings suggest that the integrative RNA networks have potential effects in ovarian phenotype differences in honeybees.

scholarly journals Genome-Wide Identification and Characterization of MicroRNAs and Target Genes in Lonicera japonica

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164140 ◽  
Author(s):  
Heng Xia ◽  
Libin Zhang ◽  
Gang Wu ◽  
Chunhua Fu ◽  
Yan Long ◽  
...  
Keyword(s):  
Target Genes ◽  
Lonicera Japonica ◽  
Genome Wide ◽  
Identification And Characterization

scholarly journals Identification and Characterization of the Glutathione Peroxidase (GPX) Gene Family in Watermelon and Its Expression under Various Abiotic Stresses

Agronomy ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 206 ◽  
Author(s):  
Yong Zhou ◽  
Jingwen Li ◽  
Junhong Wang ◽  
Wenting Yang ◽  
Youxin Yang
Keyword(s):  
Abiotic Stress ◽  
Glutathione Peroxidase ◽  
Regulatory Elements ◽  
Promoter Regions ◽  
Cis Acting ◽  
Genome Wide ◽  
A Genome ◽  
Identification And Characterization ◽  
Lower Expression

Plant glutathione peroxidase (GPX) is an important antioxidant enzyme to maintain H2O2 homeostasis and regulate plant response to abiotic stress. In this paper, we present the first report of a genome-wide identification of GPX genes in watermelon. A total of six genes (ClGPX1–ClGPX6) were identified, which were unevenly located on four chromosomes of the watermelon genome. Based on phylogenetic analysis, the GPX genes of Arabidopsis, rice, cucumber, and sorghum were classified into four groups. Through analyzing the promoter regions of ClGPX genes, many development-, stress-, and hormone-responsive cis-acting regulatory elements were also identified. Expression pattern analysis by qRT-PCR indicated that all ClGPX genes were actively expressed in flowers and fruits, and exhibited relatively lower expression in other tissues, particularly roots and stems. In addition, the expression of ClGPX genes was significantly induced by salt, drought, and cold stresses, as well as abscisic acid (ABA) treatment at different time points, suggesting that they may be involved in response to abiotic stress and ABA. Taken together, our findings demonstrated that ClGPX genes might function in watermelon development, especially in flower and fruit tissue, as well as in response to abiotic stress and hormones.

Genome-wide identification and characterization of long non-coding RNAs during differentiation of visceral preadipocytes in rabbit

2019 ◽  
Vol 20 (3) ◽  
pp. 409-419 ◽  
Author(s):  
Kun Du ◽  
Guo-Ze Wang ◽  
An-yong Ren ◽  
Ming-cheng Cai ◽  
Gang Luo ◽  
...  
Keyword(s):  
Genome Wide ◽  
Non Coding Rnas ◽  
Identification And Characterization
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