lncRNA DLEU2 acts as a miR-181a sponge to regulate SEPP1 and inhibit skeletal muscle differentiation and regeneration

Wang, Yao; Zhao, Zhi-hui; Kang, Xueran; Bian, Tao; Shen, Zan; Jiang, Yang; Sun, Bei; Hu, Han-Bing; Chen, Yisheng

doi:10.18632/aging.104095

Cited by 41 publications

(42 citation statements)

References 74 publications

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“…We focused on the top 20 genes with transcriptome P -values. Nine of these genes, including BCAP31 ( 48 ), CD59 ( 49 ), EGF ( 50 ), GLUL ( 51 ), GOT1 ( 52 ), MYBPC1 ( 53 ), PDK4 ( 54 ), PVALB ( 55 ), and SHISA2 ( 56 ), have been reported to be involved in muscle development. Five genes, namely ASNS ( 57 ), CARNS1 ( 58 ), G0S2 ( 59 ), PPP1R14C ( 60 , 61 ), and SH3BP5 ( 62 ), have been reported to be potentially associated with muscle development.…”

Section: Discussionmentioning

confidence: 99%

Integrative ATAC-seq and RNA-seq Analysis of the Longissimus Muscle of Luchuan and Duroc Pigs

Miao

Tang

et al. 2021

Front. Nutr.

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Luchuan pig is a typical obese pig breed in China, and the diameter and area of its longissimus dorsi muscle fibers are significantly smaller than those of Duroc (lean) pig. Skeletal muscle fiber characteristics are related to meat quality of livestock. There is a significant correlation between the quality of different breeds of pork and the characteristics of muscle fiber, which is an important factor affecting the quality of pork. The diameter and area of muscle fibers are related to muscle growth and development. Therefore, we used the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing (RNA-seq) analysis to investigate the potential mechanism underlying the difference in skeletal muscle growth and development between the two types of pigs. First, transposase-accessible chromatin was analyzed to map the landscape of open chromatin regions and transcription factor binding sites. We identified several transcription factors that potentially affected muscle growth and development, including TFAP4, MAX, NHLH1, FRX5, and TGIF1. We also found that transcription factors with basic helix-loop-helix structures had a preference for binding to genes involved in muscle development. Then, by integrating ATAC-seq and RNA-seq, we found that the Wnt signaling pathway, the mTOR signaling pathway, and other classical pathways regulate skeletal muscle development. In addition, some pathways that might regulate skeletal muscle growth, such as parathyroid hormone synthesis, secretion, and action, synthesis and degradation of ketone bodies, and the thyroid hormone signaling pathway, which were significantly enriched. After further study, we identified a number of candidate genes (ASNS, CARNS1, G0S2, PPP1R14C, and SH3BP5) that might be associated with muscle development. We also found that the differential regulation of chromatin openness at the level of some genes was contrary to the differential regulation at the level of transcription, suggesting that transcription factors and transcriptional repressors may be involved in the regulation of gene expression. Our study provided an in-depth understanding of the mechanism behind the differences in muscle fibers from two species of pig and provided an important foundation for further research on improving the quality of pork.

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Section: Discussionmentioning

confidence: 99%

Integrative ATAC-seq and RNA-seq Analysis of the Longissimus Muscle of Luchuan and Duroc Pigs

Miao

Tang

et al. 2021

Front. Nutr.

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“…LASSO regression has more advantages than ridge regression in terms of variable selection. Therefore, we choose LASSO regression to filter the variables as reported in a previous study [29]. ROC curves were used for visualization of AUC values to assess the accuracy of the model [30].…”

Section: Discussionmentioning

confidence: 99%

A Prediction Model for Cognitive Impairment Risk in Colorectal Cancer after Chemotherapy Treatment

Zhou

Fei

Han

et al. 2021

BioMed Research International

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Background. A prediction model can be developed to predict the risk of cancer-related cognitive impairment in colorectal cancer patients after chemotherapy. Methods. A regression analysis was performed on 386 colorectal cancer patients who had undergone chemotherapy. Three prediction models (random forest, logistic regression, and support vector machine models) were constructed using collected clinical and pathological data of the patients. Calibration and ROC curves and C -indexes were used to evaluate the selected models. A decision curve analysis (DCA) was used to determine the clinical utility of the line graph. Results. Three prediction models including a random forest, a logistic regression, and a support vector machine were constructed. The logistic regression model had the strongest predictive power with an area under the curve (AUC) of 0.799. Age, BMI, colostomy, complications, CRA, depression, diabetes, QLQ-C30 score, exercise, hypercholesterolemia, diet, marital status, education level, and pathological stage were included in the nomogram. The C -index (0.826) and calibration curve showed that the nomogram had good predictive ability and the DCA curves indicated that the model had strong clinical utility. Conclusions. A prediction model with good predictive ability and practical clinical value can be developed for predicting the risk of cognitive impairment in colorectal cancer after chemotherapy.

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“…Another study reported that LOC541471 is a novel prognostic biomarker for head and neck squamous cell carcinoma [32]. The leukaemia 2 gene (DLEU2) has been reported to play an important role in a variety of diseases [33,34], especially in tumour diseases, including thyroid cancer, gastric cancer, sarcopenia, and laryngeal squamous cell carcinoma, and has been shown to play a role through the ceRNA mechanism [35][36][37][38].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of the Long Noncoding RNA‑associated Competitive Endogenous RNA Network in the Osteogenic Differentiation of Periodontal Ligament Stem Cells

Lai¹,

Wang

Qiu

et al. 2021

Preprint

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BACKGROUDThe mechanism implicated in the osteoblast differentiation of human periodontal ligament stem cells (PDLSCs) has been investigated for years. Previous genomics data analyses showed that long noncoding RNA (lncRNA), microRNA (miRNA) and messenger RNA (mRNA) have significant expression differences between induced and control human PDLSCs. Competing for endogenous RNAs (ceRNA), as a widely studied mechanism in regenerative medicine, while rarely reported in periodontal regeneration. The key lncRNAs and their ceRNA network might provide new insights into molecular therapies of periodontal regeneration based on PDLSCs.RESULTSTwo networks reflecting the relationships among differentially expressed RNAs were constructed. One ceRNA network was composed of 6 upregulated lncRNAs, 280 upregulated mRNAs, and 18 downregulated miRNAs. The other network contained 33 downregulated lncRNAs, 73 downregulated mRNAs, and 5 upregulated miRNAs. Functional analysis revealed that 38 GO terms and 8 pathways related with osteogenesis were enriched. Twenty-four osteogenesis-related gene-centred lncRNA-associated ceRNA networks were successfully constructed. Among these pathways, we highlighted MAPK and TGF-beta pathways that are closely related to osteogenesis. Subsequently, subnetworks potentially linking the GO:0001649 (osteoblast differentiation), MAPK and TGF-beta pathways were constructed. The qRT-PCR validation results were consistent with the microarray analysis.CONCLUSIONWe construct a comprehensively identified lncRNA-associated ceRNA network might be involved in the osteogenesis differentiation of PDLSCs, which could provide insights into the regulatory mechanisms and treatment targets of periodontal regeneration.

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lncRNA DLEU2 acts as a miR-181a sponge to regulate SEPP1 and inhibit skeletal muscle differentiation and regeneration

Cited by 41 publications

References 74 publications

Integrative ATAC-seq and RNA-seq Analysis of the Longissimus Muscle of Luchuan and Duroc Pigs

Integrative ATAC-seq and RNA-seq Analysis of the Longissimus Muscle of Luchuan and Duroc Pigs

A Prediction Model for Cognitive Impairment Risk in Colorectal Cancer after Chemotherapy Treatment

Comprehensive Analysis of the Long Noncoding RNA‑associated Competitive Endogenous RNA Network in the Osteogenic Differentiation of Periodontal Ligament Stem Cells

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