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Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis

Background: Rheumatoid arthritis (RA) is a disabling autoimmune disease that affects multiple joints. Accumulating evidence suggests that imbalances in liquid–liquid phase separation (LLPS) can lead to altered spatiotemporal coordination of biomolecular condensates, which play important roles in car...

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Autores principales: Tai, Jiaojiao, Wang, Linbang, Yan, Ziqiang, Liu, Jingkun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634374/
https://www.ncbi.nlm.nih.gov/pubmed/37953920
http://dx.doi.org/10.3389/fgene.2023.1210722
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author Tai, Jiaojiao
Wang, Linbang
Yan, Ziqiang
Liu, Jingkun
author_facet Tai, Jiaojiao
Wang, Linbang
Yan, Ziqiang
Liu, Jingkun
author_sort Tai, Jiaojiao
collection PubMed
description Background: Rheumatoid arthritis (RA) is a disabling autoimmune disease that affects multiple joints. Accumulating evidence suggests that imbalances in liquid–liquid phase separation (LLPS) can lead to altered spatiotemporal coordination of biomolecular condensates, which play important roles in carcinogenesis and inflammatory diseases. However, the role of LLPS in the development and progression of RA remains unclear. Methods: We screened RA and normal samples from GSE12021, GSE55235, and GSE55457 transcriptome datasets and GSE129087 and GSE109449 single-cell sequencing datasets from Gene Expression Omnibus database to investigate the pathogenesis of LLPS-related hub genes at the transcriptome and single cell sequencing levels. Machine learning algorithms and weighted gene co-expression network analysis were applied to screen hub genes, and hub genes were validated using correlation studies. Results: Differential analysis showed that 36 LLPS-related genes were significantly differentially expressed in RA, further random forest and support vector machine identified four and six LLPS-related genes, respectively, and weighted gene co-expression network analysis identified 396 modular genes. Hybridization of the three sets revealed two hub genes, MYC and MAP1LC3B, with AUCs of 0.907 and 0.911, respectively. Further ROC analysis of the hub genes in the GSE55457 dataset showed that the AUCs of MYC and MAP1LC3B were 0.815 and 0.785, respectively. qRT-PCR showed that the expression of MYC and MAP1LC3B in RA synovial tissues was significantly lower than that in the normal control synovial tissues. Correlation analysis between hub genes and the immune microenvironment and single-cell sequencing analysis revealed that both MYC and MAP1LC3B were significantly correlated with the degree of infiltration of various innate and acquired immune cells. Conclusion: Our study reveals a possible mechanism for LLPS in RA pathogenesis and suggests that MYC and MAP1LC3B may be potential novel molecular markers for RA with immunological significance.
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spelling pubmed-106343742023-11-10 Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis Tai, Jiaojiao Wang, Linbang Yan, Ziqiang Liu, Jingkun Front Genet Genetics Background: Rheumatoid arthritis (RA) is a disabling autoimmune disease that affects multiple joints. Accumulating evidence suggests that imbalances in liquid–liquid phase separation (LLPS) can lead to altered spatiotemporal coordination of biomolecular condensates, which play important roles in carcinogenesis and inflammatory diseases. However, the role of LLPS in the development and progression of RA remains unclear. Methods: We screened RA and normal samples from GSE12021, GSE55235, and GSE55457 transcriptome datasets and GSE129087 and GSE109449 single-cell sequencing datasets from Gene Expression Omnibus database to investigate the pathogenesis of LLPS-related hub genes at the transcriptome and single cell sequencing levels. Machine learning algorithms and weighted gene co-expression network analysis were applied to screen hub genes, and hub genes were validated using correlation studies. Results: Differential analysis showed that 36 LLPS-related genes were significantly differentially expressed in RA, further random forest and support vector machine identified four and six LLPS-related genes, respectively, and weighted gene co-expression network analysis identified 396 modular genes. Hybridization of the three sets revealed two hub genes, MYC and MAP1LC3B, with AUCs of 0.907 and 0.911, respectively. Further ROC analysis of the hub genes in the GSE55457 dataset showed that the AUCs of MYC and MAP1LC3B were 0.815 and 0.785, respectively. qRT-PCR showed that the expression of MYC and MAP1LC3B in RA synovial tissues was significantly lower than that in the normal control synovial tissues. Correlation analysis between hub genes and the immune microenvironment and single-cell sequencing analysis revealed that both MYC and MAP1LC3B were significantly correlated with the degree of infiltration of various innate and acquired immune cells. Conclusion: Our study reveals a possible mechanism for LLPS in RA pathogenesis and suggests that MYC and MAP1LC3B may be potential novel molecular markers for RA with immunological significance. Frontiers Media S.A. 2023-10-25 /pmc/articles/PMC10634374/ /pubmed/37953920 http://dx.doi.org/10.3389/fgene.2023.1210722 Text en Copyright © 2023 Tai, Wang, Yan and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Tai, Jiaojiao
Wang, Linbang
Yan, Ziqiang
Liu, Jingkun
Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title_full Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title_fullStr Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title_full_unstemmed Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title_short Single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
title_sort single-cell sequencing and transcriptome analyses in the construction of a liquid–liquid phase separation-associated gene model for rheumatoid arthritis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634374/
https://www.ncbi.nlm.nih.gov/pubmed/37953920
http://dx.doi.org/10.3389/fgene.2023.1210722
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