Identification of Differentially Expressed Genes and Molecular Pathways Involved in Osteoclastogenesis Using RNA-seq

小桶 转录组 生物 基因 生物途径 基因表达谱 下调和上调 基因表达 代谢途径 细胞生物学 RNA序列 基因表达的系列分析 遗传学
作者
Sarah Rashid,Scott G. Wilson,Kun Zhu,John P. Walsh,Jiake Xu,Benjamin H. Mullin
出处
期刊:Genes [Multidisciplinary Digital Publishing Institute]
卷期号:14 (4): 916-916 被引量:9
标识
DOI:10.3390/genes14040916
摘要

Osteoporosis is a disease that is characterised by reduced bone mineral density (BMD) and can be exacerbated by the excessive bone resorption of osteoclasts (OCs). Bioinformatic methods, including functional enrichment and network analysis, can provide information about the underlying molecular mechanisms that participate in the progression of osteoporosis. In this study, we harvested human OC-like cells differentiated in culture and their precursor peripheral blood mononuclear cells (PBMCs) and characterised the transcriptome of the two cell types using RNA-sequencing in order to identify differentially expressed genes. Differential gene expression analysis was performed in RStudio using the edgeR package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify enriched GO terms and signalling pathways, with inter-connected regions characterised using protein–protein interaction analysis. In this study, we identified 3201 differentially expressed genes using a 5% false discovery rate; 1834 genes were upregulated, whereas 1367 genes were downregulated. We confirmed a significant upregulation of several well-established OC genes including CTSK, DCSTAMP, ACP5, MMP9, ITGB3, and ATP6V0D2. The GO analysis suggested that upregulated genes are involved in cell division, cell migration, and cell adhesion, while the KEGG pathway analysis highlighted oxidative phosphorylation, glycolysis and gluconeogenesis, lysosome, and focal adhesion pathways. This study provides new information about changes in gene expression and highlights key biological pathways involved in osteoclastogenesis.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
CodeCraft应助倩倩采纳,获得10
刚刚
安小敏发布了新的文献求助10
1秒前
欢呼的棒棒糖完成签到,获得积分10
1秒前
adamchris发布了新的文献求助10
1秒前
科研通AI6应助fsxadada123采纳,获得30
1秒前
2秒前
Lucas应助何以载道采纳,获得10
2秒前
qq发布了新的文献求助10
3秒前
不器君发布了新的文献求助10
3秒前
斜阳正浓发布了新的文献求助10
4秒前
光仔发布了新的文献求助30
5秒前
平淡半山完成签到,获得积分10
5秒前
想去快乐里躲躲完成签到,获得积分10
5秒前
ZJX完成签到,获得积分10
6秒前
cc发布了新的文献求助10
6秒前
6秒前
无敌通发布了新的文献求助10
7秒前
DC-CIK军团完成签到 ,获得积分10
7秒前
JamesPei应助dls采纳,获得10
9秒前
我是老大应助不器君采纳,获得10
9秒前
piggybunny完成签到,获得积分10
10秒前
luckly发布了新的文献求助20
10秒前
风中大楚完成签到,获得积分10
11秒前
bkagyin应助三无采纳,获得10
12秒前
12秒前
12秒前
reed1220发布了新的文献求助10
13秒前
YamKinWah发布了新的文献求助10
13秒前
14秒前
蓝韵完成签到,获得积分10
15秒前
15秒前
15秒前
squrreil发布了新的文献求助10
15秒前
wxy完成签到,获得积分10
16秒前
17秒前
yy发布了新的文献求助30
17秒前
倩倩发布了新的文献求助10
17秒前
18秒前
Akim应助隔壁海绵宝宝采纳,获得30
18秒前
jennyyu完成签到,获得积分10
20秒前
高分求助中
Comprehensive Toxicology Fourth Edition 24000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
LRZ Gitlab附件(3D Matching of TerraSAR-X Derived Ground Control Points to Mobile Mapping Data 附件) 2000
Pipeline and riser loss of containment 2001 - 2020 (PARLOC 2020) 1000
World Nuclear Fuel Report: Global Scenarios for Demand and Supply Availability 2025-2040 800
Handbook of Social and Emotional Learning 800
The Social Work Ethics Casebook(2nd,Frederic G. R) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5132036
求助须知:如何正确求助?哪些是违规求助? 4333560
关于积分的说明 13501173
捐赠科研通 4170621
什么是DOI,文献DOI怎么找? 2286445
邀请新用户注册赠送积分活动 1287303
关于科研通互助平台的介绍 1228340