Bioinformatics approaches to predict target genes from transcription factor binding data

Essebier, Alexandra; Lamprecht, Marnie L.; Piper, Michael; Bodén, Mikael

doi:10.1016/j.ymeth.2017.09.001

Cited by 10 publications

(7 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TFs are a group of protein molecules that could bind to the specific sequence of target genes and regulate gene expression at a time and space specific manner. By analyzing the characteristic of validated binding sites of TFs, we could predict the target gene by computational approaches [23]. Bioinformatic analysis method displayed important role in predicting new TFs and biomarkers in many diseases.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic identification of hub genes and related transcription factors in low shear stress treated endothelial cells

Yang

2021

BMC Med Genomics

View full text Add to dashboard Cite

Background Recent evidences indicated that shear stress is critical in orchestrating gene expression in cardiovascular disease. It is necessary to identify the mechanism of shear stress influencing gene expression in physiology and pathophysiology conditions. This paper aimed to identify candidate hub genes and its transcription factors with bioinformatics. Methods We analyzed microarray expression profile of GSE16706 to identify differentially expressed genes (DEGs) in low shear stress (1 dyne/cm2) treated human umbilical vein endothelial cells (HUVECs) compared with static condition for 24 h. Results 652 DEGs, including 333 up-regulated and 319 down-regulated DEGs, were screen out. Functional enrichment analysis indicated enrichment items mainly included cytokine-cytokine receptor interaction and cell cycle. Five hub genes (CDC20, CCNA2, KIF11, KIF2C and PLK1) and one significant module (score = 17.39) were identified through protein–protein interaction (PPI) analysis. Key transcriptional factor FOXC1 displayed close interaction with all the hub genes via gene-transcriptional factor network. Single-gene GSEA analysis indicated that CDC20 was linked to the G2M_CHECKPOINT pathway and cell cycle pathway. Conclusions By using integrated bioinformatic analysis, a new transcriptional factor and hub-genes network related to HUVECs treated with low shear stress were identified. The new regulation mechanism we discovered may be a promising potential therapeutic target for cardiovascular disease.

show abstract

Section: Discussionmentioning

confidence: 99%

Bioinformatic identification of hub genes and related transcription factors in low shear stress treated endothelial cells

Yang

2021

BMC Med Genomics

View full text Add to dashboard Cite

show abstract

“…23 Transcription factors have been elucidated to mediate gene expression and are involved in the regulation of proliferative status, cellular differentiation and cell fate. 24 LncRNAs usually recruit these proteins forming RNP complex and specifically binding to the promoter region of target genes. For instance, the regulatory role of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in cell cycle progression is facilitated via the oncogenic transcription factor B-MYB.…”

Section: Discussionmentioning

confidence: 99%

Knockdown of long non‐coding RNA LINC00176 suppresses ovarian cancer progression by BCL3‐mediated down‐regulation of ceruloplasmin

Dai

Niu

Feng

2019

J Cellular Molecular Medi

View full text Add to dashboard Cite

Ovarian cancer is a common malignancy among women with some clinically approved diagnostic coding gene biomarkers. However, long non‐coding RNAs (lncRNAs) have been indicated to play an important role in controlling tumorigenesis of ovarian cancer. Hereby, the aim of the study was to uncover the function of lncRNA LINC00176 in the development and progression of ovarian cancer by regulating ceruloplasmin (CP). Bioinformatics prediction in combination with RT‐qPCR analysis for the expression pattern of LINC00176 revealed that LINC00176 was highly expressed in ovarian cancer tissues as well as in ovarian cancer cell lines, respectively. LINC00176 was predominantly localized in the nucleus. Delivery of si‐LINC00176, oe‐LINC00176, si‐BCL3 and si‐CP plasmids was conducted to explore the effects of LINC00176 on ovarian cancer. Promoted proliferation, migration and invasion along with reduced apoptosis were observed in cells treated with oe‐LINC00176, while si‐BCL3 and si‐CP were able to block the promoting effects. Investigations with regard to the correlation between LINC00176 and promoter region of CP turned out to be positive via B‐cell CLL/lymphoma 3 (BCL3) by means of dual‐luciferase reporter gene assay, ChIP and RIP assays. Furthermore, oncogenic properties of the LINC00176/BCL3/CP axis were also demonstrated by tumour formation in vivo generated upon injecting cells in nude mice. Our results demonstrate that restored LINC00176 initiates tumorigenesis in ovarian cancer by increasing CP expression via recruiting BCL3, the mechanism of which represented a potential and promising therapeutic target for the disease.

show abstract

“…Transcription factors (TFs) are a group of DNA-binding proteins that regulate the expression of the relative genes, which play a pivotal part in plant tolerance to abiotic stress [22,23].…”

Section: Discussionmentioning

confidence: 99%

Early Response of Radish to Heat Stress by Strand-Specific Transcriptome and miRNA Analysis

Yang

Wen

et al. 2019

IJMS

View full text Add to dashboard Cite

Radish is a crucial vegetable crop of the Brassicaceae family with many varieties and large cultivated area in China. Radish is a cool season crop, and there are only a few heat tolerant radish varieties in practical production with little information concerning the related genes in response to heat stress. In this work, some physiological parameter changes of young leaves under short-term heat stress were detected. Furthermore, we acquired 1802 differentially expressed mRNAs (including encoding some heat shock proteins, heat shock factor and heat shock-related transcription factors), 169 differentially expressed lncRNAs and three differentially expressed circRNAs (novel_circ_0000265, novel_circ_0000325 and novel_circ_0000315) through strand-specific RNA sequencing technology. We also found 10 differentially expressed miRNAs (ath-miR159b-3p, athmiR159c, ath-miR398a-3p, athmiR398b-3p, ath-miR165a-5p, ath-miR169g-3p, novel_86, novel_107, novel_21 and ath-miR171b-3p) by small RNA sequencing technology. Through function prediction and enrichment analysis, our results suggested that the significantly possible pathways/complexes related to heat stress in radish leaves were circadian rhythm-plant, photosynthesis—antenna proteins, photosynthesis, carbon fixation in photosynthetic organisms, arginine and proline metabolism, oxidative phosphorylation, peroxisome and plant hormone signal transduction. Besides, we identified one lncRNA–miRNA–mRNAs combination responsive to heat stress. These results will be helpful for further illustration of molecular regulation networks of how radish responds to heat stress.

show abstract

Bioinformatics approaches to predict target genes from transcription factor binding data

Cited by 10 publications

References 63 publications

Bioinformatic identification of hub genes and related transcription factors in low shear stress treated endothelial cells

Bioinformatic identification of hub genes and related transcription factors in low shear stress treated endothelial cells

Knockdown of long non‐coding RNA LINC00176 suppresses ovarian cancer progression by BCL3‐mediated down‐regulation of ceruloplasmin

Early Response of Radish to Heat Stress by Strand-Specific Transcriptome and miRNA Analysis

Contact Info

Product

Resources

About