In Silico Analysis of Transcription Factor Repertoires and Prediction of Stress-Responsive Transcription Factors from Six Major Gramineae Plants

Abstract Background Single nucleotide polymorphisms (SNPs) in genes encoding mitotic kinases could influence development and progression of gastric cancer (GC). Methods Case-control study of nine SNPs in mitotic genes was conducted using qPCR. The study included 116 GC patients and 203 controls. In silico analysis was performed to evaluate the effects of polymorphisms on transcription factors binding sites. Results The AURKA rs1047972 genotypes (CT vs. CC: OR, 1.96; 95% CI, 1.05–3.65; p = 0.033; CC + TT vs. CT: OR, 1.94; 95% CI, 1.04–3.60; p = 0.036) and rs911160 (CC vs. GG: OR, 5.56; 95% CI, 1.24–24.81; p = 0.025; GG + CG vs. CC: OR, 5.26; 95% CI, 1.19–23.22; p = 0.028), were associated with increased GC risk, whereas certain rs8173 genotypes (CG vs. CC: OR, 0.60; 95% CI, 0.36–0.99; p = 0.049; GG vs. CC: OR, 0.38; 95% CI, 0.18–0.79; p = 0.010; CC + CG vs. GG: OR, 0.49; 95% CI, 0.25–0.98; p = 0.043) were protective. Association with increased GC risk was demonstrated for AURKB rs2241909 (GG + AG vs. AA: OR, 1.61; 95% CI, 1.01–2.56; p = 0.041) and rs2289590 (AC vs. AA: OR, 2.41; 95% CI, 1.47–3.98; p = 0.001; CC vs. AA: OR, 6.77; 95% CI, 2.24–20.47; p = 0.001; AA+AC vs. CC: OR, 4.23; 95% CI, 1.44–12.40; p = 0.009). Furthermore, AURKC rs11084490 (GG + CG vs. CC: OR, 1.71; 95% CI, 1.04–2.81; p = 0.033) was associated with increased GC risk. A combined analysis of five SNPs, associated with an increased GC risk, detected polymorphism profiles where all the combinations contribute to the higher GC risk, with an OR increased 1.51-fold for the rs1047972(CT)/rs11084490(CG + GG) to 2.29-fold for the rs1047972(CT)/rs911160(CC) combinations. In silico analysis for rs911160 and rs2289590 demonstrated that different transcription factors preferentially bind to polymorphic sites, indicating that AURKA and AURKB could be regulated differently depending on the presence of particular allele. Conclusions Our results revealed that AURKA (rs1047972 and rs911160), AURKB (rs2241909 and rs2289590) and AURKC (rs11084490) are associated with a higher risk of GC susceptibility. Our findings also showed that the combined effect of these SNPs may influence GC risk, thus indicating the significance of assessing multiple polymorphisms, jointly. The study was conducted on a less numerous but ethnically homogeneous Bosnian population, therefore further investigations in larger and multiethnic groups and the assessment of functional impact of the results are needed to strengthen the findings.

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A clinical and in-silico analysis of hsa-miR-21 and Growth Differentiation factor-15 expression in Diabetic Nephropathy

10.21203/rs.3.rs-396068/v1 ◽

2021 ◽

Author(s):

Riddhi Girdhar Agarwal ◽

Purvi Purohit ◽

Manoj Khokhar ◽

Anupama Modi ◽

Nitin Kumar Bajpai ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Transcription Factors ◽

In Silico ◽

Clinical Chemistry ◽

In Silico Analysis ◽

Healthy Controls ◽

Ppi Network ◽

Renal Disorder ◽

Stage Renal Disease ◽

Silico Analysis

Abstract Background: Diabetic Nephropathy (DN), a microvascular complication, is a major cause of end-stage renal disease (ESRD). GDF-15 and hsa-miR-21 are closely associated with endothelial dysfunction and inflammation.Methods: In-silico analysis was used to identify GDF-15 and insulin related protein-protein interaction (PPI) network and a common set of GDF-15 regulating transcription factors. Common targeting miRNA of GDF-15 regulating transcription factors were investigated in miRNet and TargetScan. Further, 30 type 2 DN patients and 30 healthy controls were included for clinical chemistry analysis, to analyze serum GDF-15 levels by ELISA and to evaluate the fold change expression (FCE) of circulating hsa-miR-21 by RT-PCR.Results: In the PPI network of IRS1, IRS2, INSR, IGF1R, INS, AKT1, PPARG, CEBPB, EGR1, TP53, KLF4, ATF3, GDF15, TWIST2, the common nodes between insulin and GDF-15 were identified. MicroRNA-21 was bioinformatically observed to directly target GDF-15 downregulating transcription factors KLF4, TP-53, and CEBPB. Serum GDF-15 was nearly ten (10) folds higher in DN patients (p˂0.0001) as compared to healthy controls. A positive and significant correlation of serum GDF-15 was found with HbA1c, HOMA-IR, serum urea and serum creatinine. The FCE of hsa-miR-21 was 9.18 folds higher in DN patients. Conclusion: Raised serum GDF-15 and circulating hsa-miR-21 can serve as clinically important therapeutic targets and biomarkers of progressive renal disorder.

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IN SILICO ANALYSIS OF THE Dof TRANSCRIPTION FACTOR FAMILY IN Coffea canephora

Colloquium Agrariae ◽

10.5747/ca.2018.v14.n4.a253 ◽

2018 ◽

Vol 14 (4) ◽

pp. 99-111

Author(s):

Vinícius Garcia ◽

Alessandra Ferreira Ribas ◽

Luiz Gonzaga Esteves Vieira ◽

Tiago Benedito dos Santos

Keyword(s):

Transcription Factor ◽

Dna Binding ◽

In Silico ◽

In Silico Analysis ◽

Coffea Canephora ◽

Transcription Factor Family ◽

Dof Transcription Factor ◽

Silico Analysis

A família Dof(DNA-binding with One Finger) é um grupo de fatores de transcrição que desempenham papéis importantes no crescimento, desenvolvimento e na resposta das plantas aos estresses bióticos e abióticos. Os genes Dofforam identificados e caracterizados em várias espécies de plantas;entretanto até o presente momento não há informações sobre esses genes em café. No presente estudo foram identificados 24 membros da família Dofno genoma de C. canephoradepositados no banco de dados Coffee Genome Hub. Análises sistemáticas de bioinformática foram realizadas para caracterizar os genes DofemC. canephora, incluindo a análise desequênciasgenômicas, domínios proteicos conservados, localizações subcelulares, relações filogenéticas e perfis de expressão gênica em diferentes tecidos. Os resultados obtidos fornecem uma melhor compreensãosobre a família dos genes CcDofpermitindo projetar experimentos futuros para caracterização molecular dessesgenes no cafeeiro.

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