RESUMEN
Adipogenesis, the developmental process of progenitor-cell differentiating into adipocytes, leads to fat metabolic disorders. Alternative splicing (AS), a ubiquitous regulatory mechanism of gene expression, allows the generation of more than one unique messenger RNA (mRNA) species from a single gene. Till now, alternative splicing events during adipogenesis from human mesenchymal stem cells (hMSCs) are not yet fully elucidated. We performed RNA-Seq coupled with bioinformatics analysis to identify the differentially expressed AS genes and events during adipogenesis from hMSCs. A global survey separately identified 1262, 1181, 1167, and 1227 ASE involved in the most common types of AS including cassette exon, alt3, and alt5, especially with cassette exon the most prevalent, at 7, 14, 21, and 28 days during adipogenesis. Interestingly, 122 differentially expressed ASE referred to 118 genes, and the three genes including ACTN1 (alt3 and cassette), LRP1 (alt3 and alt5), and LTBP4 (cassette, cassette_multi, and unknown), appeared in multiple AS types of ASE during adipogenesis. Except for all the identified ASE of LRP1 occurred in the extracellular topological domain, alt3 (84) in transmembrane domain significantly differentially expressed was the potential key event during adipogenesis. Overall, we have, for the first time, conducted the global transcriptional profiling during adipogenesis of hMSCs to identify differentially expressed ASE and ASE-related genes. This finding would provide extensive ASE as the regulator of adipogenesis and the potential targets for future molecular research into adipogenesis-related metabolic disorders.
Asunto(s)
Adipocitos/citología , Adipogénesis/genética , Empalme Alternativo/genética , Regulación de la Expresión Génica/genética , Células Madre Mesenquimatosas/citología , Actinina/genética , Células Cultivadas , Perfilación de la Expresión Génica , Humanos , Proteínas de Unión a TGF-beta Latente/genética , Proteína 1 Relacionada con Receptor de Lipoproteína de Baja Densidad/genética , Dominios Proteicos , ARN Mensajero/genética , Adulto JovenRESUMEN
BACKGROUND: Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the Kir6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic ß cell KATP channel respectively with a critical role in insulin secretion and glucose homeostasis. TCF7L2 encodes a transcription factor expressed in pancreatic ß cells that regulates insulin production and processing. Because mutations of these genes could affect insulin secretion stimulated by sulfonylureas, the aim of this study is to assess associations between molecular variants of KCNJ11, ABCC8 and TCF7L2 genes and response to sulfonylurea treatment and to predict their potential functional effects. METHODS: Based on a comprehensive literature search, we found 13 pharmacogenetic studies showing that single nucleotide polymorphisms (SNPs) located in KCNJ11: rs5219 (E23K), ABCC8: rs757110 (A1369S), rs1799854 (intron 15, exon 16 -3C/T), rs1799859 (R1273R), and TCF7L2: rs7903146 (intron 4) were significantly associated with responses to sulfonylureas. For in silico bioinformatics analysis, SIFT, PolyPhen-2, PANTHER, MutPred, and SNPs3D were applied for functional predictions of 36 coding (KCNJ11: 10, ABCC8: 24, and TCF7L2: 2; all are missense), and HaploReg v4.1, RegulomeDB, and Ensembl's VEP were used to predict functions of 7 non-coding (KCNJ11: 1, ABCC8: 1, and TCF7L2: 5) SNPs, respectively. RESULTS: Based on various in silico tools, 8 KCNJ11 missense SNPs, 23 ABCC8 missense SNPs, and 2 TCF7L2 missense SNPs could affect protein functions. Of them, previous studies showed that mutant alleles of 4 KCNJ11 missense SNPs and 5 ABCC8 missense SNPs can be successfully rescued by sulfonylurea treatments. Further, 3 TCF7L2 non-coding SNPs (rs7903146, rs11196205 and rs12255372), can change motif(s) based on HaploReg v4.1 and are predicted as risk factors by Ensembl's VEP. CONCLUSIONS: Our study indicates that a personalized medicine approach by tailoring sulfonylurea therapy of T2D patients according to their genotypes of KCNJ11, ABCC8, and TCF7L2 could attain an optimal treatment efficacy.
Asunto(s)
Diabetes Mellitus Tipo 2/genética , Canales de Potasio de Rectificación Interna/genética , Compuestos de Sulfonilurea/uso terapéutico , Receptores de Sulfonilureas/genética , Proteína 2 Similar al Factor de Transcripción 7/genética , Alelos , Biología Computacional , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Exones , Genotipo , Humanos , Insulina/metabolismo , Secreción de Insulina , Células Secretoras de Insulina , Mutación Missense , Estudios Observacionales como Asunto , Polimorfismo de Nucleótido Simple , Medicina de Precisión , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
BACKGROUND: Leptin receptor (LEPR) plays a pivotal role in the control of body weight, energy metabolism, and insulin sensitivity. Various genetic association studies were performed to evaluate associations of LEPR genetic variants with type 2 diabetes (T2D) susceptibility. METHODS: A comprehensive search was conducted to identify all eligible case-control studies for examining the associations of LEPR single nucleotide polymorphisms (SNPs) Q223R (rs1137101) and K109R (rs1137100) with T2D risk. Odds ratios (OR) and corresponding 95% confidence intervals (CIs) were used to measure the magnitudes of association. RESULTS: For Q223R, 13 studies (11 articles) consisting of a total of 4030 cases and 2844 controls, and for K109R 7 studies (7 articles) consisting of 3319 cases and 2465 controls were available. Under an allele model, Q223R was not significantly associated with T2D risk (OR = 1.09, 95% CI: 0.80-1.48, P-value = 0.5989), which was consistent with results obtained under four genotypic models (ranges: ORs 1.08-1.20, 95% CIs: 0.58-2.02 to 0.64-2.26; P-values, 0.3650-0.8177, which all exceeded multiplicity-adjusted α = 0.05/5 = 0.01). In addition, no significant association was found between K109R and T2D risk based on either an allele model (OR = 0.93, 95% CI: 0.85-1.03, P-value = 0.1868) or four genotypic models (ranges: ORs 0.81-0.99, 95% CIs: 0.67-0.86 to 0.97-1.26, P-values, 0.0207-0.8804 which all exceeded multiplicity-adjusted α of 0.01). The magnitudes of association for these two SNPs were not dramatically changed in subgroup analyses by ethnicity or sensitivity analyses. Funnel plot inspections as well as Begg and Mazumdar adjusted rank correlation test and Egger linear regression test did not reveal significant publication biases in main and subgroup analyses. Bioinformatics analysis predicted that both missense SNPs were functionally neutral and benign. CONCLUSIONS: The present meta-analysis did not detect significant genetic associations between LEPR Q223R and K109R polymorphisms and T2D risk.