[Objectives]This study was conducted to investigate characteristics of the human TCF7 L2 gene promoter.[Methods]The 2000 bp sequence of the 5’regulatory region of the human TCF7 L2 gene was obtained from the UCSC gen...[Objectives]This study was conducted to investigate characteristics of the human TCF7 L2 gene promoter.[Methods]The 2000 bp sequence of the 5’regulatory region of the human TCF7 L2 gene was obtained from the UCSC genome database.The promoter,transcription factor binding sites,CpG islands,SNPs and so on were analyzed by a variety of online softwares.[Results]The bioinformatics analysis results showed there were at least 5 potential promoters in the positive-sense strand of the 2000 bp sequence,among which-242--192 bp,-853--803 bp might contain core promoters.A TATA box and a CpG island with a length of 499 bp were found.241,944 and 1035(positive-sense strand)transcription factor binding sites were predicted by the AliBaba2.1,PROMO and JASPAR softwares,respectively.207 common transcription factor binding sites in the conserved region of human and mouse homologous TCF7 L2 gene promoter were identified with CONREAL program,involving 66 kinds of transcription factors.Two SNPs were found in the promoter region.[Conclusions]The promoter of the human TCF7 L2 gene was analyzed by bioinformatics,and the promoter characteristics were obtained.展开更多
Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple t...Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.展开更多
Gene transcriptional regulation research is one of the major challenges in the post-genome era. Bioinformatics has become more important with the rapid accumulation of complete genome sequences and the advances of com...Gene transcriptional regulation research is one of the major challenges in the post-genome era. Bioinformatics has become more important with the rapid accumulation of complete genome sequences and the advances of computational methods and related databases. The current computational approaches in promoter prediction, transcription factor binding site identification, composite elements prediction, co-regulation of gene expression analysis and phylogenetic footprinting in the regulatory region analysis are discussed in this review.展开更多
基金the Diabetes Special Fund Project of Hubei University of Science and Technology(2016-18XZ12)。
文摘[Objectives]This study was conducted to investigate characteristics of the human TCF7 L2 gene promoter.[Methods]The 2000 bp sequence of the 5’regulatory region of the human TCF7 L2 gene was obtained from the UCSC genome database.The promoter,transcription factor binding sites,CpG islands,SNPs and so on were analyzed by a variety of online softwares.[Results]The bioinformatics analysis results showed there were at least 5 potential promoters in the positive-sense strand of the 2000 bp sequence,among which-242--192 bp,-853--803 bp might contain core promoters.A TATA box and a CpG island with a length of 499 bp were found.241,944 and 1035(positive-sense strand)transcription factor binding sites were predicted by the AliBaba2.1,PROMO and JASPAR softwares,respectively.207 common transcription factor binding sites in the conserved region of human and mouse homologous TCF7 L2 gene promoter were identified with CONREAL program,involving 66 kinds of transcription factors.Two SNPs were found in the promoter region.[Conclusions]The promoter of the human TCF7 L2 gene was analyzed by bioinformatics,and the promoter characteristics were obtained.
基金supported by funds from the National Key R&D Program of China (2016YFC0901603)the China 863 Program (2015AA020108)+1 种基金the State Key Laboratory of Protein and Plant Gene Researchsupported in part by the National Program for Support of Top-notch Young Professionals
文摘Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.
文摘Gene transcriptional regulation research is one of the major challenges in the post-genome era. Bioinformatics has become more important with the rapid accumulation of complete genome sequences and the advances of computational methods and related databases. The current computational approaches in promoter prediction, transcription factor binding site identification, composite elements prediction, co-regulation of gene expression analysis and phylogenetic footprinting in the regulatory region analysis are discussed in this review.
