AIM To identify punitive transcriptional factor binding sites(TFBS) from regulatory single nucleotide polymorphisms(rS NPs) that are significantly associated with disease.METHODS The genome-wide association studies ha...AIM To identify punitive transcriptional factor binding sites(TFBS) from regulatory single nucleotide polymorphisms(rS NPs) that are significantly associated with disease.METHODS The genome-wide association studies have provided us with nearly 6500 disease or trait-predisposing SNPs where 93% are located within non-coding regions such as gene regulatory or intergenic areas of the genome. In the regulatory region of a gene, a SNP can change the DNA sequence of a transcriptional factor(TF) motif and in turn may affect the process of gene regulation. SNP changes that affect gene expression and impact gene regulatory sequences such as promoters, enhancers, and silencers are known as rS NPs. Computational tools can be used to identify unique punitive TFBS created by rS NPs that are associated with disease or sickness. Computational analysis was used to identify punitive TFBS generated by the alleles of these rS NPs.RESULTS r SNPs within nine genes that have been significantly associated with disease or sickness were used to illustrate the tremendous diversity of punitive unique TFBS that can be generated by their alleles. The genes studied are the adrenergic, beta, receptor kinase 1, the v-akt murine thymoma viral oncogene homolog 3, the activating transcription factor 3, the type 2 demodkinase gene, the endothetal Per-Arnt-Sim domain protein 1, the lysosomal acid lipase A, the signal Transducer and Activator of Transcription 4, the thromboxane A2 receptor and the vascular endothelial growth factor A. From this sampling of SNPs among the nine genes, there are 73 potential unique TFBS generated by the common alleles comparedto 124 generated by the minor alleles indicating the tremendous diversity of potential TFs that are capable of regulating these genes.CONCLUSION From the diversity of unique punitive binding sites for TFs, it was found that some TFs play a role in the disease or sickness being studied.展开更多
A full set of disease resistance(R) candidate genes encoding nucleotide-binding sites(NBS) in a complete genome of Populus trichocarpa was identified and characterized by structural diversities,physical positions,phyl...A full set of disease resistance(R) candidate genes encoding nucleotide-binding sites(NBS) in a complete genome of Populus trichocarpa was identified and characterized by structural diversities,physical positions,phylogenetic relationships.Based on structures of N-terminal motif and leucine-rich repeat domains motif,we found 381 NBS-coding sequences with 122 non-regular NBS genes and 259 regular NBS genes that were further classified into 13 types such as TNL,CNL,NL,XNL,TN and other minor types.Meanwhile 81.9% of the NBS genes were distributed in cluster,and 81.8% of the cluster genes had duplicates.The results showed that there were many duplicate phenomenon occurred in the evolution of disease resistance genes of P.trichocarpa.After analysis of NBS standard phylogenetic tree in the genome of P.trichocarpa,the structure of tree exhibited a star topology,and the regular NBS genes were classified into 68 groups by less than 30% amino acid sequence diversity in each domain.展开更多
以谷子(Setaria italica Beauv.)抗锈病植株十里香和感锈病植株豫谷1号为材料,利用抗病基因同源序列(RGA)技术克隆谷子核苷酸结合位点(NBS)类型RGA并进行分析。共获得了3个RGA,分别命名为RUS1-1、RUS1-2、RUS1-3(Resistance against Uro...以谷子(Setaria italica Beauv.)抗锈病植株十里香和感锈病植株豫谷1号为材料,利用抗病基因同源序列(RGA)技术克隆谷子核苷酸结合位点(NBS)类型RGA并进行分析。共获得了3个RGA,分别命名为RUS1-1、RUS1-2、RUS1-3(Resistance against Uromyces setariae-italicae,RUS),它们编码的蛋白质均含有NBS类型抗病基因编码蛋白的共有特征结构域P-loop和Kinase2α。BLASTX分析结果表明,3个RGA的编码蛋白与水稻中含有NB-ARC信号传导结构域的蛋白质、NBS-LRR类型抗病基因等的编码蛋白同源性为47%～66%。聚类分析结果表明,3个RGA属于NBS-LRR类型抗病基因,且与番茄NBS-LRR类型抗病基因I2聚为一类。展开更多
文摘AIM To identify punitive transcriptional factor binding sites(TFBS) from regulatory single nucleotide polymorphisms(rS NPs) that are significantly associated with disease.METHODS The genome-wide association studies have provided us with nearly 6500 disease or trait-predisposing SNPs where 93% are located within non-coding regions such as gene regulatory or intergenic areas of the genome. In the regulatory region of a gene, a SNP can change the DNA sequence of a transcriptional factor(TF) motif and in turn may affect the process of gene regulation. SNP changes that affect gene expression and impact gene regulatory sequences such as promoters, enhancers, and silencers are known as rS NPs. Computational tools can be used to identify unique punitive TFBS created by rS NPs that are associated with disease or sickness. Computational analysis was used to identify punitive TFBS generated by the alleles of these rS NPs.RESULTS r SNPs within nine genes that have been significantly associated with disease or sickness were used to illustrate the tremendous diversity of punitive unique TFBS that can be generated by their alleles. The genes studied are the adrenergic, beta, receptor kinase 1, the v-akt murine thymoma viral oncogene homolog 3, the activating transcription factor 3, the type 2 demodkinase gene, the endothetal Per-Arnt-Sim domain protein 1, the lysosomal acid lipase A, the signal Transducer and Activator of Transcription 4, the thromboxane A2 receptor and the vascular endothelial growth factor A. From this sampling of SNPs among the nine genes, there are 73 potential unique TFBS generated by the common alleles comparedto 124 generated by the minor alleles indicating the tremendous diversity of potential TFs that are capable of regulating these genes.CONCLUSION From the diversity of unique punitive binding sites for TFs, it was found that some TFs play a role in the disease or sickness being studied.
文摘A full set of disease resistance(R) candidate genes encoding nucleotide-binding sites(NBS) in a complete genome of Populus trichocarpa was identified and characterized by structural diversities,physical positions,phylogenetic relationships.Based on structures of N-terminal motif and leucine-rich repeat domains motif,we found 381 NBS-coding sequences with 122 non-regular NBS genes and 259 regular NBS genes that were further classified into 13 types such as TNL,CNL,NL,XNL,TN and other minor types.Meanwhile 81.9% of the NBS genes were distributed in cluster,and 81.8% of the cluster genes had duplicates.The results showed that there were many duplicate phenomenon occurred in the evolution of disease resistance genes of P.trichocarpa.After analysis of NBS standard phylogenetic tree in the genome of P.trichocarpa,the structure of tree exhibited a star topology,and the regular NBS genes were classified into 68 groups by less than 30% amino acid sequence diversity in each domain.
文摘以谷子(Setaria italica Beauv.)抗锈病植株十里香和感锈病植株豫谷1号为材料,利用抗病基因同源序列(RGA)技术克隆谷子核苷酸结合位点(NBS)类型RGA并进行分析。共获得了3个RGA,分别命名为RUS1-1、RUS1-2、RUS1-3(Resistance against Uromyces setariae-italicae,RUS),它们编码的蛋白质均含有NBS类型抗病基因编码蛋白的共有特征结构域P-loop和Kinase2α。BLASTX分析结果表明,3个RGA的编码蛋白与水稻中含有NB-ARC信号传导结构域的蛋白质、NBS-LRR类型抗病基因等的编码蛋白同源性为47%～66%。聚类分析结果表明,3个RGA属于NBS-LRR类型抗病基因,且与番茄NBS-LRR类型抗病基因I2聚为一类。
