Disease-associated mutations that alter the RNA structural ensemble.
Disease-associated mutations that alter the RNA structural ensemble.
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DOI：
10.1371/journal.pgen.1001074
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发表时间：
2010-08-19
期刊：
影响因子：
4.5
通讯作者：
Laederach A
中科院分区：
文献类型：
--
作者：
Halvorsen M;Martin JS;Broadaway S;Laederach A
全基因组关联研究 (GWAS) 通常会识别基因组基因间和非编码区域中与疾病相关的突变。鉴于人类基因组被转录的比例很高，我们假设对于一些观察到的关联，疾病表型是由 RNA 转录调节区域的结构重排引起的。为了识别此类突变，我们对人类基因突变数据库 (HGMD) 中所有已知的与疾病相关的单核苷酸多态性 (SNP) 进行了全基因组分析，这些单核苷酸多态性 (SNP) 映射到基因的非翻译区 (UTR)。我们不使用最小自由能方法（例如 mFold），而是使用分配函数计算，该计算考虑了给定序列可能的 RNA 构象的集合。我们在人类基因组中发现了与疾病相关的 SNP，这些 SNP 显着改变了它们所映射的 UTR 的整体构象。对于六种疾病状态（高铁蛋白血症白内障综合征、β-地中海贫血、软骨毛发发育不全、视网膜母细胞瘤、慢性阻塞性肺疾病（COPD）和高血压），我们在 UTR 中发现了多个 SNP，这些 SNP 改变了相关基因的 mRNA 结构整体。使用玻尔兹曼采样程序来获取次优 RNA 结构，我们能够表征和可视化由结构整体中与疾病相关的突变引起的构象变化的性质。我们在几种情况下（特别是 FTL 和 RB1 的 5' UTR）观察到 SNP 诱导的构象变化，类似于特定配体结合时在细菌调节核糖开关中观察到的构象变化。我们提出，我们确定的 UTR 和 SNP 组合构成了“RiboSNitch”，这是一种调节 RNA，其中特定的 SNP 具有导致疾病表型的结构后果。我们的 SNPfold 算法可以利用 GWAS 数据和 mRNA 结构整体分析来帮助识别 RiboSNitches。全基因组关联研究识别人类基因组中与特定疾病相关的突变。在基因组的非编码区域中发现与疾病相关的突变是很常见的。这些非编码突变在分子水平上更难以解释，因为它们不影响蛋白质序列。在这项研究中，我们分析了基因组非编码区域中与疾病相关的突变对细胞中遗传信息（RNA）的结构影响。我们特别关注基因的调控部分，即非翻译区。我们发现这些调控非翻译区中的某些与疾病相关的突变对 RNA 信息的结构有显着影响。我们将这些元件称为“RiboSNitches”，因为它们的作用就像打开和关闭基因的开关，但它们是由单核苷酸多态性 (SNP) 引起的，SNP 是我们基因组中的单点突变。我们发现的 RiboSNitches 可能是一类新的药物靶标，因为它可以用类似药物的小分子改变 RNA 的结构。
Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble. Genome-wide association studies identify mutations in the human genome that correlate with a particular disease. It is common to find mutations associated with disease in the non-coding region of the genome. These non-coding mutations are more difficult to interpret at a molecular level, because they do not affect the protein sequence. In this study, we analyze disease-associated mutations in non-coding regions of our genome in the context of their structural effect on the message of genetic information in our cells, Ribonucleic Acid (RNA). We focus in particular on the regulatory parts of our genes known as untranslated regions. We find that certain disease-associated mutations in these regulatory untranslated regions have a significant effect on the structure of the RNA message. We call these elements “RiboSNitches,” because they act like switches turning on and off genes, but are caused by Single Nucleotide Polymorphisms (SNPs), which are single point mutations in our genome. The RiboSNitches we identify are potentially a new class of pharmaceutical targets, as it is possible to change the structure of RNA with small drug-like molecules.
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DOI：
10.1093/bioinformatics/btp250
发表时间：
2009-08-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Darty K;Denise A;Ponty Y
通讯作者：
Ponty Y
影响因子：
14.9
作者：
Ding, Y;Chan, CY;Lawrence, CE
通讯作者：
Lawrence, CE
影响因子：
4.3
作者：
Glinskii, Anna B.;Ma, Jun;Glinsky, Gennadi V.
通讯作者：
Glinsky, Gennadi V.
影响因子：
64.8
作者：
Gibbs, RA;Belmont, JW;Tanaka, T
通讯作者：
Tanaka, T
影响因子：
6.5
作者：
Cremonesi, L;Paroni, R;Arosio, P
通讯作者：
Arosio, P