Department of Computer Science, Columbia University, New York, NY 10027, USA.
BMC Med. 2011 Feb 3;9:12. doi: 10.1186/1741-7015-9-12.
During gene conversion, genetic information is transferred unidirectionally between highly homologous but non-allelic regions of DNA. While germ-line gene conversion has been implicated in the pathogenesis of some diseases, somatic gene conversion has remained technically difficult to investigate on a large scale.
A novel analysis technique is proposed for detecting the signature of somatic gene conversion from SNP microarray data. The Wellcome Trust Case Control Consortium has gathered SNP microarray data for two control populations and cohorts for bipolar disorder (BD), cardiovascular disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type-1 diabetes (T1D) and type-2 diabetes (T2D). Using the new analysis technique, the seven disease cohorts are analyzed to identify cohort-specific SNPs at which conversion is predicted. The quality of the predictions is assessed by identifying known disease associations for genes in the homologous duplicons, and comparing the frequency of such associations with background rates.
Of 28 disease/locus pairs meeting stringent conditions, 22 show various degrees of disease association, compared with only 8 of 70 in a mock study designed to measure the background association rate (P < 10-9). Additional candidate genes are identified using less stringent filtering conditions. In some cases, somatic deletions appear likely. RA has a distinctive pattern of events relative to other diseases. Similarities in patterns are apparent between BD and HT.
The associations derived represent the first evidence that somatic gene conversion could be a significant causative factor in each of the seven diseases. The specific genes provide potential insights about disease mechanisms, and are strong candidates for further study.
在基因转换过程中,遗传信息在高度同源但非等位基因区域的 DNA 之间单向转移。虽然种系基因转换已被牵涉到一些疾病的发病机制中,但体细胞基因转换在很大程度上仍然难以进行技术研究。
提出了一种新的分析技术,用于从 SNP 微阵列数据中检测体细胞基因转换的特征。威康信托基金会病例对照联合会收集了双相情感障碍 (BD)、心血管疾病 (CAD)、克罗恩病 (CD)、高血压 (HT)、类风湿关节炎 (RA)、1 型糖尿病 (T1D) 和 2 型糖尿病 (T2D) 的两个对照人群和队列的 SNP 微阵列数据。使用新的分析技术,分析了七个疾病队列,以识别预测发生转换的队列特异性 SNP。通过识别同源重复基因中的已知疾病关联,并将这些关联的频率与背景率进行比较,来评估预测的质量。
在满足严格条件的 28 个疾病/基因对中,有 22 个显示出不同程度的疾病相关性,而在设计用于测量背景关联率的模拟研究中,仅有 70 个中的 8 个显示出相关性(P<10-9)。使用较不严格的过滤条件,还可以鉴定出其他候选基因。在某些情况下,体细胞缺失似乎是可能的。RA 相对于其他疾病具有独特的事件模式。BD 和 HT 之间存在明显的模式相似性。
得出的关联代表了第一个证据,表明体细胞基因转换可能是这七种疾病中的每一种的重要致病因素。特定的基因提供了关于疾病机制的潜在见解,并且是进一步研究的有力候选者。