School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
PLoS One. 2012;7(8):e42336. doi: 10.1371/journal.pone.0042336. Epub 2012 Aug 7.
Cystic fibrosis (CF) is the most common genetic disease among Caucasians, and accordingly the cystic fibrosis transmembrane conductance regulator (CFTR) protein has perhaps the best characterized disease mutation spectrum with more than 1,500 causative mutations having been identified. In this study, we took advantage of that wealth of mutational information in an effort to relate site-specific evolutionary parameters with the propensity and severity of CFTR disease-causing mutations. To do this, we devised a scoring scheme for known CFTR disease-causing mutations based on the Grantham amino acid chemical difference matrix. CFTR site-specific evolutionary constraint values were then computed for seven different evolutionary metrics across a range of increasing evolutionary depths. The CFTR mutational scores and the various site-specific evolutionary constraint values were compared in order to evaluate which evolutionary measures best reflect the disease-causing mutation spectrum. Site-specific evolutionary constraint values from the widely used comparative method PolyPhen2 show the best correlation with the CFTR mutation score spectrum, whereas more straightforward conservation based measures (ConSurf and ScoreCons) show the greatest ability to predict individual CFTR disease-causing mutations. While far greater than could be expected by chance alone, the fraction of the variability in mutation scores explained by the PolyPhen2 metric (3.6%), along with the best set of paired sensitivity (58%) and specificity (60%) values for the prediction of disease-causing residues, were marginal. These data indicate that evolutionary constraint levels are informative but far from determinant with respect to disease-causing mutations in CFTR. Nevertheless, this work shows that, when combined with additional lines of evidence, information on site-specific evolutionary conservation can and should be used to guide site-directed mutagenesis experiments by more narrowly defining the set of target residues, resulting in a potential savings of both time and money.
囊性纤维化（CF）是白种人中最常见的遗传疾病，相应地，囊性纤维化跨膜电导调节因子（CFTR）蛋白可能具有特征最明显的疾病突变谱，已经确定了超过 1500 种致病突变。在这项研究中，我们利用了丰富的突变信息，努力将特定部位的进化参数与 CFTR 致病突变的倾向和严重程度联系起来。为此，我们根据格兰瑟姆氨基酸化学差异矩阵，为已知的 CFTR 致病突变设计了一种评分方案。然后，针对七种不同的进化指标，在一系列不断增加的进化深度上计算了 CFTR 特定部位的进化约束值。比较了 CFTR 突变评分和各种特定部位的进化约束值，以评估哪些进化指标最能反映致病突变谱。广泛使用的比较方法 PolyPhen2 的 CFTR 特定部位进化约束值与 CFTR 突变评分谱相关性最好，而更直接的基于保守性的衡量标准（ConSurf 和 ScoreCons）则最能预测个别 CFTR 致病突变。虽然远远超过仅凭偶然就能解释的变异分数，但 PolyPhen2 指标解释突变评分变异的分数（3.6%），以及预测致病残基的最佳配对灵敏度（58%）和特异性（60%）值，都很微小。这些数据表明，进化约束水平虽然提供了信息，但对于 CFTR 的致病突变来说，远非决定性的。尽管如此，这项工作表明，当与其他证据相结合时，关于特定部位进化保守性的信息可以而且应该用于指导基于位点的诱变实验，通过更严格地定义目标残基集，从而节省时间和金钱。
