Evaluation of performance of five bioinformatics software for the prediction of missense mutations / 中华医学遗传学杂志

<p><b>OBJECTIVE</b>To study the prediction performance evaluation with five kinds of bioinformatics software (SIFT, PolyPhen2, MutationTaster, Provean, MutationAssessor).</p><p><b>METHODS</b>From own database for genetic mutations collected over the past five years, Chinese literature database, Human Gene Mutation Database, and dbSNP, 121 missense mutations confirmed by functional studies, and 121 missense mutations suspected to be pathogenic by pedigree analysis were used as positive gold standard, while 242 missense mutations with minor allele frequency (MAF)>5% in dominant hereditary diseases were used as negative gold standard. The selected mutations were predicted with the five software. Based on the results, the performance of the five software was evaluated for their sensitivity, specificity, positive predict value, false positive rate, negative predict value, false negative rate, false discovery rate, accuracy, and receiver operating characteristic curve (ROC).</p><p><b>RESULTS</b>In terms of sensitivity, negative predictive value and false negative rate, the rank was MutationTaster, PolyPhen2, Provean, SIFT, and MutationAssessor. For specificity and false positive rate, the rank was MutationTaster, Provean, MutationAssessor, SIFT, and PolyPhen2. For positive predict value and false discovery rate, the rank was MutationTaster, Provean, MutationAssessor, PolyPhen2, and SIFT. For area under the ROC curve (AUC) and accuracy, the rank was MutationTaster, Provean, PolyPhen2, MutationAssessor, and SIFT.</p><p><b>CONCLUSION</b>The prediction performance of software may be different when using different parameters. Among the five software, MutationTaster has the best prediction performance.</p>

Paramyotonia congenita caused by a novel mutation of SCN4A gene in a Chinese family / 中华医学遗传学杂志

<p><b>OBJECTIVE</b>To detect SCN4A gene mutation in a pedigree with paramyotonia congenita in order to facilitate genetic counseling and assisted reproduction.</p><p><b>METHODS</b>Clinical data of the family was collected. DNA was extracted from peripheral blood samples. Potential mutation of the SCN4A gene was screened using PCR-Sanger sequencing. Potential mutation was detected in 3 affected relatives, 4 unaffected relatives and 100 unrelated healthy controls. Bioinformatics software was used to predict the effect of mutation on the protein function and conservation of the sequence at the mutation site across various species.</p><p><b>RESULTS</b>A novel missense mutation c.4427T>C (p.Met1476Thr) was detected in the exon 24 of the SCN4A gene in the proband and other 3 affected relatives, but not in 4 unaffected relatives and 100 unrelated controls. Bioinformatic analysis indicated that the codon is highly conserved across various species, and that the mutation has caused damage to the structure and function of SCN4A protein.</p><p><b>CONCLUSION</b>The c.4427 T>C (p.Met1476Thr) mutation of the SCN4A gene may contribute to the paramyotonia congenita. Detection of SCN4A gene mutation is an effective method for the diagnosis of paramyotonic congenita.</p>