Incorporating the amino acid properties to predict the significance of missense mutations

Computational prediction of deleterious nonsynonymous SNPs in the CTNS gene: implications for cystinosis

BACKGROUND

Cystinosis is a rare autosomal recessive lysosomal storage disorder caused by mutations in the CTNS gene, which encodes cystinosin, a lysosomal cystine transporter. These mutations disrupt cystine efflux, leading to its accumulation in lysosomes and subsequent cellular damage. While more than 140 mutations have been identified, the functional and structural impacts of many nonsynonymous single nucleotide polymorphisms (nsSNPs) remain poorly understood. Nonsynonymous SNPs are of particular interest because they can directly alter protein structure and function, potentially leading to disease. Clinically, cystinosis most often presents with renal Fanconi syndrome, photophobia and vision loss due to corneal cystine crystals, and progressive neuromuscular complications such as distal myopathy and swallowing difficulties This study aimed to identify deleterious nsSNPs in the CTNS gene and evaluate their effects on cystinosin stability, structure, and function via computational tools and molecular dynamics simulations.

RESULTS

From a dataset of 12,028 SNPs, 327 nsSNPs were identified, among which 19 were consistently classified as deleterious across multiple predictive tools, including SIFT, PolyPhen, and molecular dynamics simulations. Stability predictions revealed that most of these mutations destabilize cystinosin, with G308R and G308V located in the sixth transmembrane domain essential for transporter function having the most severe effects. Molecular dynamics simulations revealed that these mutations significantly increase local flexibility, alter hydrogen bonding patterns, and enhance solvent accessibility, resulting in structural perturbations. Notably, D305G and F142S disrupted the transmembrane domains essential for the function of cystinosin, whereas compared with the wild-type protein, G309V resulted in increased stability. Conservation analysis revealed that 16 of the 19 mutations affected highly conserved residues, indicating their crucial roles in the function of cystinosin. Additionally, protein interaction analyses suggested that mutations could impact associations with lysosomal and membrane transport proteins.

CONCLUSIONS

This study identified 19 deleterious nsSNPs in the CTNS gene that impair cystinosin stability and function. These findings highlight the structural and functional importance of key residues, such as G308, D305, and F142, which play critical roles in maintaining the active conformation and transport capacity of cystinosin. These insights provide a foundation for future experimental validation and the development of targeted therapeutic strategies to mitigate the effects of pathogenic mutations in cystinosis.

New recurrent BRCA1/2 mutations in Polish patients with familial breast/ovarian cancer detected by next generation sequencing

Background

Targeted PCR-based genetic testing for BRCA1 and BRCA2 can be performed at a lower cost than full gene testing; however, it may overlook mutations responsible for familial breast and/or ovarian cancers. In the present study, we report the utility of next generation sequencing (NGS) to identify new pathogenic variants of BRCA1/2.

Methods

BRCA1 and BRCA2 exons were amplified using the Ion AmpliSeq BRCA1/2 Panel and sequenced on the Ion Torrent PGM sequencer in 512 women with familial and/or only early onset breast and/or ovarian cancers who were negative for selected BRCA1/2 mutations.

Results

146 single nucleotide variants (SNVs) and 32 indels were identified. Of them, 14 SNVs and 17 indels were considered as pathogenic or likely pathogenic. One and 18 pathogenic mutations had been detected previously in the Polish and other populations, respectively, and 12 deleterious mutations were previously unknown. Eight mutations were recurrent; Q563X (BRCA1), N3124I (BRCA2) and c.4516delG (BRCA1) were found in eight, six and four patients, respectively, and two other mutations (c.9118-2A > G and c.7249delCA in BRCA2) were detected in three patients each. Altogether, BRCA1/2 pathogenic mutations were identified in 52 out of 512 (10%) patients.

Conclusions

NGS substantially improved the detection rates of a wide spectrum of mutations in Polish patients with familial breast and/or ovarian cancer. Although targeted screening for specific BRCA1 mutations can be offered to all Polish breast or ovarian cancer patients, NGS-based testing is justified in patients with breast or ovarian cancer likely related to BRCA1/2 who test negative for the selected BRCA1/2 pathogenic mutations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0092-2) contains supplementary material, which is available to authorized users.

EFIN: predicting the functional impact of nonsynonymous single nucleotide polymorphisms in human genome

BACKGROUND

Predicting the functional impact of amino acid substitutions (AAS) caused by nonsynonymous single nucleotide polymorphisms (nsSNPs) is becoming increasingly important as more and more novel variants are being discovered. Bioinformatics analysis is essential to predict potentially causal or contributing AAS to human diseases for further analysis, as for each genome, thousands of rare or private AAS exist and only a very small number of which are related to an underlying disease. Existing algorithms in this field still have high false prediction rate and novel development is needed to take full advantage of vast amount of genomic data.

RESULTS

Here we report a novel algorithm that features two innovative changes: 1. making better use of sequence conservation information by grouping the homologous protein sequences into six blocks according to evolutionary distances to human and evaluating sequence conservation in each block independently, and 2. including as many such homologous sequences as possible in analyses. Random forests are used to evaluate sequence conservation in each block and to predict potential impact of an AAS on protein function. Testing of this algorithm on a comprehensive dataset showed significant improvement on prediction accuracy upon currently widely-used programs. The algorithm and a web-based application tool implementing it, EFIN (Evaluation of Functional Impact of Nonsynonymous SNPs) were made freely available (http://paed.hku.hk/efin/) to the public.

CONCLUSIONS

Grouping homologous sequences into different blocks according to the evolutionary distance of the species to human and evaluating sequence conservation in each group independently significantly improved prediction accuracy. This approach may help us better understand the roles of genetic variants in human disease and health.