A novel elastin gene frameshift mutation in a Russian family with cutis laxa: a case report.

BACKGROUND: Cutis laxa (CL) is a rare connective tissue disorder characterized by loose, redundant, inelastic and wrinkled skin. Patients develop a prematurely aged appearance. Inheritance can be autosomal dominant or autosomal recessive. The X-linked form is now classified in the group of copper transport diseases. Autosomal dominant CL is characterized by wrinkled, redundant and sagging, inelastic skin and in some cases is associated with internal organ involvement. CASE PRESENTATION: We report a familial case of autosomal dominant CL, which includes a 33-year-old woman and her 11-year-old son with dry, thin and wrinkled skin that appeared prematurely aged. No serious involvement of internal organs was found. In both patients, we identified novel heterozygous mutation c.2323delG (p.Ala775fs) in exon 34 of elastin transcript NM_001278939.1. Similar frameshift mutations in the last exons of elastin gene were previously reported in patients with autosomal dominant CL. CONCLUSIONS: Our results show a novel frameshift mutation that was found in patients with cutis laxa. Exome sequencing is effective and useful technology for properly diagnosis of diseases with similar phenotype to ensure proper treatment is provided.

[A bioinformatic pipeline for NGS data analysis and mutation calling in human solid tumors]. / Bioinformaticheskii protokol dlia obrabotki NGS-dannykh i identifikatsii mutatsii v solidnykh opukholiakh cheloveka.

We aimed to develop a pipeline for the bioinformatic analysis and interpretation of NGS data and detection of a wide range of single-nucleotide somatic mutations within tumor DNA. Initially, the NGS reads were submitted to a quality control check by the Cutadapt program. Low-quality 3¢-nucleotides were removed. After that the reads were mapped to the reference genome hg19 (GRCh37.p13) by BWA. The SAMtools program was used for exclusion of duplicates. MuTect was used for SNV calling. The functional effect of SNVs was evaluated using the algorithm, including annotation and evaluation of SNV pathogenicity by SnpEff and analysis of such databases as COSMIC, dbNSFP, Clinvar, and OMIM. The effect of SNV on the protein function was estimated by SIFT and PolyPhen2. Mutation frequencies were obtained from 1000 Genomes and ExAC projects, as well as from our own databases with frequency data. In order to evaluate the pipeline we used 18 breast cancer tumor biopsies. The MYbaits Onconome KL v1.5 Panel ("MYcroarray") was used for targeted enrichment. NGS was performed on the Illumina HiSeq 2500 platform. As a result, we identified alterations in BRCA1, BRCA2, ATM, CDH1, CHEK2, TP53 genes that affected the sequence of encoded proteins. Our pipeline can be used for effective search and annotation of tumor SNVs. In this study, for the first time, we have tested this pipeline for NGS data analysis of samples from patients of the Russian population. However, further confirmation of efficiency and accuracy of the pipeline is required on NGS data from larger datasets as well as data from several types of solid tumors.