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The KCNT1 gene encodes for subunits contributing to the Na(+)-activated K(+) current (KNa), expressed in many cell types. Mutations in KCNT1 have been found in patients affected with a wide spectrum of early-onset epilepsies, including Malignant Migrating Partial Seizures in Infancy (MMPSI), a severe early-onset epileptic encephalopathy characterized by pharmacoresistant focal seizures migrating from one brain region or hemisphere to another and neurodevelopment arrest or regression, resulting in profound disability. In the present study we report identification by whole exome sequencing (WES) of two de novo, heterozygous KCNT1 mutations (G288S and, not previously reported, M516V) in two unrelated MMPSI probands. Functional studies in a heterologous expression system revealed that channels formed by mutant KCNT1 subunits carried larger currents when compared to wild-type KCNT1 channels, both as homo- and heteromers with these last. Both mutations induced a marked leftward shift in homomeric channel activation gating. Interestingly, the KCNT1 blockers quinidine (3-1000μM) and bepridil (0.03-10μM) inhibited both wild-type and mutant KCNT1 currents in a concentration-dependent manner, with mutant channels showing higher sensitivity to blockade. This latter result suggests two genotype-tailored pharmacological strategies to specifically counteract the dysfunction of KCNT1 activating mutations in MMPSI patients.
Pubmed ID: 26784557 RIS Download
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International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes
View all literature mentionsAn efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)
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