@article {274, title = {Mutations in TBC1D24, a gene associated with epilepsy, also cause nonsyndromic deafness DFNB86.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 Jan 02}, pages = {144-52}, abstract = {

Inherited deafness is clinically and genetically heterogeneous. We recently mapped DFNB86, a locus associated with nonsyndromic deafness, to chromosome 16p. In this study, whole-exome sequencing was performed with genomic DNA from affected individuals from three large consanguineous families in which markers linked to DFNB86 segregate with profound deafness. Analyses of these data revealed homozygous mutation c.208G>T (p.Asp70Tyr) or c.878G>C (p.Arg293Pro) in TBC1D24 as the underlying cause of deafness in the three families. Sanger sequence analysis of TBC1D24 in an additional large family in which deafness segregates with DFNB86 identified the c.208G>T (p.Asp70Tyr) substitution. These mutations affect TBC1D24 amino acid residues that are conserved in orthologs ranging from fruit fly to human. Neither variant was observed in databases of single-nucleotide variants or in 634 chromosomes from ethnically matched control subjects. TBC1D24 in the mouse inner ear was immunolocalized predominantly to spiral ganglion neurons, indicating that DFNB86 deafness might be an auditory neuropathy spectrum disorder. Previously, six recessive mutations in TBC1D24 were reported to cause seizures (hearing loss was not reported) ranging in severity from epilepsy with otherwise normal development to epileptic encephalopathy resulting in childhood death. Two of our four families in which deafness segregates with mutant alleles of TBC1D24 were available for neurological examination. Cosegregation of epilepsy and deafness was not observed in these two families. Although the causal relationship between genotype and phenotype is not presently understood, our findings, combined with published data, indicate that recessive alleles of TBC1D24 can cause either epilepsy or nonsyndromic deafness.

}, keywords = {Alleles, Amino Acid Sequence, Carrier Proteins, Chromosomes, Human, Pair 16, Consanguinity, Deafness, Epilepsy, Exome, Exons, Female, Genes, Recessive, Genetic Loci, Genome-Wide Association Study, Heterozygote, Homozygote, Humans, Male, Molecular Sequence Data, Mutation, Pakistan, Pedigree, Phenotype, Polymorphism, Single Nucleotide, RNA, Messenger, Sequence Analysis, DNA}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2013.12.004}, author = {Rehman, Atteeq U and Santos-Cortez, Regie Lyn P and Morell, Robert J and Drummond, Meghan C and Ito, Taku and Lee, Kwanghyuk and Khan, Asma A and Basra, Muhammad Asim R and Wasif, Naveed and Ayub, Muhammad and Ali, Rana A and Raza, Syed I and Nickerson, Deborah A and Shendure, Jay and Bamshad, Michael and Riazuddin, Saima and Billington, Neil and Khan, Shaheen N and Friedman, Penelope L and Griffith, Andrew J and Ahmad, Wasim and Riazuddin, Sheikh and Leal, Suzanne M and Friedman, Thomas B} } @article {320, title = {Utilizing graph theory to select the largest set of unrelated individuals for genetic analysis.}, journal = {Genet Epidemiol}, volume = {37}, year = {2013}, month = {2013 Feb}, pages = {136-41}, abstract = {

Many statistical analyses of genetic data rely on the assumption of independence among samples. Consequently, relatedness is either modeled in the analysis or samples are removed to "clean" the data of any pairwise relatedness above a tolerated threshold. Current methods do not maximize the number of unrelated individuals retained for further analysis, and this is a needless loss of resources. We report a novel application of graph theory that identifies the maximum set of unrelated samples in any dataset given a user-defined threshold of relatedness as well as all networks of related samples. We have implemented this method into an open source program called Pedigree Reconstruction and Identification of a Maximum Unrelated Set, PRIMUS. We show that PRIMUS outperforms the three existing methods, allowing researchers to retain up to 50\% more unrelated samples. A unique strength of PRIMUS is its ability to weight the maximum clique selection using additional criteria (e.g. affected status and data missingness). PRIMUS is a permanent solution to identifying the maximum number of unrelated samples for a genetic analysis.

}, keywords = {Algorithms, Genome-Wide Association Study, HapMap Project, Humans, Models, Theoretical}, issn = {1098-2272}, doi = {10.1002/gepi.21684}, author = {Staples, Jeffrey and Nickerson, Deborah A and Below, Jennifer E} } @article {325, title = {The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions.}, journal = {Am J Med Genet A}, volume = {158A}, year = {2012}, month = {2012 Jul}, pages = {1523-5}, abstract = {

Next generation exome sequencing (ES) and whole genome sequencing (WGS) are new powerful tools for discovering the gene(s) that underlie Mendelian disorders. To accelerate these discoveries, the National Institutes of Health has established three Centers for Mendelian Genomics (CMGs): the Center for Mendelian Genomics at the University of Washington; the Center for Mendelian Genomics at Yale University; and the Baylor-Johns Hopkins Center for Mendelian Genomics at Baylor College of Medicine and Johns Hopkins University. The CMGs will provide ES/WGS and extensive analysis expertise at no cost to collaborating investigators where the causal gene(s) for a Mendelian phenotype has yet to be uncovered. Over the next few years and in collaboration with the global human genetics community, the CMGs hope to facilitate the identification of the genes underlying a very large fraction of all Mendelian disorders; see http://mendelian.org.

}, keywords = {Academies and Institutes, Genetic Diseases, Inborn, Genetics, Medical, Genome, Human, Genome-Wide Association Study, Genomics, High-Throughput Nucleotide Sequencing, Humans}, issn = {1552-4833}, doi = {10.1002/ajmg.a.35470}, author = {Bamshad, Michael J and Shendure, Jay A and Valle, David and Hamosh, Ada and Lupski, James R and Gibbs, Richard A and Boerwinkle, Eric and Lifton, Richard P and Gerstein, Mark and G{\"u}nel, Murat and Mane, Shrikant and Nickerson, Deborah A} }