@article {652, title = {Variants in KIAA0825 underlie autosomal recessive postaxial polydactyly.}, journal = {Hum Genet}, volume = {138}, year = {2019}, month = {2019 Jun}, pages = {593-600}, abstract = {

Postaxial polydactyly (PAP) is a common limb malformation that often leads to cosmetic and functional complications. Molecular evaluation of polydactyly can serve as a tool to elucidate genetic and signaling pathways that regulate limb development, specifically, the anterior-posterior specification of the limb. To date, only five genes have been identified for nonsyndromic PAP: FAM92A, GLI1, GLI3, IQCE and ZNF141. In this study, two Pakistani multiplex consanguineous families with autosomal recessive nonsyndromic PAP were clinically and molecularly evaluated. From both pedigrees, a DNA sample from an affected member underwent exome sequencing. In each family, we identified a segregating frameshift (c.591dupA [p.(Q198Tfs*21)]) and nonsense variant (c.2173A > T [p.(K725*)]) in KIAA0825 (also known as C5orf36). Although KIAA0825 encodes a protein of unknown function, it has been demonstrated that its murine ortholog is expressed during limb development. Our data contribute to the establishment of a catalog of genes important in limb patterning, which can aid in diagnosis and obtaining a better understanding of the biology of polydactyly.

}, keywords = {Animals, Consanguinity, Family Health, Female, Fingers, Genes, Recessive, Genetic Predisposition to Disease, Genotype, Humans, Intracellular Signaling Peptides and Proteins, Male, Mice, Inbred C57BL, Mutation, Pedigree, Phenotype, Polydactyly, Toes, Whole Exome Sequencing}, issn = {1432-1203}, doi = {10.1007/s00439-019-02000-0}, author = {Ullah, Irfan and Kakar, Naseebullah and Schrauwen, Isabelle and Hussain, Shabir and Chakchouk, Imen and Liaqat, Khurram and Acharya, Anushree and Wasif, Naveed and Santos-Cortez, Regie Lyn P and Khan, Saadullah and Aziz, Abdul and Lee, Kwanghyuk and Couthouis, Julien and Horn, Denise and Kragesteen, Bj{\o}rt K and Spielmann, Malte and Thiele, Holger and Nickerson, Deborah A and Bamshad, Michael J and Gitler, Aaron D and Ahmad, Jamil and Ansar, Muhammad and Borck, Guntram and Ahmad, Wasim and Leal, Suzanne M} } @article {485, title = {A variant in LMX1A causes autosomal recessive severe-to-profound hearing impairment.}, journal = {Hum Genet}, volume = {137}, year = {2018}, month = {2018 Jul}, pages = {471-478}, abstract = {

Hereditary hearing impairment is a common sensory disorder that is genetically and phenotypically heterogeneous. In this study, we used a homozygosity mapping and exome sequencing strategy to study a consanguineous Pakistani family with autosomal recessive severe-to-profound hearing impairment. This led to the identification of a missense variant (p.Ile369Thr) in the LMX1A gene affecting a conserved residue in the C-terminus of the protein, which was predicted damaging by an in silico bioinformatics analysis. The p.Ile369Thr variant disrupts several C-terminal and homeodomain residue interactions, including an interaction with homeodomain residue p.Val241 that was previously found to be involved in autosomal dominant progressive HI. LIM-homeodomain factor Lmx1a is expressed in the inner ear through development, shows a progressive restriction to non-sensory epithelia, and is important in the separation of the sensory and non-sensory domains in the inner ear. Homozygous Lmx1a mutant mice (Dreher) are deaf with dysmorphic ears with an abnormal morphogenesis and fused and misshapen sensory organs; however, computed tomography performed on a hearing-impaired family member did not reveal any cochleovestibular malformations. Our results suggest that LMX1A is involved in both human autosomal recessive and dominant sensorineural hearing impairment.

}, keywords = {Adolescent, Adult, Animals, Child, Disease Models, Animal, Ear, Inner, Female, Genes, Dominant, Genes, Recessive, Hearing Loss, Hearing Loss, Sensorineural, Homozygote, Humans, LIM-Homeodomain Proteins, Male, Mice, Mutation, Missense, Pedigree, Transcription Factors, Whole Exome Sequencing}, issn = {1432-1203}, doi = {10.1007/s00439-018-1899-7}, author = {Schrauwen, Isabelle and Chakchouk, Imen and Liaqat, Khurram and Jan, Abid and Nasir, Abdul and Hussain, Shabir and Nickerson, Deborah A and Bamshad, Michael J and Ullah, Asmat and Ahmad, Wasim and Leal, Suzanne M} } @article {249, title = {Variant association tools for quality control and analysis of large-scale sequence and genotyping array data.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 May 01}, pages = {770-83}, abstract = {

Currently there is great interest in detecting associations between complex traits and rare variants. In this report, we describe Variant Association Tools (VAT) and the VAT pipeline, which implements best practices for rare-variant association studies. Highlights of VAT include variant-site and call-level quality control (QC), summary statistics, phenotype- and genotype-based sample selection, variant annotation, selection of variants for association analysis, and a collection of rare-variant association methods for analyzing qualitative and quantitative traits. The association testing framework for VAT is regression based, which readily allows for flexible construction of association models with multiple covariates and weighting themes based on allele frequencies or predicted functionality. Additionally, pathway analyses, conditional analyses, and analyses of gene-gene and gene-environment interactions can be performed. VAT is capable of rapidly scanning through data by using multi-process computation, adaptive permutation, and simultaneously conducting association analysis via multiple methods. Results are available in text or graphic file formats and additionally can be output to relational databases for further annotation and filtering. An interface to R language also facilitates user implementation of novel association methods. The VAT{\textquoteright}s data QC and association-analysis pipeline can be applied to sequence, imputed, and genotyping array, e.g., "exome chip," data, providing a reliable and reproducible computational environment in which to analyze small- to large-scale studies with data from the latest genotyping and sequencing technologies. Application of the VAT pipeline is demonstrated through analysis of data from the 1000 Genomes project.

}, keywords = {Genetic Association Studies, Genetic Variation, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Multifactorial Inheritance, Quality Control, Software}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.04.004}, author = {Wang, Gao T and Peng, Bo and Leal, Suzanne M} }