Project description:Premature ovarian insufficiency (POI) is defined as a primary ovarian defect characterized by absent menarche (primary amenorrhea) or premature depletion of ovarian follicles before the age of 40 (secondary amenorrhea) with hypergonadotropism and hypoestrogenism. Premature ovarian insufficiency has few known genetic causes but in familial cases a genetic link is often suspected. A large consanguineous family with three female affected with POI was investigated. All samples including 3 affected and 5 unaffecd underwent whole genome SNP genotyping using Affymetric Axiom_GW_Hu_SNP array. Linkage analysis was carried out using HomozygosityMapper and Allegro softwares.Linkage analysis mapped the disease phenotype to long arm of chromosome 20. Sequence data analysis of potential candidate genes failed to detect any pathogenic variant. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from peripheral blood samples. DNA of eight individuals including three affected subjects was used for homozygosity mapping. Genotyping was performed using the Affymetrix Axiom_GW_Hu_SNP array. Briefly, 250 ng genomic DNA was digested with Digestion Master Mix containing 2 µl NE buffer 2 (10X), 0.5 µl BSA (100X; 10 mg/ml) and 1 µl Nsp1. Digested DNA sample was ligated to Nsp1 adaptor using T4 DNA ligase and amplified by 2 µl of TITANIUM Taq DNA polymerase (50X) and 100 µM PCR primer. PCR products were purified on a Clean-Up plate (Clontech Lab, Madison, USA) and eluted by RB buffer. Purified PCR products were fragmented using Fragmentation Reagent (0.05U/µl DNase 1) for 35 minutes at 37°C followed by labeling of fragmented samples with Labeling Master Mix (30 mM GeneChip DNA Labeling Reagent, 30 U/µl Terminal Deoxynucleotidyl Transferase) for 4 hours at 37°C. Labeled samples were hybridized to Axiom_GW_Hu_SNP array by mixing the sample with Hybridization Master Mix, denatured on thermoblock and loaded on to Array. Array was then placed in a hybridization oven (GeneChip Hybridization Oven 640, USA) for 16-18 hours. After hybridization, array was washed and stained on an automated Fluidic Station 450 followed by scanning on GeneChip Scanner 3000 7G using GeneChip Operating Software (GCOS).

Project description:300,000 SNPs genotyped (Illumina CytoSNP12v2 array) in a family with unexplained inherited kidney disease. Analysed using parametric and Combinatorial Conflicting Homozygosity analysis, as described in Levine et al. BMC Genomics 2015. Abstract: Background: The ability to identify regions of the genome inherited with a dominant trait in one or more families has become increasingly valuable with the wide availability of next generationhigh throughput sequencing technology. While a number of methods exist for mapping of homozygous variants segregating with recessive traits in consanguineous families, dominant conditions are conventionally analysed by by linkage analysis, which requires computationally demanding haplotype reconstruction from marker genotypes and, even using advanced parallel approximation implementations, can take substantial time. In addition, linkage analysis lacks sensitivity in the presence of phenocopies (individuals sharing the trait but not the genetic variant responsible). Combinatorial Conflicting Homozygosity (CCH) analysis uses bi-allelic single nucleotide polymorphism (SNP) marker genotypes to identify genetic loci within which consecutive markers are not homozygous for different alleles. This allows inference of identical by descent (IBD) inheritance of a haplotype among a set or subsets of related or unrelated individuals. Results: A single genome-wide conflicting homozygosity analysis takes <3 seconds and parallelisation permits multiple combinations of subsets of individuals to be analysed quickly. Analysis of unrelated individuals demonstrated that in the absence of IBD inheritance, runs of no- CH exceeding 4 cM are not observed. At this threshold, CCH is >97% sensitive and specific for IBD regions within a pedigree exceeding this length and was able to identify the locus responsible for a dominantly inherited kidney disease in a Turkish Cypriot family in which 6 six out 17 affected individuals were phenocopies. It also revealed shared ancestry at the disease-linked locus among affected individuals from two different Cypriot populations. Conclusions: CCH does not require computationally demanding haplotype reconstruction and can detect regions of shared inheritance of a haplotype among subsets of related or unrelated individuals directly from SNP genotype data. In contrast to parametric linkage allowing for phenocopies, CCH directly provides the exact number and identity of individuals sharing each locus. CCH can also identify regions of shared ancestry among ostensibly unrelated individuals who share a trait. CCH is implemented in Python and is freely available (as source code) for download at http://sourceforge.net/projects/cchsnp/. Linkage and identity-by-descent studies in a single family with 17 individuals affected with kidney disease

Project description:300,000 SNPs genotyped (Illumina CytoSNP12v2 array) in a family with unexplained inherited kidney disease. Analysed using parametric and Combinatorial Conflicting Homozygosity analysis, as described in Levine et al. BMC Genomics 2015. Abstract: Background: The ability to identify regions of the genome inherited with a dominant trait in one or more families has become increasingly valuable with the wide availability of next generationhigh throughput sequencing technology. While a number of methods exist for mapping of homozygous variants segregating with recessive traits in consanguineous families, dominant conditions are conventionally analysed by by linkage analysis, which requires computationally demanding haplotype reconstruction from marker genotypes and, even using advanced parallel approximation implementations, can take substantial time. In addition, linkage analysis lacks sensitivity in the presence of phenocopies (individuals sharing the trait but not the genetic variant responsible). Combinatorial Conflicting Homozygosity (CCH) analysis uses bi-allelic single nucleotide polymorphism (SNP) marker genotypes to identify genetic loci within which consecutive markers are not homozygous for different alleles. This allows inference of identical by descent (IBD) inheritance of a haplotype among a set or subsets of related or unrelated individuals. Results: A single genome-wide conflicting homozygosity analysis takes <3 seconds and parallelisation permits multiple combinations of subsets of individuals to be analysed quickly. Analysis of unrelated individuals demonstrated that in the absence of IBD inheritance, runs of no- CH exceeding 4 cM are not observed. At this threshold, CCH is >97% sensitive and specific for IBD regions within a pedigree exceeding this length and was able to identify the locus responsible for a dominantly inherited kidney disease in a Turkish Cypriot family in which 6 six out 17 affected individuals were phenocopies. It also revealed shared ancestry at the disease-linked locus among affected individuals from two different Cypriot populations. Conclusions: CCH does not require computationally demanding haplotype reconstruction and can detect regions of shared inheritance of a haplotype among subsets of related or unrelated individuals directly from SNP genotype data. In contrast to parametric linkage allowing for phenocopies, CCH directly provides the exact number and identity of individuals sharing each locus. CCH can also identify regions of shared ancestry among ostensibly unrelated individuals who share a trait. CCH is implemented in Python and is freely available (as source code) for download at http://sourceforge.net/projects/cchsnp/.

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Affymetrix SNP array data for ovarian dysgenesis samples

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