Variant In Pedigree Research Articles

A Novel PAX3 Variant in a Chinese Pedigree with Nonsyndromic Cleft Lip With or Without Palate.

Objectives: Nonsyndromic cleft lip with or without palate (NSCL/P) is a common congenital orofacial defect, which is associated with severe disruption of orofacial development. The present study was designed to identify potential underlying gene variants in a Chinese pedigree with NSCL/P, in which the proband and the proband's father were affected. Methods: DNA was extracted from the participants' peripheral venous blood, and whole-exome sequencing was performed on the proband and the proband's parents. Results: After filtering, a paired box gene 3 (PAX3) missense variant (c.92C>G_p.Thr31Ser) was identified, which was verified by Sanger sequencing. This variant, which was not present in 113 unrelated healthy individuals or in a Chinese public database, may affect the transcription inhibition domain of the PAX3 protein. Conservation analysis and in silico predictions suggested that this variant may be evolutionarily conserved and potentially deleterious. In addition, it was reported that mice with PAX3 variants show cleft palates. Thus, the PAX3 missense variant (c.92C>G_p.Thr31Ser) is a candidate causative variant in this family. Conclusions: To the best of our knowledge, the present study is the first to report on a PAX3 variant in a pedigree with NSCL/P. The present study further suggests that PAX3 may be associated with CL/P etiology.

Analysis of DFNA5 gene variant in a Chinese pedigree affected with late-onset non-syndromic hearing loss

To explore the genetic basis for a Chinese pedigree affected with autosomal dominant late-onset non-syndromic hearing loss (NSHL). Clinical data of the pedigree were collected. Genomic DNA was extracted from peripheral blood samples of the proband and other family members. Trio whole exome sequencing was carried out for 19 396 genes to identify potential pathogenic variants. Sanger sequencing was carried out to verify the candidate variant in the pedigree. The proband and his father were found to carry a c.1183+1delG p.? variant of the DFNA5 gene. The variant was confirmed to be co-segregating with the disease phenotype in the pedigree. The c.1183+1delG p.? variant of the DFNA5 gene probably underlay the late onset NSHL in this pedigree. Above finding has enabled accurate genetic counseling for this pedigree.

Phenotype Driven Analysis of Whole Genome Sequencing Identifies Deep Intronic Variants that Cause Retinal Dystrophies by Aberrant Exonization.

PurposeTo demonstrate the effectiveness of combining retinal phenotyping and focused variant filtering from genome sequencing (GS) in identifying deep intronic disease causing variants in inherited retinal dystrophies.MethodsAffected members from three pedigrees with classical enhanced S-cone syndrome (ESCS; Pedigree 1), congenital stationary night blindness (CSNB; Pedigree 2), and achromatopsia (ACHM; Pedigree 3), respectively, underwent detailed ophthalmologic evaluation, optical coherence tomography, and electroretinography. The probands underwent panel-based genetic testing followed by GS analysis. Minigene constructs (NR2E3, GPR179 and CNGB3) and patient-derived cDNA experiments (NR2E3 and GPR179) were performed to assess the functional effect of the deep intronic variants.ResultsThe electrophysiological findings confirmed the clinical diagnosis of ESCS, CSNB, and ACHM in the respective pedigrees. Panel-based testing revealed heterozygous pathogenic variants in NR2E3 (NM_014249.3; c.119-2A>C; Pedigree 1) and CNGB3 (NM_019098.4; c.1148delC/p.Thr383Ilefs*13; Pedigree 3). The GS revealed heterozygous deep intronic variants in Pedigrees 1 (NR2E3; c.1100+1124G>A) and 3 (CNGB3; c.852+4751A>T), and a homozygous GPR179 variant in Pedigree 2 (NM_001004334.3; c.903+343G>A). The identified variants segregated with the phenotype in all pedigrees. All deep intronic variants were predicted to generate a splice acceptor gain causing aberrant exonization in NR2E3 [89 base pairs (bp)], GPR179 (197 bp), and CNGB3 (73 bp); splicing defects were validated through patient-derived cDNA experiments and/or minigene constructs and rescued by antisense oligonucleotide treatment.ConclusionsDeep intronic mutations contribute to missing heritability in retinal dystrophies. Combining results from phenotype-directed gene panel testing, GS, and in silico splice prediction tools can help identify these difficult-to-detect pathogenic deep intronic variants.

Identification of SDHD c.170-1G>T variant in pedigree affected with carotid body tumor

To carry out genetic testing for a pedigree affected with carotid body tumor (CBT). Members of the pedigree were enrolled and underwent physical examination, ultrasonography and CT scan. Genomic DNA of the proband was extracted from peripheral blood sample and subjected to exome sequencing. Candidate variants were predicted using bioinformatic tools and verified among members from his pedigree. A c.170-1G>T splicing variant of the SDHD gene was detected in 15 individuals from the pedigree. Physical examination and imaging confirmed that 9 of them had CBT and hypertension, while the remaining 6 died of cardiovascular and cerebrovascular diseases. The c.170-1G>T variant of the SDHD gene probably underlies the CBT in this pedigree. Genetic testing should be considered for CBT patients with CBT in addition to conventional clinical examination.

A Novel FLVCR1 Variant Implicated in Retinitis Pigmentosa.

Here we describe the identification and evaluation of a rare novel autosomal recessive mutation in FLVCR1 which is implicated solely in RP, with no evidence of posterior column ataxia in a number of affected patients. The mutation was detected as part of an ongoing target capture NGS study (Target 5000), aimed at identifying candidate variants in pedigrees with inherited retinal degenerations (IRDs) in Ireland. The mutation, FLVCR1 p.Tyr341Cys, was observed homozygously in seven affected patients across four pedigrees. FLVCR1 p.Tyr341Cys is a very rare mutation, with no previous reports of pathogenicity and no homozygous cases reported in online allele frequency databases. Our sequencing study identified seven homozygotes across multiple pedigrees, all with similar clinical presentations of RP without ataxia, a scenario extremely unlikely to occur by chance for a benign allele, particularly given the low population frequency of p.Tyr341Cys.

Leveraging Identity-by-Descent for Accurate Genotype Inference in Family Sequencing Data.

Sequencing family DNA samples provides an attractive alternative to population based designs to identify rare variants associated with human disease due to the enrichment of causal variants in pedigrees. Previous studies showed that genotype calling accuracy can be improved by modeling family relatedness compared to standard calling algorithms. Current family-based variant calling methods use sequencing data on single variants and ignore the identity-by-descent (IBD) sharing along the genome. In this study we describe a new computational framework to accurately estimate the IBD sharing from the sequencing data, and to utilize the inferred IBD among family members to jointly call genotypes in pedigrees. Through simulations and application to real data, we showed that IBD can be reliably estimated across the genome, even at very low coverage (e.g. 2X), and genotype accuracy can be dramatically improved. Moreover, the improvement is more pronounced for variants with low frequencies, especially at low to intermediate coverage (e.g. 10X to 20X), making our approach effective in studying rare variants in cost-effective whole genome sequencing in pedigrees. We hope that our tool is useful to the research community for identifying rare variants for human disease through family-based sequencing.

Detection of Mendelian Consistent Genotyping Errors in Pedigrees

Detection of genotyping errors is a necessary step to minimize false results in genetic analysis. This is especially important when the rate of genotyping errors is high, as has been reported for high-throughput sequence data. To detect genotyping errors in pedigrees, Mendelian inconsistent (MI) error checks exist, as do multi-point methods that flag Mendelian consistent (MC) errors for sparse multi-allelic markers. However, few methods exist for detecting MC genotyping errors, particularly for dense variants on large pedigrees. Here, we introduce an efficient method to detect MC errors even for very dense variants (e.g., SNPs and sequencing data) on pedigrees that may be large. Our method first samples inheritance vectors (IVs) using a moderately sparse but informative set of markers using a Markov chain Monte Carlo-based sampler. Using sampled IVs, we considered two test statistics to detect MC genotyping errors: the percentage of IVs inconsistent with observed genotypes (A1) or the posterior probability of error configurations (A2). Using simulations, we show that this method, even with the simpler A1 statistic, is effective for detecting MC genotyping errors in dense variants, with sensitivity almost as high as the theoretical best sensitivity possible. We also evaluate the effectiveness of this method as a function of parameters, when including the observed pattern for genotype, density of framework markers, error rate, allele frequencies, and number of sampled inheritance vectors. Our approach provides a line of defense against false findings based on the use of dense variants in pedigrees.

The power comparison of the haplotype-based collapsing tests and the variant-based collapsing tests for detecting rare variants in pedigrees

BackgroundBoth common and rare genetic variants have been shown to contribute to the etiology of complex diseases. Recent genome-wide association studies (GWAS) have successfully investigated how common variants contribute to the genetic factors associated with common human diseases. However, understanding the impact of rare variants, which are abundant in the human population (one in every 17 bases), remains challenging. A number of statistical tests have been developed to analyze collapsed rare variants identified by association tests. Here, we propose a haplotype-based approach. This work inspired by an existing statistical framework of the pedigree disequilibrium test (PDT), which uses genetic data to assess the effects of variants in general pedigrees. We aim to compare the performance between the haplotype-based approach and the rare variant-based approach for detecting rare causal variants in pedigrees.ResultsExtensive simulations in the sequencing setting were carried out to evaluate and compare the haplotype-based approach with the rare variant methods that drew on a more conventional collapsing strategy. As assessed through a variety of scenarios, the haplotype-based pedigree tests had enhanced statistical power compared with the rare variants based pedigree tests when the disease of interest was mainly caused by rare haplotypes (with multiple rare alleles), and vice versa when disease was caused by rare variants acting independently. For most of other situations when disease was caused both by haplotypes with multiple rare alleles and by rare variants with similar effects, these two approaches provided similar power in testing for association.ConclusionsThe haplotype-based approach was designed to assess the role of rare and potentially causal haplotypes. The proposed rare variants-based pedigree tests were designed to assess the role of rare and potentially causal variants. This study clearly documented the situations under which either method performs better than the other. All tests have been implemented in a software, which was submitted to the Comprehensive R Archive Network (CRAN) for general use as a computer program named rvHPDT.

A simplified method for segregation analysis (SISA) to determine penetrance and expression of a genetic variant in a family

A method for SImplified rapid Segregation Analysis (SISA) to assess penetrance and expression of genetic variants in pedigrees of any complexity is presented. For this purpose the probability for recombination between the variant and the gene is zero. An assumption is that the variant of undetermined significance (VUS) is introduced into the family once only. If so, all family members in between two members demonstrated to carry a VUS, are obligate carriers. Probabilities for cosegregation of disease and VUS by chance, penetrance, and expression, may be calculated. SISA return values do not include person identifiers and need no explicit informed consent. There will be no ethical complications in submitting SISA return values to central databases. Values for several families may be combined. Values for a family may be updated by the contributor. SISA is used to consider penetrance whenever sequencing demonstrates a VUS in the known cancer-predisposing genes. Any family structure at hand in a genetic clinic may be used. One may include an extended lineage in a family through demonstrating the same VUS in a distant relative, and thereby identifying all obligate carriers in between. Such extension is a way to escape the selection biases through expanding the families outside the clusters used to select the families.

Morphological Analysis of 13 LMNA Variants Identified in a Cohort of 324 Unrelated Patients With Idiopathic or Familial Dilated Cardiomyopathy

Mutations in the LMNA gene, encoding lamins A/C, represent a significant cause of dilated cardiomyopathy. We recently identified 18 protein-altering LMNA variants in a cohort of 324 unrelated patients with dilated cardiomyopathy. However, at least one family member with dilated cardiomyopathy in each of 6 pedigrees lacked the LMNA mutation (nonsegregation), whereas small sizes of 5 additional families precluded definitive determinations of segregation, raising questions regarding contributions by those variants to disease. We have consequently expressed, in COS7 cells, GFP-prelamin A (GFPLaA) fusion constructs incorporating the 6 variants in pedigrees with nonsegregation (R101P, A318T, R388H, R399C, S437Hfsx1, and R654X), the 4 variants in pedigrees with unknown segregation (R89L, R166P [in 2 families], I210S, R471H), and 3 additional missense variants (R190Q, E203K, and L215P) that segregated with disease. Confocal immunofluorescence microscopy was used to characterize GFP-lamin A localization and nuclear morphology. Abnormal phenotypes were observed for 10 of 13 (77%) variants (R89L, R101P, R166P, R190Q, E203K, I210S, L215P, R388H, S437Hfsx1, and R654X), including 4 of 6 showing nonsegregation and 3 of 4 with uncertain segregation. All 7 variants affecting coil 1B and the lamin A-only mutation, R654X, exhibited membrane-bound GFP-lamin A aggregates and nuclear shape abnormalities. Unexpectedly, R388H largely restricted GFP-lamin A to the cytoplasm. Equally unexpected were unique streaked aggregates with S437Hfsx1 and giant aggregates with both S437Hfsx1 and R654X. This work expands the recognized spectrum of lamin A localization abnormalities in dilated cardiomyopathy. It also provides evidence supporting pathogenicity of 10 of 13 tested LMNA variants, including some with uncertain or nonsegregation.

Analysis of four DLX homeobox genes in autistic probands.

BackgroundLinkage studies in autism have identified susceptibility loci on chromosomes 2q and 7q, regions containing the DLX1/2 and DLX5/6 bigene clusters. The DLX genes encode homeodomain transcription factors that control craniofacial patterning and differentiation and survival of forebrain inhibitory neurons. We investigated the role that sequence variants in DLX genes play in autism by in-depth resequencing of these genes in 161 autism probands from the AGRE collection.ResultsSequencing of exons, exon/intron boundaries and known enhancers of DLX1, 2, 5 and 6 identified several nonsynonymous variants in DLX2 and DLX5 and a variant in a DLX5/6intragenic enhancer. The nonsynonymous variants were detected in 4 of 95 families from which samples were sequenced. Two of these four SNPs were not observed in 378 undiagnosed samples from North American populations, while the remaining 2 were seen in one sample each.ConclusionSegregation of these variants in pedigrees did not generally support a contribution to autism susceptibility by these genes, although functional analyses may provide insight into the biological understanding of these important proteins.