Dataset Information

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila.

ABSTRACT: Advances in sequencing technology have made whole-genome and whole-exome datasets more accessible for both clinical diagnosis and cutting-edge human genetics research. Although a number of in silico algorithms have been developed to predict the pathogenicity of variants identified in these datasets, functional studies are critical to determining how specific genomic variants affect protein function, especially for missense variants. In the Undiagnosed Diseases Network (UDN) and other rare disease research consortia, model organisms (MO) including Drosophila, C. elegans, zebrafish, and mice are actively used to assess the function of putative human disease-causing variants. This protocol describes a method for the functional assessment of rare human variants used in the Model Organisms Screening Center Drosophila Core of the UDN. The workflow begins with gathering human and MO information from multiple public databases, using the MARRVEL web resource to assess whether the variant is likely to contribute to a patient's condition as well as design effective experiments based on available knowledge and resources. Next, genetic tools (e.g., T2A-GAL4 and UAS-human cDNA lines) are generated to assess the functions of variants of interest in Drosophila. Upon development of these reagents, two-pronged functional assays based on rescue and overexpression experiments can be performed to assess variant function. In the rescue branch, the endogenous fly genes are "humanized" by replacing the orthologous Drosophila gene with reference or variant human transgenes. In the overexpression branch, the reference and variant human proteins are exogenously driven in a variety of tissues. In both cases, any scorable phenotype (e.g., lethality, eye morphology, electrophysiology) can be used as a read-out, irrespective of the disease of interest. Differences observed between reference and variant alleles suggest a variant-specific effect, and thus likely pathogenicity. This protocol allows rapid, in vivo assessments of putative human disease-causing variants of genes with known and unknown functions.

SUBMITTER: Harnish JM

PROVIDER: S-EPMC7418855 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila.

Harnish J Michael JM Deal Samantha L SL Chao Hsiao-Tuan HT Wangler Michael F MF Yamamoto Shinya S

Journal of visualized experiments : JoVE 20190820 150

Advances in sequencing technology have made whole-genome and whole-exome datasets more accessible for both clinical diagnosis and cutting-edge human genetics research. Although a number of in silico algorithms have been developed to predict the pathogenicity of variants identified in these datasets, functional studies are critical to determining how specific genomic variants affect protein function, especially for missense variants. In the Undiagnosed Diseases Network (UDN) and other rare diseas ...[more]

PMID: 31498321

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Project description:BackgroundGenome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson's disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.ResultsWe propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson's disease case-control dataset as a model to demonstrate the application of our method. Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson's disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson's disease.ConclusionsOur method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson's disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

Project description:Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

Project description:Atypical hemolytic uremic syndrome (aHUS) is a rare disease characterized by microangiopathic hemolytic anemia, thrombocytopenia and renal failure. It is caused by genetic or acquired defects of the complement alternative pathway. Factor H autoantibodies (anti-FHs) have been reported in 10% of aHUS patients and are associated with the deficiency of factor H-related 1 (FHR1). However, FHR1 deficiency is not enough to cause aHUS, since it is also present in about 5% of Caucasian healthy subjects. In this study we evaluated the prevalence of genetic variants in CFH, CD46, CFI, CFB, C3, and THBD in aHUS patients with anti-FHs, using healthy subjects with FHR1 deficiency, here defined "supercontrols," as a reference group. "Supercontrols" are more informative than general population because they share at least one risk factor (FHR1 deficiency) with aHUS patients. We analyzed anti-FHs in 305 patients and 30 were positive. The large majority were children (median age: 7.7 [IQR, 6.6-9.9] years) and 83% lacked FHR1 (n = 25, cases) due to the homozygous CFHR3-CFHR1 deletion (n = 20), or the compound heterozygous CFHR3-CFHR1 and CFHR1-CFHR4 deletions (n = 4), or the heterozygous CFHR3-CFHR1 deletion combined with a frameshift mutation in CFHR1 that generates a premature stop codon (n = 1). Of the 960 healthy adult subjects 48 had the FHR1 deficiency ("supercontrols"). Rare likely pathogenetic variants in CFH, THBD, and C3 were found in 24% of cases (n = 6) compared to 2.1% of the "supercontrols" (P-value = 0.005). We also found that the CFH H3 and the CD46 GGAAC haplotypes are not associated with anti-FHs aHUS, whereas these haplotypes are enriched in aHUS patients without anti-FHs, which highlights the differences in the genetic basis of the two forms of the disease. Finally, we confirm that common infections are environmental factors that contribute to the development of anti-FHs aHUS in genetically predisposed individuals, which fits with the sharp peak of incidence during scholar-age. Further studies are needed to fully elucidate the complex genetic and environmental factors underlying anti-FHs aHUS and to establish whether the combination of anti-FHs with likely pathogenetic variants or other risk factors influences disease outcome and response to therapies.

Dataset Information

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila.

Publications

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila.

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