%0 Journal Article %J Nat Genet %D 2021 %T Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics. %A Bonder, Marc Jan %A Smail, Craig %A Gloudemans, Michael J %A Frésard, Laure %A Jakubosky, David %A D'Antonio, Matteo %A Li, Xin %A Ferraro, Nicole M %A Carcamo-Orive, Ivan %A Mirauta, Bogdan %A Seaton, Daniel D %A Cai, Na %A Vakili, Dara %A Horta, Danilo %A Zhao, Chunli %A Zastrow, Diane B %A Bonner, Devon E %A Wheeler, Matthew T %A Kilpinen, Helena %A Knowles, Joshua W %A Smith, Erin N %A Frazer, Kelly A %A Montgomery, Stephen B %A Stegle, Oliver %K Bardet-Biedl Syndrome %K Calcium Channels %K Cell Line %K Cerebellar Ataxia %K DNA Methylation %K Gene Expression %K Genetic Variation %K Humans %K Induced Pluripotent Stem Cells %K Polymorphism, Single Nucleotide %K Proteins %K Quantitative Trait Loci %K Rare Diseases %K Regulatory Sequences, Nucleic Acid %K Sequence Analysis, RNA %K Whole Genome Sequencing %X

Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.

%B Nat Genet %V 53 %P 313-321 %8 2021 03 %G eng %N 3 %1 https://www.ncbi.nlm.nih.gov/pubmed/33664507?dopt=Abstract %R 10.1038/s41588-021-00800-7 %0 Journal Article %J Nat Med %D 2019 %T Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. %A Frésard, Laure %A Smail, Craig %A Ferraro, Nicole M %A Teran, Nicole A %A Li, Xin %A Smith, Kevin S %A Bonner, Devon %A Kernohan, Kristin D %A Marwaha, Shruti %A Zappala, Zachary %A Balliu, Brunilda %A Davis, Joe R %A Liu, Boxiang %A Prybol, Cameron J %A Kohler, Jennefer N %A Zastrow, Diane B %A Reuter, Chloe M %A Fisk, Dianna G %A Grove, Megan E %A Davidson, Jean M %A Hartley, Taila %A Joshi, Ruchi %A Strober, Benjamin J %A Utiramerur, Sowmithri %A Lind, Lars %A Ingelsson, Erik %A Battle, Alexis %A Bejerano, Gill %A Bernstein, Jonathan A %A Ashley, Euan A %A Boycott, Kym M %A Merker, Jason D %A Wheeler, Matthew T %A Montgomery, Stephen B %K Acid Ceramidase %K Case-Control Studies %K Child %K Child, Preschool %K Cohort Studies %K Female %K Genetic Variation %K Humans %K Male %K Models, Genetic %K Mutation %K Oxidoreductases Acting on CH-CH Group Donors %K Potassium Channels %K Rare Diseases %K RNA %K RNA Splicing %K Sequence Analysis, RNA %K Whole Exome Sequencing %X

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases. This includes muscle biopsies from patients with undiagnosed rare muscle disorders, and cultured fibroblasts from patients with mitochondrial disorders. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

%B Nat Med %V 25 %P 911-919 %8 2019 06 %G eng %N 6 %1 https://www.ncbi.nlm.nih.gov/pubmed/31160820?dopt=Abstract %R 10.1038/s41591-019-0457-8 %0 Journal Article %J Hum Mutat %D 2017 %T Whole-transcriptome sequencing in blood provides a diagnosis of spinal muscular atrophy with progressive myoclonic epilepsy. %A Kernohan, Kristin D %A Frésard, Laure %A Zappala, Zachary %A Hartley, Taila %A Smith, Kevin S %A Wagner, Justin %A Xu, Hongbin %A McBride, Arran %A Bourque, Pierre R %A Consortium, Care Rare Canada %A Bennett, Steffany A L %A Dyment, David A %A Boycott, Kym M %A Montgomery, Stephen B %A Warman Chardon, Jodi %K Acid Ceramidase %K Child, Preschool %K Humans %K Male %K Muscular Atrophy, Spinal %K Mutation %K Myoclonic Epilepsies, Progressive %K Pathology, Molecular %K RNA Splicing %K Sequence Analysis, DNA %K Transcriptome %X

At least 15% of the disease-causing mutations affect mRNA splicing. Many splicing mutations are missed in a clinical setting due to limitations of in silico prediction algorithms or their location in noncoding regions. Whole-transcriptome sequencing is a promising new tool to identify these mutations; however, it will be a challenge to obtain disease-relevant tissue for RNA. Here, we describe an individual with a sporadic atypical spinal muscular atrophy, in whom clinical DNA sequencing reported one pathogenic ASAH1 mutation (c.458A>G;p.Tyr153Cys). Transcriptome sequencing on patient leukocytes identified a highly significant and atypical ASAH1 isoform not explained by c.458A>G(p<10 ). Subsequent Sanger-sequencing identified the splice mutation responsible for the isoform (c.504A>C;p.Lys168Asn) and provided a molecular diagnosis of autosomal-recessive spinal muscular atrophy with progressive myoclonic epilepsy. Our findings demonstrate the utility of RNA sequencing from blood to identify splice-impacting disease mutations for nonhematological conditions, providing a diagnosis for these otherwise unsolved patients.

%B Hum Mutat %V 38 %P 611-614 %8 2017 06 %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/28251733?dopt=Abstract %R 10.1002/humu.23211