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Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.

ABSTRACT: The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remain unclear. We performed a systematic secondary-variant burden analysis of two independent cohorts of patients with Bardet-Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants in patients with BBS compared with either population controls or a cohort of individuals with a non-BBS diagnosis and recessive variants in the same gene set. Strikingly, we found a significant over-representation of secondary alleles in chaperonin-encoding genes-a finding corroborated by the observation of epistatic interactions involving this complex in vivo. These data indicate a complex genetic architecture for BBS that informs the biological properties of disease modules and presents a model for secondary-variant burden analysis in recessive disorders.

SUBMITTER: Kousi M

PROVIDER: S-EPMC8272915 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.

Kousi Maria M Söylemez Onuralp O Ozanturk Aysegül A Mourtzi Niki N Akle Sebastian S Jungreis Irwin I Muller Jean J Cassa Christopher A CA Brand Harrison H Mokry Jill Anne JA Wolf Maxim Y MY Sadeghpour Azita A McFadden Kelsey K Lewis Richard A RA Talkowski Michael E ME Dollfus Hélène H Kellis Manolis M Davis Erica E EE Sunyaev Shamil R SR Katsanis Nicholas N

Nature genetics 20201012 11

The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remain unclear. We performed a systematic secondary-variant burden analysis of two independent cohorts of patients with Bardet-Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants in patient ...[more]

PMID: 33046855

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Project description:Among neonatal cardiomyopathies, primary endocardial fibroelastosis (pEFE) remains a mysterious disease of the endomyocardium that is poorly genetically characterized, affecting 1/5000 live births and accounting for 25% of the entire pediatric dilated cardiomyopathy (DCM) with a devastating course and grave prognosis. To investigate the potential genetic contribution to pEFE, we performed integrative genomic analysis, using whole exome sequencing (WES) and RNA-seq in a female infant with confirmed pathological diagnosis of pEFE. Within regions of homozygosity in the proband genome, WES analysis revealed novel parent-transmitted homozygous mutations affecting three genes with known roles in cilia assembly or function. Among them, a novel homozygous variant [c.1943delA] of uncertain significance in ALMS1 was prioritized for functional genomic and mechanistic analysis. Loss of function mutations of ALMS1 have been implicated in Alstrom syndrome (AS) [OMIM 203800], a rare recessive ciliopathy that has been associated with cardiomyopathy. The variant of interest results in a frameshift introducing a premature stop codon. RNA-seq of the proband's dermal fibroblasts confirmed the impact of the novel ALMS1 variant on RNA-seq reads and revealed dysregulated cellular signaling and function, including the induction of epithelial mesenchymal transition (EMT) and activation of TGFβ signaling. ALMS1 loss enhanced cellular migration in patient fibroblasts as well as neonatal cardiac fibroblasts, while ALMS1-depleted cardiomyocytes exhibited enhanced proliferation activity. Herein, we present the unique pathological features of pEFE compared to DCM and utilize integrated genomic analysis to elucidate the molecular impact of a novel mutation in ALMS1 gene in an AS case. Our report provides insights into pEFE etiology and suggests, for the first time to our knowledge, ciliopathy as a potential underlying mechanism for this poorly understood and incurable form of neonatal cardiomyopathy. KEY MESSAGE: Primary endocardial fibroelastosis (pEFE) is a rare form of neonatal cardiomyopathy that occurs in 1/5000 live births with significant consequences but unknown etiology. Integrated genomics analysis (whole exome sequencing and RNA sequencing) elucidates novel genetic contribution to pEFE etiology. In this case, the cardiac manifestation in Alstrom syndrome is pEFE. To our knowledge, this report provides the first evidence linking ciliopathy to pEFE etiology. Infants with pEFE should be examined for syndromic features of Alstrom syndrome. Our findings lead to a better understanding of the molecular mechanisms of pEFE, paving the way to potential diagnostic and therapeutic applications.

Project description:BackgroundThe etiology of cancer involves a complex series of genetic and environmental conditions. To better represent and study the intricate genetics of cancer onset and progression, we construct a network of biological interactions to search for groups of genes that compose cancer-related modules. Three cancer expression datasets are investigated to prioritize genes and interactions associated with cancer outcomes. Using a graph-based approach to search for communities of phenotype-related genes in microarray data, we find modules of genes associated with cancer phenotypes in a weighted interaction network.ResultsWe implement Walktrap, a random-walk-based community detection algorithm, to identify biological modules predisposing to tumor growth in 22 hepatocellular carcinoma samples (GSE14520), adenoma development in 32 colorectal cancer samples (GSE8671), and prognosis in 198 breast cancer patients (GSE7390). For each study, we find the best scoring partitions under a maximum cluster size of 200 nodes. Significant modules highlight groups of genes that are functionally related to cancer and show promise as therapeutic targets; these include interactions among transcription factors (SPIB, RPS6KA2 and RPS6KA6), cell-cycle regulatory genes (BRSK1, WEE1 and CDC25C), modulators of the cell-cycle and proliferation (CBLC and IRS2) and genes that regulate and participate in the map-kinase pathway (MAPK9, DUSP1, DUSP9, RIPK2). To assess the performance of Walktrap to find genomic modules (Walktrap-GM), we evaluate our results against other tools recently developed to discover disease modules in biological networks. Compared with other highly cited module-finding tools, jActiveModules and Matisse, Walktrap-GM shows strong performance in the discovery of modules enriched with known cancer genes.ConclusionsThese results demonstrate that the Walktrap-GM algorithm identifies modules significantly enriched with cancer genes, their joint effects and promising candidate genes. The approach performs well when evaluated against similar tools and smaller overall module size allows for more specific functional annotation and facilitates the interpretation of these modules.

Dataset Information

Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.

Publications

Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy.

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