Dataset Information

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery.

ABSTRACT: Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98% of the genome and are distributed unevenly across chromosomes. MCRs containing the same MCS tend to be located on the same chromosome. Gene Ontology (GO) analyses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgi-related cellular component terms and various enzymatic activities in the GO biological function category. MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks. Moreover, genetic variants discovered by genome-wide association studies and recorded in dbSNP are significantly underrepresented in MCRs. Using simulated HTS datasets, we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions. These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.

SUBMITTER: Sun J

PROVIDER: S-EPMC8377240 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery.

Sun Jing J Zhang Yanfang Y Wang Minhui M Guan Qian Q Yang Xiujia X Ou Jin Xia JX Yan Mingchen M Wang Chengrui C Zhang Yan Y Li Zhi-Hao ZH Lan Chunhong C Mao Chen C Zhou Hong-Wei HW Hao Bingtao B Zhang Zhenhai Z

Genomics, proteomics & bioinformatics 20200819 5

Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98% of the g ...[more]

PMID: 32827758

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Project description:BACKGROUND:1q21.1 Copy Number Variant (CNV) is associated with a highly variable phenotype ranging from congenital anomalies, learning deficits/intellectual disability (ID), to a normal phenotype. Hence, the clinical significance of this CNV can be difficult to evaluate. Here we described the consequences of the 1q21.1 CNV on genome-wide gene expression and function of selected candidate genes within 1q21.1 using cell lines from clinically well described subjects. METHODS AND RESULTS:Eight subjects from 3 families were included in the study: six with a 1q21.1 deletion and two with a 1q21.1 duplication. High resolution Affymetrix 2.7M array was used to refine the 1q21.1 CNV breakpoints and exclude the presence of secondary CNVs of pathogenic relevance. Whole genome expression profiling, studied in lymphoblast cell lines (LBCs) from 5 subjects, showed enrichment of genes from 1q21.1 in the top 100 genes ranked based on correlation of expression with 1q21.1 copy number. The function of two top genes from 1q21.1, CHD1L/ALC1 and PRKAB2, was studied in detail in LBCs from a deletion and a duplication carrier. CHD1L/ALC1 is an enzyme with a role in chromatin modification and DNA damage response while PRKAB2 is a member of the AMP kinase complex, which senses and maintains systemic and cellular energy balance. The protein levels for CHD1L/ALC1 and PRKAB2 were changed in concordance with their copy number in both LBCs. A defect in chromatin remodeling was documented based on impaired decatenation (chromatid untangling) checkpoint (DCC) in both LBCs. This defect, reproduced by CHD1L/ALC1 siRNA, identifies a new role of CHD1L/ALC1 in DCC. Both LBCs also showed elevated levels of micronuclei following treatment with a Topoisomerase II inhibitor suggesting increased DNA breaks. AMP kinase function, specifically in the deletion containing LBCs, was attenuated. CONCLUSION:Our studies are unique as they show for the first time that the 1q21.1 CNV not only causes changes in the expression of its key integral genes, associated with changes at the protein level, but also results in changes in their known function, in the case of AMPK, and newly identified function such as DCC activation in the case of CHD1L/ALC1. Our results support the use of patient lymphoblasts for dissecting the functional sequelae of genes integral to CNVs in carrier cell lines, ultimately enhancing understanding of biological processes which may contribute to the clinical phenotype.

Project description:Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject's CNVs case by case.

Dataset Information

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery.

Publications

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery.

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