Dataset Information

Characterization of the microDNA through the response to chemotherapeutics in lymphoblastoid cell lines.

ABSTRACT: Recently, a new class of extrachromosomal circular DNA, called microDNA, was identified. They are on average 100 to 400 bp long and are derived from unique non-repetitive genomic regions with high gene density. MicroDNAs are thought to arise from DNA breaks associated with RNA metabolism or replication slippage. Given the paucity of information on this entirely novel phenomenon, we aimed to get an additional insight into microDNA features by performing the microDNA analysis in 20 independent human lymphoblastoid cell lines (LCLs) prior and after treatment with chemotherapeutic drugs. The results showed non-random genesis of microDNA clusters from the active regions of the genome. The size periodicity of 190 bp was observed, which matches DNA fragmentation typical for apoptotic cells. The chemotherapeutic drug-induced apoptosis of LCLs increased both number and size of clusters further suggesting that part of microDNAs could result from the programmed cell death. Interestingly, proportion of identified microDNA sequences has common loci of origin when compared between cell line experiments. While compatible with the original observation that microDNAs originate from a normal physiological process, obtained results imply complementary source of its production. Furthermore, non-random genesis of microDNAs depicted by redundancy between samples makes these entities possible candidates for new biomarker generation.

SUBMITTER: Mehanna P

PROVIDER: S-EPMC5587290 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Characterization of the microDNA through the response to chemotherapeutics in lymphoblastoid cell lines.

Mehanna Pamela P Gagné Vincent V Lajoie Mathieu M Spinella Jean-François JF St-Onge Pascal P Sinnett Daniel D Brukner Ivan I Krajinovic Maja M

PloS one 20170906 9

Recently, a new class of extrachromosomal circular DNA, called microDNA, was identified. They are on average 100 to 400 bp long and are derived from unique non-repetitive genomic regions with high gene density. MicroDNAs are thought to arise from DNA breaks associated with RNA metabolism or replication slippage. Given the paucity of information on this entirely novel phenomenon, we aimed to get an additional insight into microDNA features by performing the microDNA analysis in 20 independent hum ...[more]

PMID: 28877255

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Project description:BackgroundStatins are widely prescribed to lower plasma low-density lipoprotein cholesterol levels. Though statins reduce cardiovascular disease risk overall, statin efficacy varies, and some people experience adverse side effects while on statin treatment. Statins also have pleiotropic effects not directly related to their cholesterol-lowering properties, but the mechanisms are not well understood. To identify potential genetic modulators of clinical statin response, we looked for genetic variants associated with statin-induced changes in gene expression (differential eQTLs or deQTLs) in lymphoblastoid cell lines (LCLs) derived from participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial. We exposed CAP LCLs to 2 μM simvastatin or control buffer for 24 h and performed polyA-selected, strand-specific RNA-seq. Statin-induced changes in gene expression from 259 European ancestry or 153 African American ancestry LCLs were adjusted for potential confounders prior to association with genotyped and imputed genetic variants within 1 Mb of each gene's transcription start site.ResultsFrom the deQTL meta-analysis of the two ancestral populations, we identified significant cis-deQTLs for 15 genes (TBC1D4, MDGA1, CHI3L2, OAS1, GATM, ASNSD1, GLUL, TDRD12, PPIP5K2, OAS3, SERPINB1, ANKDD1A, DTD1, CYFIP2, and GSDME), eight of which were significant in at least one of the ancestry subsets alone. We also conducted eQTL analyses of the endogenous (control-treated), statin-treated, and average of endogenous and statin-treated LCL gene expression levels. We identified eQTLs for approximately 6000 genes in each of the three (endogenous, statin-treated, and average) eQTL meta-analyses, with smaller numbers identified in the ancestral subsets alone.ConclusionsSeveral of the genes in which we identified deQTLs have functions in human health and disease, such as defense from viruses, glucose regulation, and response to chemotherapy drugs. This suggests that DNA variation may play a role in statin effects on various health outcomes. These findings could prove useful to future studies aiming to assess benefit versus risk of statin treatment using individual genetic profiles.

Project description:Lymphoblastoid cell line (LCL) is a common tool to study genetic disorders. However, it has not been fully characterized to what degree LCLs preserve the in vivo status of non-genetic biological systems, such as DNA methylation and gene transcription. We previously reported that DNA methylation in LCLs is highly variable in a data set of ~27,000 CpG dinucleotide sites around transcription start site (TSS) and 63 human subjects including healthy controls and probands of genetic disorders. Disease-causing mutations are linked to differential methylation at some CpG sites, but account for a small proportion of the total variance. In this study, we repeated the experiments to ensure that the high variance is not due to technical error and scrutinized the characteristics of DNA methylation and its association with other biological systems. Using sequence information and ChIP-seq data, we conclude that local CpG density and histone modifications not only correlate to baseline methylation level, but also affect the direction of methylation change in LCLs. Integrative analysis of gene transcription and DNA methylation data of the same subjects shows that medium or high methylation around TSS blocks the transcription while low methylation is a necessary, but not sufficient condition of downstream gene transcription. We utilized epigenetic information around TSS to predict active gene transcription via logistic regression models. The multivariate model using DNA methylation, eight histone modifications, and two regulatory protein complexes (CTCF and cohesin) as predictors has better performance (accuracy=95.1%) than any univariate models of single predictors. Linear regression analysis further shows that the transcriptional levels predicted by epigenetic markers have significant correlation to microarray measurements (p=2.2e-10). This study provides new insights into the epigenetic systems of LCLs and suggests that more specifically designed experiments are needed to improve our understanding on this topic.

Dataset Information

Characterization of the microDNA through the response to chemotherapeutics in lymphoblastoid cell lines.

Publications

Characterization of the microDNA through the response to chemotherapeutics in lymphoblastoid cell lines.

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