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Telomere Q-PNA-FISH--reliable results from stochastic signals.

ABSTRACT: Structural and functional analysis of telomeres is very important for understanding basic biological functions such as genome stability, cell growth control, senescence and aging. Recently, serious concerns have been raised regarding the reliability of current telomere measurement methods such as Southern blot and quantitative polymerase chain reaction. Since telomere length is associated with age related pathologies, including cardiovascular disease and cancer, both at the individual and population level, accurate interpretation of measured results is a necessity. The telomere Q-PNA-FISH technique has been widely used in these studies as well as in commercial analysis for the general population. A hallmark of telomere Q-PNA-FISH is the wide variation among telomere signals which has a major impact on obtained results. In the present study we introduce a specific mathematical and statistical analysis of sister telomere signals during cell culture senescence which enabled us to identify high regularity in their variations. This phenomenon explains the reproducibility of results observed in numerous telomere studies when the Q-PNA-FISH technique is used. In addition, we discuss the molecular mechanisms which probably underlie the observed telomere behavior.

SUBMITTER: Cukusic Kalajzic A

PROVIDER: S-EPMC3958560 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Telomere Q-PNA-FISH--reliable results from stochastic signals.

Cukusic Kalajzic Andrea A Vidacek Nikolina Skrobot NS Huzak Miljenko M Ivankovic Milena M Rubelj Ivica I

PloS one 20140318 3

Structural and functional analysis of telomeres is very important for understanding basic biological functions such as genome stability, cell growth control, senescence and aging. Recently, serious concerns have been raised regarding the reliability of current telomere measurement methods such as Southern blot and quantitative polymerase chain reaction. Since telomere length is associated with age related pathologies, including cardiovascular disease and cancer, both at the individual and popula ...[more]

PMID: 24643066

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Project description:BackgroundTelomere maintenance mechanisms (TMM) are a hallmark of high-risk neuroblastoma, and are conferred by activation of telomerase or alternative lengthening of telomeres (ALT). However, detection of TMM is not yet part of the clinical routine, and consensus on TMM detection, especially on ALT assessment, remains to be achieved.MethodsWhole genome sequencing (WGS) data of 68 primary neuroblastoma samples were analyzed. Telomere length was calculated from WGS data or by telomere restriction fragment analysis (n = 39). ALT was assessed by C-circle assay (CCA, n = 67) and detection of ALT-associated PML nuclear bodies (APB) by combined fluorescence in situ hybridization and immunofluorescence staining (n = 68). RNA sequencing was performed (n = 64) to determine expression of TERT and telomeric long non-coding RNA (TERRA). Telomerase activity was examined by telomerase repeat amplification protocol (TRAP, n = 15).ResultsTumors were considered as telomerase-positive if they harbored a TERT rearrangement, MYCN amplification or high TERT expression (45.6%, 31/68), and ALT-positive if they were positive for APB and CCA (19.1%, 13/68). If all these markers were absent, tumors were considered TMM-negative (25.0%, 17/68). According to these criteria, the majority of samples were classified unambiguously (89.7%, 61/68). Assessment of additional ALT-associated parameters clarified the TMM status of the remaining seven cases with high likelihood: ALT-positive tumors had higher TERRA expression, longer telomeres, more telomere insertions, a characteristic pattern of telomere variant repeats, and were associated with ATRX mutations.ConclusionsWe here propose a workflow to reliably detect TMM in neuroblastoma. We show that unambiguous classification is feasible following a stepwise approach that determines both, activation of telomerase and ALT. The workflow proposed in this study can be used in clinical routine and provides a framework to systematically and reliably determine telomere maintenance mechanisms for risk stratification and treatment allocation of neuroblastoma patients.

Project description:Stochastic Epigenetic Mutations (SEMs) have been proposed as novel aging biomarkers that have the potential to capture heterogeneity in age-related DNA methylation (DNAme) changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide (CpG) sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. While individual SEMs are rarely consistent across subjects, the SEM load - the total number of SEMs - increases with age. However, given poor technical reliability of measurement for many DNA methylation sites, we posited that many outliers might represent technical noise. Our study of whole blood samples from 36 individuals, each measured twice, found that 23.3% of hypoSEM and 45.6% hyperSEM are not shared between replicates. This diminishes the reliability of SEM loads, where intraclass correlation coefficients are 0.96 for hypoSEM and 0.90 for hyperSEM. We linked SEM reliability to multiple factors, including blood cell type composition, probe beta-value statistics, and presence of SNPs. A machine learning approach, leveraging these factors, filtered unreliable SEMs, enhancing reliability in a separate dataset of technical replicates from 128 individuals. Analysis of the Framingham Heart Study confirmed previously reported SEM association with mortality and revealed novel connections to cardiovascular disease. We discover that associations with aging outcomes are primarily driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations are preserved after filtering out unreliable SEMs and are enhanced after adjusting for blood cell composition. Finally, we utilize these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which utilizes parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

Dataset Information

Telomere Q-PNA-FISH--reliable results from stochastic signals.

Publications

Telomere Q-PNA-FISH--reliable results from stochastic signals.

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