Dataset Information

Assessing the significance of conserved genomic aberrations using high resolution genomic microarrays.

ABSTRACT: Genomic aberrations recurrent in a particular cancer type can be important prognostic markers for tumor progression. Typically in early tumorigenesis, cells incur a breakdown of the DNA replication machinery that results in an accumulation of genomic aberrations in the form of duplications, deletions, translocations, and other genomic alterations. Microarray methods allow for finer mapping of these aberrations than has previously been possible; however, data processing and analysis methods have not taken full advantage of this higher resolution. Attention has primarily been given to analysis on the single sample level, where multiple adjacent probes are necessarily used as replicates for the local region containing their target sequences. However, regions of concordant aberration can be short enough to be detected by only one, or very few, array elements. We describe a method called Multiple Sample Analysis for assessing the significance of concordant genomic aberrations across multiple experiments that does not require a-priori definition of aberration calls for each sample. If there are multiple samples, representing a class, then by exploiting the replication across samples our method can detect concordant aberrations at much higher resolution than can be derived from current single sample approaches. Additionally, this method provides a meaningful approach to addressing population-based questions such as determining important regions for a cancer subtype of interest or determining regions of copy number variation in a population. Multiple Sample Analysis also provides single sample aberration calls in the locations of significant concordance, producing high resolution calls per sample, in concordant regions. The approach is demonstrated on a dataset representing a challenging but important resource: breast tumors that have been formalin-fixed, paraffin-embedded, archived, and subsequently UV-laser capture microdissected and hybridized to two-channel BAC arrays using an amplification protocol. We demonstrate the accurate detection on simulated data, and on real datasets involving known regions of aberration within subtypes of breast cancer at a resolution consistent with that of the array. Similarly, we apply our method to previously published datasets, including a 250K SNP array, and verify known results as well as detect novel regions of concordant aberration. The algorithm has been fully implemented and tested and is freely available as a Java application at http://www.cbil.upenn.edu/MSA.

SUBMITTER: Guttman M

PROVIDER: S-EPMC1950957 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Chromosomal microarray (CMA) is the reference in evaluation of copy number variations (CNVs) in individuals with neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and/or autism spectrum disorder (ASD), which affect around 3-4% of the world's population. Modern platforms for CMA, also include probes for single nucleotide polymorphisms (SNPs) that detect homozygous regions in the genome, such as long contiguous stretches of homozygosity (LCSH). These regions result from complete or segmental chromosomal homozygosis and may be indicative of uniparental disomy (UPD), inbreeding, population characteristics, as well as replicative DNA repair events. In this retrospective study, we analyzed CMA reading files requested by geneticists and neurologists for diagnostic purposes along with available clinical data. Our objectives were interpreting CNVs and assess the frequencies and implications of LCSH detected by Affymetrix CytoScan HD (41%) or 750K (59%) platforms in 1012 patients from the south of Brazil. The patients were mainly children with NDDs and/or congenital anomalies (CAs). A total of 206 CNVs, comprising 132 deletions and 74 duplications, interpreted as pathogenic, were found in 17% of the patients in the cohort and across all chromosomes. Additionally, 12% presented rare variants of uncertain clinical significance, including LPCNVs, as the only clinically relevant CNV. Within the realm of NDDs, ASD carries a particular importance, owing to its escalating prevalence and its growing repercussions for individuals, families, and communities. ASD was one clinical phenotype, if not the main reason for referral to testing, for about one-third of the cohort, and these patients were further analyzed as a sub-cohort. Considering only the patients with ASD, the diagnostic rate was 10%, within the range reported in the literature (8-21%). It was higher (16%) when associated with dysmorphic features and lower (7%) for "isolated" ASD (without ID and without dysmorphic features). In 953 CMAs of the whole cohort, LCSH (≥ 3 Mbp) were analyzed not only for their potential pathogenic significance but were also explored to identify common LCSH in the South Brazilians population. CMA revealed at least one LCSH in 91% of the patients. For about 11.5% of patients, the LCSH suggested consanguinity from the first to the fifth degree, with a greater probability of clinical impact, and in 2.8%, they revealed a putative UPD. LCSH found at a frequency of 5% or more were considered common LCSH in the general population, allowing us to delineate 10 regions as potentially representing ancestral haplotypes of neglectable clinical significance. The main referrals for CMA were developmental delay (56%), ID (33%), ASD (33%) and syndromic features (56%). Some phenotypes in this population may be predictive of a higher probability of indicating a carrier of a pathogenic CNV. Here, we present the largest report of CMA data in a cohort with NDDs and/or CAs from the South of Brazil. We characterize the rare CNVs found along with the main phenotypes presented by each patient and show the importance and usefulness of LCSH interpretation in CMA results that incorporate SNPs, as well as we illustrate the value of CMA to investigate CNV in ASD.

Dataset Information

Assessing the significance of conserved genomic aberrations using high resolution genomic microarrays.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets