A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data
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PROVIDER: EGAS00001002428 | EGA |
REPOSITORIES: EGA
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Project description:A resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect.
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Project description:Missense mutations can have diverse effects on proteins, depending on their location within the protein and the specific amino acid substitution. Mutations in the DNA mismatch repair gene MLH1 are associated with Lynch syndrome, yet the underlying mechanism of most disease-causing mutations remain elusive. To address this gap, we aim to disentangle the mutational effects on two essential properties for MLH1 function: protein stability and protein-protein interaction. We systematically examine the cellular abundance and interaction with PMS2 of 4839 (94%) MLH1 variants in the C-terminal domain. Our combined data shows that most MLH1 variants lose interaction with PMS2 due to reduced cellular abundance. However, substitutions to charged residues in the canonical interface lead to reduced interaction with PMS2. Unexpectedly, we also identify a distal region in the C-terminal domain of MLH1 where substitutions cause both decreased and increased binding with PMS2. Our data successfully distinguish benign from pathogenic MLH1 variants and correlate with thermodynamic stability predictions and evolutionary conservation. This work provides mechanistic insights into variant consequences and may help interpret MLH1 variants.
2024-08-01 | GSE273652 | GEO
Project description:MutLα, a heterodimer consisting of MLH1 and PMS2, is a key player of DNA mismatch repair (MMR), yet little is known about its regulation. In this study, we used mass spectrometry to identify phosphorylated residues within MLH1 and PMS2. The most frequently detected phosphorylated amino acid was serine 477 of MLH1. Isolation of nuclear and cytoplasmic fractions showed that p-MLH1S477 remains predominantly in the cytoplasm. Pharmacological treatment indicates that Casein Kinase II (CK2) could be responsible for the phosphorylation of MLH1 at serine 477 in vivo. In vitro kinase assay verified MLH1 as a substrate of CK2. Most importantly, using in vitro MMR assay we could demonstrate that p-MLH1S477 lost MMR activity while the activity of MLH1S477A, which could not be phosphorylated at position S477, was not modified. In summary, we identified that post-translational phosphorylation of MLH1 by CK2 at amino acid position 477 can switch off MMR activity in vitro. Since CK2 is overexpressed in many tumors and is able to inactivate MMR by phosphorylation of MLH1, the new mechanism here described could have an important impact on tumors overactive in CK2.
2018-08-28 | PXD009524 | Pride
Project description:Mass spectrometry based PTM phosphorylation analysis to study regulation mechanism of MUTL alpha, a heterodimer consisting of MLH1 and PMS2 and a key player in DNA mismatch repair (MMR). It could be demonstrated that phosphorylation of MLH1 by Casein Kinase II (CK2) at amino acid position 477 can switch off MMR activity in vitro.
2018-08-29 | PXD009026 | Pride
Project description:Lynch syndrome, caused by germline heterozygous mutations of the DNA mismatch repair genes MLH1, MSH2, MSH6 and PMS2, or deletions affecting the EPCAM gene upstream of MSH2, is characterized by a predisposition to early-onset colorectal and additional extracolonic cancers. An alternative but rare cause of Lynch syndrome is a constitutional epimutation of MLH1, which is characterized by promoter methylation and transcriptional silencing of a single allele in normal tissues. Worldwide, five families with autosomal dominant transmission of a constitutional MLH1 epimutation linked to an MLH1 haplotype with two single nucleotide variants (c.-27C>A and c.85G>T) have been identified. Array-based genotyping using Affymetrix SNP 6.0 data in four of these families revealed a shared haplotype extending across a ≤2.6 Mb region of chromosome 3p22 encompassing MLH1 and additional flanking genes, indicating common ancestry. Genomic DNA from 5 carriers of the c.-27C>A and c.85G>T variants was hybridized on Affymetrix SNP6.0 array according to manufacturer's procedures
2013-04-01 | E-GEOD-45149 | biostudies-arrayexpress
Project description:Goal: To identify copy number variation in normal individuals using high density, non-polymorphic oligonucleotide probes Background DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1kb to over 3Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. Results In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3M independent NspI restriction enzyme fragments in the 200bp to 1100bp size range, which is a several fold increase in marker density as compared to the 500K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. Conclusions Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization. Keywords: Copy number variation (CNV) detection
2008-04-24 | GSE9053 | GEO
Project description:Goal: To identify copy number variation in normal individuals using high density, non-polymorphic oligonucleotide probes Background DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1kb to over 3Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. Results In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3M independent NspI restriction enzyme fragments in the 200bp to 1100bp size range, which is a several fold increase in marker density as compared to the 500K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. Conclusions Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization. A set of five genomic DNA samples containing different numbers of X chromosomes (1X to 5X sample set, including NA15510 and NA10851) were hybridized to Nsp copy number (CN) arrays in triplicate to evaluate detection of copy number variation using high density, non-polymorphic oligonucleotide probes. 6 Hapmap samples were hybridized to Nsp CN arrays to evaluate Mendelian inheritance of CNVs.
2008-04-24 | E-GEOD-9053 | biostudies-arrayexpress
Project description:Lynch syndrome, caused by germline heterozygous mutations of the DNA mismatch repair genes MLH1, MSH2, MSH6 and PMS2, or deletions affecting the EPCAM gene upstream of MSH2, is characterized by a predisposition to early-onset colorectal and additional extracolonic cancers. An alternative but rare cause of Lynch syndrome is a constitutional epimutation of MLH1, which is characterized by promoter methylation and transcriptional silencing of a single allele in normal tissues. Worldwide, five families with autosomal dominant transmission of a constitutional MLH1 epimutation linked to an MLH1 haplotype with two single nucleotide variants (c.-27C>A and c.85G>T) have been identified. Array-based genotyping using Affymetrix SNP 6.0 data in four of these families revealed a shared haplotype extending across a ≤2.6 Mb region of chromosome 3p22 encompassing MLH1 and additional flanking genes, indicating common ancestry.
2013-04-01 | GSE45149 | GEO
Project description:Copy number variants (CNVs) reshape gene structure, modulate gene expression, and contribute to significant phenotypic variation. Previous studies have revealed CNV patterns in natural populations of Drosophila melanogaster and suggested that selection and mutational bias shape genomic patterns of CNV. While previous CNV studies focused on heterogeneous strains, here we established a number of second-chromosome substitution lines to uncover CNV characteristics when homozygous. The percentage of genes harboring CNVs is higher than found in previous studies. More CNVs are detected in homozygous than heterozygous substitution strains, suggesting the comparative genomic hybridization arrays underestimate CNV owing to heterozygous masking. We incorporated previous gene expression data collected from some of the same substitution lines to investigate relationships between CNV gene dosage and expression. Most genes present in CNVs show no evidence of increased or diminished transcription, and the fraction of such dosage-insensitive CNVs is greater in heterozygotes. More than 70% of the dosage-sensitive CNVs are recessive with undetectable effects on transcription in heterozygotes. A deficiency of singletons in recessive dosage-sensitive CNVs supports the hypothesis that most CNVs are subject to negative selection. On the other hand, relaxed purifying selection might account for the higher number of protein-protein interactions in dosage insensitive CNVs than in dosage-sensitive CNVs. Dosage-sensitive CNVs that are up-regulated and down-regulated coincide with copy number increases and decreases. Our results help clarify the relation between CNV dosage and gene expression in the D. melanogaster genome.
2011-03-03 | GSE27632 | GEO
Project description:Background: High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. Results: The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4 - 489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0 - 86 %). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. Conclusions: High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies. NA12878 hybridization to Affymetrix CytoScan HD array for CNV detection
2017-03-23 | GSE96897 | GEO