Dataset Information

Heterogeneous lengths of copy number mutations in human coagulopathy revealed by genome-wide high-density SNP array.

ABSTRACT: BACKGROUND: The recent advent of genome-wide molecular platforms has facilitated our understanding of the human genome and disease, particularly copy number aberrations. We performed genome-wide single nucleotide polymorphism-array in hereditary coagulopathy to delineate the extent of copy number mutations and to assess its diagnostic utility. DESIGN AND METHODS: The study subjects were 17 patients with hereditary coagulopathy from copy number mutations in coagulation genes detected by multiple ligation-dependent probe amplification. Eleven had hemophilia (7 hemophilia A and 4 hemophilia B) and 6 had thrombophilia (4 protein S deficiency and 2 antithrombin deficiency). Single nucleotide polymorphism-array experiments were performed using Affymetrix Genome-Wide Human SNP arrays 6.0. RESULTS: Copy number mutations were identified by single nucleotide polymorphism-array in 9 patients, which ranged in length from 51 Kb to 6,288 Kb harboring 2 to ~160 genes. Single nucleotide polymorphism-array showed a neutral copy number status in 8 patients including 7 with either a single-exon copy number mutation or duplication mutations of PROS1. CONCLUSIONS: This study revealed unexpectedly heterogeneous lengths of copy number mutations underlying human coagulopathy. Single nucleotide polymorphism-array had limitations in detecting copy number mutations involving a single exon or those of a gene with homologous sequences such as a pseudogene.

SUBMITTER: Kim HJ

PROVIDER: S-EPMC3269493 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Heterogeneous lengths of copy number mutations in human coagulopathy revealed by genome-wide high-density SNP array.

Kim Hee-Jin HJ Kim Duk-Kyung DK Yoo Ki-Young KY You Chur-Woo CW Yoo Jong-Ha JH Lee Ki-O KO Park In-Ae IA Choung Hae-Sun HS Kim Hee-Jung HJ Song Min-Jung MJ Kim Sun-Hee SH

Haematologica 20111011 2

<h4>Background</h4>The recent advent of genome-wide molecular platforms has facilitated our understanding of the human genome and disease, particularly copy number aberrations. We performed genome-wide single nucleotide polymorphism-array in hereditary coagulopathy to delineate the extent of copy number mutations and to assess its diagnostic utility.<h4>Design and methods</h4>The study subjects were 17 patients with hereditary coagulopathy from copy number mutations in coagulation genes detected ...[more]

PMID: 21993689

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Project description:BackgroundBtau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases.ResultsIn this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7 kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to the UMD3.1 assembly's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development.ConclusionWe present a comprehensive result of cattle CNVs at a higher resolution and sensitivity. We identified over 3,000 candidate CNV regions on both Btau_4.0 and UMD3.1, further compared current datasets with previous results, and examined the impacts of genome assemblies on CNV calling.

Project description:BackgroundCopy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform.We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the "gold standard". Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the "gold standard". Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package.ResultsSimply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest.ConclusionWe found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling.

Project description:BACKGROUND: In recent years, genome-wide association studies have successfully uncovered single-nucleotide polymorphisms (SNPs) associated with complex traits such as diseases and quantitative phenotypes. These variations account for a small proportion of heritability. With the development of high throughput techniques, abundant submicroscopic structural variations have been found in organisms, of which the main variations are copy number variations (CNVs). Therefore, CNVs are increasingly recognized as an important and abundant source of genetic variation and phenotypic diversity. RESULTS: Analyses of CNVs in the genomes of three sheep breeds were performed using the Ovine SNP50 BeadChip array. A total of 238 CNV regions (CNVRs) were identified, including 219 losses, 13 gains, and six with both events (losses and gains), which cover 60.35 Mb of the sheep genomic sequence and correspond to 2.27% of the autosomal genome sequence. The length of the CNVRs on autosomes range from 13.66 kb to 1.30 Mb with a mean size of 253.57 kb, and 75 CNVRs events had a frequency > 3%. Among these CNVRs, 47 CNVRs identified by the PennCNV overlapped with the CNVpartition. Functional analysis indicated that most genes in the CNVRs were significantly enriched for involvement in the environmental response. Furthermore, 10 CNVRs were selected for validation and 6 CNVRs were further experimentally confirmed by qPCR. In addition, there were 57 CNVRs overlapped in our new dataset and other published ruminant CNV studies. CONCLUSIONS: In this study, we firstly constructed a sheep CNV map based on the Ovine SNP50 array. Our results demonstrated the differences of two detection tools and integration of multiple algorithms can enhance the detection of sheep genomic structure variations. Furthermore, our findings would be of help for understanding the sheep genome and provide preliminary foundation for carrying out the CNVs association studies with economically important phenotypes of sheep in the future.

Project description:BackgroundCopy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.ResultsAPT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.ConclusionsIf the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.

Dataset Information

Heterogeneous lengths of copy number mutations in human coagulopathy revealed by genome-wide high-density SNP array.

Publications

Heterogeneous lengths of copy number mutations in human coagulopathy revealed by genome-wide high-density SNP array.

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