Copy Number Variations Breakpoints Research Articles

A Single Cell Level Based Method for Copy Number Variation Analysis by Low Coverage Massively Parallel Sequencing

Copy number variations (CNVs), a common genomic mutation associated with various diseases, are important in research and clinical applications. Whole genome amplification (WGA) and massively parallel sequencing have been applied to single cell CNVs analysis, which provides new insight for the fields of biology and medicine. However, the WGA-induced bias significantly limits sensitivity and specificity for CNVs detection. Addressing these limitations, we developed a practical bioinformatic methodology for CNVs detection at the single cell level using low coverage massively parallel sequencing. This method consists of GC correction for WGA-induced bias removal, binary segmentation algorithm for locating CNVs breakpoints, and dynamic threshold determination for final signals filtering. Afterwards, we evaluated our method with seven test samples using low coverage sequencing (4∼9.5%). Four single-cell samples from peripheral blood, whose karyotypes were confirmed by whole genome sequencing analysis, were acquired. Three other test samples derived from blastocysts whose karyotypes were confirmed by SNP-array analysis were also recruited. The detection results for CNVs of larger than 1 Mb were highly consistent with confirmed results reaching 99.63% sensitivity and 97.71% specificity at base-pair level. Our study demonstrates the potential to overcome WGA-bias and to detect CNVs (>1 Mb) at the single cell level through low coverage massively parallel sequencing. It highlights the potential for CNVs research on single cells or limited DNA samples and may prove as a promising tool for research and clinical applications, such as pre-implantation genetic diagnosis/screening, fetal nucleated red blood cells research and cancer heterogeneity analysis.

MATCHCLIP: locate precise breakpoints for copy number variation using CIGAR string by matching soft clipped reads

Copy number variations (CNVs) are associated with many complex diseases. Next generation sequencing data enable one to identify precise CNV breakpoints to better under the underlying molecular mechanisms and to design more efficient assays. Using the CIGAR strings of the reads, we develop a method that can identify the exact CNV breakpoints, and in cases when the breakpoints are in a repeated region, the method reports a range where the breakpoints can slide. Our method identifies the breakpoints of a CNV using both the positions and CIGAR strings of the reads that cover breakpoints of a CNV. A read with a long soft clipped part (denoted as S in CIGAR) at its 3′(right) end can be used to identify the 5′(left)-side of the breakpoints, and a read with a long S part at the 5′ end can be used to identify the breakpoint at the 3′-side. To ensure both types of reads cover the same CNV, we require the overlapped common string to include both of the soft clipped parts. When a CNV starts and ends in the same repeated regions, its breakpoints are not unique, in which case our method reports the left most positions for the breakpoints and a range within which the breakpoints can be incremented without changing the variant sequence. We have implemented the methods in a C++ package intended for the current Illumina Miseq and Hiseq platforms for both whole genome and exon-sequencing. Our simulation studies have shown that our method compares favorably with other similar methods in terms of true discovery rate, false positive rate and breakpoint accuracy. Our results from a real application have shown that the detected CNVs are consistent with zygosity and read depth information. The software package is available at http://statgene.med.upenn.edu/softprog.html.

Mutation spectrum of Drosophila CNVs revealed by breakpoint sequencing

BackgroundThe detailed study of breakpoints associated with copy number variants (CNVs) can elucidate the mutational mechanisms that generate them and the comparison of breakpoints across species can highlight differences in genomic architecture that may lead to lineage-specific differences in patterns of CNVs. Here, we provide a detailed analysis of Drosophila CNV breakpoints and contrast it with similar analyses recently carried out for the human genome.ResultsBy applying split-read methods to a total of 10x coverage of 454 shotgun sequence across nine lines of D. melanogaster and by re-examining a previously published dataset of CNVs detected using tiling arrays, we identified the precise breakpoints of more than 600 insertions, deletions, and duplications. Contrasting these CNVs with those found in humans showed that in both taxa CNV breakpoints fall into three classes: blunt breakpoints; simple breakpoints associated with microhomology; and breakpoints with additional nucleotides inserted/deleted and no microhomology. In both taxa CNV breakpoints are enriched with non-B DNA sequence structures, which may impair DNA replication and/or repair. However, in contrast to human genomes, non-allelic homologous-recombination (NAHR) plays a negligible role in CNV formation in Drosophila. In flies, non-homologous repair mechanisms are responsible for simple, recurrent, and complex CNVs, including insertions of de novo sequence as large as 60 bp.ConclusionsHumans and Drosophila differ considerably in the importance of homology-based mechanisms for the formation of CNVs, likely as a consequence of the differences in the abundance and distribution of both segmental duplications and transposable elements between the two genomes.

Hydroxyurea induces de novo copy number variants in human cells

Copy number variants (CNVs) are widely distributed throughout the human genome, where they contribute to genetic variation and phenotypic diversity. Spontaneous CNVs are also a major cause of genetic and developmental disorders and arise frequently in cancer cells. As with all mutation classes, genetic and environmental factors almost certainly increase the risk for new and deleterious CNVs. However, despite the importance of CNVs, there is limited understanding of these precipitating risk factors and the mechanisms responsible for a large percentage of CNVs. Here we report that low doses of hydroxyurea, an inhibitor of ribonucleotide reductase and an important drug in the treatment of sickle cell disease and other diseases induces a high frequency of de novo CNVs in cultured human cells that resemble pathogenic and aphidicolin-induced CNVs in size and breakpoint structure. These CNVs are distributed throughout the genome, with some hotspots of de novo CNV formation. Sequencing revealed that CNV breakpoint junctions are characterized by short microhomologies, blunt ends, and short insertions. These data provide direct experimental support for models of replication-error origins of CNVs and suggest that any agent or condition that leads to replication stress has the potential to induce deleterious CNVs. In addition, they point to a need for further study of the genomic consequences of the therapeutic use of hydroxyurea.

Mutation spectrum revealed by breakpoint sequencing of human germline CNVs

Precisely characterizing the breakpoints of copy number variants (CNVs) is crucial for assessing their functional impact. However, fewer than 10% of known germline CNVs have been mapped to the single-nucleotide level. We characterized the sequence breakpoints from a dataset of all CNVs detected in three unrelated individuals in previous array-based CNV discovery experiments. We used targeted hybridization-based DNA capture and 454 sequencing to sequence 324 CNV breakpoints, including 315 deletions. We observed two major breakpoint signatures: 70% of the deletion breakpoints have 1-30 bp of microhomology, whereas 33% of deletion breakpoints contain 1-367 bp of inserted sequence. The co-occurrence of microhomology and inserted sequence is low (10%), suggesting that there are at least two different mutational mechanisms. Approximately 5% of the breakpoints represent more complex rearrangements, including local microinversions, suggesting a replication-based strand switching mechanism. Despite a rich literature on DNA repair processes, reconstruction of the molecular events generating each of these mutations is not yet possible.

Fetal Hemoglobin in Sickle Cell Anemia: A Novel Method for High-Resolution Discovery of Associated Genomic Copy Number Variations

Fetal hemoglobin (HbF) can inhibit the polymerization of sickle hemoglobin, and the HbF level is an important modulator of the severity and course of sickle cell anemia. Genetic regulation of HbF levels is complex and under active investigation. Although multiple quantitative trait loci have been discovered, it is estimated that half of the genetic variance of HbF levels remains unaccounted for. Genomic copy number variations (CNVs), defined as inherited duplications or deletions of kilo-to mega-base lengths of DNA, represent a significant source of genetic heterogeneity among humans that might be involved in HbF regulation. Additionally, CNVs can significantly alter assumptions about genotype frequencies in their genomic region, and are therefore important to locate for multiple types of genetic association studies. Here, we present a novel method for the high-resolution discovery of CVNs related to HbF levels in sickle cell anemia, using genome-wide association study (GWAS) data. We used the Illumina 610K single nucleotide polymorphism (SNP) genotyping array to examine 727 adult subjects with sickle cell anemia, with or without a thalassemia, who were enrolled in the Cooperative Study of Sickle Cell Disease (CSSCD; aged 18 to 69 years, mean age 31 years; 44% male; not on hydroxyurea therapy). The Illumina array consisted of ~610K probes spread across the entire genome. At each locus, the relative amount of DNA detected was compared to a reference and expressed as the log R ratio score (LRR). Normal diploid regions of DNA have LRRs close to zero, whereas regions with CNVs have LRRs that are either higher for areas of duplication or lower for areas of deletion. Using LRR information in the context of a GWAS, we developed a novel, two-step signal-processing technique that combines CNV discovery with subsequent phenotypical association analysis. First, the distribution of LRR values at each locus is stratified using a +/− 1.5 standard deviation band-pass filter. This created three groups: a central major group comprised of people with diploid amounts of DNA, and two minor variant groups, one composed of people with elevated LRRs, suggesting >2 DNA copies, and one of people with decreased LRRs, suggesting <2 DNA copies at that locus. To reduce noise, loci without at least one minor group containing >5% of the sample were excluded from further analysis. In the second step, a two-sample Student's t-test was used at each locus to examine the variation in distributions of HbF between the major, diploid group and any variant groups with >5% of the population. Using this method, we examined chromosomes 2, 6, and 11, which include regions known to modulate HbF in patients with sickle cell anemia, individuals with β thalassemia, and in the normal population. We successfully detected multiple clear duplications and deletions (approx. 1 per 6–22 mbp, depending on the chromosome) that showed typical CNV LRR distributions with >10% of the population exhibiting the polymorphism. Several of these were mildly related to HbF levels (p<0.05), including deletions in ASB1 on chromosome 2, and HACE1 on chromosome 6, both ankyrin motif containing proteins involved in the ubiquitin ligase system, as well as an upstream duplication and intragenic deletion involving HLA-DRB5 on chromosome 6. None of these clear CNVs, however, overlapped regions known to affect HbF concentration. Additional potential CNVs were detected throughout each chromosome, many exhibiting atypical LRR distributions not easily classified as either a normal diploid or clear CNV region. Further studies are required to confirm the presence of a CNV at these atypical loci. With this method, we were able to detect CNVs and CNV breakpoints across a population with a single-probe resolution, to within <1kb in some cases. This resolution offers a distinct advantage over other detection methods that utilize a multiple-probe, sliding-window approach to detect LRR deviations in an individual sample. In conclusion, this two-step method of high-resolution detection of CNVs followed by analysis of phenotypical associations shows promise for explaining variations in expressed protein levels, such as those typical of HbF in sickle cell anemia, and possibly for future exploration of differences in HbF responses to therapeutics in sickle cell anemia.

Systematic prediction and validation of breakpoints associated with copy-number variants in the human genome

Copy-number variants (CNVs) are an abundant form of genetic variation in humans. However, approaches for determining exact CNV breakpoint sequences (physical deletion or duplication boundaries) across individuals, crucial for associating genotype to phenotype, have been lacking so far, and the vast majority of CNVs have been reported with approximate genomic coordinates only. Here, we report an approach, called BreakPtr, for fine-mapping CNVs (available from http://breakptr.gersteinlab.org). We statistically integrate both sequence characteristics and data from high-resolution comparative genome hybridization experiments in a discrete-valued, bivariate hidden Markov model. Incorporation of nucleotide-sequence information allows us to take into account the fact that recently duplicated sequences (e.g., segmental duplications) often coincide with breakpoints. In anticipation of an upcoming increase in CNV data, we developed an iterative, "active" approach to initially scoring with a preliminary model, performing targeted validations, retraining the model, and then rescoring, and a flexible parameterization system that intuitively collapses from a full model of 2,503 parameters to a core one of only 10. Using our approach, we accurately mapped >400 breakpoints on chromosome 22 and a region of chromosome 11, refining the boundaries of many previously approximately mapped CNVs. Four predicted breakpoints flanked known disease-associated deletions. We validated an additional four predicted CNV breakpoints by sequencing. Overall, our results suggest a predictive resolution of approximately 300 bp. This level of resolution enables more precise correlations between CNVs and across individuals than previously possible, allowing the study of CNV population frequencies. Further, it enabled us to demonstrate a clear Mendelian pattern of inheritance for one of the CNVs.