Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data

Background

Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells.

Principal Finding

Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection.

Conclusion

Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.     

Digital PCR Validates 8q Dosage as Prognostic Tool in Uveal Melanoma

Background

Uveal melanoma (UM) development and progression is correlated with specific molecular changes. Recurrent mutations in GNAQ and GNA11 initiate UM development while tumour progression is correlated with monosomy of chromosome 3 and gain of chromosome 8q. Hence, molecular analysis of UM is useful for diagnosis and prognosis. The aim of this study is to evaluate the use of digital PCR (dPCR) for molecular analysis of UM.

Methods

A series of 66 UM was analysed with dPCR for three hotspot mutations in GNAQ/GNA11 with mutation specific probes. The status of chromosomes 3 and 8 were analysed with genomic probes. The results of dPCR analysis were cross-validated with Sanger sequencing, SNP array analysis, and karyotyping.

Results

Using dPCR, we were able to reconstitute the molecular profile of 66 enucleated UM. With digital PCR, GNAQ/GNA11 mutations were detected in 60 of the 66 UM. Sanger sequencing revealed three rare variants, and, combined, these assays revealed GNAQ/GNA11 mutations in 95% of UM. Monosomy 3 was present in 43 and chromosome 8 aberrations in 52 of the 66 UM. Survival analysis showed that increasing 8q copy numbers were positively correlated with metastasis risk.

Conclusion

Molecular analysis with dPCR is fast and sensitive. Just like the recurrent genomic aberrations of chromosome 3 and 8, hotspot mutations in GNAQ and GNA11 are effectively detected in heterogeneous samples. Increased sensitivity contributes to the number of mutations and chromosomal aberrations detected. Moreover, quantification of copy number with dPCR validated 8q dosage as a sensitive prognostic tool in UM, of which implementation in disease prediction models will further improve prognostication.     

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

Introduction

In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.

Methods

We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).

Results

Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.

Conclusion

Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.     

SNP rs10248565 in HDAC9 as a novel genomic aberration biomarker of lung adenocarcinoma in non-smoking women

Background

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Although cigarette smoking is the primary risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. Since cancer results from progressive accumulation of genetic aberrations, genomic rearrangements may be early events in carcinogenesis.

Results

In order to identify biomarkers of early-stage adenocarcinoma, the genome-wide DNA aberrations of 60 pairs of lung adenocarcinoma and adjacent normal lung tissue in non-smoking women were examined using Affymetrix Genome-Wide Human SNP 6.0 arrays. Common copy number variation (CNV) regions were identified by ≥30% of patients with copy number beyond 2 ± 0.5 of copy numbers for each single nucleotide polymorphism (SNP) and at least 100 continuous SNP variant loci. SNPs associated with lung adenocarcinoma were identified by McNemar’s test. Loss of heterozygosity (LOH) SNPs were identified in ≥18% of patients with LOH in the locus. Aberration of SNP rs10248565 at HDAC9 in chromosome 7p21.1 was identified from concurrent analyses of CNVs, SNPs, and LOH.

Conclusion

The results elucidate the genetic etiology of lung adenocarcinoma by demonstrating that SNP rs10248565 may be a potential biomarker of cancer susceptibility.     

Mismatch and G-Stack Modulated Probe Signals on SNP Microarrays

Background

Single nucleotide polymorphism (SNP) arrays are important tools widely used for genotyping and copy number estimation. This technology utilizes the specific affinity of fragmented DNA for binding to surface-attached oligonucleotide DNA probes. We analyze the variability of the probe signals of Affymetrix GeneChip SNP arrays as a function of the probe sequence to identify relevant sequence motifs which potentially cause systematic biases of genotyping and copy number estimates.

Methodology/Principal Findings

The probe design of GeneChip SNP arrays enables us to disentangle different sources of intensity modulations such as the number of mismatches per duplex, matched and mismatched base pairings including nearest and next-nearest neighbors and their position along the probe sequence. The effect of probe sequence was estimated in terms of triple-motifs with central matches and mismatches which include all 256 combinations of possible base pairings. The probe/target interactions on the chip can be decomposed into nearest neighbor contributions which correlate well with free energy terms of DNA/DNA-interactions in solution. The effect of mismatches is about twice as large as that of canonical pairings. Runs of guanines (G) and the particular type of mismatched pairings formed in cross-allelic probe/target duplexes constitute sources of systematic biases of the probe signals with consequences for genotyping and copy number estimates. The poly-G effect seems to be related to the crowded arrangement of probes which facilitates complex formation of neighboring probes with at minimum three adjacent G''s in their sequence.

Conclusions

The applied method of “triple-averaging” represents a model-free approach to estimate the mean intensity contributions of different sequence motifs which can be applied in calibration algorithms to correct signal values for sequence effects. Rules for appropriate sequence corrections are suggested.     

Detection of MET Gene Copy Number in Cancer Samples Using the Droplet Digital PCR Method

Purpose

The analysis of MET gene copy number (CN) has been considered to be a potential biomarker to predict the response to MET-targeted therapies in various cancers. However, the current standard methods to determine MET CN are SNP 6.0 in the genomic DNA of cancer cell lines and fluorescence in situ hybridization (FISH) in tumor models, respectively, which are costly and require advanced technical skills and result in relatively subjective judgments. Therefore, we employed a novel method, droplet digital PCR (ddPCR), to determine the MET gene copy number with high accuracy and precision.

Methods

The genomic DNA of cancer cell lines or tumor models were tested and compared with the MET gene CN and MET/CEN-7 ratio determined by SNP 6.0 and FISH, respectively.

Results

In cell lines, the linear association of the MET CN detected by ddPCR and SNP 6.0 is strong (Pearson correlation = 0.867). In tumor models, the MET CN detected by ddPCR was significantly different between the MET gene amplification and non-amplification groups according to FISH (mean: 15.4 vs 2.1; P = 0.044). Given that MET gene amplification is defined as MET CN >5.5 by ddPCR, the concordance rate between ddPCR and FISH was 98.0%, and Cohen''s kappa coefficient was 0.760 (95% CI, 0.498–1.000; P <0.001).

Conclusions

The results demonstrated that the ddPCR method has the potential to quantify the MET gene copy number with high precision and accuracy as compared with the results from SNP 6.0 and FISH in cancer cell lines and tumor samples, respectively.     

Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

Background

Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays.

Results

We evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection.

Conclusion

We observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity.     

Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data

Intra-tumor heterogeneity concerns the existence of genetically different subclones within the same tumor. Single sample quantification of heterogeneity relies on precise determination of chromosomal copy numbers throughout the genome, and an assessment of whether identified mutation variant allele fractions match clonal or subclonal copy numbers. We discuss these issues using data from SNP arrays, whole exome sequencing and pathologist purity estimates on several breast cancers characterized by ERBB2 amplification. We show that chromosomal copy numbers can only be estimated from SNP array signals or sequencing depths for subclonal tumor samples with simple subclonal architectures under certain assumptions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0470-7) contains supplementary material, which is available to authorized users.     

Inferring copy number and genotype in tumour exome data

Background

Using whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequencing, however is predominantly used for variant detection and infrequently utilised for detection of somatic copy number variation.

Results

We propose a new method to infer copy number and genotypes using whole exome data from paired tumour/normal samples. Our algorithm uses two Hidden Markov Models to predict copy number and genotypes and computationally resolves polyploidy/aneuploidy, normal cell contamination and signal baseline shift. Our method makes explicit detection on chromosome arm level events, which are commonly found in tumour samples. The methods are combined into a package named ADTEx (Aberration Detection in Tumour Exome). We applied our algorithm to a cohort of 17 in-house generated and 18 TCGA paired ovarian cancer/normal exomes and evaluated the performance by comparing against the copy number variations and genotypes predicted using Affymetrix SNP 6.0 data of the same samples. Further, we carried out a comparison study to show that ADTEx outperformed its competitors in terms of precision and F-measure.

Conclusions

Our proposed method, ADTEx, uses both depth of coverage ratios and B allele frequencies calculated from whole exome sequencing data, to predict copy number variations along with their genotypes. ADTEx is implemented as a user friendly software package using Python and R statistical language. Source code and sample data are freely available under GNU license (GPLv3) at http://adtex.sourceforge.net/.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-732) contains supplementary material, which is available to authorized users.     

Conditional random pattern model for copy number aberration detection

Background  

DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.     

Development of a High-Throughput Resequencing Array for the Detection of Pathogenic Mutations in Osteogenesis Imperfecta

Objective

Osteogenesis imperfecta (OI) is a rare inherited skeletal disease, characterized by bone fragility and low bone density. The mutations in this disorder have been widely reported to be on various exonal hotspots of the candidate genes, including COL1A1, COL1A2, CRTAP, LEPRE1, and FKBP10, thus creating a great demand for precise genetic tests. However, large genome sizes make the process daunting and the analyses, inefficient and expensive. Therefore, we aimed at developing a fast, accurate, efficient, and cheaper sequencing platform for OI diagnosis; and to this end, use of an advanced array-based technique was proposed.

Method

A CustomSeq Affymetrix Resequencing Array was established for high-throughput sequencing of five genes simultaneously. Genomic DNA extraction from 13 OI patients and 85 normal controls and amplification using long-range PCR (LR-PCR) were followed by DNA fragmentation and chip hybridization, according to standard Affymetrix protocols. Hybridization signals were determined using GeneChip Sequence Analysis Software (GSEQ). To examine the feasibility, the outcome from new resequencing approach was validated by conventional capillary sequencing method.

Result

Overall call rates using resequencing array was 96–98% and the agreement between microarray and capillary sequencing was 99.99%. 11 out of 13 OI patients with pathogenic mutations were successfully detected by the chip analysis without adjustment, and one mutation could also be identified using manual visual inspection.

Conclusion

A high-throughput resequencing array was developed that detects the disease-associated mutations in OI, providing a potential tool to facilitate large-scale genetic screening for OI patients. Through this method, a novel mutation was also found.     

The Degree of Segmental Aneuploidy Measured by Total Copy Number Abnormalities Predicts Survival and Recurrence in Superficial Gastroesophageal Adenocarcinoma

Background

Prognostic biomarkers are needed for superficial gastroesophageal adenocarcinoma (EAC) to predict clinical outcomes and select therapy. Although recurrent mutations have been characterized in EAC, little is known about their clinical and prognostic significance. Aneuploidy is predictive of clinical outcome in many malignancies but has not been evaluated in superficial EAC.

Methods

We quantified copy number changes in 41 superficial EAC using Affymetrix SNP 6.0 arrays. We identified recurrent chromosomal gains and losses and calculated the total copy number abnormality (CNA) count for each tumor as a measure of aneuploidy. We correlated CNA count with overall survival and time to first recurrence in univariate and multivariate analyses.

Results

Recurrent segmental gains and losses involved multiple genes, including: HER2, EGFR, MET, CDK6, KRAS (recurrent gains); and FHIT, WWOX, CDKN2A/B, SMAD4, RUNX1 (recurrent losses). There was a 40-fold variation in CNA count across all cases. Tumors with the lowest and highest quartile CNA count had significantly better overall survival (p = 0.032) and time to first recurrence (p = 0.010) compared to those with intermediate CNA counts. These associations persisted when controlling for other prognostic variables.

Significance

SNP arrays facilitate the assessment of recurrent chromosomal gain and loss and allow high resolution, quantitative assessment of segmental aneuploidy (total CNA count). The non-monotonic association of segmental aneuploidy with survival has been described in other tumors. The degree of aneuploidy is a promising prognostic biomarker in a potentially curable form of EAC.     

Quantifying stability in gene list ranking across microarray derived clinical biomarkers

Background

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples.

Methods

To address these limitations, we designed a novel "Virtual Normal" algorithm (VN), which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set.

Results

The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions.

Conclusions

We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.     

Effect of MPG Gene rs2858056 Polymorphism,Copy Number Variation,and Level of Serum MPG Protein on the Risk for Rheumatoid Arthritis

Objective

This study examined the role of SNP rs2858056 of the MPG gene on the incidence and severity of rheumatoid arthritis (RA).

Methods

This cohort study enrolled 365 RA patients and 375 age- and gender-matched healthy controls, all of whom had Han Chinese ethnicity and were from Taiwan. Gene polymorphism of the SNP rs2858056 of MPG was determined from genomic DNA. Allelic frequencies and genotypes were compared among cases and controls. Quantitation of rs2858056 copy number variation (CNV) was determined. Serum samples from RA patients and controls were analyzed to determine serum levels of MPG. The relationship between rs2858056 polymorphism and clinical manifestations of RA was evaluated.

Results

Our results indicated a statistically significant difference in genotype frequency distributions at rs2858056 for RA patients and controls (p = 0.05) and a significant difference in allelic frequency in patients and controls (p = 0.04). Furthermore, there was a significantly greater level of serum MPG protein in patients than controls (p < 0.001). However, the cases and controls had no significant differences in MPG CNV (p = 0.12). We also did not detect any association of the MPG rs2858056 with rheumatoid factor (RF), extraarticular involvement, or bone erosion in the RA patients.

Conclusion

Our study suggests that RA is associated with a polymorphism in the MPG gene (rs2858056) and increased serum level of the MPG protein.     

Aberrations Involving Chromosome 1 as a Possible Predictor of Odds Ratio for Colon Cancer - Results from the Krakow Case-Control Study

Background

There is still an open question how to predict colorectal cancer risk before any morphological changes appear in the colon.

Objective

The purpose was to investigate aberrations in chromosomes 1, 2 and 4 in peripheral blood lymphocytes analyzed by fluorescence in situ hybridization technique as a tool to assess the likelihood of colorectal cancer.

Methods

A hospital-based case-control study included 20 colon cancer patients and 18 hospital-based controls. Information about potential covariates was collected by interview. The frequency of stable and unstable chromosome aberrations in chromosome 1, 2 and 4 was assessed by fluorescence in situ hybridization technique.

Results

Colorectal cancer patients, as compared to controls, had a relatively higher frequency of chromosome 1 translocations (median: 3.5 versus 1.0 /1000 cells, p = 0.006), stable aberrations (3.8 versus 1.0 /1000 cells, p = 0.007) and total aberrations (p = 0.009). There were no differences observed for chromosomes 2 and 4. Our results showed an increase in the odds of having colon cancer by about 50–80% associated with an increase by 1/1000 cells in the number of chromosome 1 aberrations.

Conclusions

The results revealed that the frequency of chromosomal aberrations, especially translocations in chromosome 1, seems to be a promising method to show a colon cancer risk. Additionally, our study suggests the reasonableness of use of biomarkers such as chromosome 1 aberrations in peripheral blood lymphocytes in screening prevention programs for individuals at higher colon cancer risk to identify those who are at increased risk and require more frequent investigations, e.g. by sigmoidoscopy.     

Microarray Analysis of Copy Number Variants on the Human Y Chromosome Reveals Novel and Frequent Duplications Overrepresented in Specific Haplogroups

Background

The human Y chromosome is almost always excluded from genome-wide investigations of copy number variants (CNVs) due to its highly repetitive structure. This chromosome should not be forgotten, not only for its well-known relevance in male fertility, but also for its involvement in clinical phenotypes such as cancers, heart failure and sex specific effects on brain and behaviour.

Results

We analysed Y chromosome data from Affymetrix 6.0 SNP arrays and found that the signal intensities for most of 8179 SNP/CN probes in the male specific region (MSY) discriminated between a male, background signals in a female and an isodicentric male containing a large deletion of the q-arm and a duplication of the p-arm of the Y chromosome. Therefore, this SNP/CN platform is suitable for identification of gain and loss of Y chromosome sequences. In a set of 1718 males, we found 25 different CNV patterns, many of which are novel. We confirmed some of these variants by PCR or qPCR. The total frequency of individuals with CNVs was 14.7%, including 9.5% with duplications, 4.5% with deletions and 0.7% exhibiting both. Hence, a novel observation is that the frequency of duplications was more than twice the frequency of deletions. Another striking result was that 10 of the 25 detected variants were significantly overrepresented in one or more haplogroups, demonstrating the importance to control for haplogroups in genome-wide investigations to avoid stratification. NO-M214(xM175) individuals presented the highest percentage (95%) of CNVs. If they were not counted, 12.4% of the rest included CNVs, and the difference between duplications (8.9%) and deletions (2.8%) was even larger.

Conclusions

Our results demonstrate that currently available genome-wide SNP platforms can be used to identify duplications and deletions in the human Y chromosome. Future association studies of the full spectrum of Y chromosome variants will demonstrate the potential involvement of gain or loss of Y chromosome sequence in different human phenotypes.     

Allele loss and down-regulation of heparanase gene are associated with the progression and poor prognosis of hepatocellular carcinoma

Objectives

The role of heparanase (HPSE) gene in cancers including hepatocellular carcinoma (HCC) is currently controversial. This study was aimed at investigating the impact of genetic alteration and expression change of HPSE on the progression and prognosis of HCC.

Methods

The HPSE gene was studied in three different aspects: (1) loss of heterozygosity (LOH) by a custom SNP microarray and DNA copy number by real-time PCR; (2) mRNA level by qRT-PCR; and (3) protein expression by immunohistochemistry. The clinical significances of allele loss and expression change of HPSE were analyzed.

Results

Microarray analysis showed that the average LOH frequency for 10 SNPs located within HPSE gene was 31.6%, three of which were significantly correlated with tumor grade, serum HBV-DNA level, and AFP concentration. In agreement with SNP LOH data, DNA copy number loss of HPSE was observed in 38.74% (43/111) of HCC cases. HPSE mRNA level was notably reduced in 74.1% (83/112) of tumor tissues compared with non-tumor liver tissues, which was significantly associated with DNA copy number loss, increased tumor size, and post-operative metastasis. HPSE protein level was also remarkably reduced in 66.3% (53/80) of tumor tissues, which was correlated with tumor grade. Patients with lower expression level of HPSE mRNA or protein had a significantly lower survival rate than those with higher expression. Cox regression analysis suggested that HPSE protein was an independent predictor of overall survival in HCC patients.

Conclusions

The results in this study demonstrate that genetic alteration and reduction of HPSE expression are associated with tumor progression and poor prognosis of HCCs, suggesting that HPSE behaves like a tumor suppressor gene and is a potential prognostic marker for HCC patients.     

Genome-Wide Association Study Identified CNP12587 Region Underlying Height Variation in Chinese Females

Introduction

Human height is a highly heritable trait considered as an important factor for health. There has been limited success in identifying the genetic factors underlying height variation. We aim to identify sequence variants associated with adult height by a genome-wide association study of copy number variants (CNVs) in Chinese.

Methods

Genome-wide CNV association analyses were conducted in 1,625 unrelated Chinese adults and sex specific subgroup for height variation, respectively. Height was measured with a stadiometer. Affymetrix SNP6.0 genotyping platform was used to identify copy number polymorphisms (CNPs). We constructed a genomic map containing 1,009 CNPs in Chinese individuals and performed a genome-wide association study of CNPs with height.

Results

We detected 10 significant association signals for height (p<0.05) in the whole population, 9 and 11 association signals for Chinese female and male population, respectively. A copy number polymorphism ({"type":"entrez-protein","attrs":{"text":"CNP12587","term_id":"893597589","term_text":"CNP12587"}}CNP12587, chr18:54081842-54086942, p = 2.41×10⁻⁴) was found to be significantly associated with height variation in Chinese females even after strict Bonferroni correction (p = 0.048). Confirmatory real time PCR experiments lent further support for CNV validation. Compared to female subjects with two copies of the CNP, carriers of three copies had an average of 8.1% decrease in height. An important candidate gene, ubiquitin-protein ligase NEDD4-like (NEDD4L), was detected at this region, which plays important roles in bone metabolism by binding to bone formation regulators.

Conclusions

Our findings suggest the important genetic variants underlying height variation in Chinese.     

A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array

Background  

DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required.