High resolution array in the clinical approach to chromosomal phenotypes

Array genomic hybridization (AGH) has recently been implemented as a diagnostic tool for the detection of submicroscopic copy number variants (CNVs) in patients with developmental disorders. However, there is no consensus regarding the choice of the platform, the minimal resolution needed and systematic interpretation of CNVs. We report our experience in the clinical diagnostic use of high resolution AGH up to 100 kb on 131 patients with chromosomal phenotypes but previously normal karyotype. We evaluated the usefulness in our clinics and laboratories by the detection rate of causal CNVs and CNVs of unknown clinical significance and to what extent their interpretation would challenge the systematic use of high-resolution arrays in clinical application. Prioritizing phenotype-genotype correlation in our interpretation strategy to criteria previously described, we identified 33 (25.2%) potentially pathogenic aberrations. 16 aberrations were confirmed pathogenic (16.4% syndromic, 8.5% non-syndromic patients); 9 were new and individual aberrations, 3 of them were pathogenic although inherited and one is as small as approx 200 kb. 13 of 16 further CNVs of unknown significance were classified likely benign, for 3 the significance remained unclear. High resolution array allows the detection of up to 12.2% of pathogenic aberrations in a diagnostic clinical setting. Although the majority of aberrations are larger, the detection of small causal aberrations may be relevant for family counseling. The number of remaining unclear CNVs is limited. Careful phenotype-genotype correlations of the individual CNVs and clinical features are challenging but remain a hallmark for CNV interpretation.     

Human gene copy number spectra analysis in congenital heart malformations

The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency "spectra" to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways.     

A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process

To study chromosomal aberrations that may lead to cancer formation or genetic diseases, the array-based Comparative Genomic Hybridization (aCGH) technique is often used for detecting DNA copy number variants (CNVs). Various methods have been developed for gaining CNVs information based on aCGH data. However, most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe (e.g., biomarker) positions/distances contained in the data. Motivated by the specific features of aCGH data, we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of multiple CNVs in the data, a sliding window process combined with our derived Bayesian posterior probability was proposed. To evaluate the performance of the method in the estimation of the CNV locus, we first performed simulation studies. Finally, we applied our approach to real data from aCGH experiments, demonstrating its applicability.     

A modified multiplex ligation-dependent probe amplification method for the detection of 22q11.2 copy number variations in patients with congenital heart disease

Background

Copy number variations (CNVs) of chromosomal region 22q11.2 are associated with a subset of patients with congenital heart disease (CHD). Accurate and efficient detection of CNV is important for genetic analysis of CHD. The aim of the study was to introduce a novel approach named CNVplex®, a high-throughput analysis technique designed for efficient detection of chromosomal CNVs, and to explore the prevalence of sub-chromosomal imbalances in 22q11.2 loci in patients with CHD from a single institute.

Results

We developed a novel technique, CNVplex®, for high-throughput detection of sub-chromosomal copy number aberrations. Modified from the multiplex ligation-dependent probe amplification (MLPA) method, it introduced a lengthening ligation system and four universal primer sets, which simplified the synthesis of probes and significantly improved the flexibility of the experiment. We used 110 samples, which were extensively characterized with chromosomal microarray analysis and MLPA, to validate the performance of the newly developed method. Furthermore, CNVplex® was used to screen for sub-chromosomal imbalances in 22q11.2 loci in 818 CHD patients consecutively enrolled from Shanghai Children’s Medical Center. In the methodology development phase, CNVplex® detected all copy number aberrations that were previously identified with both chromosomal microarray analysis and MLPA, demonstrating 100% sensitivity and specificity. In the validation phase, 22q11.2 deletion and 22q11.2 duplication were detected in 39 and 1 of 818 patients with CHD by CNVplex®, respectively. Our data demonstrated that the frequency of 22q11.2 deletion varied among sub-groups of CHD patients. Notably, 22q11.2 deletion was more commonly observed in cases with conotruncal defect (CTD) than in cases with non-CTD (P < 0.001). With higher resolution and more probes against selected chromosomal loci, CNVplex® also identified several individuals with small CNVs and alterations in other chromosomes.

Conclusions

CNVplex® is sensitive and specific in its detection of CNVs, and it is an alternative to MLPA for batch screening of pathogenetic CNVs in known genomic loci.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1590-5) contains supplementary material, which is available to authorized users.     

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.     

The fine-scale and complex architecture of human copy-number variation

Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.     

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.     

Copy Number Variation in Thai Population

Copy number variation (CNV) is a major genetic polymorphism contributing to genetic diversity and human evolution. Clinical application of CNVs for diagnostic purposes largely depends on sufficient population CNV data for accurate interpretation. CNVs from general population in currently available databases help classify CNVs of uncertain clinical significance, and benign CNVs. Earlier studies of CNV distribution in several populations worldwide showed that a significant fraction of CNVs are population specific. In this study, we characterized and analyzed CNVs in 3,017 unrelated Thai individuals genotyped with the Illumina Human610, Illumina HumanOmniexpress, or Illumina HapMap550v3 platform. We employed hidden Markov model and circular binary segmentation methods to identify CNVs, extracted 23,458 CNVs consistently identified by both algorithms, and cataloged these high confident CNVs into our publicly available Thai CNV database. Analysis of CNVs in the Thai population identified a median of eight autosomal CNVs per individual. Most CNVs (96.73%) did not overlap with any known chromosomal imbalance syndromes documented in the DECIPHER database. When compared with CNVs in the 11 HapMap3 populations, CNVs found in the Thai population shared several characteristics with CNVs characterized in HapMap3. Common CNVs in Thais had similar frequencies to those in the HapMap3 populations, and all high frequency CNVs (>20%) found in Thai individuals could also be identified in HapMap3. The majorities of CNVs discovered in the Thai population, however, were of low frequency, or uniquely identified in Thais. When performing hierarchical clustering using CNV frequencies, the CNV data were clustered into Africans, Europeans, and Asians, in line with the clustering performed with single nucleotide polymorphism (SNP) data. As CNV data are specific to origin of population, our population-specific reference database will serve as a valuable addition to the existing resources for the investigation of clinical significance of CNVs in Thais and related ethnicities.     

A map of copy number variations in Chinese populations

It has been shown that the human genome contains extensive copy number variations (CNVs). Investigating the medical and evolutionary impacts of CNVs requires the knowledge of locations, sizes and frequency distribution of them within and between populations. However, CNV study of Chinese minorities, which harbor the majority of genetic diversity of Chinese populations, has been underrepresented considering the same efforts in other populations. Here we constructed, to our knowledge, a first CNV map in seven Chinese populations representing the major linguistic groups in China with 1,440 CNV regions identified using Affymetrix SNP 6.0 Array. Considerable differences in distributions of CNV regions between populations and substantial population structures were observed. We showed that ～35% of CNV regions identified in minority ethnic groups are not shared by Han Chinese population, indicating that the contribution of the minorities to genetic architecture of Chinese population could not be ignored. We further identified highly differentiated CNV regions between populations. For example, a common deletion in Dong and Zhuang (44.4% and 50%), which overlaps two keratin-associated protein genes contributing to the structure of hair fibers, was not observed in Han Chinese. Interestingly, the most differentiated CNV deletion between HapMap CEU and YRI containing CCL3L1 gene reported in previous studies was also the highest differentiated regions between Tibetan and other populations. Besides, by jointly analyzing CNVs and SNPs, we found a CNV region containing gene CTDSPL were in almost perfect linkage disequilibrium between flanking SNPs in Tibetan while not in other populations except HapMap CHD. Furthermore, we found the SNP taggability of CNVs in Chinese populations was much lower than that in European populations. Our results suggest the necessity of a full characterization of CNVs in Chinese populations, and the CNV map we constructed serves as a useful resource in further evolutionary and medical studies.     

Genome-wide copy number analysis uncovers a new HSCR gene: NRG3

Hirschsprung disease (HSCR) is a congenital disorder characterized by aganglionosis of the distal intestine. To assess the contribution of copy number variants (CNVs) to HSCR, we analysed the data generated from our previous genome-wide association study on HSCR patients, whereby we identified NRG1 as a new HSCR susceptibility locus. Analysis of 129 Chinese patients and 331 ethnically matched controls showed that HSCR patients have a greater burden of rare CNVs (p = 1.50 × 10(-5)), particularly for those encompassing genes (p = 5.00 × 10(-6)). Our study identified 246 rare-genic CNVs exclusive to patients. Among those, we detected a NRG3 deletion (p = 1.64 × 10(-3)). Subsequent follow-up (96 additional patients and 220 controls) on NRG3 revealed 9 deletions (combined p = 3.36 × 10(-5)) and 2 de novo duplications among patients and two deletions among controls. Importantly, NRG3 is a paralog of NRG1. Stratification of patients by presence/absence of HSCR-associated syndromes showed that while syndromic-HSCR patients carried significantly longer CNVs than the non-syndromic or controls (p = 1.50 × 10(-5)), non-syndromic patients were enriched in CNV number when compared to controls (p = 4.00 × 10(-6)) or the syndromic counterpart. Our results suggest a role for NRG3 in HSCR etiology and provide insights into the relative contribution of structural variants in both syndromic and non-syndromic HSCR. This would be the first genome-wide catalog of copy number variants identified in HSCR.     

The contribution of de novo and rare inherited copy number changes to congenital heart disease in an unselected sample of children with conotruncal defects or hypoplastic left heart disease

Congenital heart disease (CHD) is the most common congenital malformation, with evidence of a strong genetic component. We analyzed data from 223 consecutively ascertained families, each consisting of at least one child affected by a conotruncal defect (CNT) or hypoplastic left heart disease (HLHS) and both parents. The NimbleGen HD2-2.1 comparative genomic hybridization platform was used to identify de novo and rare inherited copy number variants (CNVs). Excluding 10 cases with 22q11.2 DiGeorge deletions, we validated de novo CNVs in 8 % of 148 probands with CNTs, 12.7 % of 71 probands with HLHS and none in 4 probands with both. Only 2 % of control families showed a de novo CNV. We also identified a group of ultra-rare inherited CNVs that occurred de novo in our sample, contained a candidate gene for CHD, recurred in our sample or were present in an affected sibling. We confirmed the contribution to CHD of copy number changes in genes such as GATA4 and NODAL and identified several genes in novel recurrent CNVs that may point to novel CHD candidate loci. We also found CNVs previously associated with highly variable phenotypes and reduced penetrance, such as dup 1q21.1, dup 16p13.11, dup 15q11.2-13, dup 22q11.2, and del 2q23.1. We found that the presence of extra-cardiac anomalies was not related to the frequency of CNVs, and that there was no significant difference in CNV frequency or specificity between the probands with CNT and HLHS. In agreement with other series, we identified likely causal CNVs in 5.6 % of our total sample, half of which were de novo.     

Novel Loci for Non-Syndromic Coarctation of the Aorta in Sporadic and Familial Cases

BackroundCoarctation of the aorta (CoA) accounts for 5-8% of all congenital heart defects. CoA can be detected in up to 20% of patients with Ullrich-Turner syndrome (UTS), in which a part or all of one of the X chromosomes is absent. The etiology of non-syndromic CoA is poorly understood. In the present work, we test the hypothesis that rare copy number variation (CNV) especially on the gonosomes, contribute to the etiology of non-syndromic CoA.MethodsWe performed high-resolution genome-wide CNV analysis using the Affymetrix SNP 6.0 microarray platform for 70 individuals with sporadic CoA, 3 families with inherited CoA (n=13) and 605 controls. Our analysis comprised genome wide association, CNV burden and linkage. CNV was validated by multiplex ligation-dependent probe amplification.ResultsWe identified a significant abundance of large (>100 kb) CNVs on the X chromosome in males with CoA (p=0.005). 11 out of 51 (~ 22%) male cases had these large CNVs. Association analysis in the sporadic cohort revealed 14 novel loci for CoA. The locus on 21q22.3 in the sporadic CoA cohort overlapped with a gene locus identified in all familial cases of CoA (candidate gene TRPM2). We identified one CNV locus within a locus with high multipoint LOD score from a linkage analysis of the familial cases (SEPT9); another locus overlapped with a region implicated in Kabuki syndrome. In the familial cases, we identified a total of 7 CNV loci that were exclusively present in cases but not in unaffected family members.ConclusionOf all candidate loci identified, the TRPM2 locus was the most frequently implicated autosomal locus in sporadic and familial cases. However, the abundance of large CNVs on the X chromosome of affected males suggests that gonosomal aberrations are not only responsible for syndromic CoA but also involved in the development of sporadic and non-syndromic CoA and their male dominance.     

Inherited deletion of 9p22.3-p24.3 and duplication of 18p11.31-p11.32 associated with neurodevelopmental delay: Phenotypic matching of involved genes

We describe a 3.5-year-old Iranian female child and her affected 10-month-old brother with a maternally inherited derivative chromosome 9 [der(9)]. The postnatally detected rearrangement was finely characterized by aCGH analysis, which revealed a 15.056 Mb deletion of 9p22.3-p24.3p22.3 encompassing 14 OMIM morbid genes such as DOCK8, KANK1, DMRT1 and SMARCA2, and a gain of 3.309 Mb on 18p11.31-p11.32 encompassing USP14, THOC1, COLEC12, SMCHD1 and LPIN2. We aligned the genes affected by detected CNVs to clinical and functional phenotypic features using PhenogramViz. In this regard, the patient's phenotype and CNVs data were entered into PhenogramViz. For the 9p deletion CNV, 53 affected genes were identified and 17 of them were matched to 24 HPO terms describing the patient's phenotypes. Also, for CNV of 18p duplication, 22 affected genes were identified and six of them were matched to 13 phenotypes. Moreover, we used DECIPHER for in-depth characterization of involved genes in detected CNVs and also comparison of patient phenotypes with 9p and 18p genomic imbalances. Based on our filtration strategy, in the 9p22.3-p24.3 region, approximately 80 pathogenic/likely pathogenic/uncertain overlapping CNVs were in DECIPHER. The size of these CNVs ranged from 12.01 kb to 18.45 Mb and 52 CNVs were smaller than 1 Mb in size affecting 10 OMIM morbid genes. The 18p11.31-p11.32 region overlapped 19 CNVs in the DECIPHER database with the size ranging from 23.42 kb to 1.82 Mb. These CNVs affect eight haploinsufficient genes.     

De novo mutations in ARID1B associated with both syndromic and non-syndromic short stature

Background

Human height is a complex trait with a strong genetic basis. Recently, a significant association between rare copy number variations (CNVs) and short stature has been identified, and candidate genes in these rare CNVs are being explored. This study aims to evaluate the association between mutations in ARID1B gene and short stature, both the syndromic and non-syndromic form.

Results

Based on a case-control study of whole genome chromosome microarray analysis (CMA), three overlapping CNVs were identified in patients with developmental disorders who exhibited short stature. ARID1B, a causal gene for Coffin Siris syndrome, is the only gene encompassed by all three CNVs. A following retrospective genotype-phenotype analysis based on a literature review confirmed that short stature is a frequent feature in those Coffin-Siris syndrome patients with ARID1B mutations. Mutation screening of ARID1B coding regions was further conducted in a cohort of 48 non-syndromic short stature patients,andfour novel missense variants including two de novo mutations were found.

Conclusion

These results suggest that haploinsufficient mutations of ARID1B are associated with syndromic short stature including Coffin-Siris syndrome and intellectual disability, while rare missense variants in ARID1B are associated with non-syndromic short stature. This study supports the notion that mutations in genes related to syndromic short stature may exert milder effect and contribute to short stature in the general population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1898-1) contains supplementary material, which is available to authorized users.     

First-trimester euploid miscarriages analysed by array-CGH

It is estimated that 10–15 % of all clinically recognised pregnancies results in a miscarriage, most of which occur during the first trimester. Large-scale chromosomal abnormalities have been found in up to 50 % of first-trimester spontaneous abortions and, for several decades, standard cytogenetic analysis has been used for their identification. Recent studies have proven that array comparative genomic hybridisation (array-CGH) is a useful tool for the detection of genome imbalances in miscarriages, showing a higher resolution, a significantly higher detection rate and overcoming problems of culture failures, maternal contamination and poor chromosome morphology. In this study, we investigated the possibility that submicroscopic chromosomal changes, not detectable by conventional cytogenetic analysis, exist in euploid miscarriages and could be causative for the spontaneous abortion. We analysed with array-CGH technology 40 foetal tissue samples derived by first-trimester miscarriages with a normal karyotype. A whole-genome microarray with a 100-Kb resolution was used for the analysis. Forty-five copy number variants (CNVs), ranging in size between 120 Kb and 4.3 Mb, were identified in 31 samples (24 gains and 21 losses). Ten samples (10/31, 32 %) have more than one CNV. Thirty-one CNVs (68 %) were defined as common CNVs and 14 were classified as unique. Six genes and five microRNAs contained within these CNVs will be discussed. This study shows that array-CGH is useful for detecting submicroscopic CNVs and identifying candidate genes which could account for euploid miscarriages.     

Identification of copy number variants on human chromosome 22 in patients with a variety of clinical findings

The aims of this study were to create a copy number variant (CNV) profile of human chromosome 22 and to establish a genotype-phenotype correlation for patients with genomic abnormalities on chromosome 22. Thus, 1,654 consecutive pediatric patients with a diversity of clinical findings were evaluated by high-resolution chromosomal microarray analysis (CMA). We identified 25 individuals with abnormal CNVs on chromosome 22, representing 1.5% of the cases analyzed in this cohort. Meanwhile, we detected 1,298 benign CNVs on this chromosome in these individuals. Twenty-one of the 25 abnormal CNVs and the majority of the benign CNVs occurred through involvement of the 8 unstable genomic regions enriched with low copy repeats (LCR22A-H). The highly dynamic status of LCR22s within the 22q11 region facilitates the formation of diverse genomic abnormalities. This CNV profile provides a general perspective of the spectrum of chromosome 22 genomic imbalances and subsequently improves the CNV-phenotype correlations.     

Application of high resolution SNP arrays in patients with congenital oral clefts in south China

Chromosome microarray analysis (CMA) has proven to be a powerful tool in postnatal patients with intellectual disabilities. However, the diagnostic capability of CMA in patients with congenital oral clefts remain mysterious. Here, we present our clinical experience in implementing whole-genome high-resolution SNP arrays to investigate 33 patients with syndromic and nonsyndromic oral clefts in whom standard karyotyping analyses showed normal karyotypes. We aim to identify the genomic aetiology and candidate genes in patients with congenital oral clefts. CMA revealed copy number variants (CNVs) in every patient, which ranged from 2 to 9 per sample. The size of detected CNVs varied from 100 to 3.2 Mb. In 33 patients, we identified six clinically significant CNVs. The incidence of clinically significant CNVs was 18.2% (6/33). Three of these six CNVs were detected in patients with nonsyndromic clefts, including one who presented with isolated cleft lip with cleft palate (CLP) and two with cleft palate only (CPO). The remaining three CNVs were detected in patients with syndromic clefts. However, no CNV was detected in patients with cleft lip only (CLO). The six clinically significant CNVs were as follows: 8p23.1 microduplication (198 kb); 10q22.2-q22.3 microdeletion (1766 kb); 18q12.3 microduplication (638 kb); 20p12.1 microdeletion (184 kb); 6q26 microdeletion (389 kb); and 22q11.21-q11.23 microdeletion (3163 kb). In addition, two novel candidate genes for oral clefts, KAT6B and MACROD2, were putatively identified. We also found a CNV of unknown clinical significance with a detection rate of 3.0% (1/33). Our results further support the notion that CNVs significantly contributed to the genetic aetiology of oral clefts and emphasize the efficacy of whole-genome high-resolution SNP arrays to detect novel candidate genes in patients with syndromic and nonsyndromic clefts.     

Implications of copy number variation in people with chromosomal abnormalities: potential for greater variation in copy number state may contribute to variability of phenotype

Copy number variation is common in the human genome with many regions, overlapping thousands of genes, now known to be deleted or amplified. Aneuploidies and other forms of chromosomal imbalance have a wide range of adverse phenotypes and are a common cause of birth defects resulting in significant morbidity and mortality. “Normal” copy number variants (CNVs) embedded within the regions of chromosome imbalance may affect the clinical outcomes by altering the local copy number of important genes or regulatory regions: this could alleviate or exacerbate certain phenotypes. In this way CNVs may contribute to the clinical variability seen in many disorders caused by chromosomal abnormalities, such as the congenital heart defects (CHD) seen in ~40% of Down’s syndrome (DS) patients. Investigation of CNVs may therefore help to pinpoint critical genes or regulatory elements, elucidating the molecular mechanisms underlying these conditions, also shedding light on the aetiology of such phenotypes in people without major chromosome imbalances, and ultimately leading to their improved detection and treatment.     

Allelic genome structural variations in maize detected by array comparative genome hybridization

DNA polymorphisms such as insertion/deletions and duplications affecting genome segments larger than 1 kb are known as copy-number variations (CNVs) or structural variations (SVs). They have been recently studied in animals and humans by using array-comparative genome hybridization (aCGH), and have been associated with several human diseases. Their presence and phenotypic effects in plants have not been investigated on a genomic scale, although individual structural variations affecting traits have been described. We used aCGH to investigate the presence of CNVs in maize by comparing the genome of 13 maize inbred lines to B73. Analysis of hybridization signal ratios of 60,472 60-mer oligonucleotide probes between inbreds in relation to their location in the reference genome (B73) allowed us to identify clusters of probes that deviated from the ratio expected for equal copy-numbers. We found CNVs distributed along the maize genome in all chromosome arms. They occur with appreciable frequency in different germplasm subgroups, suggesting ancient origin. Validation of several CNV regions showed both insertion/deletions and copy-number differences. The nature of CNVs detected suggests CNVs might have a considerable impact on plant phenotypes, including disease response and heterosis.