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.     

tRNA gene copy number variation in humans

The human tRNAome consists of more than 500 interspersed tRNA genes comprising 51 anticodon families of largely unequal copy number. We examined tRNA gene copy number variation (tgCNV) in six individuals; two kindreds of two parents and a child, using high coverage whole genome sequence data. Such differences may be important because translation of some mRNAs is sensitive to the relative amounts of tRNAs and because tRNA competition determines translational efficiency vs. fidelity and production of native vs. misfolded proteins. We identified several tRNA gene clusters with CNV, which in some cases were part of larger iterations. In addition there was an isolated tRNALysCUU gene that was absent as a homozygous deletion in one of the parents. When assessed by semiquantitative PCR in 98 DNA samples representing a wide variety of ethnicities, this allele was found deleted in hetero- or homozygosity in all groups at ~ 50% frequency. This is the first report of copy number variation of human tRNA genes. We conclude that tgCNV exists at significant levels among individual humans and discuss the results in terms of genetic diversity and prior genome wide association studies (GWAS) that suggest the importance of the ratio of tRNALys isoacceptors in Type-2 diabetes.     

Functional profiling and gene expression analysis of chromosomal copy number alterations

Contrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.     

Bayesian DNA copy number analysis

Background  

Some diseases, like tumors, can be related to chromosomal aberrations, leading to changes of DNA copy number. The copy number of an aberrant genome can be represented as a piecewise constant function, since it can exhibit regions of deletions or gains. Instead, in a healthy cell the copy number is two because we inherit one copy of each chromosome from each our parents.     

Rapid PCR-based determination of transgene copy number in rice

We present a simple, rapid, and low-cost method to determine transgene copy number in rice. More than 100 first- and second-generation transgenic rice plants were tested. The plasmid (pRCopy) used for rice transformation contains the specific gene of interest and a partially deleted cytochrome c gene (cyc), a single-copy gene in rice. A 132-bp segment of the cloned ricecyc was shortened to 108 bp by deleting a 24-bp internal fragment. After PCR amplification of the genomic DNA from transgenic rice harboring pRCopy, the 2 expected bands were found. The 121-bp band corresponds to the endogenouscyc; the 97-bp band comes from the integrated pRCopy. Clear distinctions can be made between single and multiple copies of the transgene by comparing band densities.     

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis

Background  

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia.     

Integrated analysis of gene expression and copy number data on gene shaving using independent component analysis

DNA microarray gene expression and microarray-based comparative genomic hybridization (aCGH) have been widely used for biomedical discovery. Because of the large number of genes and the complex nature of biological networks, various analysis methods have been proposed. One such method is "gene shaving," a procedure which identifies subsets of the genes with coherent expression patterns and large variation across samples. Since combining genomic information from multiple sources can improve classification and prediction of diseases, in this paper we proposed a new method, "ICA gene shaving" (ICA, independent component analysis), for jointly analyzing gene expression and copy number data. First we used ICA to analyze joint measurements, gene expression and copy number, of a biological system and project the data onto statistically independent biological processes. Next, we used these results to identify patterns of variation in the data and then applied an iterative shaving method. We investigated the properties of our proposed method by analyzing both simulated and real data. We demonstrated that the robustness of our method to noise using simulated data. Using breast cancer data, we showed that our method is superior to the Generalized Singular Value Decomposition (GSVD) gene shaving method for identifying genes associated with breast cancer.     

Integrated analysis of DNA copy number and gene expression microarray data using gene sets

Background  

Genes that play an important role in tumorigenesis are expected to show association between DNA copy number and RNA expression. Optimal power to find such associations can only be achieved if analysing copy number and gene expression jointly. Furthermore, some copy number changes extend over larger chromosomal regions affecting the expression levels of multiple resident genes.     

Rapid determination of transgene copy number in stably-transfected mammalian cells by competitive PCR

We describe here an application of the competitive PCR technique to the analysis of copy number of recombinant rat parathyroid hormone-related protein (rPTHrP) gene in stably-transfected murine erythroleukemia (MEL) cell lines. A single-copy reference gene (endogenous mouse PTHrP gene or mPTHrP) is used as an internal control. This control gene, present in the genome of MEL cells, shares the same primer binding sites as the rPTHrP cDNA but contains an internal PvuII site, which allows resolution of the amplified products after restriction enzyme digestion by polyacrylamide gel electrophoresis (PAGE). The transgene copy number is determined by the ratio of band intensity of the rPTHrP product to that of the mPTHrP product. Using this method, we have determined the copy number of the rPTHrP transgene from isolated genomic DNA, and compared the results with those obtained from Southern blot analysis. In addition, we have demonstrated that the procedure can be applied very simply to whole MEL cells without DNA extractions and that as few as 10⁴ cells are required for the analysis.     

Analysis of gene copy number changes in tumor phylogenetics

Backgound

Evolution of cancer cells is characterized by large scale and rapid changes in the chromosomal  landscape. The fluorescence in situ hybridization (FISH) technique provides a way to measure the copy numbers of preselected genes in a group of cells and has been found to be a reliable source of data to model the evolution of tumor cells. Chowdhury et al. (Bioinformatics 29(13):189–98, 23; PLoS Comput Biol 10(7):1003740, 24) recently develop a computational model for tumor progression driven by gains and losses in cell count patterns obtained by FISH probes. Their model aims to find the rectilinear Steiner minimum tree (RSMT) (Chowdhury et al. in Bioinformatics 29(13):189–98, 23) and the duplication Steiner minimum tree (DSMT) (Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) that describe the progression of FISH cell count patterns over its branches in a parsimonious manner. Both the RSMT and DSMT problems are NP-hard and heuristics are required to solve the problems efficiently.

Methods

In this paper we propose two approaches to solve the RSMT problem, one inspired by iterative methods to address the “small phylogeny” problem (Sankoff et al. in J Mol Evol 7(2):133–49, 27; Blanchette et al. in Genome Inform 8:25–34, 28), and the other based on maximum parsimony phylogeny inference. We further show how to extend these heuristics to obtain solutions to the DSMT problem, that models large scale duplication events.

Results

Experimental results from both simulated and real tumor data show that our methods outperform previous heuristics (Chowdhury et al. in Bioinformatics 29(13):189–98, 23; Chowdhury et al. in PLoS Comput Biol 10(7):1003740, 24) in obtaining solutions to both RSMT and DSMT problems.

Conclusion

The methods introduced here are able to provide more parsimony phylogenies compared to earlier ones which are consider better choices.

     

Detection of DNA copy number abnormality by microarray expression analysis

Gene copy-number abnormalities (CNAs) are characteristic of solid tumors and are found in association with developmental abnormalities and/or mental retardation. The ultimate impact of CNAs is exerted by the altered expression of encoded genes. We have utilized high-density oligonucleotide arrays from Affymetrix to identify DNA CNAs via their impact on mRNA expression levels. In these studies, we have used three different trisomic cell lines (trisomy 9, trisomy 18, trisomy 21) as models of CNAs and have compared mRNA expression in those trisomic cells with that observed in diploid cell lines of matched tissue origin. Our data clearly show that genes from CNA chromosome regions are substantially over-represented (P<0.000001 by chi-square analysis) in the differentially expressed subset from comparisons of all three trisomic cell lines with normal matching cells. In addition, we have been able to detect the origin of the duplication by a statistical scan for over-expressed genes. These data show that microarray detection of differential mRNA expression can be used to identify significant DNA CNAs.     

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.     

Generation of a chromosome-22-specific c-DNA library as confirmed by FISH analysis

We have recently developed a strategy for the rapid enrichment of c-DNA fragments from selected human chromosomes. Heteronuclear RNA (hn-RNA) is isolated from a somatic cell hybrid that retains a single human chromosome in a rodent background. Following c-DNA synthesis, human sequences are selectively amplified by the Alu polymerase chain reaction (Alu-PCR). Here we have applied this protocol for the selective isolation of novel c-DNAs encoded by chromosome 22. Fluorescence in situ hybridization has been used to confirm the chromosome-22-specific origin of the c-DNA fragments. Controls show DNAse-free RNase-treated hn-RNA results in no c-DNAs or Alu-PCR products. As demonstrated by competitive in situ suppression hybridization (CISS), the majority of the Alu-PCR products from hybrid GM 10027 are located on chromosome 22. Without competition, hybridization signals have also been identified on other human chromosomes. These unspecific hybridization signals result from Alu sequences and can successfully be reduced by competition with cot 1 DNA. This is the first report of the use of CISS for the localization of chromosome-specific c-DNAs.     

Integrated analysis of gene copy number, copy neutral LOH, and microRNA profiles in adult acute lymphoblastic leukemia

We adopted an integrated analysis of gene copy number alterations (CNAs), copy number neutral loss of heterozygosity (CNN LOH), and microRNA (miRNA) profiling in 21 adult acute lymphoblastic leukemia (ALL) patients. This study revealed the most frequent CNAs to be at chromosomes 9p, 7, and 17 and recurrent CNN LOH at 5p, 9p, and Xq. As for the most differentially expressed miRNAs, they included 8 upregulated and 14 downregulated miRNAs, of which miR-148a at 7p15.2, miR-22 at 17p13.3, miR-223 at Xq12, as well as miR-101-2 at 9p24.1 exhibited recurrent CNAs or CNN LOH. miR-101-2 was recurrently downregulated, and although the related CNN LOH was detected only in BCR-ABL1 negative cases (2/14), deletions of miR-101-2 were observed solely in BCR-ABL1 positive cases (4/7). Finally, BCR-ABL1 positive cases, in contrast to negative ones, were characterized by slightly, but still significantly, higher expression levels of miR-29b.     

Plasmid copy number and stability determination in Clostridium perfringens transformants

The copy number of the streptococcal plasmid pAM beta 1 (26.5 kb), and its deletion derivatives, pVA1 (11 kb) and pVA677 (7.6 kb) contained in Clostridium perfringens 3624A transformants was determined by incorporation of [methyl-3H]thymidine (4 muCi/ml) into chromosomal and plasmid DNA and sizing of the C. perfringens genome using transverse alternating field electrophoresis. Plasmids pAM beta 1, pVA1, and pVA677 were found to be present at 1.0, 97, and 216 copies/cell, respectively. 10.2, 54, and 96% of the initial pAM beta 1-, pVA1- and pVA677-containing transformants, respectively, remained resistant to erythromycin over 220 generations of growth. The results indicate a size-dependent relationship between plasmid stability and plasmid copy number in C. perfringens.     

Genome-wide copy number analysis of single cells

Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ～3 d from flow cytometry to sequence-ready DNA libraries.     

Human gene copy number variation and infectious disease

Variability in the susceptibility to infectious disease and its clinical manifestation can be determined by variation in the environment and by genetic variation in the pathogen and the host. Despite several successes based on candidate gene studies, defining the host variation affecting infectious disease has not been as successful as for other multifactorial diseases. Both single nucleotide variation and copy number variation (CNV) of the host contribute to the host’s susceptibility to infectious disease. In this review we focus on CNV, particularly on complex multiallelic CNV that is often not well characterised either directly by hybridisation methods or indirectly by analysis of genotypes and flanking single nucleotide variants. We summarise the well-known examples, such as α-globin deletion and susceptibility to severe malaria, as well as more recent controversies, such as the extensive CNV of the chemokine gene CCL3L1 and HIV infection. We discuss the potential biological mechanisms that could underly any genetic association and reflect on the extensive complexity and functional variation generated by a combination of CNV and sequence variation, as illustrated by the Fc gamma receptor genes FCGR3A, FCGR3B and FCGR2C. We also highlight some understudied areas that might prove fruitful areas for further research.     

Microarray analysis of copy number variation in single cells

We present a protocol for reliably detecting DNA copy number aberrations in a single human cell. Multiple displacement-amplified DNAs of a cell are hybridized to a 3,000-bacterial artificial chromosome (BAC) array and to an Affymetrix 250,000 (250K)-SNP array. Subsequent copy number calling is based on the integration of BAC probe-specific copy number probabilities that are estimated by comparing probe intensities with a single-cell whole-genome amplification (WGA) reference model for diploid chromosomes, as well as SNP copy number and loss-of-heterozygosity states estimated by hidden Markov models (HMM). All methods for detecting DNA copy number aberrations in single human cells have difficulty in confidently discriminating WGA artifacts from true genetic variants. Furthermore, some methods lack thorough validation for segmental DNA imbalance detection. Our protocol minimizes false-positive variant calling and enables uniparental isodisomy detection in single cells. Additionally, it provides quality assessment, allowing the exclusion of uninterpretable single-cell WGA samples. The protocol takes 5-7 d.