scholarly journals Gene Copy Number Analysis for Family Data Using Semiparametric Copula Model

2008 ◽  
Vol 2 ◽  
pp. BBI.S839 ◽  
Author(s):  
Ao Yuan ◽  
Guanjie Chen ◽  
Zhong-Cheng Zhou ◽  
George Bonney ◽  
Charles Rotimi

Gene copy number changes are common characteristics of many genetic disorders. A new technology, array comparative genomic hybridization (a-CGH), is widely used today to screen for gains and losses in cancers and other genetic diseases with high resolution at the genome level or for specific chromosomal region. Statistical methods for analyzing such a-CGH data have been developed. However, most of the existing methods are for unrelated individual data and the results from them provide explanation for horizontal variations in copy number changes. It is potentially meaningful to develop a statistical method that will allow for the analysis of family data to investigate the vertical kinship effects as well. Here we consider a semiparametric model based on clustering method in which the marginal distributions are estimated nonparametrically, and the familial dependence structure is modeled by copula. The model is illustrated and evaluated using simulated data. Our results show that the proposed method is more robust than the commonly used multivariate normal model. Finally, we demonstrated the utility of our method using a real dataset.

2012 ◽  
Vol 19 (3) ◽  
pp. 409-421 ◽  
Author(s):  
Katrin-Janine Heiliger ◽  
Julia Hess ◽  
Donata Vitagliano ◽  
Paolo Salerno ◽  
Herbert Braselmann ◽  
...  

For an identification of novel candidate genes in thyroid tumourigenesis, we have investigated gene copy number changes in aTrk-T1transgenic mouse model of thyroid neoplasia. For this aim, 30 thyroid tumours fromTrk-T1transgenics were investigated by comparative genomic hybridisation. Recurrent gene copy number alterations were identified and genes located in the altered chromosomal regions were analysed by Gene Ontology term enrichment analysis in order to reveal gene functions potentially associated with thyroid tumourigenesis. In thyroid neoplasms fromTrk-T1mice, a recurrent gain on chromosomal bands 1C4–E2.3 (10.0% of cases), and losses on 3H1–H3 (13.3%), 4D2.3–E2 (43.3%) and 14E4–E5 (6.7%) were identified. The genesTwist2,Ptma,Pde6d,Bmpr1b,Pdlim5,Unc5c,Srm,Trp73,Ythdf2,Taf12andSlitrk5are located in these chromosomal bands. Copy number changes of these genes were studied by fluorescencein situhybridisation on 30 human papillary thyroid carcinoma (PTC) samples and altered gene expression was studied by qRT-PCR analyses in 67 human PTC. Copy number gains were detected in 83% of cases forTWIST2and in 100% of cases forPTMAandPDE6D. DNA losses ofSLITRK1andSLITRK5were observed in 21% of cases and ofSLITRK6in 16% of cases. Gene expression was significantly up-regulated forUNC5CandTP73and significantly down-regulated forSLITRK5in tumours compared with normal tissue. In conclusion, a global genomic copy number analysis of thyroid tumours fromTrk-T1transgenic mice revealed a number of novel gene alterations in thyroid tumourigenesis that are also prevalent in human PTCs.


Genomics ◽  
2003 ◽  
Vol 82 (2) ◽  
pp. 122-129 ◽  
Author(s):  
Chun Cheng ◽  
Robert Kimmel ◽  
Paul Neiman ◽  
Lue Ping Zhao

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2430-2430
Author(s):  
Saskia Langemeijer ◽  
Roland Kuiper ◽  
Peter Vandenberghe ◽  
Estelle Verburgh ◽  
Jan Boezeman ◽  
...  

Abstract Conventional cytogenetics and FISH reveal chromosomal defects in approximately 50% of MDS patients. These mostly consist of gross gains and losses of specific chromosomal regions or entire chromosomes like 5q-, monosomy 7 and trisomy 8. Currently, the genes that are critical for MDS development remain largely unknown, which hampers both a proper diagnosis of clonal disease as well as development of targeted therapy. To identify the affected genetic loci and to map the critical regions and genes in MDS, we performed high-resolution (250k) SNP-based CGH. So far, 231 controls and 87 MDS patients from various subclasses were analyzed. In all patients and controls, loss of heterozygosity (LOH) without copy number changes was observed at multiple loci across the entire genome. Although large areas of LOH encompassing the main part of the p- or q-arm of chromosomes were only seen in MDS patients, no genomic regions were identified that were statistically more often affected in patients compared to control DNA. Copy number changes (excluding known regions of normal variation) were seen in 53% of patients with a normal karyotype (n=54). In 231 controls and in non-malignant T cells of a subset of patients, these areas were not affected, indicating that they were disease-specific. The number of affected regions per patient ranged from 0–7. The majority (82%) of karyotypic aberrations were confirmed using SNP-arrays. Only balanced translocations and some subclonal aberrations could not be detected. Importantly, SNP-array analysis revealed additional copy number changes in 70% of patients with an abnormal karyotype. Copy number changes that were observed in only one patient might reflect general genomic instability in the tumor cells and may not represent genes that are implicated in the pathogenesis of MDS. Therefore, we selected areas that were affected in at least two patients. In total, we found 51 different recurrent genomic loci. This indicates that MDS is genetically diverse, which is in agreement with its diverse clinical and morphological presentation. Among the 51 recurrent loci, 15 contained only a single gene (Table). Among these genes, there were several known to be implicated in MDS (e.g. ETV6 and RUNX1), whereas others represent novel genes that are potentially implicated in the pathogenesis of MDS. For several of these, a biological function has been described that may be linked to control of differentiation and proliferation, like the transcription- and proliferation-regulating gene JARID2 and the transcription factor DMTF1. Currently, we are performing a high thoughput mutation- and expression-analysis of these genes in a larger group of patients. Single gene copy number changes in MDS Chr Cytoband Loss/Gain Cases Size (Mb) Gene 1 p35.1 loss 2 0.01 CSMD2 3 p24.2 loss 2 0.07 LRRC3B 6 p22.3 loss 3 0.02 JARID2 8 p23.2-1 gain 2 0.14 MCPH1 9 p13.2 gain 2 0.23 MELK 9 p24.3 gain 2 1.14 SMARCA2 11 q22.3 gain 2 0.05 SLC35F2 12 p12.1 loss 3 0.08 ST8SIA1 12 p13.2 loss 4 0.08 ETV6 12 q23.2 loss 2 0.03 IGF1 16 q23.3 loss 2 0.06 MPHOSPH6 21 q22.12 loss 3 0.07 RUNX1 21 q22.2 gain 2 0.62 DSCAM 22 q12.2 gain 2 0.00 PES1 X q13.1 loss 2 0.17 EDA


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