scholarly journals SNP array mapping of chromosome 20p deletions: Genotypes, phenotypes, and copy number variation

2009 ◽  
Vol 30 (3) ◽  
pp. 371-378 ◽  
Author(s):  
Binita M. Kamath ◽  
Brian D. Thiel ◽  
Xiaowu Gai ◽  
Laura K. Conlin ◽  
Pedro S. Munoz ◽  
...  
2020 ◽  
Author(s):  
Gita A Pathak ◽  
Renato Polimanti ◽  
Talisa K Silzer ◽  
Frank R Wendt ◽  
Ranajit Chakraborty ◽  
...  

Abstract Proctitis is an inflammation of the rectum and may be induced by radiation treatment for cancer. We investigated proctitis as a radiotoxic endpoint in prostate cancer patients who received radiotherapy (n=222). We analyzed the copy number variation and SNP-derived transcriptomic profiles of whole-blood and prostate tissue associated with proctitis. The SNP and copy number data were genotyped on Affymetrix® Genome-wide Human SNP Array 6.0. Following QC measures, the genotypes were used to obtain gene expression by leveraging GTEx, a reference dataset for gene expression association based on genotype and RNA-seq information for prostate (n= 132) and whole-blood tissue (n=369). In prostate tissue, 62 genes were significantly associated with proctitis, and 98 genes in whole-blood tissue. Six genes - CABLES2, ATP6AP1L, IFIT5, ATRIP, TELO2 , and PARD6G were common to both tissues. The copy number analysis identified seven regions associated with proctitis, one of which ( ALG1L2) was also associated with proctitis based on transcriptomic profiles in the whole-blood tissue. The genes identified via transcriptomics and copy number variation association were further investigated for enriched pathways and gene ontology. Some of the enriched processes were DNA repair, mitochondrial apoptosis regulation, cell-to-cell signaling interaction processes for renal and urological system, and organismal injury.


2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Jeanette E Eckel-Passow ◽  
Elizabeth J Atkinson ◽  
Sooraj Maharjan ◽  
Sharon LR Kardia ◽  
Mariza de Andrade

2011 ◽  
Vol 32 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Gaëlle Marenne ◽  
Benjamín Rodríguez-Santiago ◽  
Montserrat García Closas ◽  
Luis Pérez-Jurado ◽  
Nathaniel Rothman ◽  
...  

2015 ◽  
Author(s):  
James Boocock ◽  
David Chagné ◽  
Tony R Merriman ◽  
Mik Black

BackgroundCopy number variation (CNV) is a common feature of eukaryotic genomes, and a growing body of evidence suggests that genes affected by CNV are enriched in processes that are associated with environmental responses. Here we use next generation sequence (NGS) data to detect copy-number variable regions (CNVRs) within the Malus x domestica genome, as well as to examine their distribution and impact.MethodsCNVRs were detected using NGS data derived from 30 accessions of M. x domestica analysed using the read-depth method, as implemented in the CNVrd2 software. To improve the reliability of our results, we developed a quality control and analysis procedure that involved checking for organelle DNA, not repeat masking, and the determination of CNVR identity using a permutation testing procedure.ResultsOverall, we identified 876 CNVRs, which spanned 3.5% of the apple genome. To verify that detected CNVRs were not artefacts, we analysed the B- allele-frequencies (BAF) within a SNP array dataset derived from a screening of 185 individual apple accessions and found the CNVRs were enriched for SNPs having aberrant BAFs (P < 1e-13, Fisher?s Exact test). Putative CNVRs overlapped 845 gene models and were enriched for resistance (R) genes (P < 1e-22, Fisher?s exact test). Of note is a cluster of resistance genes on chromosome 2 near a region containing multiple major gene loci conferring resistance to apple scab.ConclusionWe present the first analysis and catalogue of CNVRs in the M. x domestica genome. The enrichment of the CNVRs with R genes and their overlap with gene loci of agricultural significance draw attention to a form of unexplored genetic variation in apple. This research will underpin further investigation of the role that CNV plays within the apple genome.  


2021 ◽  
Author(s):  
Margaux Louise Anna Hujoel ◽  
Maxwell A Sherman ◽  
Alison R Barton ◽  
Ronen E Mukamel ◽  
Vijay G. Sankaran ◽  
...  

The human genome contains hundreds of thousands of regions exhibiting copy number variation (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs (spanning tens of kilobases) have been ascertainable from the SNP-array data generated by large biobanks. We developed a new computational approach that leverages abundant haplotype-sharing in biobank cohorts to more sensitively detect CNVs co-inherited within extended SNP haplotypes. Applied to UK Biobank, this approach achieved 6-fold increased CNV detection sensitivity compared to previous analyses, accounting for approximately half of all rare gene inactivation events produced by genomic structural variation. This extensive CNV call set enabled the most comprehensive analysis to date of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (P < 5 x 10-8) - involving 97 loci - that rigorous statistical fine-mapping analyses indicated were likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling new insights into dosage-sensitivity of these genes and implicating several novel gene-trait relationships. CNVs at several loci created extended allelic series including deletions or duplications of distal enhancers that associated with much stronger phenotypic effects than SNPs within these regulatory elements. These results demonstrate the ability of haplotype-informed analysis to empower structural variant detection and provide insights into the genetic basis of human complex traits.


2019 ◽  
Vol 47 (7) ◽  
pp. e39-e39 ◽  
Author(s):  
Zhongyang Zhang ◽  
Haoxiang Cheng ◽  
Xiumei Hong ◽  
Antonio F Di Narzo ◽  
Oscar Franzen ◽  
...  

2009 ◽  
Vol 10 (10) ◽  
pp. R119 ◽  
Author(s):  
Gökhan Yavaş ◽  
Mehmet Koyutürk ◽  
Meral Özsoyoğlu ◽  
Meetha P Gould ◽  
Thomas LaFramboise

2009 ◽  
Vol 2 (1) ◽  
pp. 54-65 ◽  
Author(s):  
Jian Wang ◽  
Tsz-Kwong Man ◽  
Kwong Kwok Wong ◽  
Pulivarthi H. Rao ◽  
Hon-Chiu Eastwood Leung ◽  
...  

Gene copy number change is an essential characteristic of many types of cancer. However, it is important to distinguish copy number variation (CNV) in the human genome of normal individuals from bona fide abnormal copy number changes of genes specific to cancers. Based on Affymetrix 50K single nucleotide polymorphism (SNP) array data, we identified genome-wide copy number variations among 104 normal subjects from three ethnic groups that were used in the HapMap project. Our analysis revealed 155 CNV regions, of which 37% were gains and 63% were losses. About 21% (30) of the CNV regions are concordant with earlier reports. These 155 CNV regions are located on more than 100 cytobands across all 23 chromosomes. The CNVs range from 68bp to 18 Mb in length, with a median length of 86 Kb. Eight CNV regions were selected for validation by quantitative PCR. Analysis of genomic sequences within and adjacent to CNVs suggests that repetitive sequences such as long interspersed nuclear elements (LINEs) and long terminal repeats (LTRs) may play a role in the origin of CNVs by facilitating non-allelic homologous recombination. Thirty-two percent of the CNVs identified in this study are associated with segmental duplications. CNVs were not preferentially enriched in gene-encoding regions. Among the 364 genes that are completely encompassed by these 155 CNVs, genes related to olfactory sensory, chemical stimulus, and other physiological responses are significantly enriched. A statistical analysis of CNVs by ethnic group revealed distinct patterns regarding the CNV location and gain-to-loss ratio. The CNVs reported here will help build a more comprehensive map of genomic variations in the human genome and facilitate the differentiation between copy number variation and somatic changes in cancers. The potential roles of certain repeat elements in CNV formation, as corroborated by other studies, shed light on the origin of CNVs and will improve our understanding of the mechanisms of genomic rearrangements in the human genome.


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