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Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets
Published on: July 7, 2010
Genome-Wide Array Analysis Reveals Novel Genomic Regions and Candidate Gene for Intellectual Disability
Xiangnan Chen1, Huanzheng Li2, Chong Chen2
1Department of Laboratory Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Introduction:
Intellectual disability (ID) is often sporadic, and its complex etiology makes clinical diagnosis extremely difficult.
Objective:
The aims of this study were to detect copy number variations (CNVs) in patients with ID and to analyze the correlation between pathogenic CNVs and clinical phenotype.
Methods:
After cases of ID caused by metabolic dysfunction or environmental factors were excluded, 64 patients with moderate to severe ID were enrolled. Karyotype and single nucleotide polymorphism (SNP) array analyses were performed for all patients. The relationship between CNVs and phenotype was identified with genotype-phenotype comparisons and by searching CNV databases.
Results:
Karyotype analysis showed four patients with chromosomal aneuploidy and seven with chromosomal structural abnormality. After excluding the four cases with chromosomal aneuploidy, the remaining 60 cases were analyzed using SNP array. The results revealed 87 CNVs in 45 cases, including 16 pathogenic CNVs in 12 individuals, with a diagnostic yield of 20.0% (12/60). We found large deletions at 16q22.2q23.1 and 3q24q25.32 in two patients, respectively, in whom specific syndromes had not been defined. Our array analysis showed one case carried a 210 kb deletion at 1p21.2p21.3, which included only one coding gene LPPR4, which might be a candidate gene for ID phenotype.
Conclusions:
Use of the genome-wide array method can improve the detection rate of CNVs, reveal chromosomal abnormalities that have not been well-characterized by cytology, and provide a new way to locate genes for patients with the ID phenotype. Interpretation of CNVs remains a major challenge. Sharing of CNVs and phenotype information from different laboratories in public databases is important.
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