Unknown

Dataset Information

0

Forging links between human mental retardation-associated CNVs and mouse gene knockout models.


ABSTRACT: Rare copy number variants (CNVs) are frequently associated with common neurological disorders such as mental retardation (MR; learning disability), autism, and schizophrenia. CNV screening in clinical practice is limited because pathological CNVs cannot be distinguished routinely from benign CNVs, and because genes underlying patients' phenotypes remain largely unknown. Here, we present a novel, statistically robust approach that forges links between 148 MR-associated CNVs and phenotypes from approximately 5,000 mouse gene knockout experiments. These CNVs were found to be significantly enriched in two classes of genes, those whose mouse orthologues, when disrupted, result in either abnormal axon or dopaminergic neuron morphologies. Additional enrichments highlighted correspondences between relevant mouse phenotypes and secondary presentations such as brain abnormality, cleft palate, and seizures. The strength of these phenotype enrichments (>100% increases) greatly exceeded molecular annotations (<30% increases) and allowed the identification of 78 genes that may contribute to MR and associated phenotypes. This study is the first to demonstrate how the power of mouse knockout data can be systematically exploited to better understand genetically heterogeneous neurological disorders.

SUBMITTER: Webber C 

PROVIDER: S-EPMC2694283 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Forging links between human mental retardation-associated CNVs and mouse gene knockout models.

Webber Caleb C   Hehir-Kwa Jayne Y JY   Nguyen Duc-Quang DQ   de Vries Bert B A BB   Veltman Joris A JA   Ponting Chris P CP  

PLoS genetics 20090626 6


Rare copy number variants (CNVs) are frequently associated with common neurological disorders such as mental retardation (MR; learning disability), autism, and schizophrenia. CNV screening in clinical practice is limited because pathological CNVs cannot be distinguished routinely from benign CNVs, and because genes underlying patients' phenotypes remain largely unknown. Here, we present a novel, statistically robust approach that forges links between 148 MR-associated CNVs and phenotypes from ap  ...[more]

Similar Datasets

| S-EPMC2858682 | biostudies-literature
2009-12-16 | GSE19457 | GEO
2022-01-11 | GSE193233 | GEO
2022-01-11 | GSE193235 | GEO
2010-05-18 | E-GEOD-19457 | biostudies-arrayexpress
| S-EPMC2583939 | biostudies-literature
| S-EPMC7070531 | biostudies-literature
| S-EPMC3130887 | biostudies-literature
| PRJNA795462 | ENA
| PRJNA795463 | ENA