4.6 Article

Affected Kindred Analysis of Human X Chromosome Exomes to Identify Novel X-Linked Intellectual Disability Genes

Journal

PLOS ONE
Volume 10, Issue 2, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0116454

Keywords

-

Funding

  1. National Institutes of Health [R01 HD056780, R01 NS073854]
  2. South Carolina Department of Disabilities and Special Needs (SCDDSN)

Ask authors/readers for more resources

X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in similar to 10% of X chromosome genes are implicated in causing XLID disorders in similar to 50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available