Affected kindred analysis of human X chromosome exomes to identify novel X-linked intellectual disability genes

Tejasvi S. Niranjan, Cindy Skinner, Melanie May, Tychele Turner, Rebecca Rose, Roger Stevenson, Charles E. Schwartz, Tao Wang

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ∼10% of X chromosome genes are implicated in causing XLID disorders in ∼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.

Original languageEnglish
Article numbere0116454
JournalPloS one
Volume10
Issue number2
DOIs
StatePublished - Feb 13 2015

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