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

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

doi:10.1371/journal.pone.0116454

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.

Highlights

X-linked Intellectual Disability (XLID) is a group of genetically highly heterogeneous disorders with mutations in genes on the X chromosome [1–3]
The rapid developments in high-throughput sequencing platforms that are coupled with effective targeted capture have made it possible to determine most coding variants that present in an individual human genome [5–7]
Our study shows that this Affected Kindred/Cross-Cohort strategy achieves a substantial reduction in variants compared to the public database-dependent discrete filters alone

Summary

Introduction

X-linked Intellectual Disability (XLID) is a group of genetically highly heterogeneous disorders with mutations in genes on the X chromosome [1–3]. With the characterization of relatively common XLID genes, it is expected that the majority of the remaining mutations in unknown XLID genes are very rare and even private to individual patients and families [4] Identification of these XLID genes is essential to provide accurate molecular diagnosis for individual XLID families and to better understand the molecular basis of intellectual function and disability in humans [2,3]. Exome-based sequencing has become a powerful approach to elucidate the genetic basis of Mendelian disorders of unknown etiology and provide gene diagnoses of specific disorders with high genetic and phenotypic heterogeneity [8–11]. This strategy has had some success in identifying a handful of additional causes for autosomal intellectual disability [12,13]. One may expect in any large scale exome sequencing study for approximately 20,000–24,000 variants to be found in an individual exome, with ~10%, coming from the X chromosome [6,8]

Methods

Results

Conclusion