Detection of chromosomal breakpoints in patients with developmental delay and speech disorders

PLoS One. 2014 Mar 6;9(6):e90852. doi: 10.1371/journal.pone.0090852. eCollection 2014.

Abstract

Delineating candidate genes at the chromosomal breakpoint regions in the apparently balanced chromosome rearrangements (ABCR) has been shown to be more effective with the emergence of next-generation sequencing (NGS) technologies. We employed a large-insert (7-11 kb) paired-end tag sequencing technology (DNA-PET) to systematically analyze genome of four patients harbouring cytogenetically defined ABCR with neurodevelopmental symptoms, including developmental delay (DD) and speech disorders. We characterized structural variants (SVs) specific to each individual, including those matching the chromosomal breakpoints. Refinement of these regions by Sanger sequencing resulted in the identification of five disrupted genes in three individuals: guanine nucleotide binding protein, q polypeptide (GNAQ), RNA-binding protein, fox-1 homolog (RBFOX3), unc-5 homolog D (C.elegans) (UNC5D), transmembrane protein 47 (TMEM47), and X-linked inhibitor of apoptosis (XIAP). Among them, XIAP is the causative gene for the immunodeficiency phenotype seen in the patient. The remaining genes displayed specific expression in the fetal brain and have known biologically relevant functions in brain development, suggesting putative candidate genes for neurodevelopmental phenotypes. This study demonstrates the application of NGS technologies in mapping individual gene disruptions in ABCR as a resource for deciphering candidate genes in human neurodevelopmental disorders (NDDs).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Base Sequence
  • Chromosome Breakpoints*
  • Chromosome Inversion
  • DNA Copy Number Variations
  • Developmental Disabilities / genetics*
  • Female
  • Genetic Association Studies
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Language Development Disorders / genetics*
  • Male
  • Molecular Sequence Data
  • Pedigree
  • Sequence Analysis, DNA
  • Translocation, Genetic

Grants and funding

This study is supported by grants from Biomedical Medical Research Council (BMRC) of the Agency for Science, Technology and Research (A*STAR), Singapore. Support is also acknowledged from the National Health and Medical Research Australia (NHMRC). KHU is funded by Singapore International Graduate Award (SINGA) fellowship. Additional support was also provided by the Genome Institute of Singapore internal research funds from the BMRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.