Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics.

ABSTRACT:

Background

Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency of RAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors.

Methods

We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants in RAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes.

Results

Potentially deleterious variants were identif

SUBMITTER: Loviglio MN 

PROVIDER: S-EPMC5088687 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature