RNA-Seq in Patients with Primordial Dwarfism

Dataset ID Technology Samples
EGAD00001000640 Illumina HiSeq 2000 24

Dataset Description

Transcriptome studies in patients with rare genetic diseases can potentially aid in the
interpretation of likely causal genetic variation through identification of altered transcript
abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating
transcript structure and abundance
The primary aim of this pilot project is to investigate to what degree integrating exome-Seq
and RNA-Seq data on the same individual can accelerate the identification of causal alleles
for rare genetic diseases. There are two main strands to this: (i) identifying which variants
discovered in exome-seq appear to be having a functional impact on transcripts, and (ii)
identifying transcript outliers, especially among known causal genes, that may not necessarily
have a causal variant identified from exome sequencing. The latter may identify the presence
of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites
deep within introns, or loss of long range regulatory elements), which can be confirmed with
further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the
Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.
nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).
This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with
primordial dwarfism syndromes, for 10 of these samples we have previously generate exome
data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining
samples are positive ... (Show More)

Data Use Conditions


See further information on Data Use Conditions

Label Code Version Modifier
general research use DUO:0000042 2021-02-23
institution specific restriction DUO:0000028 2021-02-23
publication required DUO:0000019 2021-02-23
user specific restriction DUO:0000026 2021-02-23
project specific restriction DUO:0000027 2021-02-23