Genetics ResearchNeurosciencePeer-reviewed journal article
In trans variant calling reveals enrichment for compound heterozygous variants in genes involved in neuronal development and growth.
Allison CoxiD, Fillan S. GradyiD, Gabriel VeleziD, Vinit B. MahajaniD, Polly J. FergusoniD, Andrew KitcheniD, Benjamin W. DarbroiD, Alexander G. BassukiD
Abstract
Compound heterozygotes occur when different mutations at the same locus on both maternal and paternal chromosomes produce a recessive trait. Here we present the tool VarCount for the quantification of mutations at the individual level. We used VarCount to characterize compound heterozygous coding variants in patients with epileptic encephalopathy and in the 1000 genomes participants. The Epi4k data contains variants identified by whole exome sequencing in patients with either Lennox-Gastaut Syndrome (LGS) or Infantile Spasms (IS), as well as their parents. We queried the Epi4k dataset (264 trios) and the phased 1000 genomes data (2504 participants) for recessive variants. To assess enrichment, transcript counts were compared between the Epi4k and 1000 genomes participants using minor allele frequency (MAF) cutoffs of 0.5% and 1.0%, and including all ancestries or only probands of European ancestry. In the Epi4k participants, we found enrichment for rare, compound heterozygous mutations in six genes, including three involved in neuronal growth and development - PRTG (p=0.00086, 1% MAF, combined ancestries), TNC (p=0.0221% MAF, combined ancestries), and MACF1 (p=0.0245, 0.5% MAF, EU ancestry). Due the total number of transcripts considered in these analyses, the enrichment detected was not significant after correction for multiple testing and higher powered or prospective studies are necessary to validate the candidacy of these genes. However, PRTG, TNC, and MACF1 are potential novel recessive epilepsy genes and our results highlight that compound heterozygous mutations should be considered in sporadic epilepsy.
- organism: human
- assay: whole-exome sequencing
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 9
- FWCI
- 0.60
- Field percentile
- top 34%
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