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MTSplice predicts effects of genetic variants on tissue-specific splicing.

Jun ChengMuhammed Hasan ÇelikAnshul KundajeJulien Gagneur
Published in: Genome biology (2021)
We develop the free and open-source model Multi-tissue Splicing (MTSplice) to predict the effects of genetic variants on splicing of cassette exons in 56 human tissues. MTSplice combines MMSplice, which models constitutive regulatory sequences, with a new neural network that models tissue-specific regulatory sequences. MTSplice outperforms MMSplice on predicting tissue-specific variations associated with genetic variants in most tissues of the GTEx dataset, with largest improvements on brain tissues. Furthermore, MTSplice predicts that autism-associated de novo mutations are enriched for variants affecting splicing specifically in the brain. We foresee that MTSplice will aid interpreting variants associated with tissue-specific disorders.
Keyphrases
  • neural network
  • gene expression
  • resting state
  • white matter
  • endothelial cells
  • copy number
  • transcription factor
  • autism spectrum disorder
  • intellectual disability
  • functional connectivity
  • multiple sclerosis