Department of Informatics, Technical University of Munich, Boltzmannstraße, Garching, 85748, Germany.
Department of Computer Science, Stanford University, Stanford, CA, USA.
Genome Biol. 2021 Mar 31;22(1):94. doi: 10.1186/s13059-021-02273-7.
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.
我们开发了免费开源的多组织剪接模型（Multi-tissue Splicing，MTSplice），用于预测遗传变异对 56 个人体组织中剪接盒外显子的影响。MTSplice 将 MMSplice（用于建模组成性调控序列）与新的神经网络（用于建模组织特异性调控序列）相结合。在预测 GTEx 数据集大多数组织中与遗传变异相关的组织特异性变化方面，MTSplice 优于 MMSplice，在脑组织方面的改进最大。此外，MTSplice 预测自闭症相关的新生突变富集了影响大脑特异性剪接的变异。我们预计 MTSplice 将有助于解释与组织特异性疾病相关的变异。
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