1. Transcriptomic signatures across human tissues identify functional rare genetic variation
- Author
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Christopher D. Brown, Austin T. Hilliard, Adolfo Correa, Nicole M. Ferraro, Maja Bucan, Alvaro N. Barbeira, Kristin G. Ardlie, Stephane E. Castel, Shweta Ramdas, Michael C. Bassik, Margot Brandt, Joe R. Davis, Stephen B. Montgomery, Nathan S. Abell, Jonah Einson, Tuuli Lappalainen, Alexis Battle, François Aguet, Alexandra J. Scott, Gaelen T. Hess, Ira M. Hall, Hae Kyung Im, Pejman Mohammadi, Themistocles L. Assimes, Aradhana, Gina M. Peloso, Pradeep Natarajan, Emily Greenwald, Benjamin J. Strober, Rachel L. Kember, Emily K. Tsang, Bence Kotis, Seyedeh M. Zekavat, YoSon Park, Marcello Ziosi, Xin Li, and Craig Smail
- Subjects
Multifactorial Inheritance ,Multidisciplinary ,Genome, Human ,Alternative splicing ,Genetic Variation ,Computational biology ,Biology ,Phenotype ,Genome ,Article ,Transcriptome ,Organ Specificity ,Genetic variation ,Humans ,Human genome ,Function (biology) - Abstract
© 2020 American Association for the Advancement of Science. All rights reserved. INTRODUCTION: The human genome contains tens of thousands of rare (minor allele frequency 800 genomes matched with transcriptomes across 49 tissues, we were able to study RVs that underlie extreme changes in the transcriptome. To capture the diversity of these extreme changes, we developed and integrated approaches to identify expression, allele-specific expression, and alternative splicing outliers, and characterized the RV landscape underlying each outlier signal. We demonstrate that personal genome interpretation and RV discovery is enhanced by using these signals. This approach provides a new means to integrate a richer set of functional RVs into models of genetic burden, improve disease gene identification, and enable the delivery of precision genomics.
- Published
- 2019