Allelic expression of deleterious protein-coding variants across human tissues.
Personal exome and genome sequencing provides access to loss-of-function and rare deleterious alleles whose interpretation is expected to provide insight into individual disease burden. However, for each allele, accurate interpretation of its effect will depend on both its penetrance and the trait's expressivity. In this regard, an important factor that can modify the effect of a pathogenic coding allele is its level of expression; a factor which itself characteristically changes across tissues. To better inform the degree to which pathogenic alleles can be modified by expression level across multiple tissues, we have conducted exome, RNA and deep, targeted allele-specific expression (ASE) sequencing in ten tissues obtained from a single individual. By combining such data, we report the impact of rare and common loss-of-function variants on allelic expression exposing stronger allelic bias for rare stop-gain variants and informing the extent to which rare deleterious coding alleles are consistently expressed across tissues. This study demonstrates the potential importance of transcriptome data to the interpretation of pathogenic protein-coding variants.
Department of Pathology, Stanford University School of Medicine, Stanford, California, United States of America; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Kimberly R
KR
Kukurba
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Rui
R
Zhang
Department of Pathology, Stanford University School of Medicine, Stanford, California, United States of America; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Xin
X
Li
Department of Pathology, Stanford University School of Medicine, Stanford, California, United States of America; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Kevin S
KS
Smith
Department of Computer Science, Stanford University School of Medicine, Stanford, California, United States of America.
David A
DA
Knowles
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Meng
M
How Tan
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Robert
R
Piskol
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.
Monkol
M
Lek
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Michael
M
Snyder
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.
Daniel G
DG
Macarthur
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Jin Billy
JB
Li
Department of Pathology, Stanford University School of Medicine, Stanford, California, United States of America; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America; Department of Computer Science, Stanford University School of Medicine, Stanford, California, United States of America.
Stephen B
SB
Montgomery
D000483:Alleles; D059472:Exome; D006801:Humans; D016133:Polymerase Chain Reaction; D011506:Proteins / Q000235:genetics*
D011506:Proteins