Accurately annotate compound effects of genetic variants using a context-sensitive framework.
In genomics, effectively identifying the biological effects of genetic variants is crucial. Current methods handle each variant independently, assuming that each variant acts in a context-free manner. However, variants within the same gene may interfere with each other, producing combinational (compound) rather than individual effects. In this work, we introduce COPE, a gene-centric variant annotation tool that integrates the entire sequential context in evaluating the functional effects of intra-genic variants. Applying COPE to the 1000 Genomes dataset, we identified numerous cases of multiple-variant compound effects that frequently led to false-positive and false-negative loss-of-function calls by conventional variant-centric tools. Specifically, 64 disease-causing mutations were identified to be rescued in a specific genomic context, thus potentially contributing to the buffering effects for highly penetrant deleterious mutations. COPE is freely available for academic use at http://cope.cbi.pku.edu.cn.
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Si-Jin
SJ
Cheng
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Fang-Yuan
FY
Shi
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Huan
H
Liu
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Yang
Y
Ding
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Shuai
S
Jiang
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Nan
N
Liang
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Center for Bioinformatics, Peking University, Beijing 100871, People's Republic of China.
Ge
G
Gao
D004843:Epistasis, Genetic; D014644:Genetic Variation; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D058977:Molecular Sequence Annotation / Q000379:methods*; D009154:Mutation; D012984:Software