Integrative annotation of variants from 1092 humans: application to cancer 
genomics

Khurana, E.; Fu, Y.; Colonna, V.; Mu, X. J.; Kang, H. M.; Lappalainen, T.; Sboner, A.; Lochovsky, L.; Chen, J.; Harmanci, A.; Das, J.; Abyzov, A.; Balasubramanian, S.; Beal, K.; Chakravarty, D.; Challis, D.; Chen, Y.; Clarke, D.; Clarke, L.; Cunningham, F.; Evani, U. S.; Flicek, P.; Fragoza, R.; Garrison, E.; Gibbs, R.; Gumus, Z. H.; Herrero, J.; Kitabayashi, N.; Kong, Y.; Lage, K.; Liluashvili, V.; Lipkin, S. M.; MacArthur, D. G.; Marth, G.; Muzny, D.; Pers, T. H.; Ritchie, G. R.; Rosenfeld, J. A.; Sisu, C.; Wei, X.; Wilson, M.; Xue, Y.; Yu, F.; 1000 Genomes Project, Consortium; Lehrach, H.; Sudbrak, R.; Albrecht, M. W.; Amstislavskiy, V.; Borodina, T. A.; Lienhard, M.; Mertes, F.; Sultan, M.; Timmermann, B.; Yaspo, M. L.; Dermitzakis, E. T.; Yu, H.; Rubin, M. A.; Tyler-Smith, C.; Gerstein, M.

doi:10.1126/science.1235587

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Integrative annotation of variants from 1092 humans: application to cancer genomics

MPS-Authors

/persons/resource/persons50409

Lehrach, H.
1000 Genomes Project Consortium;
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50580

Sudbrak, R.
1000 Genomes Project Consortium;
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50066

Amstislavskiy, V.
Human Chromosome 21 (Marie-Laure Yaspo), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons73812

Lienhard, M.
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50430

Mertes, F.
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50584

Sultan, M.
Human Chromosome 21 (Marie-Laure Yaspo), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50598

Timmermann, B.
Sequencing (Head: Bernd Timmermann), Scientific Service (Head: Christoph Krukenkamp), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50655

Yaspo, M. L.
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

Khurana.pdf
(Publisher version), 3MB

Supplementary Material (public)

There is no public supplementary material available

Citation

Khurana, E., Fu, Y., Colonna, V., Mu, X. J., Kang, H. M., Lappalainen, T., et al. (2013). Integrative annotation of variants from 1092 humans: application to cancer genomics. Science, 342(6154), 1235587-1235587. doi:10.1126/science.1235587.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0019-02F5-1

Abstract

Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations ("ultrasensitive") and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, "motif-breakers"). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.