Interpretation, Stratification and Evidence for Sequence Variants Affecting mRNA Splicing in Complete Human Genome Sequences

Genomics, Proteomics and Bioinformatics

Volumn 11, Issue 2, 2013, Pages 77-85

  Shirley, Ben C ^a   Mucaki, Eliseos J ^b   Whitehead, Tyson ^c   Costea, Paul I ^d   Akan, Pelin ^d   Rogan, Peter K ^a,b,e  

^a UNIVERSITY OF WESTERN ONTARIO   (Canada)

^b WESTERN UNIVERSITY   (Canada)

^c SHARCNET   (Canada)

^d ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^e Cytognomix Inc   (Canada)

Author keywords

Genome interpretation; Information theory; MRNA splicing; Mutation; Next generation sequencing

Indexed keywords

MESSENGER RNA;

ARTICLE; CANCER CELL CULTURE; COMPUTER PROGRAM; CONTROLLED STUDY; GENE EXPRESSION; GENE MUTATION; GENE SEQUENCE; GENETIC VARIABILITY; GENOME; GENOME ANALYSIS; GENOMICS; HUMAN; HUMAN CELL; MICROARRAY ANALYSIS; RNA SPLICING; SEQUENCE ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM;

GENE EXPRESSION; GENOME, HUMAN; HUMANS; MUTATION; POINT MUTATION; POLYMORPHISM, SINGLE NUCLEOTIDE; RNA SPLICING; RNA, MESSENGER; RNA, NEOPLASM; SOFTWARE;

EID: 84876809756     PISSN: 16720229     EISSN: 22103244     Source Type: Journal    
DOI: 10.1016/j.gpb.2013.01.008     Document Type: Article

References (49)

1. Gullapalli R.R., Desai K.V., Santana-Santos L., Kant J.A., Becich M.J. Next generation sequencing in clinical medicine: challenges and lessons for pathology and biomedical informatics. J Pathol Inform 2012, 3:40.
2. Kavanagh D., Anderson H.E. Interpretation of genetic variants of uncertain significance in atypical hemolytic uremic syndrome. Kidney Int 2012, 81:11-13.
3. Spurdle A.B., Healey S., Devereau A., Hogervorst F.B., Monteiro A.N., Nathanson K.L., et al. ENIGMA-evidence-based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes. Hum Mutat 2012, 33:2-7.
4. Adzhubei I.A., Schmidt S., Peshkin L., Ramensky V.E., Gerasimova A., Bork P., et al. A method and server for predicting damaging missense mutations. Nat Methods 2010, 7:248-249.
5. Nalla V.K., Rogan P.K. Automated splicing mutation analysis by information theory. Hum Mutat 2005, 25:334-342.
6. Kumar A., White T.A., MacKenzie A.P., Clegg N., Lee C., Dumpit R.F., et al. Exome sequencing identifies a spectrum of mutation frequencies in advanced and lethal prostate cancers. Proc Natl Acad Sci U S A 2011, 108:17087-17092.
7. O'Roak B.J., Vives L., Fu W., Egertson J.D., Stanaway I.B., Phelps I.G., et al. Multiplex targeted sequencing identifies recurrently mutated genes in autism spectrum disorders. Science 2012, 338:1619-1622.
8. Churbanov A., Vorechovský I., Hicks C. A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements. BMC Bioinformatics 2010, 11:22.
9. Churbanov A., Rogozin I.B., Deogun J.S., Ali H. Method of predicting splice sites based on signal interactions. Biol Direct 2006, 1:10.
10. Yeo G., Burge C.B. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol 2004, 11:377-394.
11. Reese M.G., Eeckman F.H., Kulp D., Haussler D. Improved splice site detection in Genie. J Comput Biol 1997, 4:311-323.
12. Pertea M., Lin X., Salzberg S.L. GeneSplicer: a new computational method for splice site prediction. Nucleic Acids Res 2001, 29:1185-1190.
13. Cooper T.A., Mattox W. The regulation of splice-site selection, and its role in human disease. Am J Hum Genet 1997, 61:259-266.
14. López-Bigas N., Audit B., Ouzounis C., Parra G., Guigó R. Are splicing mutations the most frequent cause of hereditary disease?. FEBS Lett 2005, 579:1900-1903.
15. Schneider T.D. Information content of individual genetic sequences. J Theor Biol 1997, 189:427-441.
16. Shannon C.E. A mathematical theory of communication: part I. Bell Syst Tech J 1948, 27:379-423.
17. Shannon C.E., Weaver W. A mathematical model of communication 1949, University of Illinois Press, Urbana, IL.
18. Shultzaberger R.K., Schneider T.D. Using sequence logos and information analysis of Lrp DNA binding sites to investigate discrepancies between natural selection and SELEX. Nucleic Acids Res 1999, 27:882-887.
19. Mucaki E.J., Ainsworth P., Rogan P.K. Comprehensive prediction of mRNA splicing effects of BRCA1 and BRCA2 variants. Hum Mutat 2011, 32:735-742.
20. Rogan P.K., Svojanovsky S., Leeder J.S. Information theory-based analysis of CYP2C19, CYP2D6 and CYP3A5 splicing mutations. Pharmacogenetics 2003, 13:207-218.
21. Robberson B.L., Cote G.J., Berget S.M. Exon definition may facilitate splice site selection in RNAs with multiple exons. Mol Cell Biol 1990, 10:84-94.
22. Sterner D.A., Carlo T., Berget S.M. Architectural limits on split genes. Proc Natl Acad Sci U S A 1996, 93:15081-15085.
23. Bhattacharya C., Wang X., Becker D. The DEAD/DEAH box helicase, DDX11, is essential for the survival of advanced melanomas. Mol Cancer 2012, 11:82.
24. Del Mare S., Kurek K.C., Stein G.S., Lian J.B., Aqeilan R.I. Role of the WWOX tumor suppressor gene in bone homeostasis and the pathogenesis of osteosarcoma. Am J Cancer Res 2011, 1:585-594.
25. Moravcikova E., Krepela E., Prochazka J., Rousalova I., Cermak J., Benkova K. Down-regulated expression of apoptosis-associated genes APIP and UACA in non-small cell lung carcinoma. Int J Oncol 2012, 40:2111-2121.
26. Lee C.H., Alpert B.O., Sankaranarayanan P., Alter O. GSVD comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival. PLoS One 2012, 7:e30098.
27. Charles N., Holland E.C. The perivascular niche microenvironment in brain tumor progression. Cell Cycle 2010, 9:3012-3021.
28. Kingsley-Kallesen M., Luster T.A., Rizzino A. Transcriptional regulation of the transforming growth factor-beta2 gene in glioblastoma cells. In Vitro Cell Dev Biol Anim 2001, 37:684-690.
29. Stransky N., Egloff A.M., Tward A.D., Kostic A.D., Cibulskis K., Sivachenko A., et al. The mutational landscape of head and neck squamous cell carcinoma. Science 2011, 333:1157-1160.
30. Sun Z., Yang P., Aubry M.C., Kosari F., Endo C., Molina J., et al. Can gene expression profiling predict survival for patients with squamous cell carcinoma of the lung?. Mol Cancer 2004, 3:35.
31. Stephens P.J., Tarpey P.S., Davies H., Van Loo P., Greenman C., Wedge D.C., et al. The landscape of cancer genes and mutational processes in breast cancer. Nature 2012, 486:400-404.
32. Cappelli E., Vecchio D., Frosina G. Delayed formation of FancD2 foci in glioma stem cells treated with ionizing radiation. J Cancer Res Clin Oncol 2012, 138:897-899.
33. Stewart G.S., Wang B., Bignell C.R., Taylor A.M., Elledge S.J. MDC1 is a mediator of the mammalian DNA damage checkpoint. Nature 2003, 421:961-966.
34. Akan P., Alexeyenko A., Costea P.I., Hedberg L., Solnestam B.W., Lundin S., et al. Comprehensive analysis of the genome transcriptome and proteome landscapes of three tumor cell lines. Genome Med 2012, 4:86.
35. Vastrik I., D'Eustachio P., Schmidt E., Gopinath G., Croft D., de Bono B., et al. Reactome: a knowledge base of biologic pathways and processes. Genome Biol 2007, 8:R39.
36. Desmet F.O., Hamroun D., Lalande M., Collod-Beroud G., Claustres M., Beroud C. Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res 2009, 37:e67.
37. Hanahan D., Weinberg R.A. Hallmarks of cancer: the next generation. Cell 2011, 144:646-674.
38. Stratton M.R., Campbell P.J., Futreal P.A. The cancer genome. Nature 2009, 458:719-724.
39. Cancer Genome Atlas Research Network Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008, 455:1061-1068.
40. Curwen V., Eyras E., Andrews T.D., Clarke L., Mongin E., Searle S.M., et al. The Ensembl automatic gene annotation system. Genome Res 2004, 14:942-950.
41. Flicek P., Ahmed I., Amode M.R., Barrell D., Beal K., Brent S., et al. Ensembl 2013. Nucleic Acids Res 2013, 41:D48-D55.
42. Biesecker L.G. Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice: lessons from the ClinSeq project. Genet Med 2012, 14:393-398.
43. Richter B.G., Sexton D.P. Managing and analyzing next-generation sequence data. PLoS Comput Biol 2009, 5:e1000369.
44. Lescai F., Bonfiglio S., Bacchelli C., Chanudet E., Waters A., Sisodiya S.M., et al. Characterisation and validation of insertions and deletions in 173 patient exomes. PLoS One 2012, 7:e51292.
45. Schneider TD, Rogan PK. Computational analysis of nucleic acid information defines binding sites. US Patent 5,867,402; 1999.
46. Danecek P., Auton A., Abecasis G., Albers C.A., Banks E., DePristo M.A., et al. The variant call format and VCFtools. Bioinformatics 2011, 27:2156-2158.
47. Rogan P.K., Faux B.M., Schneider T.D. Information analysis of human splice site mutations. Hum Mutat 1998, 12:153-171.
48. Trapnell C., Pachter L., Salzberg S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009, 25:1105-1111.
49. Robinson J.T., Thorvaldsdóttir H., Winckler W., Guttman M., Lander E.S., Getz G., et al. Integrative genomics viewer. Nat Biotechnol 2011, 29:24-26.