Nucleic Acids Research

This Article Abstract Print PDF (83K) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Commercial Re-use Guidelines for Open Access NAR Content Google Scholar Articles by Stitziel, N. O. Articles by Liang, J. Search for Related Content PubMed PubMed Citation Articles by Stitziel, N. O. Articles by Liang, J. Social Bookmarking          What's this?

Nucleic Acids Research, 2004, Vol. 32, Database issue D520-D522
© 2004 Oxford University Press

topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association

Nathan O. Stitziel, T. Andrew Binkowski, Yan Yuan Tseng, Simon Kasif¹ and Jie Liang^*

Department of Bioengineering, University of Illinois at Chicago, M/C 063, 851 S. Morgan Street, Chicago, IL 60607, USA and ¹ Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA

*To whom correspondence should be addressed. Tel: +1 312 355 1789; Fax: +1 312 996 5921; Email: jliang@uic.edu

Received August 15, 2003; Revised and Accepted October 13, 2003

	ABSTRACT

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
The database of topographic mapping of Single Nucleotide Polymorphism (topoSNP) provides an online resource for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. The current release also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data. The database will be updated at regular intervals and can be accessed at: http://gila.bioengr.uic.edu/snp/toposnp.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
Non-synonymous single nucleotide polymorphisms (nsSNPs) have been implicated in numerous disease processes because they may alter protein function (1), alter splice sites (2), destabilize protein core structure and reduce protein solubility (3). However, not all nsSNPs are associated with disease, and it is useful to explore general structural and conservational features of disease-associated nsSNPs versus non disease-associated nsSNPs. For example, solvent accessibility and other features such as experimental B-factors are found to be indicative of functional changes accompanying nsSNPs (4–6). Additionally, sequence conservation has been shown to be useful for predicting when a nsSNP is likely to have deleterious effects (7–9). In another recent study, it was found that disease-associated nsSNPs are more likely to be located in surface pockets or interior voids when compared with control nsSNPs (10). In addition, disease-associated nsSNPs buried in the protein interior are more likely to occur at conserved residue sites, whereas disease-associated nsSNPs located in surface pockets or interior voids do not have such propensity (10). Two data sets of nsSNPs were used in this study, one for disease-associated SNPs, which is derived from the Online Mendelian Inheritance in Man (OMIM) database (11), and one for non disease-associated or control nsSNPs, which is derived from dbSNP (dbSNP is a resource at the National Center for Biotechnology Information that catalogs SNPs as well as other genetic differences) (12). This study suggests that nsSNPs occurring in conserved and interior locations are likely to have dramatic effects. Although results obtained using this approach alone cannot lead to prediction of deleterious effects of nsSNP sites, these studies illustrate that structural characterization of nsSNP sites and their sequence conservation as measured by entropy scores are useful information that can be incorporated into studies addressing the fundamental problem of predicting when nsSNPs are likely to cause disease or significant phenotypic changes. Here we make the structural mapping of both disease- and non-disease-associated nsSNPs available through a web-accessible database topoSNP (http://gila.bioengr.uic.edu/snp/toposnp). In addition, we also provide structural characterization and entropy measurement of these nsSNP sites. TopoSNP also allows for convenient visualization of both disease-associated and non-disease-associated nsSNPs.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
Disease-associated nsSNPs were extracted from the OMIM database (http://www.ncbi.nlm.nih.gov/omim) (11). The control nsSNPs were extracted from dbSNP (12) (release 103) (ftp://ftp.ncbi.nlm.nih.gov/snp/human). While not a perfect source of negative control nsSNPs, it is reasonable to expect that a much smaller fraction of the nsSNPs from dbSNP would be associated with disease. Geometric locations and entropy calculations were performed as described previously (10).

	DATABASE ACCESS

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
The database can be accessed at http://gila.bioengr.uic.edu/snp/toposnp. This site hosts an interactive session based on the CHIME plug-in (freely available from http://www.mdlchime. com, a plug-in that interactively displays 3D molecules), allowing for the visualization of the mutation along with its classification of geometric location and entropy score. After selecting a gene and a specific protein structure to explore, the 3D representation of the protein is displayed, along with a list of known nsSNPs. Selecting a SNP will highlight its position in the protein as well as its corresponding pocket or void if appropriate (Fig. 1). Selecting a SNP will also bring up its specific assignment of geometric class and relative entropy score, which are displayed below the protein visualization.

View larger version (37K): [in this window] [in a new window]   Figure 1. Example of topoSNP visualization for a nsSNP from alcohol dehydrogenase (PDB code 1htb [PDB] ). The R47 mutation is highlighted along with the surface pocket where it is located.

 
There is an online help page as well as a walk-through example for familiarization with the database. The entire database is also downloadable in tar format from the topoSNP website (http://gila.bioengr.uic.edu/snp/toposnp).

	DATABASE STATUS AND FUTURE WORK

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
The database currently contains 27 417 nsSNP mappings (26 859 from disease-associated nsSNPs as derived from the OMIM database and 558 control nsSNPs as derived from the dbSNP database) that correspond to 770 protein structures. These 770 protein structures are derived from 421 gene loci. This is a much larger data set than was previously published (10) as it was expanded to include redundant and homologous protein structures. The database will be updated at regular intervals as new SNP data and structure data become available.

	DISCUSSION

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 
We present here a resource for accessing both geometric location information and conservation information from a study of disease-associated nsSNPs and control nsSNPs. Conservation is assessed here by entropy calculated using a Hidden Markov Model (HMM). There are other approaches for assessing conservation at SNP sites. For example, recent studies demonstrated that position-specific scoring matrices (PSSMs) are quite effective for SNP analysis (7). A comparison of PSSM and HMM methods for remote homology detection showed that these two methods often obtain comparable results (13), although it is unclear exactly to what extent these two approaches differ when assessing conservation at individual sites. In addition, phylogenetic information ideally should be incorporated when assessing sequence conservation, e.g. into a codon or amino acid substitution model, together with a maximum likelihood estimator, or a Bayesian estimator (14–16). However, these methods are not easily scalable for a large set of proteins. Entropy calculation in this case provides an efficient, albeit less precise, assessment of sequence conservation. An area of ongoing work is the rapid construction of multiple alignment, which provides the basis for entropy calculation.

In this study, we do not differentiate missense mutations that cause Mendelian type diseases from nsSNPs that are associated with complex disease phenotypes. Our purpose is to examine nsSNPs that are clearly associated with disease. It is possible that these two sub-populations of nsSNPs may have different characteristics.

	ACKNOWLEDGEMENTS

 
This work is supported by grants from the National Science Foundation (CAREER DBI0133856, DBI0078270, and KDI MCB998008) and the National Institutes of Health (GM68958). N.S. was supported in part by an NIH/NIDDK-funded predoctoral training program (T32 DK007739) in ‘Signal Transduction and Cellular Endocrinology’.

	REFERENCES

TOP ABSTRACT INTRODUCTION METHODS DATABASE ACCESS DATABASE STATUS AND FUTURE... DISCUSSION REFERENCES

 

1. Yoshida,A., Huang,I.Y. and Ikawa,M. (1984) Molecular abnormality of an inactive aldehyde dehydrogenase variant commonly found in Orientals. Proc. Natl Acad. Sci. USA, 81, 258–261.[Abstract/Free Full Text]

2. Jaruzelska,J., Abadie,V., d’Aubenton-Carafa,Y., Brody,E., Munnich,A. and Marie,J. (1995) In vitro splicing deficiency induced by a C to T mutation at position –3 in the intron 10 acceptor site of the phenylalanine hydroxylase gene in a patient with phenylketonuria. J. Biol. Chem., 270, 20370–20375.[Abstract/Free Full Text]

3. Proia,R.L. and Neufeld,E.F. (1982) Synthesis of ß-hexosaminidase in cell-free translation and in intact fibroblasts: an insoluble precursor chain in a rare form of Tay–Sachs disease. Proc. Natl Acad. Sci. USA, 79, 6360–6364.[Abstract/Free Full Text]

4. Sunyaev,S., Ramensky,V. and Bork,P. (2000) Towards a structural basis of human non-synonymous single nucleotide polymorphisms. Trends Genet., 16, 198–200.[CrossRef][Web of Science][Medline]

5. Chasman,D. and Adams,R.M. (2001) Predicting the functional consequences of non-synonymous single nucleotide polymorphisms: Structure-based assessment of amino acid variation. J. Mol. Biol., 307, 683–706.[CrossRef][Web of Science][Medline]

6. Ramensky,V., Bork,P. and Sunyaev,S. (2002) Human non-synonymous SNPs: server and survey. Nucleic Acids Res., 30, 3894–3900.[Abstract/Free Full Text]

7. Ng,P.C. and Henikoff,S. (2001) Predicting deleterious amino acid substitutions. Genome Res., 11, 863–874.[Abstract/Free Full Text]

8. Ng,P.C. and Henikoff,S. (2002) Accounting for human polymorphisms predicted to affect protein function. Genome Res., 12, 436–446.[Abstract/Free Full Text]

9. Ng,P.C. and Henikoff,S. (2003) SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res., 31, 3812–3814.[Abstract/Free Full Text]

10. Stitziel,N.O., Tseng,Y.Y., Pervouchine,D., Goddeau,D., Kasif,S. and Liang,J. (2003) Structural location of disease-associated single-nucleotide polymorphisms. J. Mol. Biol., 327, 1021–1030.[CrossRef][Web of Science][Medline]

11. Wheeler,D.L., Church,D.M., Federhen,S., Lash,A.E., Madden,T.L., Pontius,J.U., Schuler,G.D., Schriml,L.M., Sequeira,E., Tatusova,T.A. et al. (2003) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res., 31, 28–33.[Abstract/Free Full Text]

12. Sherry,S.T., Ward,M.H., Kholodov,M., Baker,J., Phan,L., Smigielski,E.M. and Sirotkin,K. (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., 29, 308–311.[Abstract/Free Full Text]

13. Madera,M. and Gough,J. (2002) A comparison of profile Hidden Markov Model procedures for remote homology detection. Nucleic Acids Res., 30, 4321–4328.[Abstract/Free Full Text]

14. Swofford,D.L., Olsen,G.L., Waddell,P.J. and Hillis,D.L. (1996) Phylogenetic inference. In Hillis,D.M., Moritz,C. and Mable,B. (eds), Molecular Systematics. Sinauer Associates, Sunderland, MA, pp. 407–514.

15. Yang,Z. (2001) Adaptive molecular evolution. In Balding,D., Bishop,M. and Cannings,C. (eds), Handbook of Statistical Genetics. Wiley, London, pp. 327–350.

16. Huelsenbeck,J.P. and Ronquist,F. (2001) MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics, 17, 754–755.[Abstract/Free Full Text]

CiteULike    Connotea    Del.icio.us    What's this?

This article has been cited by other articles:

				H. Xi, J. Park, G. Ding, Y.-H. Lee, and Y. Li SysPIMP: the web-based systematical platform for identifying human disease-related mutated sequences from mass spectrometry Nucleic Acids Res., January 1, 2009; 37(suppl_1): D913 - D920. [Abstract] [Full Text] [PDF]

				H. Kono, T. Yuasa, S. Nishiue, and K. Yura coliSNP database server mapping nsSNPs on protein structures Nucleic Acids Res., January 11, 2008; 36(suppl_1): D409 - D413. [Abstract] [Full Text] [PDF]

				A. Uzun, C. M. Leslin, A. Abyzov, and V. Ilyin Structure SNP (StSNP): a web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways Nucleic Acids Res., July 13, 2007; 35(suppl_2): W384 - W392. [Abstract] [Full Text] [PDF]

				A. G. Jegga, S. Gowrisankar, J. Chen, and B. J. Aronow PolyDoms: a whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease Nucleic Acids Res., January 12, 2007; 35(suppl_1): D700 - D706. [Abstract] [Full Text] [PDF]

				J. Dundas, Z. Ouyang, J. Tseng, A. Binkowski, Y. Turpaz, and J. Liang CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W116 - W118. [Abstract] [Full Text] [PDF]

				A. Han, H. J. Kang, Y. Cho, S. Lee, Y. J. Kim, and S. Gong SNP@Domain: a web resource of single nucleotide polymorphisms (SNPs) within protein domain structures and sequences. Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W642 - W644. [Abstract] [Full Text] [PDF]

				E. Mathe, M. Olivier, S. Kato, C. Ishioka, P. Hainaut, and S. V. Tavtigian Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods Nucleic Acids Res., March 6, 2006; 34(5): 1317 - 1325. [Abstract] [Full Text] [PDF]

				M. Y. Galperin The Molecular Biology Database Collection: 2006 update. Nucleic Acids Res., January 1, 2006; 34(Database issue): D3 - D5. [Abstract] [Full Text] [PDF]

This Article Abstract Print PDF (83K) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Commercial Re-use Guidelines for Open Access NAR Content Google Scholar Articles by Stitziel, N. O. Articles by Liang, J. Search for Related Content PubMed PubMed Citation Articles by Stitziel, N. O. Articles by Liang, J. Social Bookmarking          What's this?

Online ISSN 1362-4962 - Print ISSN 0305-1048

Copyright © 2009 Oxford University Press

Oxford Journals Oxford University Press

• Site Map
• Privacy Policy
• Frequently Asked Questions

Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan American National Biography Booksellers' Information Service Children's Fiction and Poetry Children's Reference Corporate & Special Sales Dictionaries Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks Humanities International Education Unit Law Medicine Music Online Products Oxford English Dictionary Reference Rights and Permissions Science School Books Social Sciences Very Short Introductions World's Classics