Home Join Contact
 

Research Article
Open Access
Study of Microsatellites Role in BRCA2 Gene Causing Pancreatic Cancer and Breast Cance
Appa Rao Allam1, Sridhar R Gumpeny2, MN Vamsi Thalatam* 1 ,3, S Sita Ram Babu1 N Ravi Shankar1 , P Anuradha1
1Department of Computer Science and Systems Engineering, Andhra University,  Visakhapatnam-530003,
  India
2Endocrine and Diabetes Center, Krishnanagar, Visakhapatnam-530002, India
3GVP College for Degree & PG Courses, Visakhapatnam, 530045,India
*Corresponding author: Dr. MN Vamsi Thalatam,
Email: senireddy.vamsidhar@gmail.com
Received April 20, 2008; Accepted May 15, 2008; Published May 25, 2008
Citation: Appa RA, Sridhar RG, Vamsi TMN, Ram Babu SS, Ravi SN, et al. (2008) Study of Microsatellites Role in BRCA2 Gene Causing Pancreatic Cancer and Breast Cancer. J Proteomics Bioinform S1: S038-S040. doi:10.4172/jpb.s1000006
 
Copyright: © 2008 Allam AR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 
Abstract
BRCA2 gene plays an important role in the development of pancreatic cancer. Diabetics may have a slightly increased risk of pancreatic cancer. Previous literature reveals that the Mutations in these genes are also causing the breast cancer. A detailed bioinformatics study of all the known mutations in the BRCA2 gene revealed interesting information. The information of all the experimentally proven mutations were collected and analyzed using bioinformatics tools and software programs. We tried to find out whether the presence of microsatellites or simple sequence repeats in the BRCA2 gene has any significance in the generation of these mutations. Our analysis revealed that there are 161 mutations available (HGMD) in BRCA2 gene under missense/nonsense Category. We report that none of these 161 mutations fall inside the microsatellite tracts and thus indicating no role of microsatellites in BRCA2 gene.

Keywords
Microsatellites; bioinformatics; pancreatic cancer; breast cancer

Introduction
”Microsatellites” are currently one of the most commonly used genetic markers. They are defined as loci (or regions within DNA sequences) where short sequences (1-6bp length per repeat unit) of DNA are repeated in tandem arrays. This means that the sequences are repeated one right after the other. Their high length polymorphism and abundance in all genomes make them the genetic marker of choice for a diverse range of applications spanning linkage analysis and genetic mapping through to forensic and ecological and evolutionary studies (Goldstein and Schlotterer, 1999). The lengths of sequences used most often are di-, tri-, or tetra-nucleotides. Microsatellites have been found in all the known genomes so far and are widely distributed both in coding and non-coding regions (Sreenu, V.B. et al 2006). They are known to be highly polymorphic as a result of high rate of mutations in the form of increase/decrease of their repeat copy numbers (Jarne, P. and Lagoda,P.J.L. 1996). Increase/decrease of repeat copy numbers in microsatellites in coding regions often lead to shifts in reading frames thereby causing changes in protein products (Li,Y.C. et al. 2004 ,Sreenu,V.B. et al. 2006) and in non-coding regions, known to effect the gene regulation (Martin,P. et al. 2005). Mutations occurring at microsatellite loci within or near certain genes have been implicated to be responsible for some human neurodegenerative diseases (Tautz, D. and Schlotterer, C, 1994). Furthermore, microsatellite instability has also been implicated in the induction of cancer (Thibodeau, S.N. et al., 1993). Owing to their high mutability, it is thought that the microsatellites are one of the sources of genetic diversity (Kashi, Y. and King, D.G., 2006). In the recent times, efforts have also been made to study the possible functional roles of microsatellites in giving rise to certain amount of plasticity and also in the evolution of genomes (Sreenu, V.B. et al. 2006).

Methods
All the experimental proved mutations of the BRCA2 gene, that are falling inside the coding regions and eventually leading to phenotypic differences were collected from the Human Gene Mutation Database (HGMD) (Stenson et al. 2003).Table 1 gives the list of some mutations considered for analysis. The mutations do not include silent mutations, which do not induce any change in the amino acid sequence. The BRCA2 gene and protein sequences were downloaded from National Center for Biotechnology Information (NCBI) (http\\www.ncbi.nih.nlm.gov) repository. The BRCA2 gene has 2 exons with an intron in between. The coding regions in the gene sequence were extracted using a perl program and submitted to the microsatellite extraction program called IMEx (Imperfect Microsatellite Extractor) (Mudunuri, S.B. and Nagarajaram, H.A. 2007). We used the intermediate version of IMEx-web server (http://www.cdfd.org.in/imex) with the default values. The mutations collected are then mapped on to these microsatellite regions.

Accession Number Codon change Amino acid change Codon number Phenotype
CM980233 gTTT-CTT Phe-Leu 32 Breast cancer
CM970178 TAT-TGT Tyr-Cys 42 Breast cancer
CM014326 tGAA-TAA Glu-Term 45 Breast cancer
CM011914 aGAA-TAA Glu-Term 49 Breast cancer
CM980234 AAA-AGA Lys-Arg 53 Breast cancer
CM041729 ACT-ATT Thr-Ile 64 Breast cancer
CM980235 aTTC-CTC Phe-Leu 81 Breast cancer
CM040380 TTA-TGA Leu-Term 105 Breast cancer
CM021250 ATG-ACG Met-Thr 192 Pancreatic cancer
CM960192 TGG-TAG Trp-Term 194 Breast cancer
CM980236 CCA-CGA Pro-Arg 201 Breast cancer
CM980237 GTC-GCC Val-Ala 211 Breast cancer
CM980238 tCCT-TCT Pro-Ser 222 Breast cancer
CM042309 tACT-GCT Thr-Ala 225 Breast cancer
CM032200 TCA-TAA Ser-Term 273 Breast cancer
CM984124 aCAA-TAA Gln-Term 321 Breast cancer
CM994736 AGCa-AGA Ser-Arg 326 Breast cancer
CM994284 cAAG-GAG Lys-Glu 327 Breast cancer
CM002750 aAAT-CAT Asn-His 372 Breast cancer
CM021509 cAAG-TAG Lys-Term 385 Breast cancer
CM970179 TTG-TAG Leu-Term 414 Breast cancer
CM004188 GAA-GGA Glu-Gly 462 Breast cancer
CM021955 tAAG-TAG Lys-Term 467 Breast cancer
CM010167 ATA-ACA Ile-Thr 505 Breast cancer
CM980239 TGTc-TGG Cys-Trp 554 Breast cancer, male
CM043454 TTA-TGA Leu-Term 557 Breast cancer
CM043977 TGGc-TGA Trp-Term 563 Breast cancer
CM033756 cACT-CCT Thr-Pro 582 Breast cancer
CM043978 TCA-TAA Ser-Term 611 Breast cancer
CM004714 ATAa-ATG Ile-Met 729 Breast cancer
CM042681 cATG-GTG Met-Val 784 Breast cancer
CM994285 tGAT-AAT Asp-Asn 935 Breast cancer
CM970180 tAAA-TAA Lys-Term 944 Breast cancer
CM040688 gAAG-TAG Lys-Term 1026 Breast cancer
CM043979 TTA-TGA Leu-Term 1053 Breast  cancer
CM020102 TCA-TGA Ser-Term 1099 Breast cancer
Table 1: List of Mutations and its corresponding disease Pheno-type collected from HGMDMaterials

Results
The Human Genome Mutation Database (HGMD) is used to identify mutations of BRCA2 gene. Interestingly 161 mutations are found. It is observed that none of these mutations fall in the homeodomain region of the microsatellites. This indicates that microsatellites play no role in the mutagenesis of BRAC2 gene.

Conclusion
Microsatellites are known for their higher rate of mutations and are known to be associated with various diseases. So, we analyzed the BRCA2 mutations and their possible association with the microsatellites. The BRCA2 mutations from HGMD database are not mapped on to the microsatellite tracts and the results seem to indicate that microsatellites play an important role in mutagenesis. Extending this work on a large scale by analyzing large number of genes might give a better evidence of the role of microsatellites in generating mutations.

Acknowledgment
This work was supported by IIT up gradation grants of AUCE (A).

Reference

  1. Goldstein DB, Schlotterer C (1999) Microsatellites: Evolution and Application Oxford University Press Oxford New York.

  2. Jarne P, Lagoda PJL (1996) Microsatellites, from molecules to populations and back. Trends Ecol Evol 11: 424-429. »  CrossRef »  Google Scholar

  3. Kashi Y, King DG (2006) Simple sequence repeats as advantageous mutators in evolution. Trends Genet 22: 253-259. »  CrossRef  »  PubMed  »  Google Scholar

  4. Li YC, etal. (2004) Microsatellites within genes: structure, function, and evolution. Mol Biol Evol 21: 991- 1007. »  CrossRef  »  PubMed  »  Google Scholar

  5. Martin P, etal. (2005) Microsatellite instability regulates transcription factor binding and gene expression. PNAS 102: 3800-3804. »  CrossRef  »  PubMed  »  Google Scholar

  6. Mudunuri SB, Nagarajaram HA (2007) IMEx: Imperfect Microsatellite Extractor. Bioinformatics 23: 1181- 1187. »  CrossRef  »  PubMed  »  Google Scholar

  7. Sreenu VB, etal. (2006) Microsatellite polymorphism across the M. tuberculosis and M. bovis genomes: implications on genome evolution and plasticity. BMC Genomics 7: 78-88. »  CrossRef  »  PubMed  »  Google Scholar

  8. Sreenu VB, etal. (2007) Simple sequence repeats in mycobacterial genomes. J Biosci 32: 3-15. »  CrossRef  »  PubMed  »  Google Scholar

  9. Stenson PD, Ball EV, Mort M, Phillips AD, Shiel JA, etal. (2003) The Human Gene Mutation Database (HGMD®): 2003 Update. Hum Mutat 21: 577-581. »  CrossRef  »  PubMed  »  Google Scholar

  10. Tautz D, Schlotterer C (1994) Simple sequences. Curr Opin Genet Dev 4: 832-837. »  PubMed  »  Google Scholar

  11. Thibodeau SN, etal. (1993) Microsatellite instability in cancer of the proximal colon. Science 260: 816-819. »  CrossRef  »  PubMed  »  Google Scholar
This Article
DOWNLOAD
» XML (18 KB)
» PDF (65 KB)
» Citation
CONTRIBUTE

SHARE

EXPLORE
Related Article at