V-MitoSNP: visualization of human mitochondrial SNPs
© Chuang et al; licensee BioMed Central Ltd. 2006
Received: 29 May 2006
Accepted: 15 August 2006
Published: 15 August 2006
Mitochondrial single nucleotide polymorphisms (mtSNPs) constitute important data when trying to shed some light on human diseases and cancers. Unfortunately, providing relevant mtSNP genotyping information in mtDNA databases in a neatly organized and transparent visual manner still remains a challenge. Amongst the many methods reported for SNP genotyping, determining the restriction fragment length polymorphisms (RFLPs) is still one of the most convenient and cost-saving methods. In this study, we prepared the visualization of the mtDNA genome in a way, which integrates the RFLP genotyping information with mitochondria related cancers and diseases in a user-friendly, intuitive and interactive manner. The inherent problem associated with mtDNA sequences in BLAST of the NCBI database was also solved.
V-MitoSNP provides complete mtSNP information for four different kinds of inputs: (1) color-coded visual input by selecting genes of interest on the genome graph, (2) keyword search by locus, disease and mtSNP rs# ID, (3) visualized input of nucleotide range by clicking the selected region of the mtDNA sequence, and (4) sequences mtBLAST. The V-MitoSNP output provides 500 bp (base pairs) flanking sequences for each SNP coupled with the RFLP enzyme and the corresponding natural or mismatched primer sets. The output format enables users to see the SNP genotype pattern of the RFLP by virtual electrophoresis of each mtSNP. The rate of successful design of enzymes and primers for RFLPs in all mtSNPs was 99.1%. The RFLP information was validated by actual agarose electrophoresis and showed successful results for all mtSNPs tested. The mtBLAST function in V-MitoSNP provides the gene information within the input sequence rather than providing the complete mitochondrial chromosome as in the NCBI BLAST database. All mtSNPs with rs number entries in NCBI are integrated in the corresponding SNP in V-MitoSNP.
V-MitoSNP is a web-based software platform that provides a user-friendly and interactive interface for mtSNP information, especially with regard to RFLP genotyping. Visual input and output coupled with integrated mtSNP information from MITOMAP and NCBI make V-MitoSNP an ideal and complete visualization interface for human mtSNPs association studies.
The human mitochondrial genome is defined by a single type of circular double-stranded DNA whose complete nucleotide sequence has been established  and corrected . It contains 16569 bps in 37 genes. Twenty-eight of these genes are encoded by the heavy strand, and nine by the light strand. Of the 37 genes, a total of 24 specify a mature RNA product: 22 mitochondrial tRNA molecules and two mitochondrial rRNA molecules (a 23S rRNA and a 16S rRNA). The remaining 13 genes encode polypeptides, which are synthesized on mitochondrial ribosomes.
Mitochondrial DNA (mtDNA) is known for high mutation rates caused by a lack of histones, inefficient DNA repair capability, and continuous exposure to oxidative stress. It has been suggested that the mitochondrial variations are linked to the origin of humans, and play a substantial role in forensics, degenerative diseases, cancers and the aging process . Mitochondrial DNA mutations are analyzed by many laboratories in order to investigate their potential role as active markers for tumorigenesis in various cancer types [4, 5], e.g. cervical , gastric , ovarian , breast , colorectal , liver and lung cancers . Many association studies for human mitochondrial genes are reported, e.g. for MT-ATP6, MT-ATP8, and MT-ND4 . The study of SNPs in mtDNA has also been applied in forensic identification . The substitution rate in mitochondria is typically five to 10 times higher than that of nuclear DNA , which has made mitochondria an attractive source for DNA polymorphism data in genetic population studies. These facts make the investigation of mtDNA polymorphisms a vital part of cancer and disease studies.
To date, several mtDNA databases have been established, i.e. mtDB , MITOMAP , GiiB-JST mtSNP  and MitoRes . The mtDB database established in 2000 is a comprehensive database of the complete human mitochondrial genome. Included are the actual sequences, many of which have not been previously deposited in a publicly available database, such a GeneBank. MITOMAP  is another comprehensive database of human mtDNA variations and contains information pertaining to human evolution, diseases and cancers. GiiB-JST mtSNP  provides information related to the functional differences among mtSNPs. It can be used for identification of mtSNPs associated with age-related conditions, such as longevity, Parkinson's disease, and Alzheimer's disease. The mtSNPs identified in this database are also associated with conditions related to energy metabolisms, such as obesity, type 2 diabetes, and atherosclerosis. MitoRes  contains data on nuclear-encoded mitochondria-related products for any metazoan species, which is useful when studying mitochondrial biogenesis, and metabolic and pathological dysfunctions. However, these web-based databases don't provide enough information for complete SNP genotyping, and typically lack a convenient visualization platform. The environment of these web-based databases is not very interactive. An improvement of the visualization and interactivity could be very important for association studies related to diseases and cancers in mtSNPs. Furthermore, none of the above mentioned databases provide a correlation between the available SNP genotyping information
In the present study, we describe a new web-based visualization interface for mtSNPs, called V-MitoSNP. It provides visualization of human mtSNPs in a format convenient for association studies. The genotype information presented in V-MitoSNP is the restriction fragment of length polymorphism (RFLP), which is the most cost-effective method used in standard laboratories. V-MitoSNP identifies the restriction enzymes and their paired natural/mismatched primer sets for RFLPs in all mtSNPs and immediately presents the results in a ready-to-use format. V-MitoSNP also provides an mtSNP search capability related to the gene locus, disease, mtSNP rs# ID, genome range, and the actual sequences.
Construction and content
V-MitoSNP is designed and implemented under the SQL server database system. Java Server Pages (JSP) and Java applets are used to input data and process files between the user and the application, as well as parse the data. The database structure for mtSNPs is downloaded from MITOMAP  with permission, and the mtSNP rs# ID is downloaded from NCBI dbSNP version b123 . The mitochondrial genome sequence rCRS is also downloaded from MITOMAP . The restriction enzyme database for RFLP genotyping is downloaded from REBASE version 601 . The restriction enzymes are transformed into the MySOL format and saved in a local database.
(1) Input module
(2) Display module
The results of the input module are processed in the display module, which provides SNP, cancer, and disease information for the mtDNA. The displayed SNP flanking sequence is used as a template in the RFLP analysis and in the primer design modules. The RFLP availability for all mtSNPs from MITOMAP  and the chromosome MT of the NCBI dbSNP  is calculated, analyzed and stored in the mtRFLP database.
(3) Position alignment module
The input sequence is matched to the human mtDNA rCRS sequence . Biological information is automatically provided for the matched position range.
(4) RFLP analysis module
The entered SNP sequences are transformed into their complementary (reverse) strands. The RFLP result for these sequences is then analyzed using the local REBASE database . V-MitoSNP provides a complete list of available restriction enzymes for each mtSNP, including commercial and non-commercial restriction enzymes. The restriction enzymes are divided into two groups. Blue and red colors (Figure 2F) are used to identify the recognition sites for the restriction enzymes with and without degenerated nucleotides, respectively. The enzyme lists are updated periodically from REBASE .
Although most endonucleases are palindromic, the flanking sequences of the recognition site containing SNPs in both sense and antisense strands are usually different. Some recognition sites are found exclusively only in sense or antisense strands. Sometimes, the sense and antisense strands provide the same restriction enzyme for RFLP genotyping because the same recognition site is chosen in both strands. V-MitoSNP provides the RFLP availability in both sense and antisense strands labeled "+" and "-" in Figure 2F. The complementary SNP sequence is separated into two sequences marked "0" and "1" for both sense and antisense strands. If different enzymes are selected the recognition sites are cut differently. This sequence separation is designed to provide information of RFLP enzymes and their corresponding genotype.
(5) Primer design module
Primer design aims to construct optimal candidates. Although various primer design approaches have been proposed, the process is usually time consuming when carried out manually. V-MitoSNP is designed to provide complete primer sets for all SNPs in mtDNA, including the primer sets for natural and mismatched PCR-RFLP. Optimal primer design follows criteria described in [21, 22], which include melting temperatures (Tm), length, base composition, 3'-end, repeated and self-complementary sequences and complementarity between members of a primer pair. Several primer design conditions are included in V-MitoSNP: (1) the length for the PCR product: 200~ 250 bp; (2) G or C preference at the 3'-end of the primer sets; (3) the primer length: 18 ~ 26 bp; (4) GC proportion: 40%~60%; (5) Tm: 50°C ~ 60°C; (6) Tm difference between primer sets: less than 5°C; (7) length difference between primer sets: 5 bp. Actual differences of these criteria are aggregated by weighting sums.
The primer design strategy depends on the RFLP availability for the target SNP. For SNPs with RFLP enzymes, the default primer design conditions can be used for designing the natural primer, while for SNPs without a natural RFLP enzyme a mismatched primer design is provided by V-MitoSNP. Only one nucleotide adjacent to the SNP candidate is changed randomly by the program in order to obtain the RFLP enzymes. The changed nucleotide faces preferentially away from the targeted SNP. Putting the system generated mismatch on the last two nucleotides of the primer is discouraged by the system. V-MitoSNP also tries to avoid the introduction of multiple mismatches because multiple mismatches and 3'-end mismatches in the PCR primer can potentially create problems for PCR optimization. Once found, the design of the mutagenic primer is accomplished and its opposite primer with compatible Tm and base composition will be designed with a PCR length of around 200 bp by default. This design ensures that the digested allelic fragments can be easily resolved on regular agarose gel electrophoresis.
(6) Virtual electrophoresis module
The natural and mismatched primer sets designed in the primer design module are blasted to the mtDNA rCRS sequence  to estimate the full length of the PCR. The RFLP analysis module provides RFLP enzyme information for in silico digestion and its corresponding SNP genotype. As described under the RFLP analysis module, the complementary SNP sequence is separated into two distinct sequences marked "0" and "1". The virtual gel patterns are different for sequences with "0" and/or "1" for sense or antisense (+ or -) strands. For example, the non-commercial restriction enzyme NcuII is cut at the C site in mtSNP at C12815T, whereas the T site in C12815T is uncut in the sequence of (+) = 0 (Figure 2F). The virtual gel pattern shows that the enzyme NcuII can digest the CC type, whereas TT cannot be digested. In contrast, enzymes listed in sequences with "1" mean that the T of C12815T is cut by HpyCH4IV and the C of C12815T is uncut. The virtual gel pattern shows that the TT type can be digested with the enzyme HpyCH4IV, but CC cannot, explaining the two distinctly different virtual gel patters produced by V-MitoSNP. After having obtained the two virtual gel patterns the in silico PCR-RFLP is prepared and analyzed by in silico electrophoresis, which shows its genotype and the corresponding PCR-RFLP length.
Validation of primer designs
DNA extraction of human blood and a standard PCR reaction were performed as previously described . To validate the functions of the designed primers in V-MitoSNP, SNPs at position 8993, 5973, 7080, 12372, 15508, and 8829 of rCRS  and their corresponding natural and/or mismatched primers were tested. The natural primers were the following: 8993 forward 5'-CATGGCCATCCCCTTATG-3', 8993 reverse 5'-ATGAGTACCTGGCCTGCAG-3', 5973 forward 5'-CACCTCGG AGCTGGTAAA-3', 5973 reverse 5'-TAAGGAGGCTTAGCGCTG-3', 7080 forward 5'-GAGCCCTAGGATTCATCT-3', and 7080 reverse 5'-TCTAGGGTGTAGCCAGAG-3'. The mismatched primers were: 12372 forward 5'-ACTACTATAACCACCCTAACCCTG-3', 12372 reverse 5'-TTAGGGAGAGCTGGGTTGTTTGG-3', 15508 forward 5'-GACCTCCTAGGCGACCCAGAC-3', 15508 reverse 5'-TTAGTGGGCGAAATATTATGCTTTG-3', 8829 forward 5'-ACCAACCACCCAACTATCTATAAAC-3', and 8829 reverse 5'-TGGCCTGCAGTAATGTTAGCGGT-3'. The PCR length for the SNP at 8993, 5973, 7080, 12372, 15508, and 8829 using these primers were 206, 200, 201, 221, 223, and 221 bp, respectively. Detailed PCR information was obtained online by range input. The PCR was performed under the following conditions: 94°C (1 min); 4 cycles of 94°C (15s), 64°C (15 s), 70°C (15 s); 4 cycles of 94°C (15 s), 61°C (15 s), 70°C (15 s); 4 cycles of 94°C (15 s), 58°C (15 s), 70°C (15 s); 60 cycles of 94°C for (15 s), 55°C (15 s), 70°C (15 s); 94°C (1 min) and 60°C (5 min). The PCR results were confirmed by 1.5% agarose electrophoresis (stained with ethidium bromide).
Graphic input and output visualization
Users can select a gene of interest on the mitochondrial genome graph, which is subdivided into different regions for each gene, simply by clicking on it (Figure 2A). Genes with similar functions are shown in the same colors. By selecting a certain region of the graph real-time information about the gene name, the total number of genes, and cancer- and disease-related SNPs within the selected genes can be provided. The visualized output data of V-MitoSNP is plotted in Figures 2B~2F in an overlapping manner. The MT-ND5 gene was chosen as an example to show the general results for the gene input. In Figure 2B, SNP information for the input gene is shown, including its map locus, map position, shorthand, description, SNP number with or without cancer and disease information, sequence of the selected SNP, NCBI rs# ID, nucleotide position, nucleotide change, amino acid change, RFLP availability and the ready-for-use primers with their respective virtual electrophoresis information. The total number of mtSNPs, cancer-related mtSNPs, and disease-related mtSNPs are shown in the red box in Figure 2B. The red box contains three available choices for SNP information: mtSNPs not related to cancers/diseases, cancer-related mtSNPs, and mtSNPs related to other diseases. Information pertaining to mtSNPs without the report for cancer and disease in MITOMAP  is shown by default (Figure 2B). Disease- and cancer-related mtSNPs are shown in Figure 2C and Figure 2D, respectively. Both Figure 2C and Figure 2D provide extra information in addition to Figure 2B, e.g. homoplasmy and heteroplasmy. V-MitoSNP also shows the full name of cancers and diseases via a hyperlink to MITOMAP. When clicking the check box "show sequence" in Figure 2B, each SNP with its corresponding flanking sequence (500 bp) is provided in Figure 2E for primer design if needed. Natural primers are designed by V-MitoSNP, and their virtual electrophoresis results are shown in Figure 2F.
In Figure 2F, sequence (+/-) is used to represent the sense and antisense sequences. Sequence (+/-) = 0 and sequence (+/-) = 1 are used to represent the sequence with C in C12815T and T in C12815T, respectively. In sequence (+) = 0, the enzyme with the recognition site CCCG is provided in detail for a noncommercial enzyme, i.e. NcuII and Sth132I. In sequence (-) = 0, enzymes with recognition sites CYCGRG and RGCB are provided for commercial enzymes like Ama87I, AvaI, BmeT110I, BsiHKCI, BsoBI, Eco88I. Noncommercial enzymes can be shown in detail via a hyperlink. The results shown in the figures suggest that the same SNP (= 0) shown in sense and antisense strands can correspond to different RFLP enzymes. In the sequence (+/-) = 1, enzymes with recognition sites ACGT and TCNGA are provided for commercial enzymes like HpyCH4IV, MaeII, TaiI, Hpy188I, and noncommercial enzymes can again be shown in detail by clicking on a hyperlink. The results for the sequence (+/-) = 1 suggest that under some circumstances the RFLP enzymes in both sense and antisense strands can be identical. Similar functions can be displayed for mismatched primers, except that only the sense strand is presented (not shown in the figures, please check results on the V-MitoSNP website).
The virtual RFLP pattern after the in silico enzyme digestion is dependent on the sequence trait, meaning the sense or antisense strands. In Figure 2F, V-MitoSNP provides two kinds of virtual gel patterns for the sequence (+/-) = 0 and the sequence (+/-) = 1. The in silico PCR-RFLP can be prepared and analyzed by in silico electrophoresis, which shows the genotype and the corresponding PCR-RFLP length pattern. The obtained virtual gel patterns and electrophoresis results facilitate RFLP genotyping enormously, since they contain information about the digested fragment length and the corresponding SNP genotypes. Information for both commercial and non-commercial restriction enzymes is provided for recognition sites with and without degenerated nucleotides. The results shown in Figure 2B~2F are also typical for output formats of a data search and of a range and sequence search, both of which are not shown in the Figures 3 and 4 for brevity.
Data search input and output
V-MitoSNP provides a keyword search function for convenience. Threekinds of keyword inputs, namely locus (gene name), disease and mtSNP rs# ID can be selected (Figure 3A). In Figure 3B the disease ADPD is shown as an output result. In addition to the common RFLP information described in Figure 2, homoplasmy, heteroplasmy and status are also provided. The disease ADPD is related to several genes, including MT-ND1 (coding & control region in point mutations), MT-RNR2 and MT-TQ (rRNA/tRNA in point mutation). The results of the search function of V-MitoSNP indicate that relationship, and provide a hyperlink for further information.
The results of the mtSNP rs# ID output (not shown for brevity) can also constitute a convenient manner for systematic RFLP genotyping association studies. The connection between the SNP in the rCRS sequence  and the chromosome MT in NCBI dbSNP  is also indicated. The SNP in the rCRS sequence obtained from the NCBI rs # ID record is shown parallel if available.
Range & sequence input and output
The range position is selectable by clicking the mtDNA color-band graph, and a real-time display for positional information is provided. In Figure 4A, positions 5303~5803 on the MITOMAP sequence of rCRS are chosen. The sequence in this range is used by V-MitoSNP for input in mtBLAST (Figure 4B). Figures 4A and 4B cover genes within the input range and the respective output results are shown in Figures 4C and 4D. Information for all mtSNPs within the input data range is shown in the order of their nucleotide positions (Figure 4C). All mtSNPs contained within the sequence can be displayed with or without cancer/disease information, and are highlighted in red color.
Validation of primer designs
V-MitoSNP was compared to some existing mitochondrial analysis tools, i.e. mtDB , MITOMAP , GiiB-JST mtSNP  and MitoRes . The results indicate that V-MitoSNP is highly efficient and more informative than these other tools, especially when taking its comprehensive input and output data, such as RFLP enzyme availability, flanking sequence for selected SNP, mtBLAST, natural and mismatched primer design, and virtual electrophoresis into account. The tools that were compared to V-MitoSNP only support simple browser functions so that a user cannot obtain the complete set of data needed for comprehensive SNP genotyping. In contrast, V-MitoSNP processes graphic and data input for mtSNP analysis and retrieval. The results are presented in a user-friendly and highly structured way, thus simplifying the RFLP genotyping process considerably.
The complete RFLP enzyme list in V-MitoSNP provides for reliable and robust genotyping assays. The six primers (position of 8993, 5973, 7080, 12372, 15508, and 8829 of rCRS) provided and tested by V-MitoSNP were proven to be successful by actual agarose gel electrophoresis (Figure 5). Actually, many SNP RFLP tools do already exist, such as NEBcutter , PIRA-PCR Designer , SNP cutter , and SNPselector . Unfortunately, the designed primer assays are usually not very effective because only SNP rs # and sequence inputs are acceptable. In the most commonly used mtDNA databases mtDB , MITOMAP , and GiiB-JST mtSNP  however, the polymorphism data of the mtDNA is not represented as SNP rs # (or as the SNP ID in NCBI dbSNP) . V-MitoSNP merges data for the polymorphisms and the SNP rs# IDs with chromosome MT data in NCBI dbSNP . The mtSNP rs# ID is also acceptable as a search input in V-MitoSNP. Commercial and non-commercial restriction enzymes for recognition sites with and without degenerated nucleotides are included, and the RFLP availability for mtSNPs is provided, extending the scope of information gathered by V-MitoSNP.
V-MitoSNP provides an almost complete RFLP restriction enzyme list, which includes corresponding primer sets for all mtSNPs from MITOMAP. MITOMAP lists 1969 mtSNPs. V-MitoSNP provides 1636 natural and 333 mismatched RFLP designed enzymes and primer sets. The mtSNPs for which RFLP enzymes and primers cannot be provided number only 18. In NCBI dbSNP (version b123) 118 mtSNPs are reported. For these, V-MitoSNP provides 105 natural and 13 mismatched RFLP enzymes and primer sets. For every mtSNP in chromosome MT listed in NCBI dbSNP complete information for RFLP genotyping is provided. Periodic updates for V-MitoSNP are planned, which will include the latest versions of NCBI dbSNP and the up-to-date information contained therein. The rate for successful enzyme and primer design for RFLP in all mtSNPs was at least 99.1% when using V-MitoSNP.
We found it convenient to manage RFLP enzymes and the corresponding primers in the graphically displayed and ready-for-use format provided by V-MitoSNP. The graphic display of the results and the organized data structure are features that set V-MitoSNP apart from the other tools tested here. V-MitoSNP presents size data of amplicons, digested allelic fragments and signature fragments in virtual electrophoresis (Figure 2F).
This data is important as a guide for evaluating genotyping results. Although PCR-RFLP is not generally recognized as a high-throughput SNP genotyping method, it does have its advantages and still plays an important role in many small laboratories due to its cost effectiveness. V-MitoSNP was specifically developed as a tool to assist investigators who are using PCR-RFLP when performing SNP genotyping in mtDNA.
V-MitoSNP provides a gene-specific homologue search of mtDNA sequences for mtBLAST. Even if the sequence used covers several genes in the mtDNA, V-MitoSNP will still shows all genes within the sequence, as well as the SNP genotyping information. The input sequence from nucleotide 5303 to 5803 in rCRS  (Figure 2D) outputs the genes MT-ND2, MT-TW, MT-NC3, and MT-TA (in Figure 3C). In contrast, the results of NCBI BLASTn  using the nr database show different isolates for the complete Homo sapiens mitochondrion genome (100 hits). A gene name output cannot be provided. The same results were obtained by analysis with the Biology Workbench 3.2 at the San Diego Supercomputer Center  using the Homo sapiens mitochondrion genome (hs_ref_chrMT.na) database. To our knowledge, V-MitoSNP is the first software that provides a gene-targeting function to BLAST mtDNA, although a score and E value are not included.
V-MitoSNP presents ready-for-use mtSNP information related to diseases and cancers in a graphic, user-friendly and structured manner. It is convenient for use in mtSNP association studies and simplifies these considerably. Primer set and its corresponding RFLP restriction enzyme are provided. Visual input and output coupled with integrated mtSNP information from MITOMAP and NCBI make V-MitoSNP an ideal and complete visualization interface for human mtSNPs association studies.
Availability and requirements
Project name: V-MitoSNP: visualization of human mitochondrial
SNPs Project home page: http://bio.kuas.edu.tw/v-mitosnp/
Operating system(s): Microsoft Windows XP
Programming language: Java
Other requirements: JSP 2.0, Servlet 2.4, Tomcat 5.5, SQL server 2000, MySQL 4.0
License: none for academic users.
For any restrictions regarding the use by non-academicians please contact the corresponding author.
Single Nucleotide Polymorphism
revised Cambridge Reference Sequence
National Center for Biotechnology Information
Restriction Fragment Length Polymorphism
Restriction Enzyme Database
Polymerase Chain Reaction
- chromosome MT:
This work is partly supported by the National Science Council in Taiwan under grant NSC94-2622-E-151-025-CC3, NSC94-2311-B037-001, NSC93-2213-E-214-037, NSC92-2213-E-214-036 and by the CGMH fund CMRPG1006.
- Anderson S, Bankier AT, Barrell BG, de Bruijn MH, Coulson AR, Drouin J, Eperon IC, Nierlich DP, Roe BA, Sanger F, et al.: Sequence and organization of the human mitochondrial genome. Nature 1981, 290(5806):457–465. 10.1038/290457a0View ArticlePubMedGoogle Scholar
- Andrews RM, Kubacka I, Chinnery PF, Lightowlers RN, Turnbull DM, Howell N: Reanalysis and revision of the Cambridge reference sequence for human mitochondrial DNA. Nat Genet 1999, 23(2):147. 10.1038/13779View ArticlePubMedGoogle Scholar
- Taylor RW, Turnbull DM: Mitochondrial DNA mutations in human disease. Nat Rev Genet 2005, 6(5):389–402. 10.1038/nrg1606PubMed CentralView ArticlePubMedGoogle Scholar
- Salas A, Yao YG, Macaulay V, Vega A, Carracedo A, Bandelt HJ: A Critical Reassessment of the Role of Mitochondria in Tumorigenesis. PLoS Med 2005, 2(11):e296. 10.1371/journal.pmed.0020296PubMed CentralView ArticlePubMedGoogle Scholar
- Zanssen S, Schon EA: Mitochondrial DNA mutations in cancer. PLoS Med 2005, 2(11):e401. 10.1371/journal.pmed.0020401PubMed CentralView ArticlePubMedGoogle Scholar
- Sharma H, Singh A, Sharma C, Jain SK, Singh N: Mutations in the mitochondrial DNA D-loop region are frequent in cervical cancer. Cancer Cell Int 2005, 5(1):34. 10.1186/1475-2867-5-34PubMed CentralView ArticlePubMedGoogle Scholar
- Han CB, Ma JM, Xin Y, Mao XY, Zhao YJ, Wu DY, Zhang SM, Zhang YK: Mutations of mitochondrial 12S rRNA in gastric carcinoma and their significance. World J Gastroenterol 2005, 11(1):31–35.PubMed CentralView ArticlePubMedGoogle Scholar
- Liu VW, Shi HH, Cheung AN, Chiu PM, Leung TW, Nagley P, Wong LC, Ngan HY: High incidence of somatic mitochondrial DNA mutations in human ovarian carcinomas. Cancer Res 2001, 61(16):5998–6001.PubMedGoogle Scholar
- Rosson D, Keshgegian AA: Frequent mutations in the mitochondrial control region DNA in breast tissue. Cancer Lett 2004, 215(1):89–94. 10.1016/j.canlet.2004.04.030View ArticlePubMedGoogle Scholar
- Habano W, Sugai T, Yoshida T, Nakamura S: Mitochondrial gene mutation, but not large-scale deletion, is a feature of colorectal carcinomas with mitochondrial microsatellite instability. Int J Cancer 1999, 83(5):625–629. 10.1002/(SICI)1097-0215(19991126)83:5<625::AID-IJC10>3.0.CO;2-NView ArticlePubMedGoogle Scholar
- Lee HC, Yin PH, Lin JC, Wu CC, Chen CY, Wu CW, Chi CW, Tam TN, Wei YH: Mitochondrial Genome Instability and mtDNA Depletion in Human Cancers. Ann N Y Acad Sci 2005, 1042: 109–122. 10.1196/annals.1338.011View ArticlePubMedGoogle Scholar
- Lutz-Bonengel S, Schmidt U, Schmitt T, Pollak S: Sequence polymorphisms within the human mitochondrial genes MTATP6, MTATP8 and MTND4. Int J Legal Med 2003, 117(3):133–142.PubMedGoogle Scholar
- Just RS, Irwin JA, O'Callaghan JE, Saunier JL, Coble MD, Vallone PM, Butler JM, Barritt SM, Parsons TJ: Toward increased utility of mtDNA in forensic identifications. Forensic Sci Int 2004, 146(Suppl):S147–149. 10.1016/j.forsciint.2004.09.045View ArticlePubMedGoogle Scholar
- Brown WM, George M Jr, Wilson AC: Rapid evolution of animal mitochondrial DNA. Proc Natl Acad Sci U S A 1979, 76(4):1967–1971. 10.1073/pnas.76.4.1967PubMed CentralView ArticlePubMedGoogle Scholar
- Ingman M, Gyllensten U: mtDB: Human Mitochondrial Genome Database, a resource for population genetics and medical sciences. Nucleic Acids Res 2006, 34(Database):D749–751. [http://www.genpat.uu.se/mtDB] 10.1093/nar/gkj010PubMed CentralView ArticlePubMedGoogle Scholar
- Brandon MC, Lott MT, Nguyen KC, Spolim S, Navathe SB, Baldi P, Wallace DC: MITOMAP: a human mitochondrial genome database – 2004 update. Nucleic Acids Res 2005, 33(Database):D611–613. [http://www.mitomap.org] 10.1093/nar/gki079PubMed CentralPubMedGoogle Scholar
- Tanaka M, Takeyasu T, Fuku N, Li-Jun G, Kurata M: Mitochondrial genome single nucleotide polymorphisms and their phenotypes in the Japanese. Ann N Y Acad Sci 2004, 1011: 7–20. [http://www.giib.or.jp/mtsnp/index_e.shtml] 10.1196/annals.1293.002View ArticlePubMedGoogle Scholar
- Catalano D, Licciulli F, Turi A, Grillo G, Saccone C, D'Elia D: MitoRes: a resource of nuclear-encoded mitochondrial genes and their products in Metazoa. BMC Bioinformatics 2006, 7(1):36. [http://www2.ba.itb.cnr.it/MitoNuc] 10.1186/1471-2105-7-36PubMed CentralView ArticlePubMedGoogle Scholar
- Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001, 29(1):308–311. [http://www.ncbi.nlm.nih.gov/projects/SNP/] 10.1093/nar/29.1.308PubMed CentralView ArticlePubMedGoogle Scholar
- Roberts RJ, Vincze T, Posfai J, Macelis D: REBASE – restriction enzymes and DNA methyltransferases. Nucleic Acids Res 2005, 33(Database):D230–232. [http://rebase.neb.com/rebase/rebase.html] 10.1093/nar/gki029PubMed CentralPubMedGoogle Scholar
- McPherson MJ, Quirke P, Taylor GR: PCR : A Practical Approach. Oxford University Press, USA; 2005.Google Scholar
- Sambrook J, Russell DW: Molecular Cloning: A Laboratory Manual. 3rd edition. Labmn: Cold Spring Harbor Laboratory Press; 2001.Google Scholar
- Chang HW, Ali SZ, Cho SK, Kurman RJ, Shih Ie M: Detection of allelic imbalance in ascitic supernatant by digital single nucleotide polymorphism analysis. Clin Cancer Res 2002, 8(8):2580–2585.PubMedGoogle Scholar
- Vincze T, Posfai J, Roberts RJ: NEBcutter: A program to cleave DNA with restriction enzymes. Nucleic Acids Res 2003, 31(13):3688–3691. [http://tools.neb.com/NEBcutter2/index.php] 10.1093/nar/gkg526PubMed CentralView ArticlePubMedGoogle Scholar
- Ke X, Collins A, Ye S: PIRA PCR designer for restriction analysis of single nucleotide polymorphisms. Bioinformatics 2001, 17(9):838–839. [http://cedar.genetics.soton.ac.uk/public_html/primer2.html] 10.1093/bioinformatics/17.9.838View ArticlePubMedGoogle Scholar
- Zhang R, Zhu Z, Zhu H, Nguyen T, Yao F, Xia K, Liang D, Liu C: SNP Cutter: a comprehensive tool for SNP PCR-RFLP assay design. Nucleic Acids Res 2005, 33(Web Server):W489–492. [http://bioinfo.bsd.uchicago.edu/SNP_cutter.htm] 10.1093/nar/gki358PubMed CentralView ArticlePubMedGoogle Scholar
- Xu H, Gregory SG, Hauser ER, Stenger JE, Pericak-Vance MA, Vance JM, Zuchner S, Hauser MA: SNPselector: a web tool for selecting SNPs for genetic association studies. Bioinformatics 2005, 21(22):4181–4186. [http://primer.duhs.duke.edu/] 10.1093/bioinformatics/bti682PubMed CentralView ArticlePubMedGoogle Scholar
- McGinnis S, Madden TL: BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res 2004, 32(Web Server):W20–25. [http://www.ncbi.nlm.nih.gov/BLAST/]PubMed CentralView ArticlePubMedGoogle Scholar
- Biology Workbench 3.2 San Diego Supercomputer Center [http://workbench.sdsc.edu/]
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