Research Article | Open Access
B. Jayashree, Manindra S. Hanspal, Rajgopal Srinivasan, R. Vigneshwaran, Rajeev K. Varshney, N. Spurthi, K. Eshwar, N. Ramesh, S. Chandra, David A. Hoisington, "An Integrated Pipeline of Open Source Software Adapted for Multi-CPU Architectures: Use in the Large-Scale Identification of Single Nucleotide Polymorphisms", International Journal of Genomics, vol. 2007, Article ID 035604, 7 pages, 2007. https://doi.org/10.1155/2007/35604
An Integrated Pipeline of Open Source Software Adapted for Multi-CPU Architectures: Use in the Large-Scale Identification of Single Nucleotide Polymorphisms
The large amounts of EST sequence data available from a single species of an organism as well as for several species within a genus provide an easy source of identification of intra- and interspecies single nucleotide polymorphisms (SNPs). In the case of model organisms, the data available are numerous, given the degree of redundancy in the deposited EST data. There are several available bioinformatics tools that can be used to mine this data; however, using them requires a certain level of expertise: the tools have to be used sequentially with accompanying format conversion and steps like clustering and assembly of sequences become time-intensive jobs even for moderately sized datasets. We report here a pipeline of open source software extended to run on multiple CPU architectures that can be used to mine large EST datasets for SNPs and identify restriction sites for assaying the SNPs so that cost-effective CAPS assays can be developed for SNP genotyping in genetics and breeding applications. At the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), the pipeline has been implemented to run on a Paracel high-performance system consisting of four dual AMD Opteron processors running Linux with MPICH. The pipeline can be accessed through user-friendly web interfaces at http://hpc.icrisat.cgiar.org/PBSWeb and is available on request for academic use. We have validated the developed pipeline by mining chickpea ESTs for interspecies SNPs, development of CAPS assays for SNP genotyping, and confirmation of restriction digestion pattern at the sequence level.
- D. G. Wang, J.-B. Fan, C.-J. Siao et al., “Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome,” Science, vol. 280, no. 5366, pp. 1077–1082, 1998.
- L. Picoult-Newberg, T. E. Ideker, M. G. Pohl et al., “Mining SNPs from EST databases,” Genome Research, vol. 9, no. 2, pp. 167–174, 1999.
- G. T. Marth, I. Korf, M. D. Yandell et al., “A general approach to single-nucleotide polymorphism discovery,” Nature Genetics, vol. 23, no. 4, pp. 452–456, 1999.
- Z. Ning, A. J. Cox, and J. C. Mullikin, “SSAHA: a fast search method for large DNA databases,” Genome Research, vol. 11, no. 10, pp. 1725–1729, 2001.
- J. A. Aerts, B. J. Jungerius, and M. A. M. Groenen, “POSA: perl objects for DNA sequencing data analysis,” BMC Genomics, vol. 5, no. 1, p. 60, 2004.
- F. J. Useche, G. Gao, M. Harafey, and A. Rafalski, “High-throughput identification, database storage and analysis of SNPs in EST sequences,” Genome Informatics, vol. 12, pp. 194–203, 2001.
- L. K. Matukumalli, J. J. Grefenstette, D. L. Hyten, I.-Y. Choi, P. B. Cregan, and C. P. Van Tassell, “SNP-PHAGE—high throughput SNP discovery pipeline,” BMC Bioinformatics, vol. 7, p. 468, 2006.
- S. Weckx, J. Del-Favero, R. Rademakers et al., “novoSNP, a novel computational tool for sequence variation discovery,” Genome Research, vol. 15, no. 3, pp. 436–442, 2005.
- B. Chevreux, T. Pfisterer, B. Drescher et al., “Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs,” Genome Research, vol. 14, no. 6, pp. 1147–1159, 2004.
- G. Barker, J. Batley, H. O'Sullivan, K. J. Edwards, and D. Edwards, “Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP,” Bioinformatics, vol. 19, no. 3, pp. 421–422, 2003.
- R. Kota, S. Rudd, A. Facius et al., “Snipping polymorphisms from large EST collections in barley (Hordeum vulgare L.),” Molecular Genetics and Genomics, vol. 270, no. 1, pp. 24–33, 2003.
- A. Kalyanaraman, S. Aluru, V. Brendel, and S. Kothari, “Space and time efficient parallel algorithms and software for EST clustering,” IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 12, pp. 1209–1221, 2003.
- X. Huang, J. Wang, S. Aluru, S.-P. Yang, and L. Hillier, “PCAP: a whole-genome assembly program,” Genome Research, vol. 13, no. 9, pp. 2164–2170, 2003.
- Z. Zhang, S. Schwartz, L. Wagner, and W. Miller, “A greedy algorithm for aligning DNA sequences,” Journal of Computational Biology, vol. 7, no. 1-2, pp. 203–214, 2000.
- T. Thiel, R. Kota, I. Grosse, N. Stein, and A. Graner, “SNP2CAPS: a SNP and INDEL analysis tool for CAPS marker development,” Nucleic Acids Research, vol. 32, no. 1, p. e5, 2004.
- G. Pertea, X. Huang, F. Liang et al., “TIGR gene indices clustering tools (TGICL): a software system for fast clustering of large EST datasets,” Bioinformatics, vol. 19, no. 5, pp. 651–652, 2003.
- E. S. Mace, H. K. Buhariwalla, and J. H. Crouch, “A high-throughput DNA extraction protocol for tropical molecular breeding programs,” Plant Molecular Biology Reporter, vol. 21, no. 4, pp. 459a–459h, 2003.
- E. Bartocci, F. Corradini, E. Merelli, and L. Scortichini, “BioWMS: a web-based workflow management system for bioinformatics,” BMC Bioinformatics, vol. 8, 1, p. S2, 2007.
- Q. Lu, P. Hao, V. Curcin et al., “KDE bioscience: platform for bioinformatics analysis workflows ,” Journal of Biomedical Informatics, vol. 39, no. 4, pp. 440–450, 2006.
- T. Oinn, M. Addis, J. Ferris et al., “Taverna: a tool for the composition and enactment of bioinformatics workflows,” Bioinformatics, vol. 20, no. 17, pp. 3045–3054, 2004.
- S. Hoon, K. K. Ratnapu, J.-M. Chia et al., “Biopipe: a flexible framework for protocol-based bioinformatics analysis,” Genome Research, vol. 13, no. 8, pp. 1904–1915, 2003.
- B. Schmidt, L. Feng, A. Laud, and Y. Santoso, “Development of distributed bioinformatics applications with GMP,” Concurrency and Computation: Practice & Experience, vol. 16, no. 9, pp. 945–959, 2004.
- P. Romano, E. Bartocci, G. Bertolini et al., “Biowep: a workflow enactment portal for bioinformatics applications,” BMC Bioinformatics, vol. 8, 1, p. S19, 2007.
Copyright © 2007 B. Jayashree et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.