Abstract
BackgroundThe discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions. One valuable approach proposed for SNP discovery is based on base-specific cleavage and mass spectrometry. However, it is still very challenging to achieve the full potential of this SNP discovery approach.ResultsIn this study, we formulate two new combinatorial optimization problems. While both problems are aimed at reconstructing the sample sequence that would attain the minimum number of SNPs, they search over different candidate sequence spaces. The first problem, denoted as , limits its search to sequences whose in silico predicted mass spectra have all their signals contained in the measured mass spectra. In contrast, the second problem, denoted as , limits its search to sequences whose in silico predicted mass spectra instead contain all the signals of the measured mass spectra. We present an exact dynamic programming algorithm for solving the problem and also show that the problem is NP-hard by a reduction from a restricted variation of the 3-partition problem.ConclusionsWe believe that an efficient solution to either problem above could offer a seamless integration of information in four complementary base-specific cleavage reactions, thereby improving the capability of the underlying biotechnology for sensitive and accurate SNP discovery.
Highlights
The discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions
While both problems are aimed at reconstructing the sample sequence that would attain the minimum number of SNPs, they search over different candidate sequence spaces
To exploit the full potential of the SNP discovery approach using base-specific cleavage and mass spectrometry, in this paper we have studied two new combinatorial optimization problems, called SNP−MSP and SNP - MSQ, respectively
Summary
The discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions. Single nucleotide polymorphisms (SNPs) is a common type of DNA sequence variations that occur when a single nucleotide base is altered at a specific locus. They are among the most important genetic factors that contribute to human disease and biological functions. Since each cleavage product is expected to be made of three non-cleavage bases, it is fairly straightforward to calculate the base composition from its measured mass signal. With all these base compositions in hand, the task of discovering SNPs in the sample sequence is left to a computational solution.
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