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Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

ABSTRACT: Cancer is a genetic disease that results from a variety of genomic alterations. Identification of some of these causal genetic events has enabled the development of targeted therapeutics and spurred efforts to discover the key genes that drive cancer formation. Rapidly improving sequencing and genotyping technology continues to generate increasingly large datasets that require analytical methods to identify functional alterations that deserve additional investigation. This review examines statistical and computational approaches for the identification of functional changes among sets of single-nucleotide substitutions. Frequency-based methods identify the most highly mutated genes in large-scale cancer sequencing efforts while bioinformatics approaches are effective for independent evaluation of both non-synonymous mutations and polymorphisms. We also review current knowledge and tools that can be utilized for analysis of alterations in non-protein-coding genomic sequence.

SUBMITTER: Lee W

PROVIDER: S-EPMC2762536 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

Lee William W Yue Peng P Zhang Zemin Z

Human genetics 20090512 4

Cancer is a genetic disease that results from a variety of genomic alterations. Identification of some of these causal genetic events has enabled the development of targeted therapeutics and spurred efforts to discover the key genes that drive cancer formation. Rapidly improving sequencing and genotyping technology continues to generate increasingly large datasets that require analytical methods to identify functional alterations that deserve additional investigation. This review examines statis ...[more]

PMID: 19434427

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Project description:Many naturally occurring RNA structures contain single mismatches, many of which occur near the ends of helices. However, previous thermodynamic studies have focused their efforts on thermodynamically characterizing centrally placed single mismatches. Additionally, algorithms currently used to predict secondary structure from sequence are based on two assumptions for predicting the stability of RNA duplexes containing this motif. It has been assumed that the thermodynamic contribution of small RNA motifs is independent of both its position in the duplex and the identity of the non-nearest neighbors. Thermodynamically characterizing single mismatches three nucleotides from both the 3' and 5' ends (i.e., off-center) of an RNA duplex and comparing these results to those of the same single mismatch-nearest neighbor combination centrally located have allowed for the investigation of these effects. The thermodynamic contributions of 13 single mismatch-nearest neighbor combinations are reported, but only nine combinations are studied at all three duplex positions and are used to determine trends and patterns. In general, the 5'- and 3'-shifted single mismatches are relatively similar, on average, and more favorable in free energy than centrally placed single mismatches. However, close examination and comparison shows there are several associated idiosyncrasies with these identified general trends. These peculiarities may be due, in part, to the identities of the single mismatch, the nearest neighbors, and the non-nearest neighbors, along with the effects of the single mismatch position in the duplex. The prediction algorithm recently proposed by Davis and Znosko [Davis, A. R., and Znosko, B. M. (2008) Biochemistry 47, 10178-10187] is used to predict the thermodynamic parameters of single mismatch contribution, and those values are compared to the measured values presented here. This comparison suggests the proposed model is a good approximation but could be improved by the addition of parameters that account for positional and/or non-nearest neighbor effects. However, more data are required to improve our understanding of these effects and to accurately account for them.

Project description:BackgroundExperimental studies of gene expression have identified some of the individual molecular components and elementary reactions that comprise and control cellular behavior. Given our current understanding of gene expression, and the goals of biotechnology research, both scientists and engineers would benefit from detailed simulators that can explicitly compute genome-wide expression levels as a function of individual molecular events, including the activities and interactions of molecules on DNA at single base pair resolution. However, for practical reasons including computational tractability, available simulators have not been able to represent genome-scale models of gene expression at this level of detail.ResultsHere we develop a simulator, TABASCO http://openwetware.org/wiki/TABASCO, which enables the precise representation of individual molecules and events in gene expression for genome-scale systems. We use a single molecule computational engine to track individual molecules interacting with and along nucleic acid polymers at single base resolution. Tabasco uses logical rules to automatically update and delimit the set of species and reactions that comprise a system during simulation, thereby avoiding the need for a priori specification of all possible combinations of molecules and reaction events. We confirm that single molecule, base-pair resolved simulation using TABASCO (Tabasco) can accurately compute gene expression dynamics and, moving beyond previous simulators, provide for the direct representation of intermolecular events such as polymerase collisions and promoter occlusion. We demonstrate the computational capacity of Tabasco by simulating the entirety of gene expression during bacteriophage T7 infection; for reference, the 39,937 base pair T7 genome encodes 56 genes that are transcribed by two types of RNA polymerases active across 22 promoters.ConclusionTabasco enables genome-scale simulation of transcription and translation at individual molecule and single base-pair resolution. By directly representing the position and activity of individual molecules on DNA, Tabasco can directly test the effects of detailed molecular processes on system-wide gene expression. Tabasco would also be useful for studying the complex regulatory mechanisms controlling eukaryotic gene expression. The computational engine underlying Tabasco could also be adapted to represent other types of processive systems in which individual reaction events are organized across a single spatial dimension (e.g., polysaccharide synthesis).

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Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

Publications

Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

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