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A program for selecting DNA fragments to detect mutations by denaturing gel electrophoresis methods.

ABSTRACT: A computer program was developed to automate the selection of DNA fragments for detecting mutations within a long DNA sequence by denaturing gel electrophoresis methods. The program, MELTSCAN, scans through a user specified DNA sequence calculating the melting behavior of overlapping DNA fragments covering the sequence. Melting characteristics of the fragments are analyzed to determine the best fragment for detecting mutations at each base pair position in the sequence. The calculation also determines the optimal fragment for detecting mutations within a user specified mutational hot spot region. The program is built around the statistical mechanical model of the DNA melting transition. The optimal fragment for a given position is selected using the criteria that its melting curve has at least two steps, the base pair position is in the fragment's lowest melting domain, and the melting domain has the smallest number of base pairs among fragments that meet the first two criteria. The program predicted fragments for detecting mutations in the cDNA and genomic DNA of the human p53 gene.

SUBMITTER: Brossette S

PROVIDER: S-EPMC331956 | biostudies-other | 1994 Oct

REPOSITORIES: biostudies-other

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A program for selecting DNA fragments to detect mutations by denaturing gel electrophoresis methods.

Brossette S S Wartell R M RM

Nucleic acids research 19941001 20

A computer program was developed to automate the selection of DNA fragments for detecting mutations within a long DNA sequence by denaturing gel electrophoresis methods. The program, MELTSCAN, scans through a user specified DNA sequence calculating the melting behavior of overlapping DNA fragments covering the sequence. Melting characteristics of the fragments are analyzed to determine the best fragment for detecting mutations at each base pair position in the sequence. The calculation also dete ...[more]

PMID: 7937161

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Project description:The effect of developing chrysanthemum roots on the presence and activity of bacterial populations in the rhizosphere was examined by using culture-independent methods. Nucleic acids were extracted from rhizosphere soil samples associated with the bases of roots or root tips of plants harvested at different stages of development. PCR and reverse transcriptase (RT) PCR were used to amplify 16S ribosomal DNA (rDNA) and 16S rRNA, respectively, and the products were subjected to denaturing gradient gel electrophoresis (DGGE). Prominent DGGE bands were excised and sequenced to gain insight into the identities of predominantly present (PCR) and predominantly active (RT-PCR) bacterial populations. The majority of DGGE band sequences were related to bacterial genera previously associated with the rhizosphere, such as Pseudomonas, Comamonas, Variovorax, and Acetobacter, or typical of root-free soil environments, such as Bacillus and Arthrobacter. The PCR-DGGE patterns observed for bulk soil were somewhat more complex than those obtained from rhizosphere samples, and the latter contained a subset of the bands present in bulk soil. DGGE analysis of RT-PCR products detected a subset of bands visible in the rDNA-based analysis, indicating that some dominantly detected bacterial populations did not have high levels of metabolic activity. The sequences detected by the RT-PCR approach were, however, derived from a wide taxonomic range, suggesting that activity in the rhizosphere was not determined at broad taxonomic levels but rather was a strain- or species-specific phenomenon. Comparative analysis of DGGE profiles grouped all DNA-derived root tip samples together in a cluster, and within this cluster the root tip samples from young plants formed a separate subcluster. Comparison of rRNA-derived bacterial profiles showed no grouping of root tip samples versus root base samples. Rather, all profiles derived from 2-week-old plant rhizosphere soils grouped together regardless of location along the root.

Dataset Information

A program for selecting DNA fragments to detect mutations by denaturing gel electrophoresis methods.

Publications

A program for selecting DNA fragments to detect mutations by denaturing gel electrophoresis methods.

Similar Datasets

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