Aligning two sequences within a specified diagonal band

Chao, Kun-Mao; Pearson, William R.; Miller, Webb

doi:10.1093/bioinformatics/8.5.481

Cited by 122 publications

(114 citation statements)

References 23 publications

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“…Functional annotation of assembled transcripts was assigned using WU-BLAST (Chao et al, 1992) by searching the Arabidopsis thaliana proteome (Lamesch et al, 2012), UniRef100 (Suzek et al, 2007), and peptides deposited in GenBank for A. belladonna using an E-value cutoff #1e-10. Pfam domains (Finn et al, 2010) were identified using HMMPfam from the HMMER package (v 3) (Krogh et al, 1994;Eddy, 1998Eddy, , 2009 with an E-value cutoff of 1e-10.…”

Section: Functional Annotationmentioning

confidence: 99%

A Root-Expressed l-Phenylalanine:4-Hydroxyphenylpyruvate Aminotransferase Is Required for Tropane Alkaloid Biosynthesis in Atropa belladonna

et al. 2014

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The tropane alkaloids, hyoscyamine and scopolamine, are medicinal compounds that are the active components of several therapeutics. Hyoscyamine and scopolamine are synthesized in the roots of specific genera of the Solanaceae in a multistep pathway that is only partially elucidated. To facilitate greater understanding of tropane alkaloid biosynthesis, a de novo transcriptome assembly was developed for Deadly Nightshade (Atropa belladonna). Littorine is a key intermediate in hyoscyamine and scopolamine biosynthesis that is produced by the condensation of tropine and phenyllactic acid. Phenyllactic acid is derived from phenylalanine via its transamination to phenylpyruvate, and mining of the transcriptome identified a phylogenetically distinct aromatic amino acid aminotransferase (ArAT), designated Ab-ArAT4, that is coexpressed with known tropane alkaloid biosynthesis genes in the roots of A. belladonna. Silencing of Ab-ArAT4 disrupted synthesis of hyoscyamine and scopolamine through reduction of phenyllactic acid levels. Recombinant Ab-ArAT4 preferentially catalyzes the first step in phenyllactic acid synthesis, the transamination of phenylalanine to phenylpyruvate. However, rather than utilizing the typical keto-acid cosubstrates, 2-oxoglutarate, pyruvate, and oxaloacetate, Ab-ArAT4 possesses strong substrate preference and highest activity with the aromatic keto-acid, 4-hydroxyphenylpyruvate. Thus, Ab-ArAT4 operates at the interface between primary and specialized metabolism, contributing to both tropane alkaloid biosynthesis and the direct conversion of phenylalanine to tyrosine.

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Section: Functional Annotationmentioning

confidence: 99%

A Root-Expressed l-Phenylalanine:4-Hydroxyphenylpyruvate Aminotransferase Is Required for Tropane Alkaloid Biosynthesis in Atropa belladonna

et al. 2014

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“…The platform was modified to calculate the performance of the algorithm for each query sequence from within the parallel program. A derivative of version 1.6 of the FASTA program (Chao et al, 1992) was used; the implementation of the Smith-Waterman algorithm was described in Pearson and Miller (1992). The platform was extended to include a global similarity score calculated by a modification of the Needleman-Wunsch algorithm (Myers & Miller, 1988).…”

Section: Similarity Searchingmentioning

confidence: 99%

Comparison of methods for searching protein sequence databases

1995

Self Cite

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We have compared commonly used sequence comparison algorithms, scoring matrices, and gap penalties using a method that identifies statistically significant differences in performance. Search sensitivity with either the Smith-Waterman algorithm or FASTA is significantly improved by using modern scoring matrices, such as BLOSUM45-55, and optimized gap penalties instead of the conventional PAM250 matrix. More dramatic improvement can be obtained by scaling similarity scores by the logarithm of the length of the library sequence (In()-scaling). With the best modern scoring matrix (BLOSUM55 or 5093) and optimal gap penalties (-12 for the first residue in the gap and -2 for additional residues), Smith-Waterman and FASTA performed significantly better than BLASTP. With In()-scaling and optimal scoring matrices (BLOSUM45 or Gonnet92) and gap penalties (-12, -l), the rigorous Smith-Waterman algorithm performs better than either BLASTP and FASTA, although with the Gonnet92 matrix the difference with FASTA was not significant. Ln()-scaling performed better than normalization based on other simple functions of library sequence length. Ln()-scaling also performed better than scores based on normalized variance, but the differences were not statistically significant for the BLOSUMSO and Gonnet92 matrices. Optimal scoring matrices and gap penalties are reported for Smith-Waterman and FASTA, using conventional or In()-scaled similarity scores. Searches with no penalty for gap extension, or no penalty for gap opening, or an infinite penalty for gaps performed significantly worse than the best methods. Differences in performance between FASTA and Smith-Waterman were not significant when partial query sequences were used. However, the best performance with complete query sequences was obtained with the Smith-Waterman algorithm and In()-scaling.Keywords: BLAST; FASTA; PAM250; sequence similarity; Smith-Waterman The concurrent development of rapid methods for molecular cloning, DNA sequencing, high-performance computer workstations, and rapid protein and DNA sequence comparison algorithms has revolutionized the practice of molecular biology. Newly determined sequences are routinely compared against large sequence databases, and inferences about structure and function are frequently based on sequence similarity. Predicted growth of sequence databases and the advent of large-scale DNA sequencing projects have prompted increased interest in better methods for comparing protein and DNA sequences. As a result, several rapid biological sequence comparison algorithms (Pearson & Lipman, 1988;Altschul et al., 1990) have become used widely, and there has been considerable discussion of the best scoring parameters for sequence comparison algorithms (Collins et al

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“…Thus, discordant results for microarray elements having the same annotation (i.e., XChipID) are best resolved by a rigorous BLAST comparison of element sequences with each other and with the target gene sequence. Although a BLAST comparison of each microarray element sequence with the entire sequence database is technically daunting, a simple comparison of such a sequence with a target sequence is quite simple using the LALIGN program (part of the FASTA package; ftp://ftp.virginia.edu/ pub/fasta/) (Chao et al 1992) and could be automated as a quality control check for the annotation of the entire microarray.…”

Section: Discussionmentioning

confidence: 99%

Annotation and cross-indexing of array elements on multiple platforms.

Mattes

2004

Environ Health Perspect

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On the surface, transcript profiling using microarrays seems to offer a way of looking at the global response of the cell to perturbation, with a focus on changes in gene expression. The difficulty, however, is that the response of a particular gene is actually measured on the array by an element that is a short, defined nucleic acid sequence. Sequences that map back to the same genetic locus may actually be given different names and descriptions when they are deposited in public sequence databases; when such sequences are used in microarray construction, elements that monitor the same genetic locus may have different names and descriptions. The algorithm described here uses a hierarchical approach to assign a single best annotation to the elements in a given microarray in such a fashion that elements from one microarray platform may be cross-indexed with those of another. The algorithm relies on the nucleic acid accession number for a given array element, and uses that to retrieve annotation from the most recent versions of LocusLink and UniGene. Both database resources are searched, with a priority being given to annotation derived from the curated LocusLink database. In lieu of annotation found in these databases, the default GenBank annotation is used. As a final outcome, a cross-chip identifier is generated that may be used to cross-index array elements. The program is available as a practical extraction and report language (Perl) script that can run under any Perl interpreter.

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Aligning two sequences within a specified diagonal band

Cited by 122 publications

References 23 publications

A Root-Expressed l-Phenylalanine:4-Hydroxyphenylpyruvate Aminotransferase Is Required for Tropane Alkaloid Biosynthesis in Atropa belladonna

A Root-Expressed l-Phenylalanine:4-Hydroxyphenylpyruvate Aminotransferase Is Required for Tropane Alkaloid Biosynthesis in Atropa belladonna

Comparison of methods for searching protein sequence databases

Annotation and cross-indexing of array elements on multiple platforms.

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