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Burkhard Morgenstern

Publications and source records attributed to Burkhard Morgenstern.

25 records · Page 2Linked to original sources

Fast and sensitive multiple alignment of large genomic sequences.

BACKGROUND: Genomic sequence alignment is a powerful method for genome analysis and annotation, as alignments are routinely used to identify functional sites such as genes or regulatory elements. With a growing number of partially or completely sequenced genomes, multiple alignment is playing an increasingly important role in these studies. In recent years, various tools for pair-wise and multiple genomic alignment have been proposed. Some of them are extremely fast, but often efficiency is achieved at the expense of sensitivity. One way of combining speed and sensitivity is to use an anchored-alignment approach. In a first step, a fast search program identifies a chain of strong local sequence similarities. In a second step, regions between these anchor points are aligned using a slower but more accurate method. RESULTS: Herein, we present CHAOS, a novel algorithm for rapid identification of chains of local pair-wise sequence similarities. Local alignments calculated by CHAOS are used as anchor points to improve the running time of DIALIGN, a slow but sensitive multiple-alignment tool. We show that this way, the running time of DIALIGN can be reduced by more than 95% for BAC-sized and longer sequences, without affecting the quality of the resulting alignments. We apply our approach to a set of five genomic sequences around the stem-cell-leukemia (SCL) gene and demonstrate that exons and small regulatory elements can be identified by our multiple-alignment procedure. CONCLUSION: We conclude that the novel CHAOS local alignment tool is an effective way to significantly speed up global alignment tools such as DIALIGN without reducing the alignment quality. We likewise demonstrate that the DIALIGN/CHAOS combination is able to accurately align short regulatory sequences in distant orthologues.

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AGenDA: homology-based gene prediction.

We present a www server for homology-based gene prediction. The user enters a pair of evolutionary related genomic sequences, for example from human and mouse. Our software system uses CHAOS and DIALIGN to calculate an alignment of the input sequences and then searches for conserved splicing signals and start/stop codons around regions of local sequence similarity. This way, candidate exons are identified that are used, in turn, to calculate optimal gene models. The server returns the constructed gene model by email, together with a graphical representation of the underlying genomic alignment.

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AltAVisT: comparing alternative multiple sequence alignments.

UNLABELLED: We introduce a WWW-based tool that is able to compare two alternative multiple alignments of a given sequence set. Regions where both alignments coincide are color-coded to visualize the local agreement between the two alignments and to identify those regions that can be considered to be reliably aligned. AVAILABILITY: http://bibiserv.techfak.uni-bielefeld.de/altavist/.

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Divide-and-conquer multiple alignment with segment-based constraints.

A large number of methods for multiple sequence alignment are currently available. Recent benchmarking tests demonstrated that strengths and drawbacks of these methods differ substantially. Global strategies can be outperformed by approaches based on local similarities and vice versa, depending on the characteristics of the input sequences. In recent years, mixed approaches that include both global and local features have shown promising results. Herein, we introduce a new algorithm for multiple sequence alignment that integrates the global divide-and-conquer approach with the local segment-based approach, thereby combining the strengths of those two strategies.

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Exon discovery by genomic sequence alignment.

MOTIVATION: During evolution, functional regions in genomic sequences tend to be more highly conserved than randomly mutating 'junk DNA' so local sequence similarity often indicates biological functionality. This fact can be used to identify functional elements in large eukaryotic DNA sequences by cross-species sequence comparison. In recent years, several gene-prediction methods have been proposed that work by comparing anonymous genomic sequences, for example from human and mouse. The main advantage of these methods is that they are based on simple and generally applicable measures of (local) sequence similarity; unlike standard gene-finding approaches they do not depend on species-specific training data or on the presence of cognate genes in data bases. As all comparative sequence-analysis methods, the new comparative gene-finding approaches critically rely on the quality of the underlying sequence alignments. RESULTS: Herein, we describe a new implementation of the sequence-alignment program DIALIGN that has been developed for alignment of large genomic sequences. We compare our method to the alignment programs PipMaker, WABA and BLAST and we show that local similarities identified by these programs are highly correlated to protein-coding regions. In our test runs, PipMaker was the most sensitive method while DIALIGN was most specific. AVAILABILITY: The program is downloadable from the DIALIGN home page at http://bibiserv.techfak.uni-bielefeld.de/dialign/.

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AGenDA: gene prediction by comparative sequence analysis.

UNLABELLED: Comparative sequence analysis is a powerful approach to identify functional elements in genomic sequences. Herein, we describe AGenDA (Alignment-based GENe Detection Algorithm), a novel method for gene prediction that is based on long-range alignment of syntenic regions in eukaryotic genome sequences. Local sequence homologies identified by the DIALIGN program are searched for conserved splice signals to define potential protein-coding exons; these candidate exons are then used to assemble complete gene structures. The performance of our method was tested on a set of 105 human-mouse sequence pairs. These test runs showed that sensitivity and specificity of AGenDA are comparable with the best gene- prediction program that is currently available. However, since our method is based on a completely different type of input information, it can detect genes that are not detectable by standard methods and vice versa. Thus, our approach seems to be a useful addition to existing gene-prediction programs. AVAILABILITY: DIALIGN is available through the Bielefeld Bioinformatics Server (BiBiServ) at http://bibiserv.techfak.uni-bielefeld.de/dialign/ The gene-prediction program AGenDA described in this paper will be available through the BiBiServ or MIPS web server at http://mips.gsf.de.

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Fast and sensitive alignment of large genomic sequences.

Comparative analysis of syntenic genome sequences can be used to identify functional sites such as exons and regulatory elements. Here, the first step is to align two or several evolutionary related sequences and, in recent years, a number of computer programs have been developed for alignment of large genomic sequences. Some of these programs are extremely fast but often time-efficiency is achieved at the expense of sensitivity. One way of combining speed and sensitivity is to use an anchored-alignment approach. In a first step, a fast heuristic identifies a chain of strong sequence similarities that serve as anchor points. In a second step, regions between these anchor points are aligned using a slower but more sensitive method. We present CHAOS, a novel algorithm for rapid identification of chains of local sequence similarities among large genomic sequences. Similarities identified by CHAOS are used as anchor points to improve the running time of the DIALIGN alignment program. Systematic test runs show that this method can reduce the running time of DIALIGN by more than 93% while affecting the quality of the resulting alignments by only 1%. The source code for CHAOS is available at http://www.stanford.edu/~brudno/chaos/ An integrated program package containing CHAOS and DIALIGN is available at http://bibiserv.techfak.uni-bielefeld.de/dialign/

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