Biomedical subjects

Michael Brudno

Publications and source records attributed to Michael Brudno.

11 recordsLinked to original sources

PubMed2005

ProbCons: Probabilistic consistency-based multiple sequence alignment.

To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.

Algorithms↗

PubMed2004

The CHAOS/DIALIGN WWW server for multiple alignment of genomic sequences.

Cross-species sequence comparison is a powerful approach to analyze functional sites in genomic sequences and many discoveries have been made based on genomic alignments. Herein, we present a WWW-based software system for multiple alignment of large genomic sequences. Our server utilizes the previously developed combination of CHAOS and DIALIGN to achieve both speed and alignment accuracy. CHAOS is a fast database search tool that creates a list of local sequence similarities. These are used by DIALIGN as anchor points to speed up the final alignment procedure. The resulting alignment is returned to the user in different formats together with a list of anchor points found by CHAOS. The CHAOS/DIALIGN software is freely available at http://dialign.gobics.de/chaos-dialign-submission.

Genomics↗

PubMed2004

Phylo-VISTA: interactive visualization of multiple DNA sequence alignments.

MOTIVATION: The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. RESULTS: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a framework based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. AVAILABILITY: Phylo-VISTA is available at http://www-gsd.lbl.gov/phylovista. It requires an Internet browser with Java Plug-in 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu

Algorithms↗

PubMed2004

Characterization of evolutionary rates and constraints in three Mammalian genomes.

We present an analysis of rates and patterns of microevolutionary phenomena that have shaped the human, mouse, and rat genomes since their last common ancestor. We find evidence for a shift in the mutational spectrum between the mouse and rat lineages, with the net effect being a relative increase in GC content in the rat genome. Our estimate for the neutral point substitution rate separating the two rodents is 0.196 substitutions per site, and 0.65 substitutions per site for the tree relating all three mammals. Small insertions and deletions of 1-10 bp in length ("microindels") occur at approximately 5% of the point substitution rate. Inferred regional correlations in evolutionary rates between lineages and between types of sites support the idea that rates of evolution are influenced by local genomic or cell biological context. No substantial correlations between rates of point substitutions and rates of microindels are found, however, implying that the influences that affect these processes are distinct. Finally, we have identified those regions in the human genome that are evolving slowly, which are likely to include functional elements important to human biology. At least 5% of the human genome is under substantial constraint, most of which is noncoding.

Animals↗

PubMed2004

Automated whole-genome multiple alignment of rat, mouse, and human.

We have built a whole-genome multiple alignment of the three currently available mammalian genomes using a fully automated pipeline that combines the local/global approach of the Berkeley Genome Pipeline and the LAGAN program. The strategy is based on progressive alignment and consists of two main steps: (1) alignment of the mouse and rat genomes, and (2) alignment of human to either the mouse-rat alignments from step 1, or the remaining unaligned mouse and rat sequences. The resulting alignments demonstrate high sensitivity, with 87% of all human gene-coding areas aligned in both mouse and rat. The specificity is also high: <7% of the rat contigs are aligned to multiple places in human, and 97% of all alignments with human sequence >100 kb agree with a three-way synteny map built independently, using predicted exons in the three genomes. At the nucleotide level <1% of the rat nucleotides are mapped to multiple places in the human sequence in the alignment, and 96.5% of human nucleotides within all alignments agree with the synteny map. The alignments are publicly available online, with visualization through the novel Multi-VISTA browser that we also present.

Animals↗

PubMed2003

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.

Algorithms↗

PubMed2003

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.

Algorithms↗

PubMed2003

LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA.

To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. We present LAGAN, a system for rapid global alignment of two homologous genomic sequences, and Multi-LAGAN, a system for multiple global alignment of genomic sequences. We tested our systems on a data set consisting of greater than 12 Mb of high-quality sequence from 12 vertebrate species. All the sequence was derived from the genomic region orthologous to an approximately 1.5-Mb region on human chromosome 7q31.3. We found that both LAGAN and Multi-LAGAN compare favorably with other leading alignment methods in correctly aligning protein-coding exons, especially between distant homologs such as human and chicken, or human and fugu. Multi-LAGAN produced the most accurate alignments, while requiring just 75 minutes on a personal computer to obtain the multiple alignment of all 12 sequences. Multi-LAGAN is a practical method for generating multiple alignments of long genomic sequences at any evolutionary distance. Our systems are publicly available at http://lagan.stanford.edu.

Animals↗

PubMed2003

Glocal alignment: finding rearrangements during alignment.

MOTIVATION: To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, where all locations of similarity between the two strings are returned. Global alignments are less prone to demonstrating false homology as each letter of one sequence is constrained to being aligned to only one letter of the other. Local alignments, on the other hand, can cope with rearrangements between non-syntenic, orthologous sequences by identifying similar regions in sequences; this, however, comes at the expense of a higher false positive rate due to the inability of local aligners to take into account overall conservation maps. RESULTS: In this paper we introduce the notion of glocal alignment, a combination of global and local methods, where one creates a map that transforms one sequence into the other while allowing for rearrangement events. We present Shuffle-LAGAN, a glocal alignment algorithm that is based on the CHAOS local alignment algorithm and the LAGAN global aligner, and is able to align long genomic sequences. To test Shuffle-LAGAN we split the mouse genome into BAC-sized pieces, and aligned these pieces to the human genome. We demonstrate that Shuffle-LAGAN compares favorably in terms of sensitivity and specificity with standard local and global aligners. From the alignments we conclude that about 9% of human/mouse homology may be attributed to small rearrangements, 63% of which are duplications.

Algorithms↗

PubMed2003

Quantitative estimates of sequence divergence for comparative analyses of mammalian genomes.

Comparative sequence analyses on a collection of carefully chosen mammalian genomes could facilitate identification of functional elements within the human genome and allow quantification of evolutionary constraint at the single nucleotide level. High-resolution quantification would be informative for determining the distribution of important positions within functional elements and for evaluating the relative importance of nucleotide sites that carry single nucleotide polymorphisms (SNPs). Because the level of resolution in comparative sequence analyses is a direct function of sequence diversity, we propose that the information content of a candidate mammalian genome be defined as the sequence divergence it would add relative to already-sequenced genomes. We show that reliable estimates of genomic sequence divergence can be obtained from small genomic regions. On the basis of a multiple sequence alignment of approximately 1.4 megabases each from eight mammals, we generate such estimates for five unsequenced mammals. Estimates of the neutral divergence in these data suggest that a small number of diverse mammalian genomes in addition to human, mouse, and rat would allow single nucleotide resolution in comparative sequence analyses.

Animals↗

PubMed2002

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/

Algorithms↗