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Biomedical subjects

Inna Dubchak

Publications and source records attributed to Inna Dubchak.

9 recordsLinked to original sources
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

Cross-species sequence comparisons: a review of methods and available resources.

With the availability of whole-genome sequences for an increasing number of species, we are now faced with the challenge of decoding the information contained within these DNA sequences. Comparative analysis of DNA sequences from multiple species at varying evolutionary distances is a powerful approach for identifying coding and functional noncoding sequences, as well as sequences that are unique for a given organism. In this review, we outline the strategy for choosing DNA sequences from different species for comparative analyses and describe the methods used and the resources publicly available for these studies.

Animals↗
PubMed2003

Strategies and tools for whole-genome alignments.

The availability of the assembled mouse genome makes possible, for the first time, an alignment and comparison of two large vertebrate genomes. We investigated different strategies of alignment for the subsequent analysis of conservation of genomes that are effective for assemblies of different quality. These strategies were applied to the comparison of the working draft of the human genome with the Mouse Genome Sequencing Consortium assembly, as well as other intermediate mouse assemblies. Our methods are fast and the resulting alignments exhibit a high degree of sensitivity, covering more than 90% of known coding exons in the human genome. We obtained such coverage while preserving specificity. With a view towards the end user, we developed a suite of tools and Web sites for automatically aligning and subsequently browsing and working with whole-genome comparisons. We describe the use of these tools to identify conserved non-coding regions between the human and mouse genomes, some of which have not been identified by other methods.

Algorithms↗
PubMed2003

AVID: A global alignment program.

In this paper we describe a new global alignment method called AVID. The method is designed to be fast, memory efficient, and practical for sequence alignments of large genomic regions up to megabases long. We present numerous applications of the method, ranging from the comparison of assemblies to alignment of large syntenic genomic regions and whole genome human/mouse alignments. We have also performed a quantitative comparison of AVID with other popular alignment tools. To this end, we have established a format for the representation of alignments and methods for their comparison. These formats and methods should be useful for future studies. The tools we have developed for the alignment comparisons, as well as the AVID program, are publicly available. See Web Site References section for AVID Web address and Web addresses for other programs discussed in this paper.

Algorithms↗
PubMed2002

Initial sequencing and comparative analysis of the mouse genome.

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

Animals↗
PubMed2002

Comparative genomics approaches to study organism similarities and differences.

Comparative genomics is a large-scale, holistic approach that compares two or more genomes to discover the similarities and differences between the genomes and to study the biology of the individual genomes. Comparative studies can be performed at different levels of the genomes to obtain multiple perspectives about the organisms. We discuss in detail the type of analyses that offer significant biological insights in the comparisons of (1) genome structure including overall genome statistics, repeats, genome rearrangement at both DNA and gene level, synteny, and breakpoints; (2) coding regions including gene content, protein content, orthologs, and paralogs; and (3) noncoding regions including the prediction of regulatory elements. We also briefly review the currently available computational tools in comparative genomics such as algorithms for genome-scale sequence alignment, gene identification, and nonhomology-based function prediction.

Animals↗
PubMed2002

The computational challenges of applying comparative-based computational methods to whole genomes.

The explosion in genomic sequence available in public databases has resulted in an unprecedented opportunity for computational whole genome analyses. A number of promising comparative-based approaches have been developed for gene finding, regulatory element discovery and other purposes, and it is clear that these tools will play a fundamental role in analysing the enormous amount of new data that is currently being generated. The synthesis of computationally intensive comparative computational approaches with the requirement for whole genome analysis represents both an unprecedented challenge and opportunity for computational scientists. We focus on a few of these challenges, using by way of example the problems of alignment, gene finding and regulatory element discovery, and discuss the issues that have arisen in attempts to solve these problems in the context of whole genome analysis pipelines.

Computational Biology↗
PubMed2002

rVista for comparative sequence-based discovery of functional transcription factor binding sites.

Identifying transcriptional regulatory elements represents a significant challenge in annotating the genomes of higher vertebrates. We have developed a computational tool, rVista, for high-throughput discovery of cis-regulatory elements that combines clustering of predicted transcription factor binding sites (TFBSs) and the analysis of interspecies sequence conservation to maximize the identification of functional sites. To assess the ability of rVista to discover true positive TFBSs while minimizing the prediction of false positives, we analyzed the distribution of several TFBSs across 1 Mb of the well-annotated cytokine gene cluster (Hs5q31; Mm11). Because a large number of AP-1, NFAT, and GATA-3 sites have been experimentally identified in this interval, we focused our analysis on the distribution of all binding sites specific for these transcription factors. The exploitation of the orthologous human-mouse dataset resulted in the elimination of > 95% of the approximately 58,000 binding sites predicted on analysis of the human sequence alone, whereas it identified 88% of the experimentally verified binding sites in this region.

Animals↗