Human and mouse gene structure: comparative analysis and application to exon prediction

By Serafim Batzoglou, Lior S. Pachter, Jill P. Mesirov, Bonnie Berger, Eric S. Lander. Annual International Conference on Research in Computational Molecular Biology, 2000

427 citations recorded by the source corpus.

We describe a novel analytical approach to gene recognition based on cross-species comparison We first undertook a comparison of orthologous genomic look from human and mouse, studying the extent of similarity in the number, size and sequence of exons and introns We then developed an approach for recognizing genes within such orthologous regions, by first aligning the regions using an iterative global alignment system and then identifying genes based on conservation of exonic features at aligned positions in both species The alignment and gene recognition are performed by new programs called GLASS and ROSETTA, respectively ROSETTA performed well at exact identification of coding exons in 117 orthologous pairs tested.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/332ee4783b91b9faa089e031f8f921a515f3f42a

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In Molecular Biology

Citations in the corpus

Identification of a novel cis-regulatory element involved in the heat shock response in Caenorhabditis elegans using microarray gene expression and computational methods. (2002, methodology): “3D) using the GLASS alignment algorithm originally developed for comparisons between human and rodent sequences (Batzoglou et al. 2000).”
Efficient large-scale sequence comparison by locality-sensitive hashing (2001, methodology): “Exact matches also provide the basic features used to construct fast global alignments between long sequences in tools such as MUMmer (Delcher et al., 1999) and GLASS (Batzoglou et al., 2000).”
Gene structure prediction and alternative splicing analysis using genomically aligned ESTs. (2001, background): “Using preselected sets of orthologous gene pairs, several studies have shown that comparing human and mouse genomic sequences is highly effective in predicting gene structures (Batzoglou et al. 2000; Bafna and Huson 2000).”
Identification of conserved regulatory elements by comparative genome analysis (2003, methodology): “In particular, new algorithms based on phylogenetic footprinting have been presented for the alignment of genomic sequences, data visualization and the identification of exons [8,9].”
Integrating genomic homology into gene structure prediction (2001, methodology): “The performance of ROSETTA, CEM, and many other gene-prediction programs has not been evaluated on HTG sequences either because their algorithms assume the input sequence contains exactly one gene or because the authors chose not to evaluate them in this way.”
Enredo and Pecan: genome-wide mammalian consistency-based multiple alignment with paralogs. (2008, background): “…yj (i.e., that position xi must precede or be aligned to position yj in the final alignment), and similarly xi < yj (i.e., that position xi must precede position yj) can be thought of as specialized types of banded alignment algorithm (Chao et al. 1993; Delcher et al. 1999; Batzoglou et al. 2000).”
VISTA : visualizing global DNA sequence alignments of arbitrary length (2000, methodology): “Comparative sequence analysis has enabled identification of regulatory non-coding regions (Loots et al., 2000; Dubchak et al., 2000), and location of coding exons (Batzoglou et al., 2000) using purely computational means.”
Current methods of gene prediction, their strengths and weaknesses. (2002, background): “ROSETTA makes ) (http://bioinformatics.iastate.edu/cgi-bin/gs.cgi) Arabidopsis, maize, generic plant dbEST or EST database”
Noncoding RNA gene detection using comparative sequence analysis (2001, methodology): “The coding model is a fully probabilistic formalization of comparative analysis ideas used by the genefinder CRITICA [16], and by comparative exon finding approaches such as the EXOFISH vertebrate/ Tetraodon comparison [38] and the human/mouse comparison in[39].”
Mauve: multiple alignment of conserved genomic sequence with rearrangements. (2004, methodology): “Alignment tools such as MUMmer, GLASS, AVID, and WABA align pairs of long sequences, implementing various methods to discover local alignments (Delcher et al. 1999; Batzoglou et al. 2000; Kent and Zahler 2000; Morgenstern 2000; Bray et al. 2003).”
AUGUSTUS: ab initio prediction of alternative transcripts (2006, methodology): “Compared to more traditional approaches, gene-ﬁnding methods based on genomic sequence alignments have a considerable advantage since they do not depend on EST or protein sequences or statistical models of gene structures (10–13).”