Identification and Characterization of Multi-Species Conserved Sequences

A key component of genomics research beyond the Human Genome Project will be the rigorous interpretation of the recently finished human genome sequence (Collins et al. 2003). Central to these efforts will be the identification of all functional elements in the human genome. Recent comparative analyses of the human and mouse genome sequences suggest that ∼5% of the mammalian genome is under active selection and thus likely serves a functional role (International Mouse Genome Sequencing Consortium 2002; Roskin et al. 2003). Within this functional subset is an estimated 1% to 2% of the genome that encodes protein (International Mouse Genome Sequencing Consortium 2002). The prospects for comprehensive identification of these coding sequences are quite good, especially in light of the availability of data sets that are complementary to the genomic sequence (e.g., ESTs [Boguski et al. 1994; also see http://www.ncbi.nlm.nih.gov/dbEST] and full-length cDNA sequences [Strausberg et al. 2002; also see http://mgc.nci.nih.gov]) and ever-improving computational methods for gene prediction (Kulp et al. 1996; Burge and Karlin 1997; Rogic et al. 2001; Solovyev 2001; Flicek et al. 2003). The complete identification and characterization of the remaining 3% to 4% of the mammalian genome that likely corresponds to functional non-coding sequence will be profoundly more challenging, due to the lack of complementary data sets, the absence of robust tools for computational predictions, and the incomplete insight about the nature of such sequence. In short, the generation of a comprehensive “parts list” of functional elements in the human genome remains an immense and important challenge. The comparison of orthologous genomic sequences has emerged as a powerful approach for identifying functional elements in the genome (Dermitzakis et al. 2002; DeSilva et al. 2002). The premise of this approach is that sequences conserved across millions of years of evolution are likely to have a functional role (Pennacchio and Rubin 2001). Comparative sequence analyses have been shown to facilitate the identification of both coding (Batzoglou et al. 2000; Korf et al. 2001; Pennacchio et al. 2001; Alexandersson et al. 2003; Flicek et al. 2003) and functional non-coding (Stojanovic et al. 1999; Dubchak et al. 2000; Gottgens et al. 2000; Loots et al. 2000, 2002; Wasserman et al. 2000; Dehal et al. 2001; Elnitski et al. 2003; Kellis et al. 2003) sequences. Among the latter are elements that regulate the spatial and temporal patterns of gene expression (Hardison 2000). When the generation of alignments between related sequences is not possible, motif-finding techniques have also been used to identify functional sequences, in particular for detecting transcription factor–binding sites (Bailey and Elkan 1995; Roth et al. 1998; Hertz and Stormo 1999; McCue et al. 2001; Blanchette and Tompa 2002). Recent efforts have produced whole-genome sequences for several vertebrates, including human (International Human Genome Sequencing Consortium 2001), mouse (International Mouse Genome Sequencing Consortium 2002), rat (http://genome.ucsc.edu/cgi-bin/hgGateway?org=rat), and pufferfish (Aparicio et al. 2002), with the sequencing of additional vertebrate genomes well underway. Increasingly, methods for visualizing (Kent et al. 2002; Clamp et al. 2003; Karolchik et al. 2003) and comparing (Stojanovic et al. 1999; Mayor et al. 2000; Blanchette and Tompa 2002; Loots et al. 2002; Giardine et al. 2003; Schwartz et al. 2003a) genomic sequences from multiple species are emerging. As a complement to these efforts, we are generating the sequence of targeted genomic regions in multiple, phylogenetically diverse vertebrates (Thomas et al. 2003) and developing computational approaches for identifying the subset of sequences that confers function. In particular, we have focused on developing algorithms for detecting sequences that are highly conserved across multiple species, which we call Multi-species Conserved Sequences (or MCSs); such sequences represent candidates for being functionally important. Here we report the development and testing of methods for MCS detection, including analyses of MCSs identified using a recently generated set of orthologous sequences from 11 non-human vertebrates (Thomas et al. 2003).