comparative genomic tools and databases: providing...

The increasing availability of genomic sequence frommultiple organisms has provided biomedical scientistswith a large dataset for orthologous-sequence compar-isons. The rationale for using cross-species sequencecomparisons to identify biologically active regions of agenome is based on the observation that sequences thatperform important functions are frequently conservedbetween evolutionarily distant species, distinguishingthem from nonfunctional surrounding sequences. Thisis most readily apparent for protein-encoding sequencesbut also holds true for the sequences involved in the reg-ulation of gene expression. While these observationshave frequently been made retrospectively following theanalysis of previously discovered genes or gene-regula-tory sequences, examination of orthologous genomicsequences from several vertebrates has shown that theinverse is also true. Specifically, studying evolutionarilyconserved sequences is a reliable strategy to uncoverregions of the human genome with biological activity.To assist biomedical investigators in taking advantage ofthis new paradigm, various comparative sequence-basedvisualization tools and databases have been developed.Already, these new publicly accessible resources havebeen successfully exploited by investigators for the dis-covery of biomedically important new genes andsequences involved in gene regulation.

Comparative genomic visualization toolsThe two most commonly used comparative genomictools are Visualization Tool for Alignment (VISTA) andPercent Identity Plot Maker (PipMaker) (1, 2). The pri-mary goal of both programs is to turn raw ortholo-gous-sequence data from multiple species into visuallyinterpretable plots to drive biological experimentation.Some of their common features include the ability tocompare multiple megabases of sequence simultane-ously from two or more species, web accessibility, andthe option to customize numerous features by the user.While each program uses different overall strategies,they both allow for the identification of conserved cod-ing as well as noncoding sequences between species.

VISTA combines a global-alignment program (AVID)(3) with a running-plot graphical tool to display thealignment (1) (http://www-gsd.lbl.gov/vista/). Globalalignments are produced when two DNA sequences arecompared and an optimal similarity score is deter-mined over the entire length of the two sequences (Fig-ure 1). In contrast, PipMaker uses BLASTZ, a modifiedlocal-alignment program, and displays plots with solid horizontal lines to indicate ungapped regions of conserved sequence (i.e., blocks of alignments that lack insertions or deletions) (http://bio.cse.psu.edu/pipmaker/) (2). Local alignments are generated whentwo DNA sequences are compared and optimal simi-larity scores are determined over numerous subregionsalong the length of the two sequences (Figure 1).

For visual comparison of the VISTA and PipMakeroutputs, orthologous ApoE genomic sequence fromhumans and chimpanzees was independently exam-ined by web-based versions of each program (Figure 2,a and b; and Table 1). In both cases, DNA sequences inFASTA format were submitted to web-based serversalong with an annotation file of the location of exonsand repeat sequences. In general, both programs pro-vide similar interpretation of the input sequence files;namely, high levels of sequence homology are notedbetween both of these closely related primate species.In this example, known functional regions (exons andgene-regulatory elements) in the interval cannot bereadily identified based on conservation because of lackof divergence time between humans and chimpanzees.As a second example, similar human versus mouseApoE genomic-sequence comparisons were performedby both VISTA and PipMaker (Figure 2, c and d). Com-parison of these more distantly related mammalsrevealed conserved sequences corresponding to previ-ously defined functional elements. These include exon-ic sequences that display high levels of homologybetween humans and mice as well as two experimen-tally defined ApoE enhancers (Figure 2, c and d) (4–6).Additional conservation is noted upstream of exon 1within the putative proximal promoter.

The Journal of Clinical Investigation | April 2003 | Volume 111 | Number 8 1099

Comparative genomic tools and databases: providing insights into the human genome

Len A. Pennacchio and Edward M. RubinGenome Sciences Department, Lawrence Berkeley NationalLaboratory, Berkeley, California, USAJoint Genome Institute, Walnut Creek, California, USA

J. Clin. Invest. 111:1099–1106 (2003). doi:10.1172/JCI200317842.

SPOTLIGHT

Address correspondence to: Len Pennacchio, Genome SciencesDepartment, MS 84-171, Lawrence Berkeley National Laboratory,One Cyclotron Road, Berkeley, California 94720, USA. Phone: (510) 486-7498; Fax: (510) 486-4229; E-mail: [email protected] of interest: The authors have declared that no conflict ofinterest exists.Nonstandard abbreviations used: Visualization Tool forAlignment (VISTA); Percent Identity Plot Maker (PipMaker);National Center for Biotechnology Information (NCBI); Universi-ty of California at Santa Cruz (UCSC); Sequence Search andAlignment by Hashing Algorithm (SSAHA); conserved noncodingsequence 1 (CNS1); stem cell leukemia (SCL).

These examples emphasize the importance of identify-ing the proper evolutionary distance for sequence com-parisons to provide the correct window for identifyingconserved sequences with functionality. For instance,human/chimpanzee comparison of the ApoE interval wasnot informative, while human/mouse comparison iden-tified functional coding and noncoding sequences in thisinterval. While in this case primate/rodent comparisonwas informative, no two mammalian species provide theideal distance for sequence comparison when the entiregenome is examined, since different regions of the mam-malian genome have evolved at significantly differentrates (7–12). Thus, evolutionary distances must be varieddepending on the genomic interval being studied and thebiological question being investigated.

A useful characteristic of PipMaker is the linear con-tiguity of blocks (lines) that represent conserved ele-ments with ungapped sequence alignments (i.e.,

blocks of alignments that lack insertions or deletions).This feature can aid in distinguishing coding sequencethat is less flexible to insertions and/or deletions com-pared with functional noncoding DNA. In Figure 2c,note the linear blocks of alignments that appearbeneath ApoE exons but not beneath regulatorysequences. A useful aspect of VISTA is the easily inter-pretable peaklike features depicting conserved DNAsequences. For instance, peaks of conservation arereadily apparent beneath exons and gene-regulatorysequences (Figure 2d). While these peak features donot enable clear demarcation of exons boundaries,they allow the user to easily identify candidate gene-regulatory elements as well as evolutionarily conservedcoding domains. Regardless of these differences in thealignment technique and display, both programs pro-vide biomedical scientists with an easily accessibleentry point to visualize comparative sequence data forregions of conservation (and putative function) sur-rounding a gene or genomic interval of interest. WhileVISTA and PipMaker are the most commonly usedvisualization packages, several additional tools forcomparative genomic alignments with plotlike out-puts are also available (13–16).

Whole-genome browsersIn the preceding section, computational tools forgene-by-gene (or region-by-region) analyses weredescribed. These original tools sought to providebiologists with user-defined features for custom,small-scale analysis, frequently from sequence gener-ated in individual laboratories that was manuallyinput into the VISTA or PipMaker web server. Therecent public availability of large amounts of whole-genome sequence for numerous organisms (human,

1100 The Journal of Clinical Investigation | April 2003 | Volume 111 | Number 8

Figure 1Comparison of local- and global-alignment algorithm strategies. Top:Global alignments are generated when two DNA sequences (A and B) arecompared and an optimal similarity score is determined over the entirelength of the two sequences. Bottom: Local alignments are producedwhen two DNA sequences (A and B) are compared and optimal similar-ity scores are determined over numerous subregions along the length ofthe two sequences. The local-alignment algorithm works by first findingvery short common segments between the input sequences (A and B),and then expanding out the matching regions as far as possible.

Figure 2Human/chimpanzee and human/mouse ApoE genomic-sequence com-parisons. (a) PipMaker analysis with human sequence depicted on thehorizontal axis and percentage similarity to chimpanzee on the verticalaxis. Exons are indicated by black boxes and repetitive elements by trian-gles above the plot. Each PIP horizontal bar indicates regions of similar-ity based on the percent identity of each gap-free segment in the align-ment. Once a gap (insertion or deletion) is found within the alignment,a new bar is created to display the adjacent correspondent gap-free seg-ment. (b) VISTA analysis with human sequence shown on the x axis andpercentage similarity to chimpanzee on the y axis. The graphical plot isbased on sliding-window analysis of the underlying genomic alignment.In this illustration, a 100-bp window is used that slides at 40-bpnucleotide increments. Blue and pink shading indicate conserved codingand noncoding DNA, respectively. Green and yellow bars immediatelyabove the VISTA plot correspond to various repetitive DNA elements. (c)PipMaker analysis with human sequence depicted on the horizontal axisand percentage similarity to mouse on the vertical axis. (d) VISTA analy-sis with human sequence shown on the x axis and percentage similarityto mouse on the y axis. Two experimentally defined enhancers are indi-cated on each of the plots (4–6).

mouse, rat, fugu, tetraodon, ciona, etc.) has enabledlarge-scale analysis of individual genomes as well asgenome-to-genome comparisons. These whole-genome analyses, accessible through web-basedbrowsers, provide preprocessed databases for the sci-entific community (17–21).

Annotation browsersThe completion of a draft sequence and assembly ofthe human genome was an enormous accomplishmentand provided a vast sequence dataset readily accessibleto biomedical investigators. While these sequence datawere initially useful for researchers seeking additionalgenomic sequence for individual genes of interest basedon homology searches, the original assembly was sim-ply a large database composed of strings of A’s, C’s, T’s,and G’s that lacked reference to and descriptions of keylandmarks. Fortunately, this void has rapidly beenfilled by the success of large computational projectsfocused on the detailed annotation of the humangenome. Today, three large centers provide human-genome annotation: the National Center for Biotech-nology Information (NCBI), the University of California

at Santa Cruz (UCSC), and the Sanger Center.These annotation outputs are all web-accessi-ble and are known as NCBI Map Viewer, UCSCGenome Browser (22), and Ensembl (23),respectively (Table 1). In addition to exon anno-tation across the entire genome, these browserscontain a tremendous amount of additionalannotation for features such as repetitive DNA,expressed-sequence tags, CpG islands, and sin-gle-nucleotide polymorphisms.

Comparative genomic browsersIn addition to gene annotation for the entirehuman genome, online resources have alsorecently become available for whole-human/whole-mouse comparative sequencedata. Several important advances have madewhole-genome comparisons possible. Whole-genome assemblies, in addition to satisfyingthe obvious need for sequence data for a givengenome, have provided the substrates forgenome-to-genome comparisons. Further-

more, the successful whole-genome annotation ofgenes, including their chromosomal location, servesas a reference for the position of a given alignment inthe genome; previous gene-by-gene comparisonsrequired the user to painstakingly input these anno-tation features. For mammals, this gene annotationis most detailed for the human genome, thoughprogress is being made in annotating the puffer fish,mouse, and rat genomes. As a consequence, currentwhole-genome comparisons primarily use the humangenome as the base reference sequence. Three majorresources are currently available for preprocessedhuman/mouse whole-genome comparisons: UCSCGenome Browser, VISTA Genome Browser, and Pip-Maker (Table 1).

The UCSC Genome Browser has recently integratedcomparative sequence information for annotation of thehuman genome. Similar to this browser’s other annota-tion fields, comparative genomic information is pre-sented as “tracks.” To illustrate the UCSC GenomeBrowser’s comparative genomic analysis, several tracksfor the human/mouse ApoE interval are shown (Figure3). These comparative data are presented in two formats.


Table 1Comparative genomic websites for various computational tools and databases

Comparative genomic visualization tools Websites

VISTA http://www-gsd.lbl.gov/vista/PipMaker http://bio.cse.psu.edu/pipmaker/

Whole-genome annotation browsers

NCBI Map Viewer http://www.ncbi.nlm.nih.govUCSC Genome Browser http://genome.ucsc.edu/Ensembl http://www.ensembl.org/

Whole-genome comparative genomic browsers

UCSC Genome Browser http://genome.ucsc.edu/VISTA Genome Browser http://pipeline.lbl.gov/PipMaker http://bio.cse.psu.edu/genome/hummus/

Custom comparisons to whole genomes

GenomeVista (AVID) http://pipeline.lbl.gov/cgi-bin/GenomeVistaUCSC Genome Browser (BLAT) http://genome.ucsc.edu/ENSEMBL (SSAHA) http://www.ensembl.org/NCBI (BLAST) http://www.ncbi.nlm.nih.gov/blast/

Figure 3UCSC Genome Browser output for human/mouse sequence comparison of the ApoE gene (22). Human sequence is depicted on the x axis, and thenumbering corresponds to the position of human chromosome 19 based on the UCSC June 2002 freeze (22). Note the different scoring system incontrast to percent identity, with peaks representing L-scores that take into account the context of the level of conservation. Conservation in rela-tively nonconserved regions receives higher L-scores than similar conservation in relatively highly conserved regions. As a second display of conserva-tion, the “best mouse” track uses blocks whose length and shading represent the conservation.

First, a highly conserved sequence track is displayedas blocks whose length and shading indicate the sizeand level of homology between humans and mice(Figure 3, best mouse track). Second, human/mouseconservation data are depicted as a track with run-ning plots displaying “L-scores” to indicate the levelof conservation (Figure 3, mouse cons track). Thepower of this latter scoring system is that conserva-tion is examined in the context of the genomic inter-val (rather than its strict percent identity for a giveninterval). Regions of high conservation in otherwisenonconserved intervals receive higher L-scores thanregions of conservation in relatively highly conservedintervals. The rationale for such a strategy is based onthe fact that neutral rates of DNA sequence changeare highly variable in the mammalian genome (20).Thus, conservation in regions with faster neutral ratesof change is more likely to be functional than conser-vation in slowly evolving intervals.

The VISTA Genome Browser is a complementaryweb-based browser for interactive visualization ofcomparative sequence data using a VISTA plot for-

mat (Table 1). Features include customized defini-tion of the window size of a region under investiga-tion (zoom), tools for extracting DNA sequence froma region of interest, and tables of highly conservedDNA within an interval. The website is also integrat-ed with the UCSC Genome Browser, allowing for aportal to immediately jump from comparativesequence data to more detailed annotation of thehuman genome.

As an example of the VISTA Genome Browser out-put, the human/mouse ApoE genomic interval wasexamined (Figure 4a). This plot was obtained by sub-mission of the gene symbol ApoE at the VISTAGenome Browser website (Table 1). Note the similar-ity between the human/mouse VISTA plot obtainedthrough genome-to-genome comparison and thegene-by-gene analysis shown in Figure 2d. Thisresource instantaneously provides precomputedhuman/mouse data, in contrast to the detailed cus-tom input files required by the standard VISTAanalysis program. Furthermore, this resource allowsfor immediate “zoom-in” and “zoom-out” options to


Figure 4VISTA Genome Browser output for human/mouse sequence comparison of the ApoE gene (1). (a) The same genomic interval found in Figure 3 wasexamined. (b) A twofold “zoom out” was performed on the interval found in a, allowing the neighboring ApoE genes to be determined. Colored barsimmediately above the VISTA plot correspond to various repetitive DNA elements.

characterize the interval in more detail. For instance,by zooming out, one can readily identify neighboringgenes, as well as candidate conserved noncodingsequences that may be important in gene regulationof ApoE (Figure 4b). While these preprocesseddatasets appear to have wide-ranging biomedicalvalue, they have not made the traditional VISTA pro-gram obsolete. The traditional VISTA programremains well suited for custom genome annotationbeyond what is publicly available, for sequence com-parisons besides human/mouse comparisons, and forspecialized user-defined VISTA plots containing non-standard features.

A third set of preprocessed genome data is availablethrough PipMaker (24) (Table 1). In this analysis,human/mouse genomic-alignment plots are providedin a nonbrowser format and are retrievable as a PDF filefor a gene or region of interest.

Efforts are being made to provide preprocessed com-parative data beyond human and mouse. For instance,the VISTA and UCSC Genome Browsers have recentlyadded rat genomic sequence. This allows the exami-nation of human/mouse, human/rat, and mouse/ratcomparative data, providing the opportunity to deter-mine what is shared and what is unique to eachspecies. In the near future, additional vertebrategenome assemblies will become available, and it isexpected that they will be integrated into a similarframework. While significant computational chal-lenges exist with such a complex dataset, more effi-cient algorithms are being developed, and the insightsgained from multiple, simultaneous genome compar-isons are likely to be significant.

Custom comparison to whole genomesIn addition to preprocessed whole-genome compara-tive data, several additional tools allow for anysequence from any organism to be compared with pre-viously assembled and annotated genomes. Theyinclude GenomeVista and a server available throughUCSC Genome Browser (Table 1).

GenomeVista uses the same data sources and algo-rithmic methods as are used to generate the align-ments for the VISTA Genome Browser, but it allowsusers to input their own sequence of interest fordirect comparison with the human, mouse, or ratgenome. One can acquire these sequence files fromin-house sequencing projects, or automaticallyretrieve them from sequence databases such as Gen-Bank by simply inputting the accession number forthe desired sequence at the GenomeVista website.The GenomeVista data output is similar to that ofthe VISTA Genome Browser but allows species otherthan those available in the current alignment to beexamined in the context of the annotated human ormouse genome.

Similar to GenomeVista, the UCSC Genome Brows-er also allows custom sequence comparison with thehuman, mouse, or rat genome assembly (Table 1).This comparison uses BLAT, a modified BLAST align-ment program, and provides an extremely fast homol-ogy search (25, 26). This tool is useful to quickly

determine the mapping location for a sequence ofinterest and the annotation within that interval. Thetool’s speed, however, comes at the cost of reducedalignment sensitivity, and the complementary use ofalternative comparative genomic tools such as VISTAor PipMaker is warranted. Similar fast homologysearches against genomes are available at Ensembland NCBI using the Sequence Search and Alignmentby Hashing Algorithm (SSAHA) (27) and BLAST (25)alignment tools, respectively.

General insights from genomic-sequencecomparisons of humans and miceWith these computational tools and databases, whatearly comparative genomic insights have beenobtained about the human genome? The recent com-pletion of the mouse genome draft sequence led to thesurprising result that approximately 40% of thehuman genome’s 3 billion base pairs could be alignedto the mouse genome at the nucleotide level (20).Using a separate conservation criterion of human/mouse sequences with ≥70% identity over ≥100 bp,more than 1 million independent human/mouse con-served elements could be defined (26). An obviousquestion arising from the identification of all this con-servation is what (if any) is the functional significanceof these conserved sequences?

Currently, the most obvious human genomic func-tional elements that display high levels of conserva-tion across species are exons. This is not unexpectedbased on the known functional importance of theproteins that they encode. In one recent study, initialcomparative data analyses indicate that greater than90% of known human exons are conserved within themouse (20, 28). Thus, we might expect that a subsetof the approximately 1 million conserved human/mouse elements coincide with exons. As an exercise,we can roughly estimate the number of exons in thehuman genome. Current data suggest that there areabout 30,000 human genes with an average of about8 exons per gene, which indicates approximately240,000 human exons (the average exon size is 150bp). With a small number of exons not displaying con-servation because of either their fast evolution or lackof an orthologous counterpart, this suggests thatapproximately 20% (200,000/1,000,000) of conservedhuman/mouse DNA elements are accounted for bycoding sequence.

What can be said for the remaining approximately800,000 roughly exon-sized conserved human/mousesequences? It appears that a large portion ofhuman/mouse conserved DNA occupies noncodingregions of the mammalian genome, although, in con-trast to exons, we have very few clues as to their imme-diate functional significance. One of our biggest cur-rent genomic challenges is to determine how many ofthese noncoding conserved sequences are functional,and their precise biological role(s).

One category of functional noncoding DNA issequences that participate in the regulation of neighbor-ing genes. On a small scale, comparative genomics hasproven its ability to uncover important gene-regulatory


elements based solely on conservation (8–10, 29–31).This is despite the fact that most transcription fac-tor–binding sites are on the order of 6–12 bp inlength. It appears that many gene-regulatory ele-ments are frequently found within much largerblocks of conservation (80–500 bp), most likelybecause regulatory elements are a composite ofnumerous transcription factor–binding sites thatdirect gene expression. Unfortunately, to date wehave only catalogued a small number of gene-regula-tory elements outside of proximal promoters, and itis difficult to estimate how many of the 800,000human/mouse exon-sized conserved noncodingsequences serve gene-regulatory (or other biological)functions. Similar to current successful exon predic-tion programs, future computational exploration ofsuch datasets may reveal common features amongvarious conserved noncoding sequence subclassesthat allow for future predictions of sequences withsimilar biological activity. With human/mouse con-servation serving as a filter for prioritizing humansequences likely to have biological activity, we predictthat hypotheses based purely on comparativesequence data should increasingly lead to biologicalinsights. In the next section, we focus on a limitednumber of recent examples in which comparativegenomics has led to biological discoveries.

Gene identificationOne of the clear utilities of comparative sequenceanalysis is for exon and gene identification. As statedpreviously, of the approximately 1 million human/mouse conserved elements, about one-fifth are prob-ably due to conserved exons. Thus, while a significantfraction of the genes in the human genome have like-ly already been identified, genome-wide scans forconserved human/mouse sequences should aid in theidentification of genes missed in the initial annota-tion of human sequence alone. Indeed, there havebeen several recent examples in which comparativesequence data have led to the discovery and func-tional understanding of previously undefined genes.

The complete human/mouse orthologous-sequencedataset proved particularly valuable in the characteri-zation of gene families in humans and mice (32). Forinstance, by comparing olfactory receptor gene fami-lies on human chromosome 19, computational analy-sis indicated that humans have approximately 49olfactory receptor genes, but only 22 had maintainedan open reading frame and appeared functional. Thiscontrasts with the vast majority of the homologousmouse genes that have retained an open readingframe. This finding of reduced olfactory receptordiversity in humans is consistent with the reducedolfactory needs and capabilities of humans relative torodents. As a second example, pheromone receptorgenes were also examined. In humans, 19 pheromonereceptor genes were identified, but only one appearedfunctional. In contrast, homologous mouse sequencesrevealed 36 pheromone receptor genes, and at least 17had maintained a complete open reading frame.Again, these data are consistent with the reduced

pheromone response in humans relative to mice. Thissubset of examples highlights the use of comparativegenomics to inventory gene content and correlate thedifferences to species-related biology.

Human/mouse comparative data have also led tothe discovery of previously undetected biomedicallyimportant genes. Of particular relevance to cardio-vascular disease was the discovery of APOA5 in thechromosome 11 apolipoprotein gene cluster (33).While the human sequence for the genomic intervalcontaining the intensively studied APOA1/C3/A4gene cluster had been available for many years, it wasonly comparison of the recently available ortholo-gous mouse sequence that alerted investigators to thepresence of APOA5. Through this comparativegenomic entry point, functional studies were per-formed in mice that indicated that alteration in thelevel of APOA5 significantly impacted plasma triglyc-eride concentrations. Mice overexpressing humanAPOA5 displayed significantly reduced triglycerides,while mice lacking ApoA5 had a large increase in thislipid parameter. In addition, multiple studies inhumans have also supported a role for commonAPOA5 genetic variation in influencing plasmatriglyceride concentrations (33–37). To date, consis-tent and strong genetic associations have been estab-lished between minor APOA5 alleles and increasedtriglycerides in Caucasian, African-American, His-panic, and Asian populations (33–37).

Thus, even in well-studied genomic intervals suchas the chromosome 11 apolipoprotein gene cluster,significant discoveries are possible through theexploitation of comparative sequence data. Thoughwhole-genome annotation efforts are providing thelocation for the majority of genes in the humangenome, undefined genes still exist. The above exam-ples provide strong evidence for the utility of com-parative genomic data to facilitate the identificationof coding sequences based on conservation. Animportant follow-up question is, how well does thisstrategy apply to the identification of sequencesencoding other important biological activitiesembedded in the human genome?

Identification of regulatory sequencesOne of the first studies to use solely human/mousecomparative genomics as an approach to identifygene-regulatory elements was the examination of acytokine gene cluster (including five ILs and 18 othergenes) on human chromosome 5q31 (38). In thiswork, human/mouse comparative analysis was per-formed on a 1-Mb region, and 90 conserved noncod-ing sequences (≥70% identity over ≥100 bp) wereidentified. Of these elements, several correspondedto previously known gene-regulatory elements. Onepreviously undefined conserved noncoding elementwas explored in finer detail based exclusively on itshuman/mouse sequence conservation (400 bp at 87%identity between human and mouse). This elementwas named conserved noncoding sequence 1 (CNS1)and was localized to the 15-kb interval between IL-4and IL-13. To characterize the function of CNS1,


transgenic and knockout mouse studies were per-formed (38–40). Through these studies it was shownthat CNS1 dramatically impacted the expression ofthree human cytokine (IL-4, IL-5, and IL-13) genesseparated by more than 120 kb of sequence. Thus,from a purely comparative sequence-based startingpoint, conservation of sequence alone led to the iden-tification of a novel gene-regulatory element that actsover long distances to modulate genes important inthe inflammatory response. Follow-up studies to theinitial discovery of CNS1 further support that this400-bp element contains transcription factor–bind-ing sites that coactivate IL-4, IL-5, and IL-13 (39, 40).The role of these ILs in a variety of common condi-tions such as asthma and inflammatory bowel dis-ease has focused attention on CNS1.

A second example of comparative sequence analysisidentifying gene-regulatory sequences prior to func-tional studies is the examination of a genomic intervalcontaining the stem cell leukemia (SCL) gene (10, 14,41). In these studies, the orthologous SCL genomicinterval was examined in human, mouse, chicken, fugu,and zebrafish. All of the exons and eight known gene-regulatory elements in the interval were conservedbetween humans and mice, though only a subset wereconserved between humans and chickens or betweenhumans and fish. These data question the utility ofsequence comparisons beyond mammals in thorough-ly identifying gene-regulatory elements. However, inthis study, power was obtained by the use of simulta-neous deep sequence comparison across all five speciesof the highly conserved SCL intervals, including thepromoter, exon 1, and the 3′ untranslated poly(A)region. Through phylogenetic footprinting (42), twohighly conserved promoter sequences were shown to benecessary for full SCL expression in erythroid cells.This study showed that pairwise sequence comparisonshad variable utility for identifying previously definedfunctional elements, and that deep sequence align-ments could reveal highly conserved functional motifs.

While these examples are limited because largestretches of human and mouse orthologous genomicsequence have only recently become accessible, theyhighlight the power of comparative sequence analysisin discovering various functional regions of thehuman genome. Based on the evolutionary relation-ship among vertebrates, conservation provides a blue-print to our shared genomic machinery. While evolu-tionary conservation of DNA sequence alone cannotindicate function, its identification provides a strate-gy to reveal and prioritize otherwise unrecognizablesequences for further biological experimentation.Though most current comparative genomic insightshave been derived from human/mouse sequence com-parisons, more distant evolutionary groups (such asfish, birds, amphibians, and reptiles) will also con-tribute to the further annotation and understandingof the human genome. Since an undefined fraction ofhuman/mouse conservation is likely to be nonfunc-tional, the analysis of sequences conserved betweenhumans and mice as well as nonmammalian specieswill further enrich for biologically active sequences.

ConclusionsThe flood of genomic-sequence data from a wide vari-ety of animal species has only just begun. While data-bases, algorithms, and strategies for simultaneouslyexamining sequence from evolutionarily relatedspecies already exist, large computational and experi-mental challenges lie ahead as sequence data expo-nentially increase. A field likely to expand significant-ly with the increasing availability of genomic sequencefrom multiple species is the computational identifica-tion of gene-regulatory and other noncoding func-tional DNA elements. Though we can currently makereasonable predictions for coding sequences embed-ded in the mammalian genome, only a limited numberof functional elements have been identified in themore than 97% of the genome that is noncoding. Thegeneration of a large dataset of conserved noncodingsequences coupled with other high-throughput ge-nomic information such as gene expression datashould contribute to the development of a vocabularyof DNA sequence that dictates gene expression andother noncoding functions embedded within thehuman genome. In the future, the annotation of thehuman genome that can be obtained through the var-ious genome browsers will likely include sequencesinvolved in gene regulation in addition to the alreadyexisting annotation of exons.

The recent availability and analysis of human andmouse genomic sequence have provided strong sup-port for the future value of sequence information inbiomedicine. We are approaching an era in whichsequence data no longer limit us but, rather, accumu-late rapidly with functional studies lagging behind.Intriguingly, though we are challenged by this glut ofsequence information, additional genome sequencesfrom mammalian and nonmammalian species will fur-ther help us to even better prioritize regions of thehuman genome for functional studies.

AcknowledgmentsThis work was supported in part by the NIH–NationalHeart, Lung, and Blood Institute Programs for Genom-ic Application grant HL-66681 (to E.M. Rubin)through the US Department of Energy under contractno. DE-AC03-76SF00098.

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