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

The increasing availability of genomic sequence from multiple organisms has provided biomedical scientists with a large dataset for orthologous-sequence comparisons. The rationale for using cross-species sequence comparisons to identify biologically active regions of a genome is based on the observation that sequences that perform important functions are frequently conserved between evolutionarily distant species, distinguishing them from nonfunctional surrounding sequences. This is most readily apparent for protein-encoding sequences but also holds true for the sequences involved in the regulation of gene expression. While these observations have frequently been made retrospectively following the analysis of previously discovered genes or gene-regulatory sequences, examination of orthologous genomic sequences from several vertebrates has shown that the inverse is also true. Specifically, studying evolutionarily conserved sequences is a reliable strategy to uncover regions of the human genome with biological activity. To assist biomedical investigators in taking advantage of this new paradigm, various comparative sequence-based visualization tools and databases have been developed. Already, these new publicly accessible resources have been successfully exploited by investigators for the discovery of biomedically important new genes and sequences involved in gene regulation.

[1]  Nicholas L. Bray,et al.  AVID: A global alignment program. , 2003, Genome research.

[2]  D. Haussler,et al.  Human-mouse alignments with BLASTZ. , 2003, Genome research.

[3]  L. Pachter,et al.  Strategies and tools for whole-genome alignments. , 2002, Genome research.

[4]  Paul Richardson,et al.  The Draft Genome of Ciona intestinalis: Insights into Chordate and Vertebrate Origins , 2002, Science.

[5]  Colin N. Dewey,et al.  Initial sequencing and comparative analysis of the mouse genome. , 2002 .

[6]  Shotai Kobayashi,et al.  The genetic effect of the apoprotein AV gene on the serum triglyceride level in Japanese. , 2002, Atherosclerosis.

[7]  M. Olivier,et al.  Relative contribution of variation within the APOC3/A4/A5 gene cluster in determining plasma triglycerides. , 2002, Human molecular genetics.

[8]  Jonathan C. Cohen,et al.  Two independent apolipoprotein A5 haplotypes influence human plasma triglyceride levels. , 2002, Human molecular genetics.

[9]  S. Tomura,et al.  Association found between the promoter region polymorphism in the apolipoprotein A-V gene and the serum triglyceride level in Japanese schoolchildren , 2002, Human Genetics.

[10]  Paramvir S. Dehal,et al.  Whole-Genome Shotgun Assembly and Analysis of the Genome of Fugu rubripes , 2002, Science.

[11]  S. Salzberg,et al.  Fast algorithms for large-scale genome alignment and comparison. , 2002, Nucleic acids research.

[12]  Tom H. Pringle,et al.  The human genome browser at UCSC. , 2002, Genome research.

[13]  Berthold Göttgens,et al.  Transcriptional regulation of the stem cell leukemia gene (SCL)--comparative analysis of five vertebrate SCL loci. , 2002, Genome research.

[14]  W. J. Kent,et al.  BLAT--the BLAST-like alignment tool. , 2002, Genome research.

[15]  Philip Lijnzaad,et al.  The Ensembl genome database project , 2002, Nucleic Acids Res..

[16]  Mouse Genome Sequencing Consortium.  Initial sequencing and comparative analysis of the mouse genome , 2002, Nature.

[17]  Jonathan C. Cohen,et al.  An Apolipoprotein Influencing Triglycerides in Humans and Mice Revealed by Comparative Sequencing , 2001, Science.

[18]  J. Mullikin,et al.  SSAHA: a fast search method for large DNA databases. , 2001, Genome research.

[19]  Edward M. Rubin,et al.  Deletion of a coordinate regulator of type 2 cytokine expression in mice , 2001, Nature Immunology.

[20]  Paul Richardson,et al.  Human Chromosome 19 and Related Regions in Mouse: Conservative and Lineage-Specific Evolution , 2001, Science.

[21]  R. Flavell,et al.  Regulation of IL-4 gene expression by distal regulatory elements and GATA-3 at the chromatin level. , 2001, Immunity.

[22]  Timothy B. Stockwell,et al.  The Sequence of the Human Genome , 2001, Science.

[23]  L. Pennacchio,et al.  Genomic strategies to identify mammalian regulatory sequences , 2001, Nature Reviews Genetics.

[24]  Johnm . Taylor,et al.  Two Distal Downstream Enhancers Direct Expression of the Human Apolipoprotein E Gene to Astrocytes in the Brain , 2001, The Journal of Neuroscience.

[25]  J. Taylor,et al.  Expression of the apolipoprotein E gene in the skin is controlled by a unique downstream enhancer. , 2001, The Journal of investigative dermatology.

[26]  D R Bentley,et al.  Long-range comparison of human and mouse SCL loci: localized regions of sensitivity to restriction endonucleases correspond precisely with peaks of conserved noncoding sequences. , 2001, Genome research.

[27]  International Human Genome Sequencing Consortium.  Initial sequencing and analysis of the human genome , 2001, Nature.

[28]  Lior Pachter,et al.  VISTA : visualizing global DNA sequence alignments of arbitrary length , 2000, Bioinform..

[29]  Johnm . Taylor,et al.  Duplicated Downstream Enhancers Control Expression of the Human Apolipoprotein E Gene in Macrophages and Adipose Tissue* , 2000, The Journal of Biological Chemistry.

[30]  R. Hardison.  Conserved noncoding sequences are reliable guides to regulatory elements. , 2000, Trends in genetics : TIG.

[31]  I-Min A. Dubchak,et al.  Active conservation of noncoding sequences revealed by three-way species comparisons. , 2000, Genome research.

[32]  R. Durbin,et al.  Alfresco--a workbench for comparative genomic sequence analysis. , 2000, Genome research.

[33]  W. Miller,et al.  Identification of a coordinate regulator of interleukins 4, 13, and 5 by cross-species sequence comparisons. , 2000, Science.

[34]  R. Gibbs,et al.  PipMaker--a web server for aligning two genomic DNA sequences. , 2000, Genome research.

[35]  Berthold Göttgens,et al.  Analysis of vertebrate SCL loci identifies conserved enhancers , 2000, Nature Biotechnology.

[36]  W. Miller,et al.  Long human-mouse sequence alignments reveal novel regulatory elements: a reason to sequence the mouse genome. , 1997, Genome research.

[37]  P. Bucher,et al.  Searching for regulatory elements in human noncoding sequences. , 1997, Current opinion in structural biology.

[38]  Wei Zhu,et al.  Evolutionary Strategies for the Elucidation ofcisandtransFactors That Regulate the Developmental Switching Programs of the β-like Globin Genes , 1996 .

[39]  M. Goodman,et al.  Evolutionary strategies for the elucidation of cis and trans factors that regulate the developmental switching programs of the beta-like globin genes. , 1996, Molecular phylogenetics and evolution.

[40]  L. Rowen,et al.  Human and Mouse T‐Cell Receptor Loci: Genomics, Evolution, Diversity, and Serendipity a , 1995, Annals of the New York Academy of Sciences.

[41]  L. Hood,et al.  Striking sequence similarity over almost 100 kilobases of human and mouse T–cell receptor DNA , 1994, Nature Genetics.

[42]  G. Jiménez,et al.  The mouse β-globin locus control region: hypersensitive sites 3 and 4 , 1992 .

[43]  G. Jiménez,et al.  The mouse beta-globin locus control region: hypersensitive sites 3 and 4. , 1992, Nucleic acids research.

[44]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[45]  R. Hardison,et al.  Complete nucleotide sequence of the rabbit β-like globin gene cluster: Analysis of intergenic sequences and comparison with the human β-like globin gene cluster , 1989 .

[46]  R. Hardison,et al.  Complete nucleotide sequence of the rabbit beta-like globin gene cluster. Analysis of intergenic sequences and comparison with the human beta-like globin gene cluster. , 1989, Journal of molecular biology.

[47]  D. Mccormick.  Sequence the Human Genome , 1986, Bio/Technology.