Abstract

Although the list of completed genome sequencing projects has expanded rapidly, sequencing and analysis of expressed sequence tags (ESTs) remain a primary tool for discovery of novel genes in many eukaryotes and a key element in genome annotation. The TIGR Gene Indices ( http://www.tigr.org/tdb/tgi ) are a collection of 77 species-specific databases that use a highly refined protocol to analyze gene and EST sequences in an attempt to identify and characterize expressed transcripts and to present them on the Web in a user-friendly, consistent fashion. A Gene Index database is constructed for each selected organism by first clustering, then assembling EST and annotated cDNA and gene sequences from GenBank. This process produces a set of unique, high-fidelity virtual transcripts, or tentative consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to genetic and physical maps, to provide links to orthologous and paralogous genes, and as a resource for comparative and functional genomic analysis.

Received September 14, 2004; Revised and Accepted October 5, 2004

INTRODUCTION

The TIGR Gene Index databases (TGI) ( http://www.tigr.org/tdb/tgi ) are constructed using all publicly available expressed sequence tags (EST) and known gene sequence data stored in GenBank for each target species. Sequences are first cleaned to identify and remove contaminating sequences, including vector, adaptor, mitochondrial, ribosomal and chimeric sequences. These sequences are then searched pairwise against each other and grouped into clusters based on shared sequence similarity. The clusters are assembled at high stringency to produce tentative consensus (TC) sequences. The virtual transcripts represented in the TCs are annotated using a variety of tools for open reading frame (ORF) prediction, single nucleotide polymorphism (SNP) prediction, long oligo prediction for microarrays, putative annotation using a controlled vocabulary, Gene Ontology (GO) and Enzyme Commission (EC) number assignments and maps onto complete or drafted genomes or available genetic maps. The TCs are used to construct a variety of other databases, including the Eukaryotic Gene Orthologs (EGO) database and RESOURCERER, a database that annotates and cross-references microarray resources for plants and animals.

At present, 77 species are represented in the Gene Index databases, including 29 animals, 25 plants, 8 fungi and 15 protists; this includes most species for which public EST projects have released more than 50 000 ESTs. Current release information for each species-specific database is summarized in Table 1 . Individual databases are updated and released three times yearly, on February 1, June 1 and October 1, if the number of available ESTs for that species has increased by either 25 000 or >10%, whichever is less.

Table 1.

Summary of the current release of TIGR Gene Indices (TGI)

Species
 
Species_name
 
TGI
 
TC
 
sET
 
sEST
 
Animals (29)      
    Human Homo sapiens HGI 15.0 221 418 19 740 594 468 
    Mouse Mus musculus MGI 14.0 167 694 7499 602 312 
    Rat Rattus norvegicus RGI 13.0 56 933 2131 87 992 
    Cattle Bos Taurus BtGI 10.0 38 760 413 56 644 
    Pig Sus scrofa SsGI 9.0 33 963 519 50 376 
    Dog Canis familiaris DogGI 4.0 6613 684 11 506 
    Chicken Gallus gallus GgGI 8.0 42 988 848 72 941 
    Frog Xenopus laevis XGI 9.0 39 724 626 37 249 
    Zebrafish Danio rerio ZGI 15.0 32 889 395 53 940 
    Catfish Ictalurus punctatus Cfgi 5.0 3254 156 16 694 
    R.trout Oncorhynchus mykiss RtGI 4.0 23 135 190 27 448 
    A.salmon Salmo salar AsGI 2.1 12 277 93 18 971 
    C.intestinalis Ciona intestinalis CinGI 3.0 20 616 39 30 690 
    Medaka Oryzias latipes OlGI 5.0 12 849 171 13 669 
    Fugu Takifugu rubripes FGI 1.0 3120 448 7667 
    A.burtoni Astatotilapia burtoni AbGI 1.0 402 15 2300 
    H.chilotes Haplochromis chilotes HchGI 1.0 2147 4030 
    H.red_tail_sheller Haplochromis sp. ‘rts’  HsGI 1.0 1883 4422 
    Killifish Fundulus heteroclitus FhGI 1.0 3540 57 11 941 
    Honeybee Apis mellifera AMGI 4.0 3700 53 7571 
    A.aegypti Aedes aegypti AeGI 4.0 15 888 32 5075 
    Drosophila Drosophila melanogaster DGI 9.0 20 693 1104 6662 
    Mosquito Anopheles gambiae AgGI 7.0 17 120 6847 14 940 
    A.variegatum Amblyomma variegatum AvGI 2.0 478 1631 
    R.appendic Rhipicephalus appendiculatus RaGI 1.0 2543 19 4797 
    C.elegans Caenorhabditis elegans CeGI 8.0 17 728 5034 5678 
    B.malayi Brugia malayi BmGI 4.0 2060 44 6841 
    O.volvulus Onchocerca volvulus OvGI 3.0 1065 23 2942 
    S.mansoni Schistosoma mansoni SmGI 5.0 12 912 39 20 753 
Plants (25)      
    Pine Pinus PGI 4.0 13 622 205 17 944 
    Cocoa Theobroma cacao TcaGI 1.0 754 26 1759 
    Cotton Gossypium CGI 5.0 6812 142 17 396 
    Arabidopsis Arabidopsis thaliana AtGI 11.0 28 010 5188 12 485 
    L.japonicus Lotus japonicus LjGI 3.0 12 485 56 15 919 
    Lettuce Lactuca sativa LsGI 2.0 7961 56 14 168 
    Sunflower Helianthus annuus HaGI 3.0 6038 110 14 372 
    Tomato Lycopersicon esculentum LeGI 9.0 20 530 164 14 923 
    Pepper Capsicum annuum CaGI 1.0 3203 47 7462 
    Potato Solanum tuberosum StGI 9.0 19 225 102 13 226 
    Tobacco Nicotiana tabacum NtGI 1.0 897 806 8529 
    N.benthamiana Nicotiana benthamiana NbGI 1.1 3819 44 3735 
    Soybean Glycine max GmGI 12.0 30 084 141 37 601 
    Medicago Medicago truncatula MtGI 7.0 17 610 25 19 341 
    Ice_plant Mesembryanthemum crystalline McGI 4.0 2851 47 5557 
    Grape Vitis vinifera VvGI 3.1 13 218 54 9837 
    Rice Oryza sativa OsGI 15.0 33 089 17 776 37 900 
    Maize Zea mays ZmGI 14.0 29 414 524 26 426 
    Wheat Triticum aestivum TaGI 8.0 44 630 169 79 008 
    Sorghum Sorghum bicolor SbGI 8.0 20 029 143 18 976 
    Barley Hordeum vulgare HvGI 9.0 21 981 168 27 041 
    S.cereale Secale cereale RyeGI 3.0 1391 66 3890 
    S.officinarum Saccharum officinarum SoGI 1.0 23 596 72 281 
    A.cepa Allium cepa OnGI 1.0 3838 18 7870 
    C.reinhardtii Chlamydomonas reinhardtii ChrGI 4.0 10 777 96 19 466 
Fungi (8)      
    A.flavus Aspergillus flavus AfGI 4.0 3749 10 3459 
    C.posadasii Coccidioides posadasii CpoGI 2.0 6275 3037 
    S.cerevisiae Saccharomyces cerevisiae ScGI 3.0 4107 2005 198 
    S.pombe Schizosaccharomyces pombe SpGI 3.0 2449 2974 510 
    Cryptococcus Filobasidiella neoformans CrGI 7.0 2384 59 3231 
    N.crassa Neurospora crassa NcrGI 3.0 4389 6547 1586 
    A.nidulans Aspergillus nidulans AnGI 4.0 3532 6664 2904 
    M.grisea Magnaporthe grisea MgGI 5.0 6375 6195 8320 
Protists (15)      
    P.berghei Plasmodium berghei PbGI 5.0 1168 41 3980 
    P.falciparum Plasmodium falciparum PfGI 7.0 3978 2487 3142 
    P.vivax Plasmodium vivax PvGI 0.5 158 175 567 
    P.yoelii Plasmodium yoelii PyGI 5.0 3611 3784 2418 
    E.tenella Eimeria tenella EtGI 4.0 2077 29 3066 
    T.gondii Toxoplasma gondii TgGI 6.0 6977 31 11 401 
    N.caninum Neospora caninum NcGI 5.0 1980 3715 
    S.neurona Sarcocystis neurona SnGI 4.0 665 1644 
    C.parvum Cryptosporidium parvum CpGI 4.0 171 485 254 
    T.vaginalis Trichomonas vaginalis TvGI 1.0 87 109 704 
    Leishmania Leishmania LshGI 4.0 600 1454 1120 
    T.cruzi Trypanosoma cruzi TcGI 4.0 2189 164 4749 
    T.brucei Trypanosoma brucei TbGI 5.0 734 1287 2018 
    D.discoideum Dictyostelium discoideum DdGI 4.0 6826 172 6392 
    T.thermophila Tetrahymena thermophila TtGI 3.0 1436 165 2626 
Species
 
Species_name
 
TGI
 
TC
 
sET
 
sEST
 
Animals (29)      
    Human Homo sapiens HGI 15.0 221 418 19 740 594 468 
    Mouse Mus musculus MGI 14.0 167 694 7499 602 312 
    Rat Rattus norvegicus RGI 13.0 56 933 2131 87 992 
    Cattle Bos Taurus BtGI 10.0 38 760 413 56 644 
    Pig Sus scrofa SsGI 9.0 33 963 519 50 376 
    Dog Canis familiaris DogGI 4.0 6613 684 11 506 
    Chicken Gallus gallus GgGI 8.0 42 988 848 72 941 
    Frog Xenopus laevis XGI 9.0 39 724 626 37 249 
    Zebrafish Danio rerio ZGI 15.0 32 889 395 53 940 
    Catfish Ictalurus punctatus Cfgi 5.0 3254 156 16 694 
    R.trout Oncorhynchus mykiss RtGI 4.0 23 135 190 27 448 
    A.salmon Salmo salar AsGI 2.1 12 277 93 18 971 
    C.intestinalis Ciona intestinalis CinGI 3.0 20 616 39 30 690 
    Medaka Oryzias latipes OlGI 5.0 12 849 171 13 669 
    Fugu Takifugu rubripes FGI 1.0 3120 448 7667 
    A.burtoni Astatotilapia burtoni AbGI 1.0 402 15 2300 
    H.chilotes Haplochromis chilotes HchGI 1.0 2147 4030 
    H.red_tail_sheller Haplochromis sp. ‘rts’  HsGI 1.0 1883 4422 
    Killifish Fundulus heteroclitus FhGI 1.0 3540 57 11 941 
    Honeybee Apis mellifera AMGI 4.0 3700 53 7571 
    A.aegypti Aedes aegypti AeGI 4.0 15 888 32 5075 
    Drosophila Drosophila melanogaster DGI 9.0 20 693 1104 6662 
    Mosquito Anopheles gambiae AgGI 7.0 17 120 6847 14 940 
    A.variegatum Amblyomma variegatum AvGI 2.0 478 1631 
    R.appendic Rhipicephalus appendiculatus RaGI 1.0 2543 19 4797 
    C.elegans Caenorhabditis elegans CeGI 8.0 17 728 5034 5678 
    B.malayi Brugia malayi BmGI 4.0 2060 44 6841 
    O.volvulus Onchocerca volvulus OvGI 3.0 1065 23 2942 
    S.mansoni Schistosoma mansoni SmGI 5.0 12 912 39 20 753 
Plants (25)      
    Pine Pinus PGI 4.0 13 622 205 17 944 
    Cocoa Theobroma cacao TcaGI 1.0 754 26 1759 
    Cotton Gossypium CGI 5.0 6812 142 17 396 
    Arabidopsis Arabidopsis thaliana AtGI 11.0 28 010 5188 12 485 
    L.japonicus Lotus japonicus LjGI 3.0 12 485 56 15 919 
    Lettuce Lactuca sativa LsGI 2.0 7961 56 14 168 
    Sunflower Helianthus annuus HaGI 3.0 6038 110 14 372 
    Tomato Lycopersicon esculentum LeGI 9.0 20 530 164 14 923 
    Pepper Capsicum annuum CaGI 1.0 3203 47 7462 
    Potato Solanum tuberosum StGI 9.0 19 225 102 13 226 
    Tobacco Nicotiana tabacum NtGI 1.0 897 806 8529 
    N.benthamiana Nicotiana benthamiana NbGI 1.1 3819 44 3735 
    Soybean Glycine max GmGI 12.0 30 084 141 37 601 
    Medicago Medicago truncatula MtGI 7.0 17 610 25 19 341 
    Ice_plant Mesembryanthemum crystalline McGI 4.0 2851 47 5557 
    Grape Vitis vinifera VvGI 3.1 13 218 54 9837 
    Rice Oryza sativa OsGI 15.0 33 089 17 776 37 900 
    Maize Zea mays ZmGI 14.0 29 414 524 26 426 
    Wheat Triticum aestivum TaGI 8.0 44 630 169 79 008 
    Sorghum Sorghum bicolor SbGI 8.0 20 029 143 18 976 
    Barley Hordeum vulgare HvGI 9.0 21 981 168 27 041 
    S.cereale Secale cereale RyeGI 3.0 1391 66 3890 
    S.officinarum Saccharum officinarum SoGI 1.0 23 596 72 281 
    A.cepa Allium cepa OnGI 1.0 3838 18 7870 
    C.reinhardtii Chlamydomonas reinhardtii ChrGI 4.0 10 777 96 19 466 
Fungi (8)      
    A.flavus Aspergillus flavus AfGI 4.0 3749 10 3459 
    C.posadasii Coccidioides posadasii CpoGI 2.0 6275 3037 
    S.cerevisiae Saccharomyces cerevisiae ScGI 3.0 4107 2005 198 
    S.pombe Schizosaccharomyces pombe SpGI 3.0 2449 2974 510 
    Cryptococcus Filobasidiella neoformans CrGI 7.0 2384 59 3231 
    N.crassa Neurospora crassa NcrGI 3.0 4389 6547 1586 
    A.nidulans Aspergillus nidulans AnGI 4.0 3532 6664 2904 
    M.grisea Magnaporthe grisea MgGI 5.0 6375 6195 8320 
Protists (15)      
    P.berghei Plasmodium berghei PbGI 5.0 1168 41 3980 
    P.falciparum Plasmodium falciparum PfGI 7.0 3978 2487 3142 
    P.vivax Plasmodium vivax PvGI 0.5 158 175 567 
    P.yoelii Plasmodium yoelii PyGI 5.0 3611 3784 2418 
    E.tenella Eimeria tenella EtGI 4.0 2077 29 3066 
    T.gondii Toxoplasma gondii TgGI 6.0 6977 31 11 401 
    N.caninum Neospora caninum NcGI 5.0 1980 3715 
    S.neurona Sarcocystis neurona SnGI 4.0 665 1644 
    C.parvum Cryptosporidium parvum CpGI 4.0 171 485 254 
    T.vaginalis Trichomonas vaginalis TvGI 1.0 87 109 704 
    Leishmania Leishmania LshGI 4.0 600 1454 1120 
    T.cruzi Trypanosoma cruzi TcGI 4.0 2189 164 4749 
    T.brucei Trypanosoma brucei TbGI 5.0 734 1287 2018 
    D.discoideum Dictyostelium discoideum DdGI 4.0 6826 172 6392 
    T.thermophila Tetrahymena thermophila TtGI 3.0 1436 165 2626 

TIGR Gene Indices are a collection of species-based databases which assemble the ESTs and the Expressed Transcripts (ETs) into TC sequences. Singletons (sET and sEST) are the ET/EST sequences that are not incorporated into a TC during assembly. TCs, sET and sEST are the unique sequences in TGI. There are 77 gene indices in total (data until September 1, 2004). Each line includes species, species name, gene index name and version, total number of TCs within current release, number of singleton ETs and number of singleton ESTs. For Leishmania, pine and cotton, the ESTs were pooled from dbEST for the genus, not a single species. The table was arranged by grouping the total 77 gene indices into animals (29), plants (25), fungi (8) and protists (15).

RECENT DEVELOPMENTS

Construction of the Gene Indices

The process used to assemble each Gene Index is similar to that described previously ( 13 ), although some modifications have been made to improve the efficiency and accuracy of the process. mgBLAST, a modified version of the Megablast ( 4 ) program, is now used for the pairwise sequence comparisons that are the basis for defining the sequence clusters which form the basis for assembly. For large clusters containing hundreds or thousands of sequences (e.g. highly expressed genes such as actin), sequence representation is reduced prior to assembly using a variety of multilayer approaches, including transitive clustering, containment clustering and seeded clustering with known genes. Following clustering, the Paracel Transcript Assembler (PTA), a modified version of CAP3 assembly program ( 5 ), is used to assemble each TC. An open source set of software tools that embody this process, TGICL, is available ( http://www.tigr.org/tdb/tgi/software ) with other open-source utilities for users interested in performing a similar analysis on their own datasets ( 6 ).

New features of the TC report

The central element of the TGI databases are the TC sequences and the TC reports that are presented through the project website. Each TC report presents a summary of the assembly and annotation process, including the consensus TC sequence in the FASTA format with a history from previous builds in the header, a map showing component EST and gene sequences, and a table providing links to the primary sequences, putative annotation, an expression summary based on the number of ESTs from various libraries, genomic locations and links to tentative orthologs in EGO. Since the last presentation of the TGI databases in Nucleic Acids Research , several new features have been added to the TC report. Putative polyadenylation signals are identified and shaded in the consensus sequence and putative poly(A/T) trimming sites are shown in sequence map for each of the component ESTs. Potential ORFs are predicted for each TC using a variety of software tools including the NCBI ORF Finder, ESTScan ( 7 ) and FrameFinder; predicted ORFs can be searched against a variety of databases using WU-BLAST. Assembly of the TCs can result in incorrect orientations for the consensus and an attempt is now made to determine the proper orientation using the annotated direction of component gene and EST sequences as well as BLAST search results. Putative SNP sites are found by analyzing the multiple sequence alignments that are produced in the assembly stage; putative SNPs are reported only if a variant is found in multiple sequences from independent libraries. Unique 70mers are predicted for each TC using OligoPicker ( 8 ). GO terms and metabolic pathway in KEGG are provided for each TC based on protein database searches. Where possible, TCs are aligned with draft genomes and displayed using TGIviewer, gbrowse, EnsEMBL and the UCSC genome viewers.

New databases and tools

The EGO ( http://www.tigr.org/tdb/tgi/ego ) ( 9 ) database, previously known as TIGR Orthologous Gene Alignments (TOGA), uses pairwise sequence similarity searches and a transitive, reciprocal closure process to identify Tentative Ortholog Groups (TOGs) in eukaryotes ( 9 ). EGO has expanded its representation to include all 77 species represented in the TGI and TOGs have been cross-referenced to the Online Mendelian in Man (OMIM) ( http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM ) database of human disease genes.

RESOURCERER ( 10 ) provides annotation based on the TIGR Gene Indices for widely available microarray resources in human, mouse, rat, zebrafish and Xenopus, including widely used clone sets and Affymetrix GeneChips™ as well as a variety of other sequence-based resources such as RefSeq. RESOURCERER provides a wide range of annotation and integration with genomic and other resources, including gene name assignments, GO term and EC number assignments, chromosomal localization, integration with genetic and quantitative trait locus (QTL) maps, ortholog identification, lists of relevant abstracts in PubMed and promoter region identification. Owing to its integration with the TGI and EGO, RESOURCERER also provides links between microarray platforms both within and between species. Users can also submit a list of GenBank accessions corresponding to their microarray databases for annotation and functional analysis. A plant-specific version, Plant RESOURCERER, was released in September 2004 with microarray resources from Arabidopsis , potato, tomato, maize and rice.

Genomic maps align TCs to available complete or draft genomes, including human, mouse, rat, zebrafish, fly, worm, Fugu, mosquito, Arabidopsis , yeast, fission yeast and rice. Also these alignments can be viewed using either TGIviewer or gbrowse or through a number of distributed annotation system (DAS) viewers ( 11 ), including one developed at TIGR. Each Gene Index also includes graphical metabolic pathway maps linked to TCs associated with specific pathways through GO term and EC number annotation. Comparisons between TCs are also used to identify putative alternative splice forms based on shared blocks of sequence similarity.

Using the TIGR Gene Indices

There are many ways in which users can access the TIGR Gene Index databases. Nucleotide or protein sequences can be searched using WU-BLAST against individual TGI databases, EGO or pre-selected classes of species, such as animals or plants. The TGI can be searched using unique identifiers (GB and TC Accessions, EST identifiers and ET numbers from the TIGR PREEGAD database), gene product names, functional classifications based on GO terms, metabolic pathways, library-related expression analysis, map position within various sequenced genomes, TOGs in the EGO database and alternative splice forms. Complete annotations for all of the ESTs and TCs in each TGI database are now also provided through the EST Annotator and TC Annotator features which provide comprehensive lists of sequences within each species-specific database.

All of the TIGR Gene Indices are available for download through the main page for each species. Downloads consist of six files, including a FASTA file for all unique sequences, the TC list, the component ESTs in each TC, GO analysis, predicted oligos and a README file.

Software

Many of the software tools used to create the TGI are available with source code to the research community through the TGI software tools website ( http://www.tigr.org/tdb/tgi/software ). The TGI Clustering tool (TGICL) ( 6 ) is a software system for fast clustering and assembly of large EST datasets. TGICL starts with a large multi-FASTA file (and an optional quality value file) and outputs the assemblies produced by CAP3 ( 5 ). Both clustering and assembly phases can be parallelized by distributing the searches and the assembly jobs across multiple CPUs, as TGICL can take advantage of either SMP or PVM (Parallel Virtual Machine) clusters. Other available software includes clview for viewing sequence assemblies in .ace format, SeqClean which is used to remove contaminating sequences from EST and gene sequences and cdbfasta/cdbyank which index FASTA-formatted files and can be used to rapidly extract sequences from them.

The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions@oupjournals.org .

The authors wish to thank TIGR IT group for their database and computer system support. This work was supported by the US Department of Energy, grant DE-FG02-99ER62852 and the US National Science Foundation, grant DBI-9983070.

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