AltTrans: Transcript pattern variants annotated for both alternative splicing and alternative polyadenylation
- Vincent Le Texier†1,
- Jean-Jack Riethoven†1, 3,
- Vasudev Kumanduri1,
- Chellappa Gopalakrishnan1,
- Fabrice Lopez2,
- Daniel Gautheret2Email author and
- Thangavel Alphonse Thanaraj1, 4
© Le Texier et al; licensee BioMed Central Ltd. 2006
Received: 14 December 2005
Accepted: 23 March 2006
Published: 23 March 2006
The three major mechanisms that regulate transcript formation involve the selection of alternative sites for transcription start (TS), splicing, and polyadenylation. Currently there are efforts that collect data & annotation individually for each of these variants. It is important to take an integrated view of these data sets and to derive a data set of alternate transcripts along with consolidated annotation. We have been developing in the past computational pipelines that generate value-added data at genome-scale on individual variant types; these include AltSplice on splicing and AltPAS on polyadenylation. We now extend these pipelines and integrate the resultant data sets to facilitate an integrated view of the contributions from splicing and polyadenylation in the formation of transcript variants.
The AltSplice pipeline examines gene-transcript alignments and delineates alternative splice events and splice patterns; this pipeline is extended as AltTrans to delineate isoform transcript patterns for each of which both introns/exons and 'terminating' polyA site are delineated; EST/mRNA sequences that qualify the transcript pattern confirm both the underlying splicing and polyadenylation. The AltPAS pipeline examines gene-transcript alignments and delineates all potential polyA sites irrespective of underlying splicing patterns. Resultant polyA sites from both AltTrans and AltPAS are merged. The generated database reports data on alternative splicing, alternative polyadenylation and the resultant alternate transcript patterns; the basal data is annotated for various biological features. The data (named as integrated AltTrans data) generated for both the organisms of human and mouse is made available through the Alternate Transcript Diversity web site at http://www.ebi.ac.uk/atd/.
The reported data set presents alternate transcript patterns that are annotated for both alternative splicing and alternative polyadenylation. Results based on current transcriptome data indicate that the contribution of alternative splicing is larger than that of alternative polyadenylation.
The three major regulatory mechanisms that bring about formation of alternative transcript patterns from an expressed gene act at the choice of alternative sites for transcription start (TS), splicing, and polyadenylation [1–4]. Use of alternative TS site and/or alternative polyA site often accompanies alternative splicing [1, 4, 5]. Currently there are efforts that collect data & annotation either for TS variants [1, 6–9], or for splice variants [10–24], or for polyA variants [3, 25–28]. These data sets provide a wealth of value-added annotation (such as tissue specificity, evolutionary conservation, and regulatory motifs). Given that there is a coupling between the machineries responsible for transcription initiation, splicing, and polyadenylation [29–33], it is important to take a coherent & integrated view of these individual variants and to derive a data set of alternate transcript patterns along with consolidated annotation. Previous attempts to integrate variants of splicing and polyadenylation (as well as of transcript start sites) introduced new methods for transcript assembly – notable examples being that of Kim et al , Sharov et al , and that of Zavolan et al . General conclusions from these studies were that (i) a majority of transcription units showing multiple splice forms contain transcripts in which the apparent use of an alternative transcription start (or stop) is accompanied by alternative splicing of the initial (or terminal) exon; and that (ii) alternative splicing is a major contributor to transcriptome diversity.
We have been generating data sets on individual variant types; such data sets include AltSplice  and AltPAS . Both the AltSplice and AltPAS pipelines generate genome-wide data based on Ensembl  gene annotation. The AltSplice pipeline examines gene-transcript alignments and delineates alternate splice events and alternate splice patterns; the pipeline characterises the generated data for various biological features. In the current work, we extend the AltSplice pipeline as AltTrans to annotate the observed splice patterns for terminating polyA site; the information on the polyA site for a splice pattern is derived by examining the transcript sequences that confirm the splice pattern; a splice pattern that could be annotated for terminating polyA site is termed as transcript pattern. The AltPAS pipeline examines gene-transcript alignments and identifies potential polyA sites independently of the underlying splicing patterns; as a result for a given set of genes, AltPAS derives a larger data set of polyA sites as compared to AltTrans.
The transcript patterns as derived by the AltTrans pipeline and the combined list of polyA sites as generated by AltTrans and AltPAS pipelines form the core of the data presented in this work; these basal data are annotated for various biological features. The resulting data for human and mouse is presented to the community in two forms: (i) through an FTP server as flat file distributions; and (ii) through user-friendly web query interfaces. Included in the database are those genes for which at least one transcript pattern (annotated both for splicing and terminating polyA site) was determined.
Construction and content
The different pipelines discussed below are (i) AltSplice (that delineates splice related data namely, splice sites, splice patterns and splice events), (ii) AltTrans (that delineates transcript patterns along with annotation for terminating polyA site from AltSplice splice patterns, and (iii) AltPAS (that delineates all potential polyA sites on the gene independently of the underlying splicing patterns). Also discussed are the approaches to integrate the resulting data.
Generating splice patterns: the AltSplice pipeline
The methodologies behind the AltSplice pipeline have been previously reported [11–13] and hence are briefly mentioned here. The considered gene set is that of the Ensembl genome annotation project . For each of the considered genes, the nucleotide sequence of a region that extends Ensembl-defined gene boundaries by 3000 bases on either flanking side is extracted as AltSplice gene. Transcript (EST and mRNA) sequences as extracted from EMBL database  are used to generate a high quality data set of gene-transcript alignments showing more than one high scoring match between gene and transcript sequences. Any transcript sequence that aligns exclusively to the flanking regions of a gene is discarded. Further, any transcript sequence that aligns with more than one gene or ambiguously with more than one region on a single gene is discarded. Alignment gaps on gene sequences are considered as potential introns and their validation as transcript-confirmed introns is a crucial step in AltSplice pipeline (see [11–13] for validation procedures). Alignment matches on the gene sequence are accepted as a confirmed exon if flanked on either side by a confirmed intron. Thus each transcript sequences that maps to a gene is described by its exon-intron structure. Transcript sequences that map to a gene are then grouped into classes in a manner that the member transcripts from a class show same exon-intron structure. Longest representative from each such class denotes a unique splice pattern for the gene. Overlapping exons and introns from the isoform splice patterns are then examined to delineate alternative splice events.
Redefinition of AltSplice gene region
If no splice pattern is observed extending into flanking regions, then AltSplice gene is trimmed down to that as annotated in Ensembl.
If a splice pattern is seen as extending into the 5' flanking region, the genome start location of the splice pattern forms the 5' bound for AltSplice gene.
If a splice pattern is seen as extending into the 3' flanking region, the genome end location of the splice pattern forms the 3' bound of AltSplice gene.
Generating transcript patterns and 'terminating' polyA sites from AltSplice splice patterns: the AltTrans pipeline
Detecting polyA sites from transcript sequences that confirm AltSplice patterns. This procedure is of the following three steps:
(i) Detecting polyA tail and polyA cleavage (PAC) site
Each of the gene-transcript alignments is examined for the presence of a 3' dangling end on the transcript sequence. Only those alignments that show 3' dangling ends of length at least 8 bases are considered further. The transcript region -5 to +5 from the end of alignment is examined for the start of a polyA tail. A polyA tail is defined as a string of 8 or more adenosines. It is observed that a higher proportion of the dangling ends are short (5 to 50 bases) and often involve runs of adenosines. While it is possible that mRNAs can possess long polyA tails, we are worried about longer dangling ends since their extra lengths can be results of artefacts in EST sequences or of genomic 'contaminations' at the 3' ends of the ESTs. We do want to include transcript patterns involving those gene-EST alignments with long dangling ends; however, we want to be sure that such dangling ends contain genuine polyA tails and hence we tightened the requirements for polyA tail on long dangling ends as below: (length of dangling end : minimum length of polyA tail) as (= 50 : 8); (>50 & = 100 : 10); (>100 & = 150 : 15); and (>150 : 20). Since it is often the case that a run of adenosines is interrupted by non-adenosine bases, we allow mismatches at up to a maximum of 10% of the positions in the identified string provided the string still contains the required number of adenosines (as per the specification mentioned above); for this purpose, we increase the search window sequence in advance by 10% to take any mismatch into account. If more than one polyA tail is identified starting in the -5 to +5 region, the one with the highest composition of adenosines is chosen as the authentic polyA tail. The gene position corresponding to the start of polyA tail is considered as the cleavage site. As many as 75% of instances of dangling ends showing a putative polyA tail are of shorter lengths (<= 50 bases), 8% are of length 50–100 bases; 4% are of length 100–150 bases, and 13% are of length > 200 bases.
(ii) Detecting polyA signal (PAS)
A region on the gene sequence that aligns to the 40 nt transcript region 5' to the identified cleavage site is scanned for the presence of one of the 13 variant signals (namely, AAUAAA, AUUAAA, UAUAAA, AGUAAA, AAGAAA, AAUAUA, AAUACA, CAUAAA, GAUAAA, AAUGAA, UUUAAA, ACUAAA and AAUAGA) reported in the literature  with the criteria that no mismatch is allowed. For every gene-transcript alignment, all such motifs are identified. Of multiple matches, a representative motif is chosen as per the following criteria: (i) one that occurs within the region of -25 to -15 to the cleavage site is chosen; if multiple such motifs are seen within this region, the one of highest ranking (as ordered in  is chosen; of the highest ranking ones, the one that is close to the position of -20 is chosen; (ii) if no signal is seen in the -25 to -15 region, then those identified outside this region are examined; if multiple signals occur outside the region, the one of highest ranking located close to the position -20 is chosen. A higher proportion of gene-transcript alignments with longer dangling ends (that passed the test for presence of polyA tail) gets removed at this step, when compared to those with shorter dangling ends – we observe the following relationship between length of dangling end and proportion of transcripts failing the signal motif test: < 50 bases : 9%; >50 bases & = 100 bases : 14%; >100 bases & = 200 bases : 25%; and >200 bases : 33%.
(iii) Grouping nearby cleavage sites and choosing a representative cleavage site as polyA site)
At this stage, gene-transcript alignments that do not show both a cleavage site and a polyadenylation signal are not considered further. Steps discussed so far identify for every gene a set of cleavage sites along with polyA signals. It is often the case that some of the identified cleavage sites are close to one another. Given that a polyA site can harbour multiple cleavage sites [3, 25, 37] and also that errors in sequences can lead to small differences in the locations of identified cleavage sites, it is possible that the adjacent sites are not distinct polyA sites. Thus it is essential to have a method in place to identify which of the close by sites can be chosen as an authentic polyA site. The identified cleavage sites are classified onto groups such that a member of a group differs from its immediate 5' neighbour by a maximum of 5 bases; the 5' most site from each such group is then chosen as the representative polyA site for that group of transcripts. Each member gene-transcript alignment of the group is annotated by such a representative polyA site and its associated signal motif.
Forming the transcript pattern classes
At this stage, for every gene a set of gene-transcript sequences with known exon-intron structure and terminating polyA site is available. The transcript sequences are then grouped into classes in such a manner that members of a class show same exon-intron structure and same terminal polyA site. The longest representative member of each such class is termed as a "Transcript Pattern".
Identifying all potential polyA sites (independent of underlying splicing patterns): the AltPAS pipeline
The list of polyA sites as identified by AltTrans pipeline is by no means comprehensive for the reason that AltTrans examines only those gene-transcript alignments confirming AltSplice splice patterns. AltPAS is a generic pipeline that identifies all potential polyA sites irrespective of whether the examined gene-transcript alignments reveal any underlying splicing pattern or not. The methodology used is described in  and is briefly discussed below.
EST sequences and full-length cDNA sequences are obtained from transcript resources such as dbEST , H-Inv , and FANTOM . Of the EST sequences, only those that are annotated as from the 3' end of gene are retained. Trailing polyA or polyT sequences of 5 nt or more are removed from the EST sequences. Both the 3' EST and cDNA sequences (termed transcript sequences) are aligned to the repeat-masked genome using the MegaBlast program . High scoring matches are retained for further analysis. The matches are then clustered in a manner that transcript members from a cluster have their end positions located within a range of 10 nucleotides from each other. Each cluster is then analyzed using a sliding 10-nt window to locate the most likely cleavage site, defined as the position where the window contains the ends of most transcripts. Alignment hits with more than 5 unmatched positions at cleavage site are discarded. Cleavage sites that are flanked by A-rich region (at least 9 out of 10 nt positions are adenosines) in the 50 nt downstream genomic sequence, and those that do not contain one of the known polyA signals in the 30 nt upstream region are discarded. Of the remaining cleavage sites, only those that are supported by at least two transcript sequences are retained as potential polyA sites. The polyA sites, thus identified, are denoted using genome coordinates. Assignment of the detected polyA sites to Ensembl genes is carried out as below: A polyA site is assigned to the Ensembl gene to which the site's genome location can be mapped; if the genome location of a polyA site does not map to any annotated gene, it is assigned to the nearest 5' gene, provided that the distance to gene is less than 3000 bases.
Integrating polyA sites from the AltPAS and AltTrans pipelines
Of the polyA sites identified by the AltPAS pipeline, considered further are only those that can be mapped within the bounds of AltTrans genes. PolyA sites identified by both pipelines are merged. Adjacent polyA sites are then grouped and a representative polyA site is chosen from each group. The procedure adopted for the grouping process is same as that used for grouping AltTrans polyA sites (discussed in earlier sections) with the following variation. If a group contains sites from both AltTrans and AltPAS, the 5' most AltTrans site is chosen as the representative. Such a set of representative polyA sites is subsequently used to annotate a gene with all potential polyA sites, and to annotate a transcript pattern for potentially "skipped" polyA sites. It is to be noted that a transcript pattern in the data set always ends with an AltTrans polyA site as the terminating polyA site.
Statistics on Transcript Pattern Variant Data presented in this work.
Splice patterns (& average number per gene)
Transcript patterns (& average number per gene)
PolyA sites as detected by AltTrans pipeline1 (& average number per gene)
AltTrans polyA sites that are "skipped"
ATD PolyA sites as detected by AltTrans and AltPAS2 pipelines (& average number per gene)
ATD polyA sites that are "skipped"
Genes showing splice events (as seen among the splice patterns)
Genes showing multiple polyA sites (considering the polyA sites from both AltTrans and AltPAS)3
Genes showing both splice events and multiple polyA sites (considering the polyA sites from both AltTrans and AltPAS)
Genes showing multiple polyA sites (considering only the AltTrans polyA sites)4
Genes showing both splice events and polyA events (considering only the AltTrans polyA sites)
Genes showing >= 2 Splice Patterns
Genes showing >= 2 Transcript patterns
EST/mRNA sequences confirming Splice Patterns
EST/mRNA sequences confirming Transcript Patterns
Human data set
The data set of human transcript patterns contains 7669 gene entries for each of which is derived at least one pattern that is fully annotated for both splicing and terminating polyA site. The total number of transcript patterns is 12559 (at an average of 1.6 per gene) encoded by 10221 terminating polyA sites. In 3179 of the 7669 AltTrans genes, two or more alternate transcript patterns could be observed. Inclusion of AltPAS polyA sites annotated an additional 6883 polyA sites raising the number of polyA sites mapped to 17104.
Mouse data set
The data set of mouse transcript patterns contains 5862 gene entries. The total number of transcript patterns is 7755 (at an average of 1.3 per gene) encoded by 6976 terminating polyA sites. In 1548 of the 5862 AltTrans genes, two or more alternate transcript patterns could be observed. Inclusion of AltPAS polyA sites annotated an additional 2475 polyA sites raising the number of polyA sites mapped to 9451.
Extent of alternative splicing versus alternative polyadenylation
Examination of data presented in Table 1 indicates that the proportion of human and mouse genes undergoing alternative splicing (at 74% and 65%, respectively) is higher than the proportion of genes undergoing alternative polyadenylation (at 60% and 42%, respectively). The above estimates are in agreement with those reported in literature – see  for estimate on alternative splicing and [3, 25] on alternative polyadenylation. It is also seen that one in two human genes (close to one in three mouse genes) may undergo both alternative splicing and alternative polyadenylation. Considering only the polyA sites detected by the AltTrans pipeline (which requires that transcripts that confirm a polyA site also confirm the splicing of the transcript pattern) reveals a conservative estimate for extent of alternative polyadenylation at 27% for human and 18% for mouse.
Limitations with regard to low number of reported transcript patterns
There is a large discrepancy in the numbers for observed splice patterns and observed transcript patterns. While the average number of observed splice patterns per human gene is 5.4, the average number of observed transcript patterns is a mere 1.6 (the corresponding numbers in the case of mouse data are 4.6 and 1.3). This discrepancy is due to the fact that for an EST/mRNA sequence to confirm a transcript pattern, it is required that the sequence confirms both the splicing and terminating polyA site. EST sequences do not often cover simultaneously both the internal and 3' regions of the gene – this is reflected in the observed numbers (see Table 1) for the EST/mRNA sequences that confirm splice patterns and transcript patterns (e.g. of the 837828 EST/mRNA sequences that confirm the human splice patterns, a mere 38731 contain enough information to confirm transcript pattern). As a result, the number of identified polyA sites by the AltTrans pipeline is expected to be reduced AltTrans detected 10221 polyA sites in 7669 human genes. AltPAS, that detects polyA sites independently of the underlying splicing process, mapped a further 6883 polyA sites to the same set of 7669 human genes. It is possible to increase the number of transcript patterns by using the AltPAS polyA sites as well to annotate the gene-transcript alignment for 'terminating' polyA site; however, we have restrained from doing this for the reason that it is our intention to provide a high quality set of transcript patterns, individual structural elements of which are confirmed by same set of EST/mRNA sequences.
Heterogeneity of cleavage sites
Core data and derived annotations
The core of the generated data comprises the following components: (i) Genes and transcript data; (ii) introns/exons, polyA sites; (iii) isoform splice patterns, isoform transcript patterns, isoform peptide sequences; and (iii) alternative splice events, alternative polyadenylation events. Various value-added annotations are also generated, some of which are as described below.
Preservation of splice events across species
An important part of our pipeline is to generate evolutionary profiles of gene expression patterns. Methods based on the identification of conserved introns/exons and of conserved splice events  have been standardized to delineate pairs of human and mouse genes that are orthologous to each other. This data enables studies on evolutionary profiles of expression patterns.
Association with data on genetic variation (SNP, single nucleotide polymorphism)
We have developed methods (as documented in the ATD web pages) to delineate the allele specificity of observed alternative splice patterns.
Derivation of peptide sequences coded by isoform splices patterns
We have developed methods to delineate the amino acid sequence of the protein sequences encoded by the isoform splice patterns.
Data access and query interfaces
The data was generated as part of the European Project on Alternate Transcript Diversity (ATD). The data can be downloaded as flat files or queried through web interfaces. The web interface provides single-box query (where a user can search the database against a keyword or gene symbol or database cross-references) or a detailed query page that searches simultaneously both the human and mouse data or a query page that provides advanced searches to either human or mouse data.
Genes can be queried by chromosomal location, gene names and synonyms, protein keywords, and database cross-references [such as EMBL and UniProt accession numbers [36, 45], HUGO gene symbols , Gene Ontology identifiers  and protein identifiers], types of splice events, types of polyA signal, number of observed polyA sites, and types of variations among isoform transcript patterns (a pair of isoform transcript patterns may differ only in splicing or only in polyadenylation or in both). Queries can be selectively restricted to specific sets of gene entries, such as set of human-mouse orthologous gene pairs or set of gene entries for which data on isoform peptide sequences is available.
Data presentation (textual & graphical displays) and integration
An output page resulting from a query to the database lists for every gene entry all the available database cross-references; an important aspect being hyperlinks to orthologous genes from other organisms (currently implemented for human and mouse).
The AltTrans data has been integrated with the Ensembl genome annotation project and is visible as DAS (Distributed Annotation System) tracks from the gene view and contigview pages in Ensembl genome browser (Fig. 6B).
We present here an integrated data set of transcript-confirmed introns/exons, polyA sites, isoform splice patterns, isoform transcript sequences, isoform peptide sequences, alternative splice events, and alternative polyadenylation events. The data is presented for both mouse and human. Future work will aim to annotate the alternate transcripts for transcription start sites and their variants. In its future extension, this work should ultimately present high quality data on full-length transcript patterns annotated for transcription start site, splice sites, and polyadenylation sites; with each of these individual signals annotated for variations and for biological characteristics such as regulatory motifs and evolutionary profile.
Availability and requirements
Release 1 of the integrated AltTrans data, presented in this manuscript, is available from http://www.ebi.ac.uk/atd. Enquiries on accessing the data can be mailed to email@example.com.
file transfer protocol
expressed sequence tag
database of Expressed Sequence Tags
Functional Annotation of the mouse
Basic Local Alignment Search Tool
Alternative Splicing Database
Alternative Exon Database
Alternate Transcript Diversity Database
Serial Analysis of Gene Expression
reverse transcription-polymerase chain reaction
Universal Protein Resource.
T.A.T. and D.G. acknowledge the European Commission for the grant (LSHG-CT-2003-503329) that supports this work. Andreas Kahari is acknowledged for his help in integrating the AltTrans data with Ensembl genome annotation project as DAS tracks visible from Ensembl genome browser.
- Landry JR, Mager DL, Wilhelm BT: Complex controls: the role of alternative promoters in mammalian genomes. Trends Genet 2003, 19: 640–648. 10.1016/j.tig.2003.09.014View ArticlePubMedGoogle Scholar
- Smith CW, Valcarcel J: Alternative pre-mRNA splicing: the logic of combinatorial control. Trends Biochem Sci 2000, 25: 381–388. 10.1016/S0968-0004(00)01604-2View ArticlePubMedGoogle Scholar
- Tian B, Hu J, Zhang H, Lutz CS: A large-scale analysis of mRNA polyadenylation of human and mouse genes. Nucleic Acids Res 2005, 33: 201–212. 10.1093/nar/gki158PubMed CentralView ArticlePubMedGoogle Scholar
- Zavolan M, Kondo S, Schönbach C, Adachi J, Hume DA, RIKEN GER Group, Members GSL, Hayashizaki Y, Gaasterland T: Impact of Alternative Initiation, Splicing, and Termination on the Diversity of the mRNA Transcripts Encoded by the Mouse Transcriptome. Genome Res 2003, 13: 1290–1300. 10.1101/gr.1017303PubMed CentralView ArticlePubMedGoogle Scholar
- Cramer P, Pesce CG, Baralle FE, Kornblihtt AR: Functional association between promoter structure and transcript alternative splicing. Proc Natl Acad Sci USA 1997, 94: 11456–11460. 10.1073/pnas.94.21.11456PubMed CentralView ArticlePubMedGoogle Scholar
- Suzuki Y, Yamashita R, Sugano S, Nakai K: DBTSS, DataBase of Transcriptional Start Sites: progress report 2004. Nucleic Acids Res 2004, 32: 78–81. 10.1093/nar/gkh076View ArticleGoogle Scholar
- Trinklein ND, Aldred SJF, Saldanha AJ, Myers RM: Identification and Functional Analysis of Human Transcriptional Promoters. Genome Res 2003, 13: 308–312. 10.1101/gr.794803PubMed CentralView ArticlePubMedGoogle Scholar
- Halees AS, Leyfer D, Weng Z: PromoSer: a large-scale mammalian promoter and transcription start site identification service. Nucleic Acids Res 2003, 31: 3554–3559. 10.1093/nar/gkg549PubMed CentralView ArticlePubMedGoogle Scholar
- Schmid CD, Praz V, Delorenzi M, Périer R, Bucher P: The Eukaryotic Promoter Database EPD: the impact of in silico primer extension. Nucleic Acids Res 2004, 32: D82–85. 10.1093/nar/gkh122PubMed CentralView ArticlePubMedGoogle Scholar
- Thanaraj TA, Stamm S: Prediction and statistical analysis of alternatively spliced exons. Progress in Molecular and Subcellular Biology 2003, 31: 1–31.View ArticlePubMedGoogle Scholar
- Thanaraj TA, Stamm S, Clark F, Riethoven J-JM, Le Texier V, Muilu J: ASD: the Alternative Splicing Database. Nucleic Acids Res 2004, 32: D64-D69. 10.1093/nar/gkh030PubMed CentralView ArticlePubMedGoogle Scholar
- Stamm S, Riethoven J-JM, Le Texier V, Gopalakrishnan C, Kumanduri V, Tang Y, Barbosa-Morais NL, Thanaraj TA: ASD: a bioinformatics resource on alternative splicing. Nucleic Acids Res 2006, 34: D46-D55. 10.1093/nar/gkj031PubMed CentralView ArticlePubMedGoogle Scholar
- Clark F, Thanaraj TA: Categorization and characterization of transcript-confirmed constitutively and alternatively spliced introns and exons from human. Hum Mol Genet 2002, 11: 451–464. 10.1093/hmg/11.4.451View ArticlePubMedGoogle Scholar
- Leipzig J, Pevzner P, Heber S: The Alternative Splicing Gallery (ASG): bridging the gap between genome and transcriptome. Nucleic Acids Res 2004, 32: 3977–3983. 10.1093/nar/gkh731PubMed CentralView ArticlePubMedGoogle Scholar
- Zheng CL, Nair TM, Gribskov M, Kwon YS, Li HR, Fu XD: Manually Annotated Alternatively Spliced Events (MAASE) database. Pac Symp Biocomput 2004, 9: 78–88.Google Scholar
- Huang HD, Horng JT, Lee CC, Liu BJ: ProSplicer: a database of putative alternative splicing information derived from protein, mRNA and expressed sequence tag sequence data. Genome Biol 2003, 4: R29. 10.1186/gb-2003-4-4-r29PubMed CentralView ArticlePubMedGoogle Scholar
- Kim P, Kim N, Lee Y, Kim B, Shin Y, Lee S: ECgene: genome annotation for alternative splicing. Nucleic Acids Res 2005, 33: D75-D79. 10.1093/nar/gki118PubMed CentralView ArticlePubMedGoogle Scholar
- Huang H-D, Horng J-T, Lin F-M, Chang Y-C, Huang C-C: SpliceInfo: an information repository for mRNA alternative splicing in human genome. Nucleic Acids Res 2005, 33: D80-D85. 10.1093/nar/gki129PubMed CentralView ArticlePubMedGoogle Scholar
- Pospisil H, Herrmann A, Bortfeldt RH, Reich JG: EASED:Extended Alternatively Spliced EST Database. Nucleic Acids Res 2004, 32: 70–74. 10.1093/nar/gkh136View ArticleGoogle Scholar
- Ji H, Zhou Q, Wen F, Xia H, Lu X, Li Y: AsMamDB: an alternative splice database of mammals. Nucleic Acids Res 2001, 29: 260–263. 10.1093/nar/29.1.260PubMed CentralView ArticlePubMedGoogle Scholar
- Dralyuk M, Brudno M, Gelfand MS, Zorn M, Dubchak I: ASDB: database of alternatively spliced genes. Nucleic Acids Res 2000, 28: 296–297. 10.1093/nar/28.1.296PubMed CentralView ArticlePubMedGoogle Scholar
- Huang Y-H, Chen Y-T, Lai J-J, Yang S-T, Yang U-C: PALS db: Putative Alternative Splicing database. Nucleic Acids Res 2002, 30: 186–190. 10.1093/nar/30.1.186PubMed CentralView ArticlePubMedGoogle Scholar
- Gupta S, Zink D, Korn B, Vingron M, Haas SA: Genome wide identification and classification of alternative splicing based on EST data. Bioinformatics 2004, 20: 2579–2585. 10.1093/bioinformatics/bth288View ArticlePubMedGoogle Scholar
- Lee C, Atanelov L, Modrek B, Xing Y: ASAP: the Alternative Splicing Annotation Project. Nucleic Acids Res 2003, 31: 101–105. 10.1093/nar/gkg029PubMed CentralView ArticlePubMedGoogle Scholar
- Beaudoing E, Gautheret D: Identification of alternate polyadenylation sites and analysis of their tissue distribution using EST data. Genome Res 2001, 9: 1520–1526. 10.1101/gr.190501View ArticleGoogle Scholar
- Zhang H, Hu J, Recce M, Tian B: PolyA_DB: a database for mammalian mRNA polyadenylation. Nucleic Acids Res 2005, 33: D116-D120. 10.1093/nar/gki055PubMed CentralView ArticlePubMedGoogle Scholar
- Kan Z, Rouchka EC, Gish WR, States DJ: Gene structure prediction and alternative splicing analysis using genomically aligned ESTs. Genome Res 2001, 11: 889–900. 10.1101/gr.155001PubMed CentralView ArticlePubMedGoogle Scholar
- Yan J, Marr TG: Computational analysis of 3'-ends of ESTs shows four classes of alternative polyadenylation in human, mouse, and rat. Genome Res 2005, 15: 369–75. 10.1101/gr.3109605PubMed CentralView ArticlePubMedGoogle Scholar
- Maniatis T, Reed R: An extensive network of coupling among gene expression machines. Nature 2002, 416: 499–506. 10.1038/416499aView ArticlePubMedGoogle Scholar
- Calvo O, Manley JL: Strange bedfellows: polyadenylation factors at the promoter. Genes Dev 2003, 17: 1321–1327. 10.1101/gad.1093603View ArticlePubMedGoogle Scholar
- Neugebauer KM: On the importance of being co-transcriptional. J. Cell. Sci 2002, 115: 3865–3871. 10.1242/jcs.00073View ArticlePubMedGoogle Scholar
- Sanford JR, Caceres JF: Pre-mRNA splicing: life at the centre of the central dogma. J Cell Sci 2004, 117: 6261–6263. 10.1242/jcs.01513View ArticlePubMedGoogle Scholar
- Kornblihtt AR, De La Mata M, Fededa JP, Munoz MJ, Nogues G: Multiple links between transcription and splicing. RNA 2004, 10: 1489–1498. 10.1261/rna.7100104PubMed CentralView ArticlePubMedGoogle Scholar
- Sharov A, Dudekula DB, Ko MSH: Genome-wide assembly and analysis of alternative transcripts in mouse. Genome Res 2005, 15: 748–754. 10.1101/gr.3269805PubMed CentralView ArticlePubMedGoogle Scholar
- Hubbard T, Andrews D, Caccamo M, Cameron G, Chen Y, Clamp M, Clarke L, Coates G, Cox T, Cunningham F, Curwen V, Cutts T, Down T, Durbin R, Fernandez-Suarez XM, Gilbert J, Hammond M, Herrero J, Hotz H, Howe K, Iyer V, Jekosch K, Kahari A, Kasprzyk A, Keefe D, Keenan S, Kokocinsci F, London D, Longden I, McVicker G, Melsopp C, Meidl P, Potter S, Proctor G, Rae M, Rios D, Schuster M, Searle S, Severin J, Slater G, Smedley D, Smith J, Spooner W, Stabenau A, Stalker J, Storey R, Trevanion S, Ureta-Vidal A, Vogel J, White S, Woodwark C, Birney E: Ensembl 2005. Nucleic Acids Res 2005, 33: D447-D453. 10.1093/nar/gki138PubMed CentralView ArticlePubMedGoogle Scholar
- Kanz C, Aldebert P, Althorpe N, Baker W, Baldwin A, Bates K, Browne P, van den Broek A, Castro M, Cochrane G, Duggan K, Eberhardt R, Faruque N, Gamble J, Diez FG, Harte N, Kulikova T, Lin Q, Lombard V, Lopez R, Mancuso R, McHale M, Nardone F, Silventoinen V, Sobhany S, Stoehr P, Tuli MA, Tzouvara K, Vaughan R, Wu D, Zhu W, Apweiler R: The EMBL Nucleotide Sequence Database. Nucleic Acids Res 2005, 33: D29-D33. 10.1093/nar/gki098PubMed CentralView ArticlePubMedGoogle Scholar
- Pauws E, van Kampen AH, van de Graaf SA, de Vijlder JJ, Ris-Stalpers C: Heterogeneity in polyadenylation cleavage sites in mammalian mRNA sequences: implications for SAGE analysis. Nucleic Acids Res 2001, 29: 1690–1694. 10.1093/nar/29.8.1690PubMed CentralView ArticlePubMedGoogle Scholar
- Boguski MS, Lowe TM, Tolstoshev CM: dbEST--database for expressed sequence tags. Nat Genet 1993, 4: 332–333. 10.1038/ng0893-332View ArticlePubMedGoogle Scholar
- Imanishi T, Itoh T, Suzuki Y, O'Donovan C, Fukuchi S, Koyanagi KO, Barrero RA, Tamura T, Yamaguchi-Kabata Y, Tanino M, Yura K, Miyazaki S, Ikeo K, Homma K, Kasprzyk A, Nishikawa T, Hirakawa M, Thierry-Mieg J, Thierry-Mieg D, Ashurst J, Jia L, Nakao M, Thomas MA, Mulder N, Karavidopoulou Y, Jin L, Kim S, Yasuda T, Lenhard B, Eveno E, Suzuki Y, Ya-masaki C, Takeda J, Gough C, Hilton P, Fujii Y, Sakai H, Tanaka S, Amid C, Bellgard M, Mde FBM, Bono H, Bromberg SK, Brookes AJ, Bruford E, Carninci P, Chelala C, Couillault C, Souza SJ, Debily MA, Devignes MD, Dubchak I, Endo T, Estreicher A, Eyras E, Fukami-Kobayashi K, Gopinath GR, Graudens E, Hahn Y, Han M, Han ZG, Hanada K, Hanaoka H, Harada E, Hashimoto K, Hinz U, Hirai M, Hishiki T, Hopkinson I, Imbeaud S, Inoko H, Kanapin A, Kaneko Y, Kasukawa T, Kelso J, Kersey P, Kikuno R, Kimura K, Korn B, Kuryshev V, Makalowska I, Makino T, Mano S, Mariage-Samson R, Mashima J, Matsuda H, Mewes HW, Minoshima S, Nagai K, Nagasaki H, Nagata N, Nigam R, Ogasawara O, Ohara O, Ohtsubo M, Okada N, Okido T, Oota S, Ota M, Ota T, Otsuki T, Piatier-Tonneau D, Poustka A, Ren SX, Saitou N, Sakai K, Sakamoto S, Sakate R, Schupp I, Servant F, Sherry S, Shiba R, Shimizu N, Shimoyama M, Simpson AJ, Soares B, Steward C, Suwa M, Suzuki M, Takahashi A, Tamiya G, Tanaka H, Taylor T, Terwilliger JD, Unneberg P, Veeramachaneni V, Watanabe S, Wilming L, Yasuda N, Yoo HS, Stodolsky M, Makalowski W, Go M, Nakai K, Takagi T, Kanehisa M, Sakaki Y, Quackenbush J, Okazaki Y, Hayashizaki Y, Hide W, Chakraborty R, Nishikawa K, Sugawara H, Tateno Y, Chen Z, Oishi M, Tonellato P, Apweiler R, Okubo K, Wagner L, Wiemann S, Strausberg RL, Isogai T, Auffray C, Nomura N, Gojobori T, Sugano S: Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones. PLoS Biology 2004, 2: 856–875. 10.1371/journal.pbio.0020162View ArticleGoogle Scholar
- Carninci P, Waki K, Shiraki T, Konno H, Shibata K, Itoh M, Aizawa K, Arakawa T, Ishii Y, Sasaki D, Bono H, Kondo S, Sugahara Y, Saito R, Osato N, Fukuda S, Sato K, Watahiki A, Hirozane-Kishikawa T, Nakamura M, Shibata Y, Yasunishi A, Kikuchi N, Yoshiki A, Kusakabe M, Gustincich S, Beisel K, Pavan W, Aidinis V, Nakagawara A, Held WA, Iwata H, Kono T, Nakauchi H, Lyons P, Wells C, Hume DA, Fagiolini M, Hensch TK, Brinkmeier M, Camper S, Hirota J, Mombaerts P, Muramatsu M, Okazaki Y, Kawai J, Hayashizaki Y: Targeting a Complex Transcriptome: The Construction of the Mouse Full-Length cDNA Encyclopedia. Genome Res 2003, 13: 1273–1289. 10.1101/gr.1119703PubMed CentralView ArticlePubMedGoogle Scholar
- Mcginnis S, Madden T: BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res 2004, 32: W20-W25. 10.1093/nar/gnh003PubMed CentralView ArticlePubMedGoogle Scholar
- Johnson JM, Castle J, Garrett-Engele P, Kan Z, Loerch PM, Armour CD, Santos R, Schadt EE, Stoughton R, Shoemaker DD: Genome-Wide Survey of Human Alternative Pre-mRNA Splicing with Exon Junction. Microarrays. Science 2003, 302: 2141–2144. 10.1126/science.1090100View ArticlePubMedGoogle Scholar
- Hajarnavis A, Korf I, Durbin R: A probabilistic model of 3' end formation in Caenorhabditis elegans . Nucleic Acids Res 2004, 32: 3392–3399. 10.1093/nar/gkh656PubMed CentralView ArticlePubMedGoogle Scholar
- Thanaraj TA, Clark F, Muilu J: Conservation of human alternative splice events in mouse. Nucleic Acids Res 2003, 31: 2544–2552. 10.1093/nar/gkg355PubMed CentralView ArticlePubMedGoogle Scholar
- Bairoch A, Apweiler R, Wu CH, Barker WC, Boeckmann B, Ferro S, Gasteiger E, Huang H, Lopez R, Magrane M, Martin MJ, Natale DA, O'Donovan C, Redaschi N, Yeh LS: The Universal Protein Resource (UniProt). Nucleic Acids Res 2005, 33: D154–159. 10.1093/nar/gki070PubMed CentralView ArticlePubMedGoogle Scholar
- Wain HM, Lush M, Ducluzeau F, Povey S: Genew: the Human Gene Nomenclature Database. Nucleic Acids Res 2002, 30: 169–171. 10.1093/nar/30.1.169PubMed CentralView ArticlePubMedGoogle Scholar
- Ashburner M, Ball CA, Blake JA, Butler H, Cherry JM, Corradi J, Dolinski K, Janan T, Eppig JT, Harris M, Hill DP, Lewis S, Marshall B, Mungall C, Reiser L, Rhee S, Richardson JE, Richter J, Ringwald M, Rubin GM, Sherlock G, Yoon J: Creating the Gene Ontology resource: design and implementation. Genome Res 2001, 11: 1425–1433. 10.1101/gr.180801View ArticleGoogle Scholar
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