NetUTR - 1.0b

Splice sites in 5' UTR regions of human genes

The NetUTR 1.0 server predicts splice sites in 5' UTR regions of human genes.


Sequence submission:

Paste a single sequence or several sequences in FASTA format into the field below:

Alternatively, submit a file in FASTA format directly from your local disk:

Currently at most 200 sequences and 500,000 nucleotides per submission, no sequence longer than 500,000 nucleotides.
The sequences are kept confidential and will be deleted after processing.


For publication of results, please cite:

Analysis and recognition of 5' UTR intron splice sites in human pre-mRNA.
E. Eden and S. Brunak.
Nucleic Acids Research, 33:1131-1142, 2004.


1. Specify the input sequences

All the input sequences must be in one-letter nucleotide code. The allowed alphabet (not case sensitive) is as follows:

A C G T and X (unknown)

All the non-alphabetic symbols will be ignored; all the alphabetic symbols not in the alphabet will be converted to X before processing. The sequences can be input in the following two ways:

  • Paste a single sequence (just the amino acids) or a number of sequences in FASTA format into the upper window of the main server page.

  • Select a FASTA file on your local disk, either by typing the file name into the lower window or by browsing the disk.

Both ways can be employed at the same time: all the specified sequences will be processed. However, currently there may be not more than 200 sequences and 500,000 nucleotides in total in one submission. Sequences longer than 500,000 nucleotides are not allowed.

2. Customize your run

Currently no custom options are enabled.

3. Submit the job

Click on the "Submit" button. The status of your job (either 'queued' or 'running') will be displayed and constantly updated until it terminates and the server output appears in the browser window.

At any time during the wait you may enter your e-mail address and simply leave the window. Your job will continue; you will be notified by e-mail when it has terminated. The e-mail message will contain the URL under which the results are stored; they will remain on the server for 24 hours for you to collect them.

Output format


The output conforms to the GFF version 2 format. For each input sequence the server prints a list of predicted splice sites, both donor and acceptor, showing their positions in the sequence and the prediction confidence scores. Only the sites with scores higher than 0.5 are predicted as splice sites and reported in the list. The sites with the scores higher than 0.8 are marked with 'H' as high confidence predictions.

The example below shows the NetUTR 1.0 output for the sequence taken from the GenBank entry X05196, containing the human aldolase C gene. The 5' UTR intron (155-1411) in that gene is predicted correctly, with high confidence.


##gff-version 2
##source-version netUTR-1.0b
##date 2006-03-16
##Type DNA
# seqname            source        feature    start     end  score +/-   ?
# ---------------------------------------------------------------------------
X05196               netUTR-1.0b   acceptor     512     512  0.575  +    
X05196               netUTR-1.0b   acceptor     577     577  0.692  +    
X05196               netUTR-1.0b   acceptor    1189    1189  0.631  +    
X05196               netUTR-1.0b   acceptor    1411    1411  0.861  +    H
X05196               netUTR-1.0b   acceptor    1621    1621  0.501  +    
X05196               netUTR-1.0b   acceptor    1949    1949  0.755  +    
X05196               netUTR-1.0b   acceptor    2378    2378  0.831  +    H
X05196               netUTR-1.0b   acceptor    2590    2590  0.604  +    
X05196               netUTR-1.0b   acceptor    3334    3334  0.532  +    
X05196               netUTR-1.0b   acceptor    3692    3692  0.574  +    
X05196               netUTR-1.0b   acceptor    5292    5292  0.522  +    
X05196               netUTR-1.0b   donor        155     155  0.971  +    H
X05196               netUTR-1.0b   donor        993     993  0.612  +    
X05196               netUTR-1.0b   donor       1536    1536  0.623  +    
X05196               netUTR-1.0b   donor       2261    2261  0.508  +    
X05196               netUTR-1.0b   donor       2463    2463  0.604  +    
X05196               netUTR-1.0b   donor       3335    3335  0.509  +    
X05196               netUTR-1.0b   donor       4297    4297  0.589  +    
X05196               netUTR-1.0b   donor       4455    4455  0.625  +    
X05196               netUTR-1.0b   donor       5929    5929  0.616  +    
# ---------------------------------------------------------------------------


Analysis and recognition of 5' UTR intron splice sites in human pre-mRNA.
E. Eden and S. Brunak.,
Nucleic Acids Research,33:1131-1142, 2004.


Prediction of splice sites in non-coding regions of genes is one of the most challenging aspects of gene structure recognition. We perform a rigorous analysis of such splice sites embedded in human 5' UTR regions, and investigate correlations between this class of splice sites and other features found in the adjacent exons and introns. By restricting the training of neural network algorithms to 'pure' untranslated regions (not extending partially into protein coding regions), we for the first time investigate the predictive power of the splicing signal proper in contrast to conventional splice site prediction, which typically rely on the change in sequence at the transition from protein coding to non-coding. By doing so the algorithms were able to pick up subtler splicing signals that were otherwise masked by 'coding' noise thus enhancing significantly the prediction of 5' UTR splice sites. For example, the non-coding splice site predicting networks pick up compositional and positional bias in the 3' ends of non-coding exons and 5' non-coding intron ends, where cytosine and guanine are overrepresented. This compositional bias at the true UTR donor sites is also visible in the synaptic weights of the neural networks trained to identify UTR donor sites. Conventional splice site prediction methods perform poorly in UTR regions, because the reading frame pattern is absent. The NetUTR method presented here performs 2-3 fold better compared to NetGene2 and GenScan in 5' UTR regions. We also tested the 5' UTR trained method on protein coding regions, and discovered surprisingly that it works quite well (although it cannot compete with NetGene2). This indicates that the local splicing pattern in UTR and coding regions largely is the same.


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