Intron exon prediction tool

With more and more genomes being sequenced, the comparative approaches become more feasible. Several programs, e. In addition to the comparative analysis between genomes, evidences from related organisms have been employed in the comparative approaches. This paper presents a web tool, GeneAlign, for protein coding gene prediction. Same as Projector, GeneAlign employs annotated genes of one organism to predict the homologous genes of another organism.

GeneAlign integrates signal detectors with CORAL 10 to efficiently align annotated coding exons with queried sequences. CORAL, a heuristic alignment program, aligns coding regions between two phylogenetically close organisms in linear time.

The approach applied by GeneAlign can identify distinctive features of well conserved gene structures and protein coding sequences between phylogenetically close organisms. GeneAlign assumes the conservation of the exon—intron structures, but it can also align some exons which differ by events of exon-splitting and exon-fusion. In addition, GeneAlign has an explicit procedure for detecting micro-exons, which is usually a difficult task for eukaryotic gene prediction Despite their small sizes, experimental studies support that small exons are usually conserved between organisms A procedure for identifying micro-exons has been developed by Volfovsky et al.

GMAP 6 furthers this work by integrating the detection procedure into the framework of a cDNA-genomic alignment program. GeneAlign looks for potential micro-exons with the appropriate boundaries and computes the optimal alignments for these potential micro-exons and corresponding annotated exons.

GeneAlign can predict gene structure by employing a fairly diverged annotated genome with conserved gene structure. Here, we show that GeneAlign performs well in identifying coding exons; specifically the rates of missing exons and wrong exons are both low. GeneAlign accepts 2 nt sequences of homologous genes and the known gene annotation of one of these two genes as inputs and predicts the coding exon positions in another sequence according to the known gene annotation.

The major components of GeneAlign for annotation-genome mapping and alignment include: i signal filtrations, ii applying CORAL to measure the sequence homologies following candidate signals for generating approximate gene structures and iii recognition of micro-exons. Splice sites are the most powerful signals for gene prediction, accurate modeling splice sites can improve the accuracy of gene prediction 1. The GeneSplicer, combined the Markov modeling techniques with a decision tree method maximal dependence decomposition , detects splice sites in various eukaryotic genomes.

The GeneSplicer can efficiently filter out many false splice signals but failed to remove false signals resulting from highly degenerate and unspecific nature. CORAL 10 is integrated to measure sequence homologies between potential regions marked by splice signals and annotated exons.

CORAL is developed on the basis of the conservation of coding regions. Most of coding regions among organisms are conserved at the amino acid level, suggesting that the hamming distance of two segments with an optimal alignment is low. Relative to SPA 19 , a probabilistic filtration method is built to efficiently find an ill-positioned pair. The ill-positioned pair is a less than optimal alignment, which is supposed to result from a shifting mutation and can be solved by inserting a gap with a length of a multiple of three.

A local optimal solution is used to obtain a significant alignment when an ill-positioned pair is detected and to determine the possible position and length for the inserted gap. CORAL employs the probabilistic analysis and the local optimal solution to efficiently align sequences by sliding windows and, thus, obtains a near optimal alignment in linear time.

GeneAlign is designed for detecting multi-exons genes. The coding exons are divided into three categories according to their location in the coding region, initial exon initiation codon-GT, first coding exon of a gene , internal exon AG-GT and terminal exon AG-stop codon, last coding exon of a gene. The alignments by CORAL are processed from the splice acceptors by aligning the first annotated internal exons with regions following the candidate splice acceptors. CORAL stops aligning when the alignment score drops significantly.

Candidate splice acceptors and the next annotated exons are examined subsequently to search for meaningful alignments. For each aligned segment, the downstream boundary is delimited by an admissible candidate splice donor.

A series of aligned segments is ended at the annotated terminal exon and delimited by a stop codon, e. If the annotated exons cannot be mapped to the queried sequence, a lower threshold of the alignment score, e. Although GeneAlign is designed to predict multi-exons genes, it can also predict single-exon genes with same structures by aligning the annotated exons with regions following the candidate translation initiation sites, which are predicted using a weight matrix model WMM The micro-exons, smaller than 30 bp in length, are frequently encountered in the eukaryotic genomes 6 , 17 ; however, they cannot be detected by applying CORAL.

Micro-exons in the annotated genes are processed by an additional procedure. Our method assumes that micro-exons are flanked by canonical boundaries. The sequence alignment is processed by a standard dynamic programming algorithm in order to compute the optimal alignment. The sequence homologies are assessed at the amino acid level by translating corresponding segments according to annotated translational reading frame and the genetic code.

The alignment only applied in a specific region of nucleotide sequence corresponding to the position of micro-exon in the annotated gene. In addition, a large splice site score e. GeneAlign applies CORAL based on the codon identity to efficiently find the partner exons to those of related known genes. The parameters are optimized by the IMOG dataset 8 of 15 homologous human—mouse gene pairs The testing dataset is the Projector dataset 12 which collects homologous human—mouse gene pairs not overlapping with the training set.

The average number of exons per gene in the test set is 8. Forty four percent of these gene pairs out of have the identical number of coding exons and the identical coding sequence length. Fifty one percent out of have identical exons number but differ in coding sequence length.

Five percent 26 out of have different number of exons. The human—mouse gene pairs share 14 initial micro-exons and 15 terminal micro-exons. They differ in the numbers of internal micro-exons that mouse has 18 and human has 19 internal micro-exons. The performance of GeneAlign was evaluated separately by the accuracy of predictions for human and mouse genes and was compared with the outputs from Projector and GeneWise The Projector program predicts gene structures by using the annotated genes of a related organism, which is the same with GeneAlign.

The GeneWise program, predicting gene structures by using the known proteins of a related organism, serves as a benchmark We measured the performance in terms of sensitivity and specificity at both the exon and the gene levels.

The results are summarized in Table 1. These results show that the predictions obtained by GeneAlign are accurate at both levels. Directly callable from ou sequencing software Gensearch. A fast, flexible system for detecting splice sites in the genomic DNA of various eukaryotes. The system has been trained and tested successfully on Plasmodium falciparum malaria , Arabidopsis thaliana, human, Drosophila, and rice. Training data sets for human and Arabidopsis thaliana are included.

Use the GeneSplicer Web Interface to run GeneSplicer directly, or see below for instructions on downloading the complete system including source code. The NetGene2 server is a service producing neural network predictions of splice sites in human, C. ASSP predicts putative alternative exon isoform, cryptic, and constitutive splice sites of internal coding exons.

Skipped splice sites are not differentiated from constitutive sites. Non-canonical splice sites are not detected. For splice site prediction within a sequence putative splice sites are preprocessed using position specific score matrices. SplicePort is a web-based tool for splice-site analysis that allows the user to make splice-site predictions for submitted sequences.

In addition, the user can also browse the rich catalog of features that underlies these predictions, and which we the authors have found capable of providing high classification accuracy on human splice sites. Feature selection is optimized for human splice sites, but the selected features are likely to be predictive for other mammals as well. MaxEntScan is based on the approach for modeling the sequences of short sequence motifs such as those involved in RNA splicing which simultaneously accounts for non-adjacent as well as adjacent dependencies between positions.

Gene Prediction in Viruses, Phages and Plasmids. Sequences of viruses, phages or plasmids can be analyzed either by the GeneMark. All the software programs mentioned here are available for download and local installation. Contact Us Home.