The ORF Finder tool identifies all potential protein-coding regions (Open Reading Frames) in DNA sequences by scanning all six reading frames. This comprehensive analysis is essential for:
- **Gene prediction**: Identifying potential coding regions in genomic sequences - **Annotation of novel sequences**: Analyzing sequences from unknown organisms - **Plasmid analysis**: Verifying cloned inserts and identifying coding regions - **Sequence verification**: Confirming gene boundaries and start/stop codons
**What are ORFs?** Open Reading Frames are sequences of DNA that begin with a start codon (ATG) and end with a stop codon (TAA, TAG, or TGA). They represent potential protein-coding genes, though not all ORFs encode functional proteins.
Why scan all 6 frames?** DNA is double-stranded, and genes can be located on either strand. The tool scans: - 3 forward frames (reading frames 0, 1, 2 on the forward strand) - 3 reverse complement frames (reading frames 0, 1, 2 on the reverse strand)
This ensures complete coverage of potential coding regions regardless of strand orientation.
Supported formats
- Raw DNA sequence (A, T, G, C characters) - FASTA format (with or without header) - Sequences of any length (recommended: 100+ nucleotides for meaningful results)
Sequence requirements
- Must contain only valid DNA nucleotide characters: A, T, G, C - Case insensitive (both uppercase and lowercase accepted) - Minimum length: 30 nucleotides (to detect minimum ORF length) - Ambiguity codes (N, R, Y, etc.) are accepted but may affect accuracy
Parameters
- **Minimum ORF length**: Default is 30 nucleotides (10 amino acids) - Smaller values (e.g., 30-60 bp): Detects shorter ORFs, more sensitive but may include false positives - Larger values (e.g., 100-300 bp): More conservative, detects only longer ORFs typical of real genes
Example input
``` ATGCGATCGATCGATCGATGCGATCGATCGATCGTAACGTAGCGATCGATCGATGCGATCGATCGATCGTAACGTAG ```
Or FASTA format: ``` >my_sequence ATGCGATCGATCGATCGATGCGATCGATCGATCGTAACGTAGCGATCGATCGATGCGATCGATCGATCGTAACGTAG ```
ORF Detection Algorithm
The tool uses the standard genetic code (translation table 1) to identify ORFs:
1. **Start codon detection**: Identifies all ATG codons as potential start sites 2. **Stop codon detection**: Finds the first downstream stop codon (TAA, TAG, or TGA) 3. **Frame assignment**: Determines which reading frame (0, 1, or 2) the ORF belongs to 4. **Strand determination**: Identifies whether the ORF is on the forward (+) or reverse (-) strand 5. **Translation**: Translates the nucleotide sequence to amino acids using the standard genetic code
Coordinate system
- Uses 1-based coordinates (first nucleotide is position 1) - Start position: First nucleotide of the start codon - End position: Last nucleotide of the stop codon - Length: Number of nucleotides including start and stop codons
Reverse complement handling
For ORFs on the reverse strand, the tool: - Identifies the ORF in the reverse complement sequence - Reports positions relative to the original forward strand - Provides the sequence in the original orientation for clarity
ORF Results Table
The tool provides comprehensive information for each detected ORF:
- **Start**: Start position (1-based coordinate of the first nucleotide of the start codon) - **End**: End position (1-based coordinate of the last nucleotide of the stop codon) - **Length**: Total length in base pairs (including start and stop codons) - **Strand**: Orientation of the ORF (+ for forward, - for reverse complement) - **Frame**: Reading frame (0, 1, or 2) within the strand - **Sequence**: Complete nucleotide sequence of the ORF - **Translation**: Complete amino acid sequence (protein translation)
Summary Statistics
- **Total ORFs**: Total number of ORFs found across all frames - **Sequence Length**: Total length of the input sequence in base pairs - **Minimum Length**: The minimum ORF length threshold used
Interpretation
- Longer ORFs (100+ bp) are more likely to be real genes - ORFs with proper start (ATG) and stop codons are candidates for protein-coding genes - Multiple overlapping ORFs in different frames may indicate alternative splicing or gene overlap - ORFs on the reverse strand are equally valid and represent genes on the complementary strand
**1. Gene Prediction and Annotation** - Identify coding regions in newly sequenced genomes - Annotate genes in genomic sequences - Verify gene boundaries and exon locations - Analyze sequences from uncultured or novel organisms
**2. Plasmid and Vector Analysis** - Verify cloned inserts and confirm correct orientation - Identify coding regions in plasmid sequences - Design cloning strategies and verify constructs - Check for unwanted ORFs in expression vectors
**3. Functional Genomics** - Identify potential protein-coding genes - Analyze gene density in genomic regions - Study gene organization and overlap - Predict gene products from DNA sequences
**4. Sequence Quality Control** - Verify sequence integrity (proper start/stop codons) - Identify potential sequencing errors - Confirm correct reading frame for known genes - Validate sequence annotations
1. **Use appropriate minimum length**: - For bacterial genomes: 60-100 bp minimum is reasonable - For eukaryotic genomes: 100-300 bp minimum reduces false positives - For plasmid verification: 30-60 bp is sufficient
2. **Consider sequence context**: - Complete genomic sequences give better results than fragments - Include upstream regions for proper start codon identification - Ensure sequences are properly oriented
3. **Filter results appropriately**: - Focus on longer ORFs for gene prediction - Consider ORF overlap patterns (real genes often don't overlap extensively) - Use additional evidence (BLAST, homology) to validate ORFs
4. **Understand frame assignments**: - Frame 0: Starts at position 1, 4, 7, etc. - Frame 1: Starts at position 2, 5, 8, etc. - Frame 2: Starts at position 3, 6, 9, etc.
5. **Reverse strand considerations**: - Always check both strands for complete gene annotation - Reverse strand ORFs are equally valid - Position coordinates are always relative to the input (forward) strand
6. **Combine with other tools**: - Use BLAST to check homology with known genes - Combine with protein structure prediction for validation - Use phylogenetic analysis to study ORF evolution