Classifying coding DNA with nucleotide statistics

Abstract

In this report, we compared the success rate of classification of coding sequences (CDS) vs. introns by Codon Structure Factor (CSF) and by a method that we called Universal Feature Method (UFM). UFM is based on the scoring of purine bias (Rrr) and stop codon frequency. We show that the success rate of CDS/intron classification by UFM is higher than by CSF. UFM classifies ORFs as coding or non-coding through a score based on (i) the stop codon distribution, (ii) the product of purine probabilities in the three positions of nucleotide triplets, (iii) the product of Cytosine (C), Guanine (G), and Adenine (A) probabilities in the 1st, 2nd, and 3rd positions of triplets, respectively, (iv) the probabilities of G in 1st and 2nd position of triplets and (v) the distance of their GC3 vs. GC2 levels to the regression line of the universal correlation. More than 80% of CDSs (true positives) of Homo sapiens (>250 bp), Drosophila melanogaster (>250 bp) and Arabidopsis thaliana (>200 bp) are successfully classified with a false positive rate lower or equal to 5%. The method releases coding sequences in their coding strand and coding frame, which allows their automatic translation into protein sequences with 95% confidence. The method is a natural consequence of the compositional bias of nucleotides in coding sequences.

Keywords: ancestral codon; coding features; genomics; open reading frame; purines bias; universal correlation.

Figure 1.

Plot of F-score for CDS/intron classification by CSF (black symbols) and UFM (white symbols) in H. sapiens (Hs), D. melanogaster (Dm) and A. thaliana (At).

Figure 2.

Classification of coding sequences (bold line) and introns (thin line) of Homo sapiens (A,D,G), Drosophila melanogaster (B,E,H) and Arabidopsis thaliana (C,F,I) at 300 (A,B,C), 400 (D,E,F) and 500 bp (G,H,I) by CSF. The dashed lines (CSF = 75) indicate the classification threshold (τ_CSF). The sample size was 500 in both the introns and coding sequences.

Figure 3.

Classification of coding sequences (solid line) and introns (dashed line) of Homo sapiens (A,D,G,J), Drosophila melanogaster (B,E,H,K) and Arabidopsis thaliana (C,F,I,L) at 150 (A,B,C), 200 (D,E,F), 250 (G,H,I) and 300 bp (J,K,L) by UFM. The number on the upper left of each panel indicates the proportion of introns (%) that do not have any ORF with the purine bias of coding sequences for the size threshold considered. The sample size was 1000 in both the introns and coding sequences.

Figure 4.

Plots of GC3 vs. GC2 in true positives (CDS, panels: A,C,E) and false positives (introns, panels: B,D,F) ORFs ≥ 250 bp after classification by UFM without filters. The sequence samples of H. sapiens (A,B), D. melanogaster (C,D) and A. thaliana (E,F) are the same as those used for Figure 3 and Table 3. The gray areas match ORFs corresponding to GC2 levels larger than the quantity (GC3 + 120)/3 when GC > 60% that are filtered out by filter 1. The gray line that matches y = 7.14 × 241.5 is for the universal correlation. The black line y = 3 × 120 matches the left border of the gray zone.

Figure 5,

Compositional properties of CDSs (bold) and introns (dashed) in H. sapiens (A,D,G), D. melanogaster (B,E,H) and A. thaliana (C,F,I). Panels A,B,C show the relative amount of sequences (%) from Figure 3 and Table 3 classified by GC level (%). Panels D,E,F show the distribution of false positives (intronic ORFs classified as coding) resulting from ORF (≥250 bp) classification by filters 1 + 3. Panels G,H,I show the distribution of false positives (intronic ORFs classified as coding) resulting from ORF (≥250 bp) classification by filters 2 + 3. The numbers on the panels’ upper left indicate the proportion of intron sequences (%) that did not have any ORF with the purine bias of coding sequences for the size threshold considered.

Figure 6.

Relationship of GC2 (gray, y axis) and GC3 (black, y axis) vs. GC (x axis) in human CDSs (>600 bp). The solid line (GC3 = 1.5*GC-27) indicates the threshold of false positive filtering. This threshold has the same rate of false positive and true positive filtering as the threshold GC3 = 3*GC2–120 (Fig. 4). False positives of coding ORFs would stand on the diagonal of this plot (GC2≈GC3).