of the 0.027% of non-conforming ORFs. This fraction represents the non-conforming exons that exceed the length predicted for a random sequence. The frequency of exons ,750 bases decreased, while the frequency of ORFs and exons .750 bases increased progressively across widely divergent species in the following order: H. sapiensRC. elegansRA. thalianaRD. melanogasterRP. falciparumRS. pombeRS. pneumoniaeRE. coli. The frequency of non-conforming ORFs in a genome was directly proportional to the frequency of non-conforming exons and increased inversely with the average number of introns per gene. The highly intron-dense human genome had the lowest percentage of non-conforming exons (and ORFs), while the prokaryotes, which contained no introns, had the highest percentage of non-conforming coding sequences analogous to eukaryotic exons (and ORFs). The fraction of non-conforming exons in the different genomes were proportionate with the fraction of ORFs .750 bases in the corresponding genomes (Table 1). The high congruence of the frequencies of the lengths of the non-conforming exons and the non- conforming ORFs in the different genomes may indicate that the longer ORFs are a direct reflection of increased exon lengths. Because non-conforming ORFs do not occur indigenously in random DNA of any reasonable length, they may be the result of the splicing of two or more exons that existed in ancestral intron- dense genes. Therefore, it is possible that the genomes with the fewest non-conforming exons are closest to the original nascent genomes, and that those with more non-conforming exons may have lost many introns from an ancestral intron-dense genome. Accordingly, the earliest common eukaryotic ancestor may have derived its split genes from random DNA with a full complement of introns, and different organisms might have since lost varying extents of introns. These results are consistent with the observation by Roy & Gilbert [2] that the intron-dense human and Arabidopsis genomes resemble the earliest common eukaryotic ancestor, and that introns must have been lost in the relatively intron-sparse genomes. These results perhaps indicate that long exons had evolved by linking together shorter, conforming exons from preexisting genes. Striking similarity between split-gene sequences and a random sequence The ROSG model predicts that the exons must be confined within ORFs, whose lengths must conform to those in random DNA sequences. Thus if split-genes had originated from random DNA, their ORF length distributions should resemble those in random DNA. Therefore, we wanted to compare the ORF distribution of genes from different genomes with those of a random DNA sequence, and analyze whether exons of these genes are confined within the ORFs that conform to a random sequence. For this, we developed a software tool: Exon ORF Plot (EOP, http://66.170.16. 154/chandancn/human) (Username: genome; password: sgopgic) that plots the occurrence of stop codons and exons of a gene in appropriate reading-frames. Control plots were generated from a random sequence of the same length as each gene, and from an ARF plot of the gene sequence (Figure S1). Examination of human genes revealed that their ORF distribution patterns were remarkably similar to that in random DNA, and that the vast majority of exons (98%) were confined within the short ORFs (sample gene-plots provided in Figure S1), consistent with the ORF and exon length distribution analysis shown in Figure 3. It is possible that the few existing non-conforming ORFs (2%) were perhaps not randomly produced. Instead, they might have been formed by the splicing of ancestral exons. The EOPs demonstrated that 1) the gene ORF plots were highly similar to that of the random DNA, 2) that exons were confined within the short ORFs naturally allowed in random DNA, Origin of Split Gene Structure and 3) exon-splicing specifically created one very long, non- conforming ORF in the spliced gene. The ORF length distribution in genes from other genomes was also largely consistent with that in random DNA. However, the frequency of non-conforming ORFs that contained long, non- conforming exons were inversely proportionate with the size of the genome (Figure S1). Here too, when exons exceeded 750 bases, the ORFs containing them were clear statistical outliers, suggesting that these were possibly derived from the prior splicing of shorter exons and simultaneous intron loss. In fact, the rare non-random exons were predictably contained within non-conforming ORFs against the background of random ORFs. Importantly, our EOP analyses indicated that the relative incidence of non-conforming exons within very long non-conforming ORFs replicated the order of organisms revealed by the NED analysis above (S. pombe.P. falciparum.D. melanogaster.A. thaliana.C. elegans.H. sapiens). Does the ROSG model explain extremely long genes with many exons embedded between very long regions of introns? How could they arise from random sequences? Since exons had to be limited in length in random sequence, the longer the coding-sequence of a gene, the more the number of exons it should be split into, and the longer the gene should be. Would this be observed to be true even if the gene was very long? We analyzed this question by tabulating these statistics for all of the genes from the human genome. The results showed that the average number of exons per gene was directly proportional to the average length of the coding sequence per gene, both of which were directly proportional to the average length of the complete split-gene (Figure 4). This was true for genes with small number of exons, and for genes containing large number of exons (e.g., up to 80 exons for which good sample data are available) from the human genome. The average length of exons (approx. 170 bases) and the average length of introns (approx. 4000 bases) were maintained throughout the entire spread. The only effect of exon-splicing: A large increase in coding-sequence ORF length If the ROSG hypothesis is true, then exon splicing in a gene should lead to a significantly long ORF that contains the complete (spliced) protein-coding sequence—a strikingly large length that is well beyond the ORF lengths available within a random genetic sequence. Furthermore, exon splicing should not change the lengths of other ORFs not containing exon sequences or the lengths between any non-stop codons. To test this principle, the exons of a gene were spliced and the stop codons were plotted in the spliced gene sequences (Figure S1). Indeed exon-splicing selectively increased the protein-coding ORF lengths to an extent that does not occur in any length of random DNA (Figure S1). Meanwhile a control study revealed that ARF lengths did not differ before and after splicing (Figure S1). This theme was repeated consistently in nearly all of the human genes, corroborating our conclusion of a specific increase in ORF lengths due to exon splicing (Figure S1). To study the effects of splicing the exons of genes in a genome- wide experiment, we selected a set of genes from the human genome. To clearly distinguish ORF lengths before and after splicing, we used only genes with a minimum coding sequence length of 2000 bases, and with all the ORFs of each gene being ,750 bases in the sense strand. Notably, the vast majority (17,500) of the 27,000 human genes in RefSeq had all of their ORFs ,750 bases. Of these, 1,700 had a total coding sequence over 2000 bases. The Negative exponential Distribution (NED) plot of ORFs from this gene set strikingly resembled that from random DNA (Figure 5A). The frequency distribution cure of exon-lengths PLoS ONE | www.plosone.org 5 October 2008 | Volume 3 | Issue 10 | e3456