GC content dependency of open reading frame prediction via stop codon frequencies

A frequently used approach for detecting potential coding regions is to search for stop codons. In the standard genetic code 3 out of 64 trinucleotides are stop codons. Hence, in random or non-coding DNA one can expect every 21st trinucleotide to have the same sequence as a stop codon. In contrast, the open reading frames (ORFs) of most protein-coding genes are considerably longer. Thus, the stop codon frequency in coding sequences deviates from the background frequency of the corresponding trinucleotides. This has been utilized for gene prediction, in particular, in detecting protein-coding ORFs. Traditional methods based on stop codon frequency are based on the assumption that the GC content is about 50%. However, many genomes show significant deviations from that value. With the presented method we can describe the effects of GC content on the selection of appropriate length thresholds of potentially coding ORFs. Conversely, for a given length threshold, we can calculate the probability of observing it in a random sequence. Thus, we can derive the maximum GC content for which ORF length is practicable as a feature for gene prediction methods and the resulting false positive rates. A rough estimate for an upper limit is a GC content of 80%. This estimate can be made more precise by including further parameters and by taking into account start codons as well. We demonstrate the feasibility of this method by applying it to the genomes of the bacteria Rickettsia prowazekii, Escherichia coli and Caulobacter crescentus, exemplifying the effect of GC content variations according to our predictions. We have adapted the method for predicting coding ORFs by stop codon frequency to the case of GC contents different from 50%. Usually, several methods for gene finding need to be combined. Thus, our results concern a specific part within a package of methods. Interestingly, for genomes with low GC content such as that of R. prowazekii, the presented method provides remarkably good results even when applied alone.     

5’UTR中AUG的分布及其对翻译起始的影响

以细菌和古菌基因组5′ UTR序列作为研究对象,分析在5′ UTR 的3个不同阅读框架中三联体AUG的分布,发现无论是细菌还是古菌基因组都在阅读框1中有非常明显的AUG缺失(depletion)。AUG的缺失表明在起始密码子上游的AUG很可能会对基因的翻译起始产生影响。分析得知：绝大部分的AUG都是以uORF(upstream open reading frame)的形式出现的,uAUG(upstream AUG)的数量很少,特别是在阅读框1中,而且在细菌基因组的阅读框1中uAUG较多地出现在了含有SD序列的基因上游。比较发现,uAUG引导的序列在同义密码子使用上的偏好性较真正的编码序列差,这可能表明细菌和古菌在同义密码子使用上的偏好性也是决定基因准确地翻译起始的重要因素之一。     

Detecting overlapping coding sequences in virus genomes

Background  

Detecting new coding sequences (CDSs) in viral genomes can be difficult for several reasons. The typically compact genomes often contain a number of overlapping coding and non-coding functional elements, which can result in unusual patterns of codon usage; conservation between related sequences can be difficult to interpret – especially within overlapping genes; and viruses often employ non-canonical translational mechanisms – e.g. frameshifting, stop codon read-through, leaky-scanning and internal ribosome entry sites – which can conceal potentially coding open reading frames (ORFs).     

Using networks to analyze and visualize the distribution of overlapping genes in virus genomes

Gene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global comparative study of overlapping open reading frames (OvRFs) of 12,609 virus reference genomes in the NCBI database. We retrieved metadata associated with all annotated open reading frames (ORFs) in each genome record to calculate the number, length, and frameshift of OvRFs. Our results show that while the number of OvRFs increases with genome length, they tend to be shorter in longer genomes. The majority of overlaps involve +2 frameshifts, predominantly found in dsDNA viruses. Antisense overlaps in which one of the ORFs was encoded in the same frame on the opposite strand (−0) tend to be longer. Next, we develop a new graph-based representation of the distribution of overlaps among the ORFs of genomes in a given virus family. In the absence of an unambiguous partition of ORFs by homology at this taxonomic level, we used an alignment-free k-mer based approach to cluster protein coding sequences by similarity. We connect these clusters with two types of directed edges to indicate (1) that constituent ORFs are adjacent in one or more genomes, and (2) that these ORFs overlap. These adjacency graphs not only provide a natural visualization scheme, but also a novel statistical framework for analyzing the effects of gene- and genome-level attributes on the frequencies of overlaps.     

Nucleotide sequence of sporulation locus spoIIA in Bacillus subtilis

We have determined a sequence of 2073 bp from two recombinant plasmids carrying the whole spoIIA locus from Bacillus subtilis, the expression of which is required for spore formation. The sequence contains three long open reading frames (ORFs), each of them being preceded by a ribosome binding site. These three putative proteins (mol. wts 13100, 16300 and 22200) are likely to be expressed and are probably encoded on the same mRNA. The stop codon of ORF1 overlaps with the start codon of ORF2 suggesting that there might be translational coupling between the two ORFs. Although some known promoter sequences were found, the only one upstream from the first open reading frame is about 260 bp from it.     

Hundreds of Out-of-Frame Remodeled Gene Families in the Escherichia coli Pangenome

All genomes include gene families with very limited taxonomic distributions that potentially represent new genes and innovations in protein-coding sequence, raising questions on the origins of such genes. Some of these genes are hypothesized to have formed de novo, from noncoding sequences, and recent work has begun to elucidate the processes by which de novo gene formation can occur. A special case of de novo gene formation, overprinting, describes the origin of new genes from noncoding alternative reading frames of existing open reading frames (ORFs). We argue that additionally, out-of-frame gene fission/fusion events of alternative reading frames of ORFs and out-of-frame lateral gene transfers could contribute to the origin of new gene families. To demonstrate this, we developed an original pattern-search in sequence similarity networks, enhancing the use of these graphs, commonly used to detect in-frame remodeled genes. We applied this approach to gene families in 524 complete genomes of Escherichia coli. We identified 767 gene families whose evolutionary history likely included at least one out-of-frame remodeling event. These genes with out-of-frame components represent ∼2.5% of all genes in the E. coli pangenome, suggesting that alternative reading frames of existing ORFs can contribute to a significant proportion of de novo genes in bacteria.     

Fine structural features of the chloroplast genome: comparison of the sequenced chloroplast genomes.

The entire nucleotide sequences of the rice, tobacco and liverwort chloroplast genomes have been determined. We compared all the chloroplast genes, open reading frames and spacer regions in the plastid genomes of these three species in order to elucidate general structural features of the chloroplast genome. Analyses of homology, GC content and codon usage of the genes enabled us to classify them into two groups: photosynthesis genes and genetic system genes. Based on comparisons of homology, GC content and codon usage, unidentified ORFs can also be assigned to each of these groups such that it is possible to speculate about the functions of products which may be produced by these ORFs. The spacer regions and intron sequences were compared and found to have no obvious homology between rice and liverwort or between tobacco and liverwort.     

Translational readthrough of the PDE2 stop codon modulates cAMP levels in Saccharomyces cerevisiae

The efficiency of translation termination in yeast can vary several 100-fold, depending on the context around the stop codon. We performed a computer analysis designed to identify yeast open reading frames (ORFs) containing a readthrough motif surrounding the termination codon. Eight ORFs were found to display inefficient stop codon recognition, one of which, PDE2, encodes the high-affinity cAMP phosphodiesterase. We demonstrate that Pde2p stability is very impaired by the readthrough-dependent extension of the protein. A 20-fold increase in readthrough of PDE2 was observed in a [PSI+] as compared with a [psi-] strain. Consistent with this observation, an important increase in cAMP concentration was observed in suppressor backgrounds. These results provide a molecular explanation for at least some of the secondary phenotypes associated with suppressor backgrounds.     

Detecting overlapping coding sequences with pairwise alignments

MOTIVATION: Overlapping gene coding sequences (CDSs) are particularly common in viruses but also occur in more complex genomes. Detecting such genes with conventional gene-finding algorithms can be difficult for several reasons. If an overlapping CDS is on the same read-strand as a known CDS, then there may not be a distinct promoter or mRNA. Furthermore, the constraints imposed by double-coding can result in atypical codon biases. However, these same constraints lead to particular mutation patterns that may be detectable in sequence alignments. RESULTS: In this paper, we investigate several statistics for detecting double-coding sequences with pairwise alignments--including a new maximum-likelihood method. We also develop a model for double-coding sequence evolution. Using simulated sequences generated with the model, we characterize the distribution of each statistic as a function of sequence composition, length, divergence time and double-coding frame. Using these results, we develop several algorithms for detecting overlapping CDSs. The algorithms were tested on known overlapping CDSs and other overlapping open reading frames (ORFs) in the hepatitis B virus (HBV), Escherichia coli and Salmonella typhimurium genomes. The algorithms should prove useful for detecting novel overlapping genes--especially short coding ORFs in viruses. AVAILABILITY: Programs may be obtained from the authors. SUPPLEMENTARY INFORMATION: http://biochem.otago.ac.nz/double.html.     

The Random Nature of Genome Architecture: Predicting Open Reading Frame Distributions

Background

A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes.

Methodology/Principal Findings

By fitting mixture models to data from whole genome sequences we show that the size-frequency distributions for ORFS are strikingly similar across prokaryotic and eukaryotic genomes. Moreover, we show that i) a large fraction (60–80%) of ORF size-frequency distributions can be predicted a priori with a stochastic assembly model based on GC content, and that (ii) size-frequency distributions of the remaining “non-random” ORFs are well-fitted by log-normal or gamma distributions, and similar to the size distributions of annotated proteins.

Conclusions/Significance

Our findings suggest stochastic processes have played a primary role in the evolution of genome complexity, and that common processes govern the conservation and loss of functional genomics units in both prokaryotes and eukaryotes.     

Coverage of whole proteome by structural genomics observed through protein homology modeling database

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE (), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics.     

Proteogenomic mapping as a complementary method to perform genome annotation

The accelerated rate of genomic sequencing has led to an abundance of completely sequenced genomes. Annotation of the open reading frames (ORFs) (i.e., gene prediction) in these genomes is an important task and is most often performed computationally based on features in the nucleic acid sequence. Using recent advances in proteomics, we set out to predict the set of ORFs for an organism based principally on expressed protein-based evidence. Using a novel search strategy, we mapped peptides detected in a whole-cell lysate of Mycoplasma pneumoniae onto a genomic scaffold and extended these "hits" into ORFs bound by traditional genetic signals to generate a "proteogenomic map". We were able to generate an ORF model for M. pneumoniae strain FH using proteomic data with a high correlation to models based on sequence features. Ultimately, we detected over 81% of the genomically predicted ORFs in M. pneumoniae strain M129 (the originally sequenced strain). We were also able to detect several new ORFs not originally predicted by genomic methods, various N-terminal extensions, and some evidence that would suggest that certain predicted ORFs are bogus. Some of these differences may be a result of the strain analyzed but demonstrate the robustness of protein analysis across closely related genomes. This technique is a cost-effective means to add value to genome annotation, and a prerequisite for proteome quantitation and in vivo interaction measures.     

Characterization of a mitochondrial ORF from the gender-associated mtDNAs of Mytilus spp. (Bivalvia: Mytilidae): identification of the "missing" ATPase 8 gene

Bivalve species are characterized by extraordinary variability in terms of mitochondrial (mt) genome size, gene arrangement and tRNA gene number. Many species are thought to lack the mitochondrial protein-coding gene atp8. Of these species, the Mytilidae appears to be the only known taxon with doubly uniparental inheritance of mtDNA that does not possess the atp8 gene. This raises the question as to whether mytilids have completely lost the ATP8 protein, whether the gene has been transferred to the nucleus or whether they possess a highly modified version of the gene/protein that has led to its lack of annotation. In the present study, we re-investigated all complete (or nearly complete) F and M mytilid mt genomes previously sequenced for the presence of conserved open reading frames (ORFs) that might code for ATP8 and/or have other functional importance in these bivalves. We also revised the annotations of all available complete mitochondrial genomes of bivalves and nematodes that are thought to lack atp8 in an attempt to detect it. Our results indicate that a novel mytilid ORF of significant length (i.e., the ORF is >85 amino acids in length), with complete start and stop codons, is a candidate for the atp8 gene: (1) it possesses a pattern of evolution expected for a protein-coding gene evolving under purifying selection (i.e., the 3rd>1st>2nd codon pattern of evolution), (2) it is actively transcribed in Mytilus species, (3) it has one predicted transmembrane helix (as do other metazoan ATP8 proteins), (4) it has conserved functional motifs and (5), comparisons of its amino acid sequence with ATP8 sequences of other molluscan or bivalve species reveal similar hydropathy profiles. Furthermore, our revised annotations also confirmed the mt presence of atp8 in almost all bivalve species and in one nematode species. Our results thus support recognizing the presence of ATPase 8 in most bivalves mt genomes (if not all) rather than the continued characterization of these genomes as lacking this gene.     

Identification of functional open reading frames in chloroplast genomes

We have used a rapid computer dot-matrix comparison method to identify all DNA regions which have been evolutionarily conserved between the completely sequenced chloroplast genomes of tobacco and a liverwort. Analysis of these regions reveals 74 homologous open reading frames (ORFs) which have been conserved as to length and amino acid sequence; these ORFs also have an excess of nucleotide substitutions at silent sites of codons. Since the nonfunctional parts of these genomes have become saturated with mutations and show no sequence similarity whatsoever, the homologous ORFs are almost certainly functional. A further four pairs of ORFs show homology limited to only a short part of their putative gene products. Amino acid sequence identities range between 50 and 99%; some chloroplast proteins are seen to be among the most slowly evolving of all known proteins. A search of the nucleotide and amino acid sequence databanks has revealed several previously unidentified genes in chloroplast sequences from other species, but no new homologies to prokaryotic genes.     

Analysis of nucleotide distribution in the genome of Streptomyces coelicolor A3(2) using the Z curve method

The nucleotide distribution of all 33 527 open reading frames (ORFs) (≥300 bp) in the genome of Streptomyces coelicolor A3(2) has been analyzed using the Z curve method. Each ORF is mapped onto a point in a 9-dimensional space. To visualize the distribution of mapping points, the points are projected onto the principal plane based on principal component analysis. Consequently, the distribution pattern of the 33 527 points in the principal plane shows a flower-like shape, in which there are seven distinct regions. In addition to the central region, there are six petal-like regions around the center, one of which corresponds to 7172 coding sequences. The central region and the remaining five petal-like regions correspond to the intergenic sequences and out-of-frame non-coding ORFs, respectively. It is shown that selective pressure produces a remarkable bias of the G+C content among three codon positions, resulting in the interesting phenomenon observed. A similar phenomenon is also observed for other bacterial genomes with high genomic G+C content, such as Pseudomonas aeruginosa PA01 (G+C=66.6%). However, for the genomes of Bacillus subtilis (G+C=43.5%) and Clostridium perfringens (G+C=28.6%), no similar phenomenon was observed. The finding presented here may be useful to improve the gene-finding algorithms for genomes with high G+C content. A set of supplementary materials including the plots displaying the base distribution patterns of ORFs in 12 prokaryotes is provided on the website http://tubic.tju.edu.cn/highGC/.     

ORF organization and gene recognition in the yeast genome

Some rules on gene recognition and ORF organization in the Saccharomyces cerevisiae genome are demonstrated by statistical analyses of sequence data. This study includes: (a) The random frame rule-that the six reading frames W1, W2, W3, C1, C2 and C3 in the double-stranded genome are randomly occupied by ORFs (related phenomena on ORF overlapping are also discussed). (b) The inhomogeneity rule-coding and non-coding ORFs differ in inhomogeneity of base composition in the three codon positions. By use of the inhomogeneity index (IHI), one can make a distinction between coding (IHI > 14) and non-coding (IHI 相似文献