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

sefOri: selecting the best-engineered sequence features to predict DNA replication origins

Motivation

Cell divisions start from replicating the double-stranded DNA, and the DNA replication process needs to be precisely regulated both spatially and temporally. The DNA is replicated starting from the DNA replication origins. A few successful prediction models were generated based on the assumption that the DNA replication origin regions have sequence level features like physicochemical properties significantly different from the other DNA regions.

Results

This study proposed a feature selection procedure to further refine the classification model of the DNA replication origins. The experimental data demonstrated that as large as 26% improvement in the prediction accuracy may be achieved on the yeast Saccharomyces cerevisiae. Moreover, the prediction accuracies of the DNA replication origins were improved for all the four yeast genomes investigated in this study.

Availability and implementation

The software sefOri version 1.0 was available at http://www.healthinformaticslab.org/supp/resources.php. An online server was also provided for the convenience of the users, and its web link may be found in the above-mentioned web page.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Brief Review: The Z-curve Theory and its Application in Genome Analysis

In theoretical physics, there exist two basic mathematical approaches, algebraic and geometrical methods, which, in most cases, are complementary. In the area of genome sequence analysis, however, algebraic approaches have been widely used, while geometrical approaches have been less explored for a long time. The Z-curve theory is a geometrical approach to genome analysis. The Z-curve is a three-dimensional curve that represents a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z-curve, therefore, contains all the information that the corresponding DNA sequence carries. The analysis of a DNA sequence can then be performed through studying the corresponding Z-curve. The Z-curve method has found applications in a wide range of areas in the past two decades, including the identifications of protein-coding genes, replication origins, horizontally-transferred genomic islands, promoters, translational start sides and isochores, as well as studies on phylogenetics, genome visualization and comparative genomics. Here, we review the progress of Z-curve studies from aspects of both theory and applications in genome analysis.

Separate base usages of genes located on the leading and lagging strands in Chlamydia muridarum revealed by the Z curve method

Background

The nucleotide compositional asymmetry between the leading and lagging strands in bacterial genomes has been the subject of intensive study in the past few years. It is interesting to mention that almost all bacterial genomes exhibit the same kind of base asymmetry. This work aims to investigate the strand biases in Chlamydia muridarum genome and show the potential of the Z curve method for quantitatively differentiating genes on the leading and lagging strands.

Results

The occurrence frequencies of bases of protein-coding genes in C. muridarum genome were analyzed by the Z curve method. It was found that genes located on the two strands of replication have distinct base usages in C. muridarum genome. According to their positions in the 9-D space spanned by the variables u₁ – u₉ of the Z curve method, K-means clustering algorithm can assign about 94% of genes to the correct strands, which is a few percent higher than those correctly classified by K-means based on the RSCU. The base usage and codon usage analyses show that genes on the leading strand have more G than C and more T than A, particularly at the third codon position. For genes on the lagging strand the biases is reverse. The y component of the Z curves for the complete chromosome sequences show that the excess of G over C and T over A are more remarkable in C. muridarum genome than in other bacterial genomes without separating base and/or codon usages. Furthermore, for the genomes of Borrelia burgdorferi, Treponema pallidum, Chlamydia muridarum and Chlamydia trachomatis, in which distinct base and/or codon usages have been observed, closer phylogenetic distance is found compared with other bacterial genomes.

Conclusion

The nature of the strand biases of base composition in C. muridarum is similar to that in most other bacterial genomes. However, the base composition asymmetry between the leading and lagging strands in C. muridarum is more significant than that in other bacteria. It's supposed that the remarkable strand biases of G/C and T/A are responsible for the appearance of separate base or codon usages in C. muridarum. On the other hand, the closer phylogenetic distance among the four bacterial genomes with separate base and/or codon usages is necessary rather than occasional. It's also shown that the Z curve method may be more sensitive than RSCU when being used to quantitatively analyze DNA sequences.

Re-prediction of protein-coding genes in the genome of Amsacta moorei entomopoxvirus

Using the Z curve method, the protein-coding genes in AmEPV genome are re-predicted. On the basis of the parameters trained on the experimentally validated genes, all of the 30 experimentally validated genes and 67 putative genes are predicted correctly as coding genes. The sensitivities of the present method for self-test and cross-validation are all 100% based on these test sets. Thirty-eight annotated conserved and hypothetical genes are predicted as non-coding ORFs. The number of re-predicted protein-coding genes in AmEPV is 256. It is significantly less than the number 294 reported in the original annotation. After extending the present method trained in AeEPV genome to the other entomopoxvirus genome, it is found that 116 of the 123 known and putative genes are predicted correctly as coding. Six of the seven falsely missed genes are less than 300bp. The present method could be extended to other poxvirus genomes with or without adaptation of training sets.

MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes

Background

Despite a remarkable success in the computational prediction of genes in Bacteria and Archaea, a lack of comprehensive understanding of prokaryotic gene structures prevents from further elucidation of differences among genomes. It continues to be interesting to develop new ab initio algorithms which not only accurately predict genes, but also facilitate comparative studies of prokaryotic genomes.

Results

This paper describes a new prokaryotic genefinding algorithm based on a comprehensive statistical model of protein coding Open Reading Frames (ORFs) and Translation Initiation Sites (TISs). The former is based on a linguistic "Entropy Density Profile" (EDP) model of coding DNA sequence and the latter comprises several relevant features related to the translation initiation. They are combined to form a so-called Multivariate Entropy Distance (MED) algorithm, MED 2.0, that incorporates several strategies in the iterative program. The iterations enable us to develop a non-supervised learning process and to obtain a set of genome-specific parameters for the gene structure, before making the prediction of genes.

Conclusion

Results of extensive tests show that MED 2.0 achieves a competitive high performance in the gene prediction for both 5' and 3' end matches, compared to the current best prokaryotic gene finders. The advantage of the MED 2.0 is particularly evident for GC-rich genomes and archaeal genomes. Furthermore, the genome-specific parameters given by MED 2.0 match with the current understanding of prokaryotic genomes and may serve as tools for comparative genomic studies. In particular, MED 2.0 is shown to reveal divergent translation initiation mechanisms in archaeal genomes while making a more accurate prediction of TISs compared to the existing gene finders and the current GenBank annotation.

Regeneration of sugarcane elite breeding lines and engineering of stem borer resistance

Five elite sugarcane breeding lines were tested for efficiency in embryogenesis and plant regeneration. All of them produced regenerative embryogenic calli but with varied efficiencies. To engineer strongly insect-resistant sugarcanes, the GC content of a truncated cry1Ac gene, which encodes the active region of Cry1Ac insecticidal delta-endotoxin, was increased from the original 37.4 to 47.5% following the sugarcane codon usage pattern. The synthetic cry1Ac gene (s-cry1Ac) was placed under the control of maize ubiquitin promoter and introduced by microprojectile bombardment into the embryogenic calli of sugarcane lines YT79-177 and ROC16. Southern blotting analysis showed that multicopies of s-cry1Ac were integrated into the genomes of transgenic sugarcane lines. Immunoblotting analysis identified 18 transgenic lines expressing detectable levels of s-Cry1Ac, which were estimated in the range of 1.8-10.0 ng mg(-1) total soluble proteins. Four transgenic and two parental lines were assayed for sugarcane stem borer resistance in leaf tissue feeding trials and greenhouse plant assays. The results showed that, while the untransformed control lines were severely damaged in both leaves and stems, the transgenic sugarcane lines expressing high levels of s-Cry1Ac proteins were highly resistant to sugarcane stem borer attack, resulting in complete mortality of the inoculated insects within 1 week after inoculation.

The Most Deviated Codon Position in AT-rich Bacterial Genomes: A Function Related Analysis

We have performed systematic study on more than 120 archaeal and bacterial genomes. Based on the index proposed in the current paper, clear patterns are observed showing the relation between the base compositional deviation at three codon positions and the genomic GC content. For AT-rich genomes, the Most Deviated Codon Position (MDCP) is the 1st codon position, while for GC-rich genomes, MDCP appears at the 2nd or 3rd codon position alternatively. According to MDCP, the CDSs of a genome can be classified into two types: typical and atypical. In AT-rich genomes the typical represent the majority and account for about 3/4 of all the CDSs. Based on the functional classification of COG database, the two types of CDSs are examined. An apparent bias of distribution is observed that the CDSs with the function of 'information processing' are more likely to present in typical type.

Identification of replication origins in archaeal genomes based on the Z-curve method

The Z-curve is a three-dimensional curve that constitutes a unique representation of a DNA sequence, i.e., both the Z-curve and the given DNA sequence can be uniquely reconstructed from the other. We employed Z-curve analysis to identify one replication origin in the Methanocaldococcus jannaschii genome, two replication origins in the Halobacterium species NRC-1 genome and one replication origin in the Methanosarcina mazei genome. One of the predicted replication origins of Halobacterium species NRC-1 is the same as a replication origin later identified by in vivo experiments. The Z-curve analysis of the Sulfolobus solfataricus P2 genome suggested the existence of three replication origins, which is also consistent with later experimental results. This review aims to summarize applications of the Z-curve in identifying replication origins of archaeal genomes, and to provide clues about the locations of as yet unidentified replication origins of the Aeropyrum pernix K1, Methanococcus maripaludis S2, Picrophilus torridus DSM 9790 and Pyrobaculum aerophilum str. IM2 genomes.