Protein coding sequence identification by simultaneously characterizing the periodic and random features of DNA sequences

General Designs Reveal Distinct Codes in Protein-Coding and Non-Coding Human DNA

This study seeks to investigate distinct signatures and codes within different genomic sequence locations of the human genome. The promoter and other non-coding regions contain sites for the binding of biological particles, for processes such as transcription regulation. The specific rules and sequence codes that govern this remain poorly understood. To derive these (codes), the general designs of sequence are investigated. Genomic signatures are a powerful tool for assessing the general designs of sequence, and cross-comparing different genomic regions for their distinct sequence properties. Through these genomic signatures, the relative non-random properties of sequences are also assessed. Furthermore, a binary components analysis is carried out making use of information theory ideas, to study the RY (purine/pyrimidine), WS (weak/strong) and KM (keto/amino) signatures in the sequences. From this comparison, it is possible to identify the relative importance of these properties within the various protein-coding and non-coding genomic locations. The results show that coding DNA has a strongly non-random WS signature, which reflects the genetic code, and the hydrogen-bond base pairing of codon-anti-codon interactions. In contrast, non-coding locations, such as the promoter, contain a distinct genomic signature. A prominent feature throughout non-coding DNA is a highly non-random RY signature, which is very different in nature to coding DNA, and suggests a structural-based RY code. This marks progress towards deciphering the unknown code(s) in non-protein-coding DNA, and a further understanding of the coding DNA. Additionally, it unravels how DNA carries information. These findings have implications for the most fundamental principles of biology, including knowledge of gene regulation, development and disease.

The DNA walk and its demonstration of deterministic chaos-relevance to genomic alterations in lung cancer

MOTIVATION

Advancements in cancer genetics have facilitated the development of therapies with actionable mutations. Although mutated genes have been studied extensively, their chaotic behavior has not been appreciated. Thus, in contrast to naïve DNA, mutated DNA sequences can display characteristics of unpredictability and sensitivity to the initial conditions that may be dictated by the environment, expression patterns and presence of other genomic alterations. Employing a DNA walk as a form of 2D analysis of the nucleotide sequence, we demonstrate that chaotic behavior in the sequence of a mutated gene can be predicted.

RESULTS

Using fractal analysis for these DNA walks, we have determined the complexity and nucleotide variance of commonly observed mutated genes in non-small cell lung cancer, and their wild-type counterparts. DNA walks for wild-type genes demonstrate varying levels of chaos, with BRAF, NTRK1 and MET exhibiting greater levels of chaos than KRAS, paxillin and EGFR. Analyzing changes in chaotic properties, such as changes in periodicity and linearity, reveal that while deletion mutations indicate a notable disruption in fractal 'self-similarity', fusion mutations demonstrate bifurcations between the two genes. Our results suggest that the fractals generated by DNA walks can yield important insights into potential consequences of these mutated genes.

AVAILABILITY AND IMPLEMENTATION

Introduction to Turtle graphics in Python is an open source article on learning to develop a script for Turtle graphics in Python, freely available on the web at https://docs.python.org/2/library/turtle.html. cDNA sequences were obtained through NCBI RefSeq database, an open source database that contains information on a large array of genes, such as their nucleotide and amino acid sequences, freely available at https://www.ncbi.nlm.nih.gov/refseq/. FracLac plugin for Fractal analysis in ImageJ is an open source plugin for the ImageJ program to perform fractal analysis, free to download at https://imagej.nih.gov/ij/plugins/fraclac/FLHelp/Introduction.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Search for potential reading frameshifts in cds from Arabidopsis thaliana and other genomes

A new mathematical method for potential reading frameshift detection in protein-coding sequences (cds) was developed. The algorithm is adjusted to the triplet periodicity of each analysed sequence using dynamic programming and a genetic algorithm. This does not require any preliminary training. Using the developed method, cds from the Arabidopsis thaliana genome were analysed. In total, the algorithm found 9,930 sequences containing one or more potential reading frameshift(s). This is ∼21% of all analysed sequences of the genome. The Type I and Type II error rates were estimated as 11% and 30%, respectively. Similar results were obtained for the genomes of Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Rattus norvegicus and Xenopus tropicalis. Also, the developed algorithm was tested on 17 bacterial genomes. We compared our results with the previously obtained data on the search for potential reading frameshifts in these genomes. This study discussed the possibility that the reading frameshift seems like a relatively frequently encountered mutation; and this mutation could participate in the creation of new genes and proteins.

New Method for Potential Fusions Detection in Protein-Coding Sequences

Gene fusion is known to be one of the mechanisms of a new gene formation. Most bioinformatics methods for studying fused genes are based on the sequence similarity search. However, if the ancestral sequences were lost during evolution or changed too much, it is impossible to detect the fusion. Previously, we have developed a method of searching for triplet periodicity (TP) change points in protein-coding sequences (CDS) and showed the possible relation of this phenomenon with gene formation as a result of fusion. In this study, we improved the TP change point detection method and studied the genes of six eukaryotic genomes. At the level of 2%-3% of the probability of type I error, TP change points were found in 20%-40% of genes. Further analysis showed that about 30% of the TP change points can be explained by amino acid repeats. Another 30% can be potentially fused genes, alignment for which was detected by the BLAST program. We believe that the rest of the results can be fused genes, the ancestral sequences for which have been lost. The method is more sensitive to TP changes and allowed us to find up to two to three times more cases of significant TP change points than our previous method.

An approach for searching insertions in bacterial genes leading to the phase shift of triplet periodicity

The concept of the phase shift of triplet periodicity (TP) was used for searching potential DNA insertions in genes from 17 bacterial genomes. A mathematical algorithm for detection of these insertions has been developed. This approach can detect potential insertions and deletions with lengths that are not multiples of three bases, especially insertions of relatively large DNA fragments (>100 bases). New similarity measure between triplet matrixes was employed to improve the sensitivity for detecting the TP phase shift. Sequences of 17,220 bacterial genes with each consisting of more than 1,200 bases were analyzed, and the presence of a TP phase shift has been shown in ~16% of analysed genes (2,809 genes), which is about 4 times more than that detected in our previous work. We propose that shifts of the TP phase may indicate the shifts of reading frame in genes after insertions of the DNA fragments with lengths that are not multiples of three bases. A relationship between the phase shifts of TP and the frame shifts in genes is discussed.

Origin of multiple periodicities in the Fourier power spectra of the Plasmodium falciparum genome

Background

Fourier transforms and their associated power spectra are used for detecting periodicities and protein-coding genes and is generally regarded as a well established technique. Many of the periodicities which have been found with this method are quite well understood such as the periodicity of 3 nt which is associated to codon usage. But what is the origin of the peculiar frequency multiples k/21 which were reported for a tiny section of chromosome 2 in P. falciparum? Are these present in other chromosomes and perhaps in related organisms? And how should we interpret fractional periodicities in genomes?

Results

We applied the binary indicator power spectrum to all chromosomes of P. falciparum, and found that the frequency overtones k/21 are present only in non-coding sections. We did not find such frequency overtones in any other related genomes. Furthermore, the frequency overtones were identified as artifacts of the way the genome is encoded into a numerical sequence, that is, they are frequency aliases. By choosing a different way to encode the sequence the overtones do not appear. In view of these results, we revisited early applications of this technique to proteins where frequency overtones were reported.

Conclusions

Some authors hinted recently at the possibility of mapping artifacts and frequency aliases in power spectra. However, in the case of P. falciparum the frequency aliases are particularly strong and can mask the 1/3 frequency which is used for gene detecting. This shows that albeit being a well known technique, with a long history of application in proteins, few researchers seem to be aware of the problems represented by frequency aliases.

Numericalization of the self adaptive spectral rotation method for coding region prediction

Recently, for identifying protein coding regions in new sequences from unknown organisms without training sets, a Self Adaptive Spectral Rotation (SASR) method has been developed to visualize the Triplet Periodicity (TP) property, which is a simple and universal coding related property. The rough locations of coding regions can be visually revealed by the SASR method, without any training. However, the method does not numerically discriminate the locations of coding regions. Based on the SASR method, we develop a new approach, named the T-Z-T analysis, to provide numerical results of coding region prediction. This approach adopts a t-test segmentation to separate coding and non-coding regions in the SASR's output and further uses a z-test filter to recognize region patterns. After that, another t-test segmentation is conducted to break down adjacent coding regions by detecting the frame shifts. Since it is based on the graphic output of the SASR, this approach does not require any training. Meanwhile, this approach is more stable, because it is not sensitive to errors in the input DNA sequence. Such advantages make it suitable for coding region prediction in the early stage, when there is insufficient training set, and even the input data are inaccurate.

Detection change points of triplet periodicity of gene

The triplet periodicity (TP) is a distinguished property of protein coding sequences. There are complex genes with more than one TP type along their sequence. We say that these genes contain a triplet periodicity change point. The aim of the work is to find all genes that contain TP change point and attempt to compare the positions of change point in genes with known biological data. We have developed a mathematical method to identify triplet periodicity changes along a sequence. We have found 311,221 genes with the TP change point in the KEGG/Genes database (version 48). It is about 8% from the total database volume (4013150). We showed that the repetitive sequences are not the only cause of such events. We suppose that the TP change point may indicate a fusion of genes or domains. We performed BLAST analysis to find potential ancestral genes for the parts of genes with TP change point. As a result we found that in 131323 cases sequences with TP change point have proper similarities for one or both parts. The relationship between TP change point and the fusion events in genes is discussed. The program realization of the method is available by request to authors.

Visualization of the protein-coding regions with a self adaptive spectral rotation approach

Identifying protein-coding regions in DNA sequences is an active issue in computational biology. In this study, we present a self adaptive spectral rotation (SASR) approach, which visualizes coding regions in DNA sequences, based on investigation of the Triplet Periodicity property, without any preceding training process. It is proposed to help with the rough coding regions prediction when there is no extra information for the training required by other outstanding methods. In this approach, at each position in the DNA sequence, a Fourier spectrum is calculated from the posterior subsequence. Following the spectrums, a random walk in complex plane is generated as the SASR's graphic output. Applications of the SASR on real DNA data show that patterns in the graphic output reveal locations of the coding regions and the frame shifts between them: arcs indicate coding regions, stable points indicate non-coding regions and corners’ shapes reveal frame shifts. Tests on genomic data set from Saccharomyces Cerevisiae reveal that the graphic patterns for coding and non-coding regions differ to a great extent, so that the coding regions can be visually distinguished. Meanwhile, a time cost test shows that the SASR can be easily implemented with the computational complexity of O(N).

Using triplet periodicity of nucleotide sequences for finding potential reading frame shifts in genes

We introduce a novel approach for the detection of possible mutations leading to a reading frame (RF) shift in a gene. Deletions and insertions of DNA coding regions are considerable events for genes because an RF shift results in modifications of the extensive region of amino acid sequence coded by a gene. The suggested method is based on the phenomenon of triplet periodicity (TP) in coding regions of genes and its relative resistance to substitutions in DNA sequence. We attempted to extend 326 933 regions of continuous TP found in genes from the KEGG databank by considering possible insertions and deletions. We revealed totally 824 genes where such extension was possible and statistically significant. Then we generated amino acid sequences according to active (KEGG's) and hypothetically ancient RFs in order to find confirmation of a shift at a protein level. Consequently, 64 sequences have protein similarities only for ancient RF, 176 only for active RF, 3 for both and 581 have no protein similarity at all. We aimed to have revealed lower bound for the number of genes in which a shift between RF and TP is possible. Further ways to increase the number of revealed RF shifts are discussed.

Identification of protein-coding sequences using the hybridization of 18S rRNA and mRNA during translation

We introduce a new approach in this article to distinguish protein-coding sequences from non-coding sequences utilizing a period-3, free energy signal that arises from the interactions of the 3′-terminal nucleotides of the 18S rRNA with mRNA. We extracted the special features of the amplitude and the phase of the period-3 signal in protein-coding regions, which is not found in non-coding regions, and used them to distinguish protein-coding sequences from non-coding sequences. We tested on all the experimental genes from Saccharomyces cerevisiae and Schizosaccharomyces pombe. The identification was consistent with the corresponding information from GenBank, and produced better performance compared to existing methods that use a period-3 signal. The primary tests on some fly, mouse and human genes suggests that our method is applicable to higher eukaryotic genes. The tests on pseudogenes indicated that most pseudogenes have no period-3 signal. Some exploration of the 3′-tail of 18S rRNA and pattern analysis of protein-coding sequences supported further our assumption that the 3′-tail of 18S rRNA has a role of synchronization throughout translation elongation process. This, in turn, can be utilized for the identification of protein-coding sequences.

Hierarchical structure of cascade of primary and secondary periodicities in Fourier power spectrum of alphoid higher order repeats

Background

Identification of approximate tandem repeats is an important task of broad significance and still remains a challenging problem of computational genomics. Often there is no single best approach to periodicity detection and a combination of different methods may improve the prediction accuracy. Discrete Fourier transform (DFT) has been extensively used to study primary periodicities in DNA sequences. Here we investigate the application of DFT method to identify and study alphoid higher order repeats.

Results

We used method based on DFT with mapping of symbolic into numerical sequence to identify and study alphoid higher order repeats (HOR). For HORs the power spectrum shows equidistant frequency pattern, with characteristic two-level hierarchical organization as signature of HOR. Our case study was the 16 mer HOR tandem in AC017075.8 from human chromosome 7. Very long array of equidistant peaks at multiple frequencies (more than a thousand higher harmonics) is based on fundamental frequency of 16 mer HOR. Pronounced subset of equidistant peaks is based on multiples of the fundamental HOR frequency (multiplication factor n for nmer) and higher harmonics. In general, nmer HOR-pattern contains equidistant secondary periodicity peaks, having a pronounced subset of equidistant primary periodicity peaks. This hierarchical pattern as signature for HOR detection is robust with respect to monomer insertions and deletions, random sequence insertions etc. For a monomeric alphoid sequence only primary periodicity peaks are present. The 1/f^β – noise and periodicity three pattern are missing from power spectra in alphoid regions, in accordance with expectations.

Conclusion

DFT provides a robust detection method for higher order periodicity. Easily recognizable HOR power spectrum is characterized by hierarchical two-level equidistant pattern: higher harmonics of the fundamental HOR-frequency (secondary periodicity) and a subset of pronounced peaks corresponding to constituent monomers (primary periodicity). The number of lower frequency peaks (secondary periodicity) below the frequency of the first primary periodicity peak reveals the size of nmer HOR, i.e., the number n of monomers contained in consensus HOR.

[Chromosomal localization and molecular organization of human genomic fragment containing TNF/LT locus in transgenic mice]

Molecular organization, copy number and chromosomal localization of human TNF/LT locus fragment were determined in genomes of two transgenic mouse lines. Genome of the first one contains two copies, organized in head-to-tail manner and determined on eighth chromosome by karyotyping; single transgene copy of the second line is observed on the fifth chromosome. These mice could serve as valuable model for studying both human tumor necrosis factor and lymphotoxin physiological functions.

Classification analysis of triplet periodicity in protein-coding regions of genes

We introduce a new concept of triplet periodicity class (TPC) and a measure of similarity between such classes. We performed classification of 472288 triplet periodicity (TP) regions found in 578868 genes from 29th release of KEGG databank. Totally 2520 classes were obtained. They contain 94% of 472288 found cases of TP. For 92% of TP regions contained in classes the same linkage of TP to open reading frame (ORF) is observed. For 8% of TP cases we revealed a shift between ORF of a gene and ORF common for majority of genes contained in a TPC. For these 8% of periodic regions the hypothetical amino acid sequences corresponding to ORF built by TPC were made. BLAST program has shown that 2679 hypothetical amino acid sequences have statistically significant similarity with proteins from UniProt databank. We suppose that 8% of TP regions contained in classes possess a mutation originating from ORF shift. Obtained TPCs can be used for identification of genes' coding regions as well as for searching for mutations arisen arising from ORF shift.

Prediction of protein coding regions by the 3-base periodicity analysis of a DNA sequence

With the exponential growth of genomic sequences, there is an increasing demand to accurately identify protein coding regions (exons) from genomic sequences. Despite many progresses being made in the identification of protein coding regions by computational methods during the last two decades, the performances and efficiencies of the prediction methods still need to be improved. In addition, it is indispensable to develop different prediction methods since combining different methods may greatly improve the prediction accuracy. A new method to predict protein coding regions is developed in this paper based on the fact that most of exon sequences have a 3-base periodicity, while intron sequences do not have this unique feature. The method computes the 3-base periodicity and the background noise of the stepwise DNA segments of the target DNA sequences using nucleotide distributions in the three codon positions of the DNA sequences. Exon and intron sequences can be identified from trends of the ratio of the 3-base periodicity to the background noise in the DNA sequences. Case studies on genes from different organisms show that this method is an effective approach for exon prediction.