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

Identification of a circular code periodicity in the bacterial ribosome: origin of codon periodicity in genes?

Three-base periodicity (TBP), where nucleotides and higher order n-tuples are preferentially spaced by 3, 6, 9, etc. bases, is a well-known intrinsic property of protein-coding DNA sequences. However, its origins are still not fully understood. One hypothesis is that the periodicity reflects a primordial coding system that was used before the emergence of the modern standard genetic code (SGC). Recent evidence suggests that the X circular code, a set of 20 trinucleotides allowing the reading frames in genes to be retrieved locally, represents a possible ancestor of the SGC. Motifs from the X circular code have been found in the reading frame of protein-coding regions in extant organisms from bacteria to eukaryotes, in many transfer RNA (tRNA) genes and in important functional regions of the ribosomal RNA (rRNA), notably in the peptidyl transferase centre and the decoding centre. Here, we have used a powerful correlation function to search for periodicity patterns involving the 20 trinucleotides of the X circular code in a large set of bacterial protein-coding genes, as well as in the translation machinery, including rRNA and tRNA sequences. As might be expected, we found a strong circular code periodicity 0 modulo 3 in the protein-coding genes. More surprisingly, we also identified a similar circular code periodicity in a large region of the 16S rRNA. This region includes the 3' major domain corresponding to the primordial proto-ribosome decoding centre and containing numerous sites that interact with the tRNA and messenger RNA (mRNA) during translation. Furthermore, 3D structural analysis shows that the periodicity region surrounds the mRNA channel that lies between the head and the body of the SSU. Our results support the hypothesis that the X circular code may constitute an ancestral translation code involved in reading frame retrieval and maintenance, traces of which persist in modern mRNA, tRNA and rRNA despite their long evolution and adaptation to the SGC.

A Spectral Rotation Method with Triplet Periodicity Property for Planted Motif Finding Problems

BACKGROUND

Genes are known as functional patterns in the genome and are presumed to have biological significance. They can indicate binding sites for transcription factors and they encode certain proteins. Finding genes from biological sequences is a major task in computational biology for unraveling the mechanisms of gene expression.

OBJECTIVE

Planted motif finding problems are a class of mathematical models abstracted from the process of detecting genes from genome, in which a specific gene with a number of mutations is planted into a randomly generated background sequence, and then gene finding algorithms can be tested to check if the planted gene can be found in feasible time.

METHODS

In this work, a spectral rotation method based on triplet periodicity property is proposed to solve planted motif finding problems.

RESULTS

The proposed method gives significant tolerance of base mutations in genes. Specifically, genes having a number of substitutions can be detected from randomly generated background sequences. Experimental results on genomic data set from Saccharomyces cerevisiae reveal that genes can be visually distinguished. It is proposed that genes with about 50% mutations can be detected from randomly generated background sequences.

CONCLUSION

It is found that with about 5 insertions or deletions, this method fails in finding the planted genes. For a particular case, if the deletion of bases is located at the beginning of the gene, that is, bases are not randomly deleted, then the tolerance of the method for base deletion is increased.

Categorical spectral analysis of periodicity in human and viral genomes

Periodicity in nucleotide sequences arises from regular repeating patterns which may reflect important structure and function. Although a three-base periodicity in coding regions has been known for some time and has provided the basis for powerful gene prediction algorithms, its origins are still not fully understood. Here, we show that, contrary to common belief, amino acid (AA) bias and codon usage bias are insufficient to create base-3 periodicity. This article applies the rigorous method of spectral envelope to systematically characterize the contributions of codon bias, AA bias and protein structural motifs to the three-base periodicity of coding sequences. The method is also used to classify CpG islands in the human genome. In addition, we show how spectral envelope can be used to trace the evolution of viral genomes and monitor global sequence changes without having to align to previously known genomes. This approach also detects reassortment events, such as those that led to the 2009 pandemic H1N1 virus.

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.

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.