Enrichment of oligonucleotide sets with transcription control signals. II: Mammalian DNA

Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data

As an important subtype of structural variations, chromosomal translocation is associated with various diseases, especially cancers, by disrupting gene structures and functions. Traditional methods for identifying translocations are time consuming and have limited resolutions. Recently, a few studies have employed next-generation sequencing (NGS) technology for characterizing chromosomal translocations on human genome, obtaining high-throughput results with high resolutions. However, these studies are mainly focused on mechanism-specific or site-specific translocation mapping. In this study, we conducted a comprehensive genome-wide analysis on the characterization of human chromosomal material exchange with regard to the chromosome translocations. Using NGS data of 1,481 subjects from the 1000 Genomes Project, we identified 15,349,092 translocated DNA fragment pairs, ranging from 65 to 1,886 bp and with an average size of approximately 102 bp. On average, each individual genome carried about 10,364 pairs, covering approximately 0.069% of the genome. We identified 16 translocation hot regions, among which two regions did not contain repetitive fragments. Results of our study overlapped with a majority of previous results, containing approximately 79% of approximately 2,340 translocations characterized in three available translocation databases. In addition, our study identified five novel potential recurrent chromosomal material exchange regions with greater than 20% detection rates. Our results will be helpful for an accurate characterization of translocations in human genomes, and contribute as a resource for future studies of the roles of translocations in human disease etiology and mechanisms.

Species-independent detection of RNA virus by representational difference analysis using non-ribosomal hexanucleotides for reverse transcription

A method for the isolation of genomic fragments of RNA virus based on cDNA representational difference analysis (cDNA RDA) was developed. cDNA RDA has been applied for the subtraction of poly(A)⁺ RNAs but not for poly(A)⁻ RNAs, such as RNA virus genomes, owing to the vast quantity of ribosomal RNAs. We constructed primers for inefficient reverse transcription of ribosomal sequences based on the distribution analysis of hexanucleotide patterns in ribosomal RNA. The analysis revealed that distributions of hexanucleotide patterns in ribosomal RNA and virus genome were different. We constructed 96 hexanucleotides (non-ribosomal hexanucleotides) and used them as mixed primers for reverse transcription of cDNA RDA. A synchronous analysis of hexanucleotide patterns in known viral sequences showed that all the known genomic-size viral sequences include non-ribosomal hexanucleotides. In a model experiment, when non-ribosomal hexanucleotides were used as primers, in vitro transcribed plasmid RNA was efficiently reverse transcribed when compared with ribosomal RNA of rat cells. Using non-ribosomal primers, the cDNA fragments of severe acute respiratory syndrome coronavirus and bovine parainfluenza virus 3 were efficiently amplified by subtracting the cDNA amplicons derived from uninfected cells from those that were derived from virus-infected cells. The results suggest that cDNA RDA with non-ribosomal primers can be used for species-independent detection of viruses, including new viruses.

Correlations and anticorrelations among nucleotide distributions along the genomes of various organisms

We have analyzed correlations of nucleotide distributions along more than 50 megabases of the longest sequenced parts of the human, mouse, Drosophila, Arabidopsis, yeast, E.coli and three kinds of viral genomes. The strongest correlations were observed between the distributions of C and G, in particular in the genome of Drosophila. This correlation was much weaker, though still strong, in the human genome and E.coli that exhibited the same level of this correlation. The C/G correlation hardly originates from the isochores because the isochores were not reported to occur in the genomes of Drosophila and E. coil. The genomic distribution curves of adenine and thymine were also positively correlated in all analyzed organisms except for the yeast where they were anticorrelated. Still stronger anticorrelations were, however, observed between the genomic distributions of A and C and between G and T. These genomic distributions anticorrelated almost generally and very strong. These anticorrelations are likely to originate from point mutations resulting from unrepaired GA mispairing as a replication intermediate. The C/A or G/T anticorrelation or compensation is a very strong and general new phenomenon that shapes the genomic nucleotide sequences.

The usage of oligopeptides in proteins correlates negatively with molecular weight

We scanned the Swissprot databank to study the distribution of oligopeptides in sequenced proteins. We observed that in 7839,000 amino acids in the bank, the frequency is strongly and negatively correlated with molecular weight. The correlation coefficient is -0.63 for single amino acids, -0.58 for dipeptides, -0.54 for tri- and -0.46 for tetrapeptides. In subsets of proteins of man, mouse, rat drosophila, yeast and E. coli, the correlations were very similar to those for the total database. The intensity of the correlation diminishes linearly with the length of the peptide. We attributed the loss of dominance of molecular weight in determining the frequency of oligopeptides of higher order, to the emergence of function in longer oligopeptides. In the case of dipeptides, we observed that those composed of the same amino acid are in great excess in comparison with their expectation. The WW dipeptide is singular, in the sense that is observed/expected ratio is 13.5 standard deviations above the average ratio.