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      Genomic DNA k-mer spectra: models and modalities

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          Abstract

          Tetrapods, unlike other organisms, have multimodal spectra of k-mers in their genomes

          Abstract

          Background

          The empirical frequencies of DNA k-mers in whole genome sequences provide an interesting perspective on genomic complexity, and the availability of large segments of genomic sequence from many organisms means that analysis of k-mers with non-trivial lengths is now possible.

          Results

          We have studied the k-mer spectra of more than 100 species from Archea, Bacteria, and Eukaryota, particularly looking at the modalities of the distributions. As expected, most species have a unimodal k-mer spectrum. However, a few species, including all mammals, have multimodal spectra. These species coincide with the tetrapods. Genomic sequences are clearly very complex, and cannot be fully explained by any simple probabilistic model. Yet we sought such an explanation for the observed modalities, and discovered that low-order Markov models capture this property (and some others) fairly well.

          Conclusions

          Multimodal spectra are characterized by specific ranges of values of C+G content and of CpG dinucleotide suppression, a range that encompasses all tetrapods analyzed. Other genomes, like that of the protozoa Entamoeba histolytica, which also exhibits CpG suppression, do not have multimodal k-mer spectra. Groupings of functional elements of the human genome also have a clear modality, and exhibit either a unimodal or multimodal behaviour, depending on the two above mentioned values.

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          Most cited references15

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          The mosaic genome of warm-blooded vertebrates.

          Most of the nuclear genome of warm-blooded vertebrates is a mosaic of very long (much greater than 200 kilobases) DNA segments, the isochores; these isochores are fairly homogeneous in base composition and belong to a small number of major classes distinguished by differences in guanine-cytosine (GC) content. The families of DNA molecules derived from such classes can be separated and used to study the genome distribution of any sequence which can be probed. This approach has revealed (i) that the distribution of genes, integrated viral sequences, and interspersed repeats is highly nonuniform in the genome, and (ii) that the base composition and ratio of CpG to GpC in both coding and noncoding sequences, as well as codon usage, mainly depend on the GC content of the isochores harboring the sequences. The compositional compartmentalization of the genome of warm-blooded vertebrates is discussed with respect to its evolutionary origin, its causes, and its effects on chromosome structure and function.
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            Compositional differences within and between eukaryotic genomes.

            Eukaryotic genome similarity relationships are inferred using sequence information derived from large aggregates of genomic sequences. Comparisons within and between species sample sequences are based on the profile of dinucleotide relative abundance values (The profile is rho*XY = f*XY/f*Xf*Y for all XY, where f*X denotes the frequency of the nucleotide X and f*XY denotes the frequency of the dinucleotide XY, both computed from the sequence concatenated with its inverted complement). Previous studies with respect to prokaryotes and this study document that profiles of different DNA sequence samples (sample size >/=50 kb) from the same organism are generally much more similar to each other than they are to profiles from other organisms, and that closely related organisms generally have more similar profiles than do distantly related organisms. On this basis we refer to the collection (rho*XY) as the genome signature. This paper identifies rho*XY extremes and compares genome signature differences for a diverse range of eukaryotic species. Interpretations on the mechanisms maintaining these profile differences center on genome-wide replication, repair, DNA structures, and context-dependent mutational biases. It is also observed that mitochondrial genome signature differences between species parallel the corresponding nuclear genome signature differences despite large differences between corresponding mitochondrial and nuclear signatures. The genome signature differences also have implications for contrasts between rodents and other mammals, and between monocot and dicot plants, as well as providing evidence for similarities among fungi and the diversity of protists.
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              Barcodes for genomes and applications

              Background Each genome has a stable distribution of the combined frequency for each k-mer and its reverse complement measured in sequence fragments as short as 1000 bps across the whole genome, for 1
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2009
                8 October 2009
                : 10
                : 10
                : R108
                Affiliations
                [1 ]School of Computer Science, Tel Aviv University, Klausner St, Ramat-Aviv, Tel-Aviv 39040, Israel
                [2 ]School of Physics and Astronomy, Tel Aviv University, Klausner St, Ramat-Aviv, Tel-Aviv 39040, Israel
                [3 ]European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
                Article
                gb-2009-10-10-r108
                10.1186/gb-2009-10-10-r108
                2784323
                19814784
                3c364919-0064-48f7-85b0-823c23d8e7c0
                Copyright ©2009 Chor et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 March 2009
                : 14 August 2009
                : 8 October 2009
                Categories
                Research

                Genetics
                Genetics

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