Journal Article

Efficient computation of all perfect repeats in genomic sequences of up to half a gigabyte, with a case study on the human genome

Verónica Becher, Alejandro Deymonnaz and Pablo Heiber

in Bioinformatics

Volume 25, issue 14, pages 1746-1753
Published in print July 2009 | ISSN: 1367-4803
Published online May 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp321
Efficient computation of all perfect repeats in genomic sequences of up to half a gigabyte, with a case study on the human genome

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Motivation: There is a significant ongoing research to identify the number and types of repetitive DNA sequences. As more genomes are sequenced, efficiency and scalability in computational tools become mandatory. Existing tools fail to find distant repeats because they cannot accommodate whole chromosomes, but segments. Also, a quantitative framework for repetitive elements inside a genome or across genomes is still missing.

Results: We present a new efficient algorithm and its implementation as a software tool to compute all perfect repeats in inputs of up to 500 million nucleotide bases, possibly containing many genomes. Our algorithm is based on a suffix array construction and a novel procedure to extract all perfect repeats in the entire input, that can be arbitrarily distant, and with no bound on the repeat length. We tested the software on the Homo sapiens DNA genome NCBI 36.49. We computed all perfect repeats of at least 40 bases occurring in any two chromosomes with exact matching. We found that each H.sapiens chromosome shares ∼10% of its full sequence with every other human chromosome, distributed more or less evenly among the chromosome surfaces. We give statistics including a quantification of repeats by diversity, length and number of occurrences. We compared the computed repeats against all biological repeats currently obtainable from Ensembl enlarged with the output of the dust program and all elements identified by TRF and RepeatMasker (ftp://ftp.ebi.ac.uk/pub/databases/ensembl/jherrero/.repeats/all_repeats.txt.bz2). We report novel repeats as well as new occurrences of repeats matching with known biological elements.

Availability: The source code, results and visualization of some statistics are accessible from http://kapow.dc.uba.ar/patterns/

Contact: vbecher@dc.uba.ar

Journal Article.  5540 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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