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. 2007 Jun 18;8:209.
doi: 10.1186/1471-2105-8-209.

CRISPR Recognition Tool (CRT): A Tool for Automatic Detection of Clustered Regularly Interspaced Palindromic Repeats

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Free PMC article

CRISPR Recognition Tool (CRT): A Tool for Automatic Detection of Clustered Regularly Interspaced Palindromic Repeats

Charles Bland et al. BMC Bioinformatics. .
Free PMC article

Abstract

Background: Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) are a novel type of direct repeat found in a wide range of bacteria and archaea. CRISPRs are beginning to attract attention because of their proposed mechanism; that is, defending their hosts against invading extrachromosomal elements such as viruses. Existing repeat detection tools do a poor job of identifying CRISPRs due to the presence of unique spacer sequences separating the repeats. In this study, a new tool, CRT, is introduced that rapidly and accurately identifies CRISPRs in large DNA strings, such as genomes and metagenomes.

Results: CRT was compared to CRISPR detection tools, Patscan and Pilercr. In terms of correctness, CRT was shown to be very reliable, demonstrating significant improvements over Patscan for measures precision, recall and quality. When compared to Pilercr, CRT showed improved performance for recall and quality. In terms of speed, CRT proved to be a huge improvement over Patscan. Both CRT and Pilercr were comparable in speed, however CRT was faster for genomes containing large numbers of repeats.

Conclusion: In this paper a new tool was introduced for the automatic detection of CRISPR elements. This tool, CRT, showed some important improvements over current techniques for CRISPR identification. CRT's approach to detecting repetitive sequences is straightforward. It uses a simple sequential scan of a DNA sequence and detects repeats directly without any major conversion or preprocessing of the input. This leads to a program that is easy to describe and understand; yet it is very accurate, fast and memory efficient, being O(n) in space and O(nm/l) in time.

Figures

Figure 1
Figure 1
An occurrence of a CRISPR. Repetitive sequences are detected by reading a small search window and then scanning ahead for exact k-mer matches separated by a similar distance.
Figure 2
Figure 2
Running time based on genome size, using repeat length 21–37 and spacer length 19–48. Running times for the three compared search tools, based on genome size (CRT is listed twice, once for windows size 6 and once for window size 8). The y-axis represents time in seconds. The x-axis lists the genome accession numbers, followed by their sizes in million base pairs (Mbp). As the size of the genomes increase, it can be seen that running times of the search tools increase at different rates. Below, the corresponding organism names are given. [IMG:AE015450] Mycoplasma gallisepticum (strain R(low)) [IMG:AE004439] Pasteurella multocida (strain Pm70) [IMG:AE017282] Methylococcus capsulatus (strain Bath/NCIMB 11132) [IMG:AP006627] Bacillus clausii (strain KSM-K16) [IMG:BX470251] Photorhabdus luminescens (subsp. laumondii, strain TT01).
Figure 3
Figure 3
Running time based on genome size, excluding Patscan. Running times for the search tools, excluding Patscan. The parameter values and organisms are the same as that in Figure 2. However, by removing Patscan, a better comparison of the execution speeds of PilerCR and CRT can be achieved.
Figure 4
Figure 4
Running time based on genome size, using repeat length 19–50 and spacer length is 19–60. Running times for two of the compared search tools, based on genome size (CRT is listed twice, once for windows size 6 and once for window size 8). This figure is the same as Figure 3, except the ranges of the repeat length and spacer length to be detected are increased.
Figure 5
Figure 5
Running time based on number of repeats, using repeat length 21–37 and spacer length 19–48. Running times for two of the compared search tools based on number of repeats processed. CRT is listed twice, once for windows size 6 and once for window size 8. The y-axis represents time in seconds. The x-axis lists the genome accession numbers, followed by the number of repeats detected in the genome. As the size of the genomes increase, it can bee seen that running times of the search tools increase at different rates. Below, the corresponding organism names and the number of CRISPR loci are given. All genomes are close in size (2.7 – 3.8 Mbp). [IMG:BA000031] Vibrio parahaemolyticus (serovar O3:K6, strain RIMD 2210633) loci: 0 [IMG:CR628337] Legionella pneumophila (strain Lens) loci: 2 [IMG:AP006840] Symbiobacterium thermophilum (strain IAM 14863/T) loci: 3 [IMG:AE017180] Geobacter sulfurreducens (strain ATCC 51573/PCA) loci: 2 [IMG:AE008691] Thermoanaerobacter tengcongensis (strain MB4/JCM 11007) loci: 3 [IMG:AE006641] Sulfolobus solfataricus P2 loci: 7 [IMG:BA000023] Sulfolobus tokodaii str. 7 DNA loci: 7.

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