Bioinformatics Advance Access originally published online on October 27, 2004
Bioinformatics 2005 21(7):846-852; doi:10.1093/bioinformatics/bti072
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ColorHOR—novel graphical algorithm for fast scan of alpha satellite higher-order repeats and HOR annotation for GenBank sequence of human genome
2
i 1
ini 3
1Faculty of Science, University of Zagreb Bijenika 32, 10000 Zagreb, Croatia
2Department of Internal Medicine, University Hospital Rebro Ki
patieva 12, Zagreb, Croatia
3Ru
r Bokovi Institute Bijenika 54, Zagreb, Croatia
*To whom correspondence should be addressed.
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Abstract |
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 TOP Abstract INTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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Motivation: GenBank data are at present lacking alpha satellite higher-order repeat (HOR) annotation. Furthermore, exact HOR consensus lengths have not been reported so far. Given the fast growth of sequence databases in the centromeric region, it is of increasing interest to have efficient tools for computational identification and analysis of HORs from known sequences.
Results: We develop a graphical user interface method, ColorHOR, for fast computational identification of HORs in a given genomic sequence, without requiring a priori information on the composition of the genomic sequence. ColorHOR is based on an extension of the key-string algorithm and provides a color representation of the order and orientation of HORs. For the key string, we use a robust 6 bp string from a consensus alpha satellite and its representative nature is tested. ColorHOR algorithm provides a direct visual identification of HORs (direct and/or reverse complement). In more detail, we first illustrate the ColorHOR results for human chromosome 1. Using ColorHOR we determine for the first time the HOR annotation of the GenBank sequence of the whole human genome. In addition to some HORs, corresponding to those determined previously biochemically, we find new HORs in chromosomes 4, 8, 9, 10, 11 and 19. For the first time, we determine exact consensus lengths of HORs in 10 chromosomes. We propose that the HOR assignment obtained by using ColorHOR be included into the GenBank database.
Availability: The program with graphical user interface application for ColorHOR is freely available at http://www.hazu.hr/KSA/colorHOR.html. It can be run on any platform on which wxPython is supported.
Contact: paar{at}hazu.hr
Supplementary information: http://www.hazu.hr/KSA/colorHOR.html.
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INTRODUCTION |
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TOPAbstractINTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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Alpha satellite DNA defined by a diverged
171 bp motif repeated in a head-to-tail tandem, was identified at centromeres of all primate chromosomes (Warburton and Willard, 1996). Human and other primate chromosomes contain alpha satellites hierarchically organized into higher-order repeat (HOR) or alphoid arrays, which were systematically studied by restriction enzyme analysis (Maio, 1971; Manuelidis and Wu, 1978; Willard, 1985; Waye and Willard, 1985; Willard and Waye, 1987a; Wevrick et al., 1992; Lee et al., 1997). Stretches of alpha satellites without additional sequence structure are known as monomeric (Wevrick et al., 1992; Alexandrov et al., 1993; Schueler et al., 2001).
Independent, 171 bp monomers of alpha satellite DNA generally exhibit substantial intermonomeric sequence divergence (20–40%), while HORs exhibit mutual sequence divergence of <5% (Maio, 1971; Manuelidis and Wu. 1978; Willard, 1985; Waye and Willard, 1985; Warburton and Willard, 1996; Puente et al., 1998; Wevrick et al., 1992; Lee et al., 1997).
Given the fast growth of sequence databases, it is of increasing interest to have tools for computational analysis of tandem repeats in a given sequence. Various algorithms for searching tandem repeats have been developed (Milosavljevic and Jurka, 1993; Benson and Waterman, 1994; Benson, 1999; Blanchard et al. 2000; Baldi and Baisnee, 2000; Bortnik et al., 1994; Castello et al., 2002; Hauth, 2002; Hauth and Joseph, 2002; Rosandi et al., 2003). However, despite significant progress in computational genomics, identification of complex repetitive patterns within anonymous DNA sequences in the presence of sizeable deviations from periodicity remains a challenge. In particular, for HORs the difficulties are largely due to imperfect patterns containing substitutions, insertions and deletions.
Recently, we introduced a novel key-string algorithm (KSA) for computational identification and study of HORs in clones containing alpha satellites (Rosandi et al., 2003). Key-string was used in KSA to segment computationally a given genomic sequence into key-string subsequences, resulting in an array of key-string lengths that enables identification of HORs. While a wide class of 3–6 bp key strings provide HORs, only for some key-strings, referred to as dominant, they are segmented simultaneously into both HORs and alpha monomers (Rosandi et al., 2003).
In this paper the KSA method is extended by developing a novel graphical method, the ColorHOR algorithm, providing a visual display. We note that coloring is widely used in some contexts of bioinformatics; for example, the subtle conservation patterns can be revealed by coloring according to the conservation of amino acid groupings (Taylor, 1986) or for consensus-based coloring of multiple alignments (Goodstadt and Ponting, 2001). A detailed presentation of ColorHOR results is given for chromosome 1 as an illustration. Applying ColorHOR we identify HORs in GenBank data of the whole human genome.
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SYSTEM AND METHODS |
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TOPAbstractINTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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ColorHOR algorithm
The graphical algorithm introduced and developed in this paper, based on the use of key-string, models a given genomic sequence onto a graph in such a way that an elegant graph-layout is obtained. This algorithm is very effective for long sequences, as for example for a whole chromosome or genome, and proceeds as follows.
Choice of key-string for human genome
The only input to ColorHOR is a key-string which segments a given sequence both into HORs and alpha satellites. Here, we provide a simple prescription for the choice of key-string for human genome, using the most robust 6 bp strings from known alpha satellite consensus sequence. In fact, the most robust 6 bp string in human alpha satellite consensus sequence from Choo et al. (1991) is GAAACA; the corresponding average percentage of consensus bases in alpha satellite monomers of wide-ranging chromosomal origin is 92%. Only slightly less robust strings from alpha satellite consensus sequence from Choo et al. (1991) are AGAAAC, GAGCAG, AAACAC and AGAGAA. Similar robustness can be seen in more recent alpha satellite consensus (Romanova et al., 1996), and is also consistent with early consensus from Waye and Willard (1987). Finally, after completing our ColorHOR treatment of human genome, we checked that the same robustness is persistent in samples of tens of thousands of alpha satellite monomers from GenBank data.
With respect to the choice of 6 bp key string, we note that the number of possible variations for 6 bp strings is 46 = 4096, leading, in general, to a spectrum of distance frequencies with pronounced peaks in a domain of HOR lengths up to a few thousands.
For the application of the ColorHOR algorithm to GenBank sequence of human genome, we choose the key-string TGTTTC, a reverse complement of GAAACA [for alpha satellite consensus sequence from Choo et al. (1991) the + strand was used].
By repeating the ColorHOR analysis of the GenBank sequence of the human genome using some other robust strings from alpha satellite consensus sequence as a key-string, we obtain results similar to those corresponding to the initial key string TGTTTC.
Computational construction of length–frequency distribution (N versus 
diagram)
Using the key-string, the GenBank genomic sequence is computationally segmented into key-string subsequences, each starting with the key-string. Distribution of frequency N versus key-string subsequence length is displayed diagrammatically (N versus diagram) (Fig. 1).
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Computational construction of alpha staircase (Nc versus n diagram) for a whole chromosome
In the next step, the cumulative frequency Nc of the key-string subsequence length
= 171 bp, up to a position n, is computed and displayed diagrammatically along the chromosome sequence (Nc versus n diagram) (Fig. 2). Any local clustering of the 171 bp subsequence lengths along the sequence results in a steep increase (stair) in the Nc versus n graph. Such a graph along a whole chromosome sequence will be referred to as the alpha staircase. The location of each alpha satellite-containing clone in a chromosome sequence will be associated with a stair in the alpha staircase. This provides fast identification of clones and/or contigs containing alpha satellites.
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Computational construction of colored bands and color-motif
For each alpha satellite-containing clone, identified in the previous step, the corresponding length–frequency distribution (N versus
diagram) is displayed for the same key-string as used in the previous step for computation of the N versus diagram of the whole chromosome sequence (Fig. 3). On the basis of the highest peaks we define the coloring rule: to each length corresponding to pronounced peaks a particular color is assigned. According to this coloring rule, the stripes displaying the corresponding key-string subsequences along the band of genomic sequence are colored. In this way, a colored band with repetitive color-motif is obtained at the location of each HOR-containing clone (Fig. 4).
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A direct visual inspection easily reveals a repetitive color-motif, corresponding to HOR. Coordinates of HOR regions and of individual HOR copies, as well as larger deviations from consensus (insertions, deletions), are easily identified from the pattern of colored bands.
Subsequent to the analysis using the key-string TGTTTC, the analysis using its reverse complement is performed, providing identification and structure of reverse complement HORs. For reverse complement HORs the color-motif is reversed with respect to the color-motif of direct HOR. Accurate visualization of such information allows the user to distinguish direct and reverse complement HORs in a given sequence.
Graphical user interface application for ColorHOR
We have implemented the application associated with ColorHOR for interactive graphical use. The application has been developed using the Python scripting language and the wxPython windows widgets library, and is available at www.hazu.hr/KSA/colorHOR.html. It can be run on Microsoft Windows where wxPython is supported. Technical information for users is provided as Supplementary information. This approach is simple and can be easily incorporated into the analysis of the GenBank database.
In addition to MS Windows binary, we provide a full source code that can be run on any platform with prerequisites satisfied (details in archive) on the project website. Besides MS Windows this application has been tested also on LINUX.
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ILLUSTRATION: IMPLEMENTATION OF ColorHOR FOR CHROMOSOME 1 |
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TOPAbstractINTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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Alpha staircase of chromosome 1
In the first step, we construct the alpha staircase for the GenBank sequence of chromosome 1 using the key-string TGTTTC. For each subsequence length
we compute the corresponding frequency N and construct the length–frequency distribution, N versus (Fig. 1). Above the background of noise the most pronounced peaks are associated with 342, 105, 256, 65 and 171 bp subsequences. The noise approximately corresponds to white noise, with superposed very slow decrease of frequency N with increasing subsequence length . Starting from N 
70 the frequency slowly decreases with , according to a weak exponential dependence exp(–k). We note that this noise corresponds to exact matches of the key-string, but at sizeably lower frequencies than the pronounced peaks.
The diagram for cumulative frequency Nc of subsequence length = 171 bp was plotted going along the GenBank sequence of chromosome 1. The computed alpha-staircase (Fig. 2) has a pronounced stair at the position of each alpha satellite region (HOR-type or monomeric type) within the GenBank sequence of chromosome 1. The alpha staircase contains only two pronounced steps, corresponding to the clones (BACs) BX284928.3 (163 725 bp) and BX248407.4 (155 428 bp).
The relationship among monomers within the 1866 bp consensus HOR is investigated by pairwise comparison. The sequence variation among 11 component monomers is 19–46%. In contrast, the average divergence between the 1866 bp HOR copies and consensus HOR is 1.8%, while the average divergence among HOR copies is 2.8%.
ColorHOR display of direct and reverse complement 1866 bp HORs in chromosome 1
After identifying alpha satellite-containing clones in the alpha staircase, we investigate whether these alpha satellites are organized into HORs.
First, we construct the N versus diagram for the clone BX284928.3 (Fig. 3). This clone corresponds to the largest step in the alpha staircase for chromosome 1. The highest peaks are at positions of 342, 171, 65, 105, 101, 402, 106, 232 and 338 bp subsequences. Already in Figure 1, we have identified peaks at these subsequence lengths in the N versus diagram computed for the whole chromosome 1. Additional peaks in Figure 1, at 256 bp and at some shorter subsequence lengths, as well as the background of noise, are not associated with clones BX284928.3 and BX248407.4.
On the basis of pronounced peaks in Figure 3, we define a coloring rule (insets in Figs 4 and 5). This rule assigns a particular color to each subsequence length of pronounced alpha satellite-related peaks in the N versus diagram.
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Each of the stripes corresponding to the key-string subsequences along the band displaying the genomic sequence of a clone is colored according to the coloring rule. In this way we construct computationally a colored band. A more detailed insight into HOR structure was achieved by further expanding segments of the colored band.
The colored band corresponding to the clone BX284928.3 is displayed in Figure 5 (direct HORs) and Figure 5 (reverse complement HORs).
In the colored band of BX284928.3, corresponding to the key-string TGTTTC, visual inspection reveals a characteristic color-motif of the 1866 bp HOR (magnified segment in Fig. 4, top left). As a signature of this color-motif we choose a pronounced black-yellow-red triplet of stripes.
In the color-motif of some HOR copies the single-base substitutions can lead to fragmentation of a colored stripe into narrower stripes. For example, the 338 bp stripe (cyan) is at some positions fragmented into a 106 bp stripe (gray) and a 232-bp stripe (violet) (magnified segment in Fig. 4, top right), without affecting the global pattern of the color-motif.
In Figure 4 there are two stretches of colored stripes, each of 50 kb, with the same characteristic color-motif corresponding to 1866 bp HORs.
In the colored band of BX284928.3 corresponding to the key-string GAAACA (reverse complement of TGTTTC), a visual inspection reveals in the front segment of 20 kb a stretch with reverse color-motif (Fig. 5). Each HOR copy in Figure 5 is identical to the reverse complement of the 1866 bp direct HOR from Figure 4 (at the level of 1–3% divergence). This is visually reflected in reversal of the characteristic triplet of stripes: the red-yellow-black triplet of stripes in Figure 5 as the signature of reverse complement HOR structure, is reversed with respect to the black-yellow-red triplet for direct HORs in Figure 4. This provides a simple visual distinction of direct and reverse complement HORs.
Combining Figures 4 and 5 we notice a broad white stripe in the central part of band (roughly between positions 73 000 and 116 000). This ‘hole’ is characterized by LINE/L1, L2 and SINE/Alu GenBank annotation.
In analogy to Figures 4 and 5 we perform the ColorHOR analysis for the GenBank sequence of BX248407.4. We find four distinct stretches of the 1866 bp 11mer HOR sequences, displaying the same color-motif as the clone BX284928.3: two stretches have the color-motif of direct 1866 bp HOR and two of the reverse complement (direct-reverse complement-direct-reverse complement).
Finally, investigating the degree of identity required by the program to declare a match to the key-string, we find that a tandem of alpha monomers is identified as HOR at the level of 5% divergence.
KSA segmentation of 1866 bp HORs in chromosome 1 into 11 alpha monomers and novel consensus sequence
Computing the alpha staircase and the ColorHOR diagram in the previous two steps we identified two clones containing HORs, BX284928.3 and BX248407.4. Now we perform a detailed KSA analysis of HORs in BX284928.3 with KSA segmentation of HORs into alpha monomers (Table 1). In supplementary data we display the KSA analysis for BX248407.4 (Table S1). Including all HORs of length 1866 bp (both direct and reverse complement) we derive the 1866 bp consensus HOR (Supplementary data, Table S3). Exactly the same consensus HOR is obtained on replacing the clone BX248407.4 by a more recent version BX248407.26, with KSA analysis displayed in Table S2.
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Thus, the 1866 bp HOR is segmented into 11 alpha monomers of lengths 168, 171, 171, 171, 171, 171, 170, 167, 169, 167 and 170 bp.
340 bp HORs in BX284928.3
Near the end of BX284928.3 we found a 4.5 kb stretch characterized by tandem with a color-motif consisting of blue-magenta doublet (magnified segment in Fig. 5, top right). It corresponds to dimers of 340 bp (171 bp, 169 bp). We note that some of the stripes remain blank, as a consequence of point mutations. We identified a stretch of 340 bp dimers. This is probably a front section of a much longer sequence of 340 bp HORs in chromosome 1, extending into a neighboring clone, not yet included in GenBank.
We have also studied the overall mutual sequence divergence of 11mer and dimeric alpha satellite. This divergence is in the range from 23 to 47%.
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HOR ANNOTATION FOR WHOLE GenBank SEQUENCE OF HUMAN GENOME AND EXACT CONSENSUS LENGTHS |
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TOPAbstractINTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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We apply the ColorHOR algorithm to GenBank data of all human chromosomes. The results of this computational search for HORs with n > 2 are displayed in Table 2.
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Some of these nmers correspond to known nmers, previously found by biochemical investigations (Waye et al., 1987b; Choo et al., 1991; Wevrick and Willard, 1991; Wevrick et al., 1992; Warburton and Willard, 1996; Lee et al., 1997): 11mers in chromosome 1; 16mers in chromosome 7; 7mers in chromosome 9; 13mers in chromosome 19; and 12mers in chromosome X. Some HORs previously identified by biochemical investigations are not found by computational analysis of GenBank data; this is not surprising having in mind the incompleteness of the centromeric region in GenBank data.
In contrast, we find several new HORs: 13mers in chromosome 4; 11mers in chromosome 8; 4mers in chromosome 9; 18mers in chromosome 10; 12mers in chromosome 11; and 17mers in chromosome 19. These HORs were not reported previously (Warburton and Willard, 1996; Lee et al., 1997). In chromosome 17 we find 14mers; in previous biochemical data (Choo et al., 1991) 12mers to 16mers were reported.
For the first time, we determine exact consensus lengths of HORs: 1866 bp in chromosome 1; 2211 bp in chromosome 4; 1868 bp in chromosome 8; 678, 680, 1190 and 1192 bp in chromosome 9; 3058 bp in chromosome 10; 2047 bp in chromosome 11; 2379 bp in chromosome 17; 2896 and 2214 bp in chromosome 19 and 2057 bp in chromosome X.
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DISCUSSION |
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TOPAbstractINTRODUCTIONSYSTEM AND METHODSILLUSTRATION: IMPLEMENTATION OF...HOR ANNOTATION FOR WHOLE...DISCUSSIONREFERENCES |
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One should take into account several issues concerning genome assembly and known higher-order alpha satellites. For example, HOR-containing BACs BX284928.3 and BX248407.4 in chromosome 1 were of working draft quality, composed of unordered pieces, not fully assembled and not included in the contiguous map. As such, they do not connect to any other contiguous chromosome 1 scaffold and are surrounded by genome gaps on both sides. It is even questionable whether these gaps are distinct, or whether they overlap each other and are in part duplicates of the same region of genome. We investigated this problem by identifying complete overlaps (100% convergence) (direct, reverse, complement or reverse complement) of intervals >1 kb. In this way we identified seven overlap intervals (Supplementary data, Table S4). These intervals are interspersed and mapped in an irregularly intertwined way. For example, the interval from position 37992 to 42322 in BX284928.3 is mapped into reverse complement of interval from 82472 to 86802 in BX248407.4. The longest overlap interval is of 23 276 bp. The total length of seven overlap intervals of these two BACs is 66 773 bp.
Furthermore, it should be noted that the sequence BX248407.4 was released in 2003 and consists of 11 unordered pieces. We performed an additional analysis, using the completed sequence BX248407.26, released in 2004. We find that HORs which are reverse complemented in BX248407.4 turn into direct HORs in BX248407.26.
Using the ColorHOR program we obtain a simple graphical display of direct HORs, corresponding to the characteristic color-motif, and of reverse complement HORs, corresponding to the reverse color-motif. We note that inversions in alpha satellite DNA have been previously found in chromosome 7 (Wevrick et al., 1992), where two of four examined clones contained large inversions. This was unexpected, as all thoroughly analyzed alpha satellite clones previously isolated have been tandem and unidirectional.
We performed a sequence divergence study taking into account that HORs in either forward or reverse orientations are not distinct species, and that, given the lack of assembly validation, one cannot be sure of orientation. Therefore, the only divergence of consequence is overall sequence divergence comparing all 11mers in both BACs in chromosome 1. The calculated divergence is somewhat higher than the previously determined sequence variation of 16–36% among monomers of pSD1–1 (Waye et al., 1987). In contrast, we compared our 1866 bp consensus HOR to the previously determined 11mer in chromosome 1, pSD1–1 (Willard and Waye, 1987b). Aligning these sequences we found that they diverge by 9%, showing a sizeable degree of similarity. Furthermore, we calculated the divergence of 11mer and dimeric alpha satellites, showing that dimeric alpha satellite in BX284928.3 is a distinct type of HOR from 11mer.
Repeat units of n bp arranged in a head-to-tail fashion have an arbitrary beginning or end that can be described as starting at any of the n registers. The historical use of location of restriction enzyme sites has resulted in different published starts of homologous repeat units (Warburton et al., 1993). In this sense, a choice of key-string in the KSA algorithm could be compared to a choice of a particular ‘computer enzyme’.
Our graphical computational method is very efficient and simple from a computational viewpoint, with powerful graphical user interface applications. It provides a fast scan of HORs in a whole chromosome sequence, taking 1 min computing time per chromosome using PC Pentium IV. Our HOR-searching method does not involve any numerical parameter, the only input being the dominant key-string, which is deduced as a robust string from known alpha satellite consensus.
Let us comment on a comparison with the well-known computational tool Tandem repeats finder (Benson, 1999). Our method is very fast and selective in screening for HORs in very long sequences, of hundreds of Mb. It also provides identification of individual HORs outside of tandem, that are not identified by Tandem repeats finder. Furthermore, the most recent version of Tandem repeats finder (ver. 3.21) could identify HORs up to the length of 2000 bp, with a suitable choice of parameters, while our method has no such limitation and can identify HORs of any length. We also point out that the KSA analysis provides a full list and structure of insertions, deletions and point mutations within HORs, and identifies HORs in the presence of more pronounced insertions and/or deletions. For example, in BX284928.3 our method identifies 60 HORs (complete or incomplete), while the Tandem repeats finder identifies 51 HORs.
We note that the ColorHOR program can be used to analyze other satellite sequences as well, as for example monomeric alpha satellites. This program could also be used for the identification of interspersed repeats by using proper robust strings.
This paper shows that it is possible to construct a simple graphical representation displaying the HOR structure within an arbitrarily large genomic sequence, like DNA sequence of a whole human chromosome. Full sequencing of the human genome (sizeable segments from the centromeric region are still missing or in draft stage) will provide the opportunity for computational identification and analysis of all HORs, leading to complete HOR-annotation of human genome.
Finally, we note that the HOR classification of genomic sequences has not yet been incorporated into the GenBank database. We suggest that the HOR assignment obtained by ColorHOR graphical user interface application be included into GenBank class of repetitions. We also suggest the ColorHOR scanning of all clones in the draft stage, not yet included into GenBank.
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Acknowledgments |
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We thank H. F. Willard for valuable comments.
Received on July 12, 2004; revised on September 15, 2004; accepted on September 15, 2004
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