Tài liệu Báo cáo khoa học: Isochore structures in the chicken genome ppt

Isochore structures in the chicken genome Feng Gao and Chun-Ting Zhang Department of Physics, Tianjin University, China The first draft genome sequence of the red jungle fowl, Gallus gallus, was published in December 2004. The chicken (G. gallus) is an important model organ- ism that bridges the evolutionary gap between mam- mals and other vertebrates and serves as a main laboratory model for the $ 9600 extant avian species. The chicken also represents the first agricultural ani- mal to have its genome sequenced. Like most bird species, the chicken has a relatively small genome of $ 1200 million base pairs, or $ 39% of the size of the human genome [1]. The nuclear genomes of vertebrates are mosaics of isochores, very long stretches [> 300 kilobases (kb)] of DNA that are fairly homogeneous in base composi- tion. Isochores can be partitioned into a small number of families that cover a range of GC levels, which is narrow in cold-blooded vertebrates, but broad in warm-blooded vertebrates [2,3]. The large-scale vari- ation in base composition correlates both coding and noncoding sequences and seems to reflect a fundamen- tal level of genome organization [4]. This isochore organization shows marked variation in a number of important genomic features, including gene density [5], chromosome bands [6,7], patterns of codon usage [8], gene length [9], replication timing [10], recombination rate [11,12], and the distribution of transposable ele- ments [13]. By in situ hybridization of fractionated DNA on mitotic and meiotic chromosomes, a com- positional map of chicken chromosomes has been obtained and the most gene-rich regions have been studied [14]. Now, the availability of the complete chicken genome sequence provides an unprecedented Keywords compositional homogeneity; compositional segmentation; Gallus gallus; isochores; windowless technique Correspondence C T. Zhang, Department of Physics, Tianjin University, Tianjin 300072, China Fax: +86 22 27402697 Tel: +86 22 27402987 E-mail: ctzhang@tju.edu.cn (Received 13 November 2005, revised 5 January 2006, accepted 14 February 2006) doi:10.1111/j.1742-4658.2006.05178.x The availability of the complete chicken genome sequence provides an unprecedented opportunity to study the global genome organization at the sequence level. Delineating compositionally homogeneous G + C domains in DNA sequences can provide much insight into the understanding of the organization and biological functions of the chicken genome. A new seg- mentation algorithm, which is simple and fast, has been proposed to parti- tion a given genome or DNA sequence into compositionally distinct domains. By applying the new segmentation algorithm to the draft chicken genome sequence, the mosaic organization of the chicken genome can be confirmed at the sequence level. It is shown herein that the chicken genome is also characterized by a mosaic structure of isochores, long DNA seg- ments that are fairly homogeneous in the G + C content. Consequently, 25 isochores longer than 2 Mb (megabases) have been identified in the chicken genome. These isochores have a fairly homogeneous G + C con- tent and often correspond to meaningful biological units. With the aid of the technique of cumulative GC profile, we proposed an intuitive picture to display the distribution of segmentation points. The relationships between G + C content and the distributions of genes (CpG islands, and other genomic elements) were analyzed in a perceivable manner. The cumu- lative GC profile, equipped with the new segmentation algorithm, would be an appropriate starting point for analyzing the isochore structures of higher eukaryotic genomes. Abbreviations SNP, single nucleotide polymorphism. FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS 1637 opportunity to study the global genome organization at the sequence level. In this article, we analyzed the isochore structures of the chicken genome using a new segmentation algo- rithm [15]. By applying the segmentation algorithm to 24 chicken chromosome sequences, the boundaries of isochores for each chromosome were obtained, respect- ively. It was found that the chicken genome is organized into a mosaic structure of isochores. Conse- quently, 25 isochores longer than 2 Mb have been identified, i.e. eight GC-rich isochores and 17 GC-poor isochores. Results and discussion The isochores in the chicken genome It should be noted that the chicken genome sequence still contains a large number of gaps (Table 1). In the case of GGA1, there are 9847 gaps remaining. There- fore, applying the segmentation algorithm to each frag- ment will fail to unveil the characteristic of the whole genome. In order to display the global G + C content distribution along chromosomes, only gaps > 1% of the chromosome size were retained; gaps < 1% of the chromosome size were simply deleted. By applying the segmentation algorithm to the resulting contigs of each chromosome, the segmentation points were obtained at a certain threshold t 0 , respectively. At a given thresh- old t 0 , the number of resulting segmentation points can reflect the compositional homogeneity of the sequences. For instance, the size of GGA6 is similar to that of GGAZ. At the same threshold t 0 ¼ 100, there are 161 segmentation points in GGA6, while there are only 58 segmentation points in GGAZ. This indicates that GGAZ sequence is more homogeneous than GGA6, and this is also confirmed by Fig. 1. The varia- tions of the cumulative GC profile for GGA6 are Table 1. The summary statistics in the chicken genome. The number of isochores longer than 300 kb obtained at t 0 ¼ 100 in each chromo- some is also presented in the table. Chromosome Chromosome size (bp) Number of gaps Percent of gaps in the chromosome (%) G+C content (%) Number of isochores 1 188 239 860 9847 2.45 39.78 186 2 147 590 765 7333 2.64 39.61 151 3 108 638 738 4411 2.59 39.82 110 4 90 634 903 4122 3.04 39.91 89 5 56 310 377 2599 4.20 40.91 50 6 33 893 787 1531 1.48 41.54 36 7 37 338 262 1505 5.46 41.24 37 8 30 024 636 1252 6.55 41.79 24 9 23 409 228 1145 1.54 42.73 23 10 20 909 726 1233 10.32 42.96 16 11 19 020 054 1395 5.67 41.40 17 12 19 821 895 880 4.10 43.13 17 13 17 279 963 1132 2.87 44.25 12 14 20 603 938 1423 2.21 44.17 20 15 12 438 626 722 1.78 45.10 14 16 239 457 37 25.86 52.55 – 17 10 632 206 832 7.47 47.42 6 18 8919 268 473 1.38 45.67 12 19 9463 882 563 1.57 46.52 5 20 13 506 680 767 1.59 45.60 9 21 6202 554 476 2.61 47.01 5 22 2228 820 90 1.90 43.47 – 23 5666 127 451 12.60 49.72 5 24 5910 111 475 2.25 49.08 6 26 4255 270 369 16.05 50.62 – 27 2668 888 325 6.68 49.13 – 28 4731 479 542 17.09 47.91 1 32 1018 878 115 2.88 52.71 – W 4916 845 629 18.89 38.81 – Z 33 651 169 4843 9.14 39.46 30 Isochores in the chicken genome F. Gao and C T. Zhang 1638 FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS much larger than those of the cumulative GC profile for GGAZ. Here, t 0 was chosen with the aid of the cumulative GC profile and the density distribution of CpG islands. For example, there are 14, 20, and 148 seg- mentation points obtained on GGA14 with t 0 set at 1000, 500, and 100, respectively. As shown in Fig. 2, the domains obtained can delineate the variations of the cumulative GC profile and the density distribution of CpG islands more and more accurately with decreasing t 0 . On the other hand, a smaller t 0 leads to more segmentation points and shorter segmented sub- sequences. Similar procedures were carried out for macrochromosomes, intermediate chromosomes and Fig. 1. The negative cumulative GC profiles for the chicken genome. The gaps in the chicken chromosome sequences are left empty in the curves. Note that sharp peaks correspond to the sites where G + C content undergoes abrupt changes, from GC-rich regions to GC-poor regions, and vice versa, indicating a mosaic structure of the chromosomes. A jump in the Àz 0 n curve indicates an increase of the G + C con- tent; whereas a drop down in the Àz 0 n curve indicates a decrease of the G + C content. An approximate straight region in the Àz 0 n curve implies that the G + C content in this region is roughly constant. F. Gao and C T. Zhang Isochores in the chicken genome FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS 1639 sex chromosome Z, respectively. Consequently, for macrochromosomes, intermediate chromosomes and sex chromosome Z, the threshold t 0 is set to 1000 to partition these chromosomes into compositionally dis- tinct domains. For microchromosomes, which are much smaller and contain higher density of CpG islands and genes, t 0 ¼ 500 is adopted in order to reflect more details. Finally, t 0 ¼ 100 is used as a threshold to identify isochores in the chicken genome. Here, the region from 12 579 268–13 821 432 nucleo- tide on GGA14 was deemed as an isochore. The distributions of length and G + C content are presented in Fig. 3, based on all the segments obtained at t 0 ¼ 100 without the constraint of the minimum length. It can be seen that the length distribution is notably skewed, with the highest value being 10.5 Mb, corresponding to a region with high-repeat density and low-gene density on GGA1. The G + C content distri- bution is also highly skewed, with a long tail of GC-rich regions. It should be noted that the view of the chicken genome we now have from the sequence may still be a compositionally biased one, as some of the most GC-rich, CpG-island-rich regions, namely several microchromosomes such as chromosomes 25, 29, 30, or 31, are essentially missing from the sequence in the currently available chicken genome draft. Consequently, 25 isochores longer than 2 Mb (exclu- ding gaps) were identified (Table 2), i.e. eight GC-rich isochores and 17 GC-poor isochores. In general, GC- rich isochores tend to be shorter than GC-poor ones. The classification of isochores adopted here was pro- posed by Zhang and Zhang [16], which is based on the relative magnitude of the G + C content of isochores with respect to the genomic G + C content. Accord- ing to this classification, the G + C content of GC- rich isochores (GC-poor isochores) is higher (lower) than the genomic G + C content. Biological implications of isochores With the aid of the technique of cumulative GC pro- file, we proposed an intuitive picture to display the dis- tribution of segmentation points. The relationships between G + C content and the distributions of genes (CpG islands, and other genomic elements) can be an- alyzed in a perceivable manner. The cumulative GC profile is also called the z 0 n curve, which is a discrete function of the nucleotide position n in a genome or Fig. 2. The negative cumulative GC profile for GGA14 marked with the segmentation points obtained. The bottom four plots show the distributions of the G + C content and CpG islands along chicken chromosome 14, respectively. The G + C contents are calculated for the domains segmented at t 0 ¼ 1000, 500, and 100, respect- ively. Note that the distribution of CpG islands is closely correlated with the segmented regions with distinct G + C content. The nota- tion used here is described as follows. Besides the position coordi- nates, the order of occurrence for each point in the segmentation process is also labeled in the figure. We used ‘f’, ‘l’, ‘r’, and an inte- ger to label the order of occurrence, where f denotes the first point occurring during the course of segmentation, and l and r denote that the point occurs in the left and right subsequence, respect- ively. The integer denotes the times of segmentation. For example, in point 12579268-rl 2 4, the first part, 12579268, is the position coordinate. The second part, rl 2 4, denotes the order of occurrence. The last integer, 4, in the second part means that this point occurs after four segmentations. In the symbol rl 2 , l appears twice, so we used ‘l 2 ’ instead of ‘ll’ for convenience. Also note that the coordi- nate value of each segmentation point has been corrected by tak- ing the gap length into account. For instance, there is a gap occurring at n 0 fi n 0 + D, where D is the gap length. If a segmen- tation point obtained is situated at n,andn > n 0 , then the actual coordinate of n adopted in this plot is n + D. Meanwhile, the gap region n 0 fi n 0 + D is represented by a blank interval in this plot. Here, n 0 and n are the relative coordinates with respect to the con- tig without gaps. Other gaps are dealt with using similar procedure. Isochores in the chicken genome F. Gao and C T. Zhang 1640 FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS chromosome. Before studying the features of the cumulative GC profiles of the chicken genome, some basic characteristics of the cumulative GC profile need to be addressed. It was shown that the average G + C content of a genome or chromosome at position n fi n + Dn is calculated by G þ C / DðÀz 0 n Þ=Dn [16]. Therefore, a jump in the Àz 0 n curve indicates an increase of the G + C content; whereas a drop down in the Àz 0 n curve indicates a decrease of the G + C content. An approximate straight region in the Àz 0 n curve implies that the G + C content in this region is roughly constant. In addition, the segmentation point obtained here is exactly a turning point of the G + C content, which corresponds to an extreme point in the cumulative GC profile [15]. Therefore, the segmenta- tion coordinates may be used to annotate the related cumulative GC profile, presenting researchers an intu- itive picture. Consequently, the coordinates of segmen- tation points for 24 chicken chromosome sequences were labeled on the cumulative GC profiles, which are accessible at http://tubic.tju.edu.cn/chicken/. Analysis of the identified isochores showed that these isochores correspond to an approximately straight line in the –z’ curves, a reflection of the fact that the G + C contents in these regions are fairly homogenous. We also found that these regions often correspond to meaningful biological units. For exam- ple, at t 0 ¼ 100 level, only three segmented domains (isochores 4, 8 and 9 in Table 2) longer than 4 Mb were identified on GGA1. These domains are located on the long arm of GGA1, corresponding to regions with high-repeat density and low-gene density [17]. For two of them (isochores 8 and 9 in Table 2), only approximate coordinates between 140 and 160 Mb were given in [17]. Here, the precise bound- aries, sizes, and G + C contents of these isochores have been determined using the present method (Table 2). As shown in Figs 2, 4 and 5, the obtained segmenta- tion points have clear biological implications. Note that the distribution of CpG islands is closely correla- ted with the segmented regions with distinct G + C content. We therefore investigated the correlation between the G + C content of isochores and the dis- tribution of CpG islands throughout the chicken gen- ome (Fig. 6). With t 0 ¼ 100, only a total of 811 segments longer than 300 kb were considered as iso- chores, according to our definition of an isochore (Table 1). It was shown that there are positive and highly significant correlations between the G + C con- tent of these isochores and the corresponding density distribution of CpG islands (R ¼ 0.82, P < 0.001). The positive correlation between the G + C content and the density distribution of CpG islands is a well- known fact. It is therefore worth pointing out that the segmentation points obtained here are exactly the boundaries of the related regions. For example, there is an abrupt increase (decrease) of the density of CpG islands at the first (second) boundary of the short GC-rich region between 15 908 133 and 16 385 348 nucleotide on GGA12 (Fig. 4). Similar phenomena are observed in other G + C distinct regions. The precise boundary coordinates obtained by the segmentation algorithm and the associated cumulative Fig. 3. Histogram of length and G + C content based on all the seg- ments obtained at t 0 ¼ 100 without the constraint of the minimum length in the draft genome sequence of chicken. (A) The length dis- tribution of all the obtained segments. The length distribution is notably skewed, with the highest value being 10.5 Mb, correspond- ing to a region with high-repeat density and low-gene density on GGA1. (B) The G + C content distribution of all the obtained seg- ments. It shows that the G + C content distribution is also highly skewed, with a long tail of GC-rich regions. F. Gao and C T. Zhang Isochores in the chicken genome FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS 1641 GC profile provide a useful platform to analyze a gen- ome or chromosome. For instance, any gene-finding algorithm would benefit from these boundary coordi- nates. To gain better gene-finding results, different parameters would be adopted in a gene-finding algo- rithm by considering different regions of distinct G + C content with precise boundary coordinates. In [1], an evidence-based system (Ensembl [18]) and two comparative gene prediction methods (twinscan [19] and SGP-2 [20]) were applied to chicken gene predic- tion, and the overall performances of these methods have been evaluated in terms of sensitivity and specific- ity indices. Here, the distribution of gene density is an- alyzed based on the prediction results, respectively. We can see from Fig. 4 that the density distribution of the predicted genes is also correlated with the segmented regions with distinct G + C content. Based on the cumulative GC profile, the performance of these meth- ods even can be assessed for a certain region in an intuitive form. As gene density is positively correlated with G + C content and CpG island density, it seems that the gene density predicted by SGP-2 is more rea- sonable than that predicted by Ensembl and twinscan at the region between 15 908 133 and 16 385 348 nucleotide on GGA12, based on Fig. 4. The obtained isochore map can also be displayed in the UCSC Genome Browser as a custom track, together with a series of tracks aligned with the genomic sequence [21]. As an example, the top track in Fig. 5 shows the isochore structure of chicken chromosome 28, integra- ted with comprehensive genome information, such as the G + C content, isochores from Pennsylvania State University (PSU) [22], gene density predicted by Ensembl, CpG islands, best alignments with the human genome, single nucleotide polymorphisms (SNPs) and repeat densities. This graphical interface allows rapid visual inspection of the correlation of different types of information [21]. Note that the density distributions of CpG islands and genes are correlated with the segmen- ted regions with distinct G + C content. Here, the region from 2 021 043 to 2 644 230 nucleotide was deemed as an isochore (with length ¼ 623 kb), which is the longest region among the obtained segments on GGA28. The G + C content of this isochore is 37.08%, the lowest G + C content among the identified iso- chores. It is clearly shown that this isochore corresponds to a desert region of genes ⁄ CpG islands ⁄ SNPs and con- tains high-density simple tandem repeats. It can also be seen from Fig. 5 that our result is more reasonable than that obtained from PSU. The isochore data from PSU Table 2. The identified isochores longer than 2 Mb (excluding gaps) in the chicken genome at t 0 ¼ 100. nt, nucleotide. Number Chromosome Type Start (nt) End (nt) Length (Mb) G + C content (%) 1 1 GC 26 077 602 28 181 264 2.1 40.29 2 1 GC 29 988 573 32 824 401 2.8 42.06 3 1 AT 37 805 223 39 913 801 2.1 35.28 4 1 AT 87 214 801 91 955 853 4.7 36.47 5 1 GC 116 177 050 118 308 306 2.1 40.30 6 1 AT 118 535 967 120 790 329 2.3 35.54 7 1 AT 133 030 407 135 339 653 2.3 36.35 8 1 AT 139 198 420 149 661 748 10.5 36.49 9 1 AT 153 131 387 157 455 517 4.3 36.60 10 1 GC 160 813 722 163 314 397 2.5 42.54 11 1 GC 170 242 840 172 762 689 2.5 41.68 12 2 AT 37 000 568 39 401 689 2.4 39.29 13 2 AT 53 100 091 55 916 444 2.8 39.24 14 2 AT 69 341 958 74 887 195 5.5 35.92 15 2 AT 92 103 722 95 811 433 3.7 35.70 16 3 GC 4284 124 6535 663 2.3 41.23 17 4 AT 5305 442 7838 037 2.5 35.35 18 4 AT 41 074 838 43 335 895 2.3 35.76 19 4 AT 70 251 475 73 231 218 3.0 35.31 20 4 AT 77 338 564 82 572 558 5.2 38.63 21 10 AT 4970 289 8586 236 3.6 39.28 22 13 AT 1821 731 4511 591 2.7 37.54 23 Z AT 17 296 997 19 878 666 2.6 38.83 24 Z GC 23 595 353 27 731 946 4.1 41.94 25 Z GC 27 740 090 30 058 946 2.3 39.48 Isochores in the chicken genome F. Gao and C T. Zhang 1642 FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS were generated based on the methods described in [22], in which a measure, compositional heterogeneity (or variability) index, was proposed to compare the dif- ferences in compositional heterogeneity between long genomic sequences. It seems that there is something wrong with the boundary coordinates of the isochores identified from PSU. For example, the region from 1 935 001 to 2 075 000 nucleotide was deemed as an isochore in the result from PSU, while both the cumula- tive GC profile for GGA28 (Fig. 1) and G + C content in five-base windows clearly showed an abrupt change in the G + C content within this region. Based on the present method, other chicken chromo- somes were also analyzed, the detailed analysis for which is accessible at http://tubic.tju.edu.cn/chicken/. The program of the new segmentation algorithm is also available on request. Comparison with the other segmentation algorithms Traditionally, the G + C content distribution of a genome is usually assessed by computing the G + C content in sliding windows moving along the genome. Fig. 4. The negative cumulative GC profile for GGA12 marked with the segmentation points obtained. The bottom five plots show the distributions of G + C content, genes and CpG islands along chicken chromosome 12, respectively. Here, the distribution of gene density is plotted based on the predic- ted results by SGP-2, Ensembl and TWINSCAN, respectively. Note that the density distributions of the predicted genes are also correlated with the segmented regions with distinct G + C content. However, it seems that the gene density predicted by SGP-2 is more reasonable than that predicted by Ensembl and TWINSCAN at the region between 15 908 133 and 16 385 348 nucleotides, respectively. The notation used here is the same as that in Fig. 2. For the details about the notation, refer to the legend of Fig. 2. Also note that there are a number of larger or smaller gaps in GGA12. Here, only gaps >1% of the chromosome size were retained; gaps <1% of the chromosome size were simply deleted. Consequently, GGA12 was split into two contigs. The superscript in front of the position coordinates is used to denote which contig the segmentation point belongs to. F. Gao and C T. Zhang Isochores in the chicken genome FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS 1643 Fig. 5. UCSC Genome Browser on chicken chromosome 28 with our own custom annotation track. The top track shows the obtained iso- chore map integrated with comprehensive genome information, such as the G + C content, isochores from Pennsylvania State University, gene density predicted by Ensembl, CpG islands, best alignments with the human genome, single nucleotide polymorphisms (SNPs) and repeat densities. Here, the obtained segments longer than 50 kb at t 0 ¼ 100 are displayed at the UCSC Genome Browser as a custom track. These segments are represented by rectangular blocks, and the corresponding G + C contents are labeled on the left of the segments. Seg- ments with higher G + C content are more darkly shaded. The precise boundary coordinates can be found at http://tubic.tju.edu.cn/chicken/. The region from 2021 043 to 2644 230 nucleotide was identified as an isochore, with the lowest G + C content (37.08%) among the obtained segments on GGA28. It is clearly shown that this isochore corresponds to a desert region of genes ⁄ CpG islands ⁄ SNPs and contains high-density simple tandem repeats. Note that there are abrupt changes in the density distributions of CpG islands, genes and other elements at the boundaries of this isochore identified by the present algorithm. Isochores in the chicken genome F. Gao and C T. Zhang 1644 FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS The disadvantage of this routinely used window-based method is that the resolution is low, e.g. the method is not sensitive in detecting the small changes in the G + C content. In addition, the distribution pattern of G + C content obtained is largely dependent on the window size. Historically, other windowless methods have been developed to calculate the G + C content, which are usually given the name of ‘segmentation of DNA sequences’. Among them, the methods of entropic seg- mentation [23,24], hidden Markov model [25,26] and wavelet shrinkage technique [27] should be mentioned. The advantages and disadvantages of the latter two methods were discussed in [28]. As the entropic seg- mentation algorithm is widely used to find segmenta- tion points for various genomes, one may wonder if the two algorithms (the entropic and our algorithm) result in the same or different results. Therefore, it is interesting to compare the two segmentation algo- rithms. Here, we focus the comparison only with the entropic segmentation algorithm. Both segmentation algorithms possess the highest resolution (single nuc- leotide accuracy). By applying the new algorithm to the chicken chromosome sequences, the coordinates of segmentation points obtained are completely identical to those derived from the entropic segmentation algo- rithm (data not shown here). Compared with the entropic segmentation algorithm, the new algorithm has a series of merits. First, the new algorithm is simpler and faster than the entropy-based algorithm. Secondly, the new algorithm is based on the genome order index S , which has a clear geometrical meaning, i.e. it is a square of a Euclidean distance [29]. Thirdly, S possesses clear biological implications, e.g. S usually has different values in coding and noncoding regions, which has been used to recognize protein-cod- ing genes in the budding yeast genome [30]. Finally, the new segmentation algorithm is superior to the entropic one in that the former is able to provide an intuitive picture by incorporating with the Z-curve rep- resentation of DNA sequences [31]. The segmentation point obtained here is exactly a turning point of the G + C content, which corresponds to an extreme point in the cumulative GC profile. Consequently, we may use the segmentation coordinates to annotate the related cumulative GC profile, presenting researchers with an intuitive picture. Conclusions Delineating compositionally homogeneous G + C domains in DNA sequences can provide much insight into the understanding of the organization and biologi- cal functions of a given genome. Compositionally homogeneous segments of genomic DNA have been shown to correlate to a number of important genomic features. Furthermore, quantitative analysis of compo- sitional heterogeneity reveals the statistical properties of DNA sequences, which is useful to locate the origin and terminus of replication in bacterial [32] and archa- eal [33] genomes, and detect horizontally transferred genes and genomic islands [28]. In this paper, it has been shown that the chicken genome is organized into a mosaic structure of iso- chores. A new algorithm has been applied to segment 24 chicken chromosome sequences, and the boundaries of isochores obtained for each chromosome have been determined precisely. In summary, the cumulative GC profile marked with the coordinates of resulting segmentation points is a useful tool for genome analysis. This leads to a neat graphical representation of G + C content variations along a genome or chromosome, and a clear-cut defini- tion of isochores. This technique allowed us to show ⁄ confirm that GC-rich isochores in a chicken chromosome have higher gene and CpG-islands densi- ties than AT-rich isochores. Although these are well- known characteristics of isochores of the vertebrate organisms, the advantage of the technique is that an investigator is able to study all of these in a perceiv- able and precise manner. We believe that a plot similar to Fig. 4 could become a common tool for analyzing Fig. 6. Correlation between the G + C content of isochore and the density distribution of CpG islands. With t 0 ¼ 100, only a total of 811 segments longer than 300 kb were considered as isochores according to the definition of isochore. Consequently, the correl- ation coefficient and equation of the linear regression line were given in the plot. It shows there are positive and highly significant correlations between the G + C content of these isochores and the corresponding density distribution of CpG islands (R ¼ 0.82, P < 0.001). F. Gao and C T. Zhang Isochores in the chicken genome FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS 1645 the G + C content variations for any genome or chro- mosome. For higher eukaryotic genomes, the cumula- tive GC profile equipped with the new segmentation algorithm would be an appropriate starting point for analyzing their isochore structures. Experimental procedures The draft chicken genome sequence, release galGal2, and its associated annotation files, such as the data of gene, CpG island, SNPs, isochores from PSU, best alignments with the human genome and so on, were downloaded from http://genome.ucsc.edu/. In the present study, we follow the convention of the International Chicken Genome Sequen- cing Consortium (ICGSC 2004) by classifying chicken chro- mosomes into three classes: five macrochromosomes (GGA1-5), five intermediate chromosomes (GGA6-10) and 28 microchromosomes (GGA11-38). Here, sex chromosome W and microchromosomes smaller than GGA28 were excluded from the study. Our analysis of the distributions of G + C content, CpG islands, and genes was only restricted to the remaining 24 chromosomes. The densities of CpG islands and genes were calculated in 100 kb long, nonoverlapping windows. A new segmentation algorithm of DNA sequences The genome order index S is defined by S ¼ SðPÞ¼a 2 þ c 2 þ g 2 þ t 2 ð1Þ where a, c, g and t denote the occurrence frequencies of A, C, G and T, respectively, in a genome or a DNA sequence. The genome order index S defined in Eqn 1 is a useful statistical quantity to reflect the compositional characteristics of a genome [29], which can serve as an appropriate divergence measure to quantify the composi- tional difference between two DNA sequences [15]. The new segmentation algorithm proposed here is based on the quadratic divergence (see Eqn 2). Consider a genome with N bases. Let n be an integer, 2 £ n £ N – 1. For a given n, the genome sequence is partitioned into two sub- sequences, one left and the other right. Let w 1 ¼ n ⁄ N and w 2 ¼ (N ) n) ⁄ N. Let P l ¼ (a l ,c l ,g l ,t l ) and P r ¼ (a r ,c r ,g r ,t r ), where a l ,c l ,g l ,t l and a r ,c r ,g r ,t r are the occur- rence frequencies of bases A, C, G and T in the left and right subsequences, respectively. Thus, DSðP l ; P r Þ¼ðn=NÞSðP l Þþ½ðN À nÞ=NSðP r Þ À Sfðn= NÞP l þ½ðN À nÞ=NP r g; ð2Þ where S(P) is defined by Eqn 1. If we suppose that n*isa position, at which DS(P l ,P r ) reaches maximum, then n*is a compositional segmentation point of the genome first found. The new algorithm is also recursive, as in [23] and [24], i.e. after n* is determined, the same procedure is applied to both the resulting left and right subsequences, respectively. The procedure should be applied recursively until DS(P l ,P r ) is less than a given threshold. However, a question which needs to be answered is the halting condition of the segmentation algorithm. This is done by defining a halting parameter, t t ¼ N  DSðP l ; P r Þð3Þ where N is the length of sequence or subsequence to be seg- mented. If t < t 0 , the segmentation procedure halts, other- wise, the procedure continues until t < t 0 . As we are only interested in segmenting concrete genomes, the choice of t 0 is based on a heuristic consideration. A larger threshold t 0 leads to less segmentation points and longer segmented sub- sequences, whereas a smaller threshold t 0 leads to more seg- mentation points and shorter segmented subsequences. For an obtained segmentation point, it is important to know whether the halting parameter value is significantly different from that of a random sequence. In order to halt the seg- mentation at different significance levels, we estimated the distribution of the halting parameter based on 100 000 ran- dom sequences with length of 1 Mb. For each of these sequences, we calculated a halting parameter for the first point occurring during the course of segmentation and obtained thus 100 000 numbers. Consequently, cumulative frequency and counts were plotted against the halting parameter, respectively (Fig. 7). For example, if the signifi- cance level is 5% then t 0 corresponds to 6.194. However, a much more stringent stopping criterion is actually required in most cases. It should be noted that in some cases the segmentation procedure also halts when the resulting subse- quence is shorter than a given minimum length. Here, we choose 3000 nucleotide as the minimum length according to a requirement imposed by the experimental characterization of isochores through DNA centrifugation [3]. In general, the choice of t 0 and the minimum length is heuristic and must be determined on a case by case basis [15]. Cumulative GC profile z n is defined as z n ¼ðA n þ T n ÞÀðC n þ G n Þ;n ¼ 0; 1;2; :::; N;z n 2½ÀN; N; ð4Þ where A n , C n , G n , and T n are the cumulative numbers of the bases A, C, G and T, respectively, occurring in the subsequence from the first base to the n-th base in the DNA sequence inspected. Here, z n is one of the compo- nents of the Z-curve, which is a three dimensional curve that uniquely represents a DNA sequence [34,35]. Usu- ally, for an AT-rich (GC-rich) genome, z n is approxi- mately a monotonously increasing (decreasing) linear function of n. To amplify the deviations of z n , the curve of z n $ n is fitted by a straight line using the least squares technique, Isochores in the chicken genome F. Gao and C T. Zhang 1646 FEBS Journal 273 (2006) 1637–1648 ª 2006 The Authors Journal compilation ª 2006 FEBS [...]... the chicken genome, respectively (Fig 1) Note that the cumulative GC profile is not the G + C content itself, rather, the derivative of the cumulative GC profile with respect to the base position n is negatively proportional to the G + C content at the given position, i.e G + C µ ) dz¢ ⁄ dn Therefore, the average slope of the cumulative GC profile within a region reflects the average G + C content of the. .. of halting parameter estimated from 100 000 random sequences The distribution of the halting parameter for the first point occurring during the course of segmentation was estimated based on 100 000 random sequences with a length of 1 Mb Cumulative frequency and counts are plotted against halting parameter, respectively The X-axis shows various intervals of halting parameter values The Y-axis in the upper... shows the cumulative percentage of the values at or below each interval The Y-axis in the lower panel shows the number of sequences scoring within the interval Consequently, segmentation procedure can be halted at different significance levels For example, if a significance level of 5% is adopted, t0 should be equal to 6.194, as indicated in the figure z ¼ kn ð5Þ where (z, n) is the coordinate of a point... and C.-T Zhang Isochores in the chicken genome a fragment of a natural DNA sequence, e.g an isochore The method above, used to calculate G + C content, is called a windowless technique [36] The cumulative GC profile can also provide a qualitative view of genome organization in an intuitive manner, by which isochores or genomic islands can be identified directly by eye [16,28] Consequently, the cumulative... curve within the region Dn The region Dn is usually chosen to be We are grateful to the referees for their constructive comments, which were very important in strengthening the presentation of the paper We would like also to thank Drs R Zhang and L.-L Chen for invaluable assistance Suggestions for writing the manuscript from Feng-Biao Guo and Wen-Xin Zheng are gratefully acknowledged The present work... 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Isochore structures in the chicken genome Feng Gao and Chun-Ting Zhang Department of Physics, Tianjin University, China The first draft genome sequence. compositionally distinct domains. By applying the new segmentation algorithm to the draft chicken genome sequence, the mosaic organization of the chicken genome can