Initial sequencing and analysis of the human genome - Vitagenes

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articles60%-50%-40%-30%-20%-60%-50%-40%-30%-20%-60%-50%-40%-30%-20%-0 Mb0 Mb0 Mb50 Mb5 Mb0.5 Mb100 Mb10 Mb1 MbFigure 13 Variation in GC content at various scales. The GC content in subregions of a100-Mb region of chromosome 1 is plotted, starting at about 83 Mb from the beginning ofthe draft genome sequence. This region is AT-rich overall. Top, the GC content of theentire 100-Mb region analysed in non-overlapping 20-kb windows. Middle, GC content ofthe ®rst 10 Mb, analysed in 2-kb windows. Bottom, GC content of the ®rst 1 Mb, analysedin 200-bp windows. At this scale, gaps in the sequence can be seen.stsG30423) with only 36% GC content. There are also examples oflarge shifts in GC content between adjacent multimegabase regions.For example, the average GC content on chromosome 17q is 50%for the distal 10.3 Mb but drops to 38% for the adjacent 3.9 Mb.There are regions of less than 300 kb with even wider swings in GCcontent, for example, from 33.1% to 59.3%.Long-range variation in GC content is evident not just fromextreme outliers, but throughout the genome. The distribution ofaverage GC content in 20-kb windows across the draft genomesequence is shown in Fig. 12. The spread is 15-fold larger thanpredicted by a uniform process. Moreover, the standard deviationbarely decreases as window size increases by successive factors offourÐ5.9%, 5.2%, 4.9% and 4.6% for windows of size 5, 20, 80 and320 kb. The distribution is also notably skewed, with 58% below theaverage and 42% above the average of 41%, with a long tail of GCrichregions.Bernardi and colleagues 118,119 proposed that the long-range variationin GC content may re¯ect that the genome is composed of amosaic of compositionally homogeneous regions that they dubbedìsochores'. They suggested that the skewed distribution is composedof ®ve normal distributions, corresponding to ®ve distincttypes of isochore (L1, L2, H1, H2 and H3, with GC contents of, 38%, 38±42%, 42±47%, 47±52% and . 52%, respectively).We studied the draft genome sequence to see whether strictisochores could be identi®ed. For example, the sequence wasdivided into 300-kb windows, and each window was subdividedinto 20-kb subwindows. We calculated the average GC content foreach window and subwindow, and investigated how much of thevariance in the GC content of subwindows across the genome can bestatistically èxplained' by the average GC content in each window.About three-quarters of the genome-wide variance among 20-kbwindows can be statistically explained by the average GC content of300-kb windows that contain them, but the residual variance amongsubwindows (standard deviation, 2.4%) is still far too large to beconsistent with a homogeneous distribution. In fact, the hypothesisof homogeneity could be rejected for each 300-kb window in thedraft genome sequence.Similar results were obtained with other window and subwindowsizes. Some of the local heterogeneity in GC content is attributable totransposable element insertions (see below). Such repeat elementstypically have a higher GC content than the surrounding sequence,with the effect being strongest for the most recent insertions.These results rule out a strict notion of isochores as compositionallyhomogeneous. Instead, there is substantial variation atmany different scales, as illustrated in Fig. 13. Although isochoresdo not appear to merit the pre®x ìso', the genome clearly doescontain large regions of distinctive GC content and it is likely to beworth rede®ning the concept so that it becomes possible rigorouslyto partition the genome into regions. In the absence of a precisede®nition, we will loosely refer to such regions as `GC contentdomains' in the context of the discussion below.Fickett et al. 120 have explored a model in which the underlyingpreference for a particular GC content drifts continuously throughoutthe genome, an approach that bears further examination.Churchill 121 has proposed that the boundaries between GC contentdomains can in some cases be predicted by a hidden Markov model,with one state representing a GC-rich region and one representingan AT-rich region. We found that this approach tended to identifyonly very short domains of less than a kilobase (data not shown),but variants of this approach deserve further attention.The correlation between GC content domains and variousbiological properties is of great interest, and this is likely to be themost fruitful route to understanding the basis of variation in GCcontent. As described below, we con®rm the existence of strongcorrelations with both repeat content and gene density. Using theintegration between the draft genome sequence and the cytogeneticmap described above, it is possible to con®rm a statisticallysigni®cant correlation between GC content and Giemsa bands (Gbands).For example, 98% of large-insert clones mapping to thedarkest G-bands are in 200-kb regions of low GC content (average37%), whereas more than 80% of clones mapping to the lightest G-bands are in regions of high GC content (average 45%) 103 . Estimatedband locations can be seen in Fig. 9 and viewed in the context ofother genome annotation at http://genome.ucsc.edu/goldenPath/mapPlots/ and http://genome.ucsc.edu/goldenPath/hgTracks.html.CpG islandsA related topic is the distribution of so-called CpG islands across thegenome. The dinucleotide CpG is notable because it is greatlyunder-represented in human DNA, occurring at only about one-®fth of the roughly 4% frequency that would be expected by simplymultiplying the typical fraction of Cs and Gs (0.21 ´ 0.21). Thede®cit occurs because most CpG dinucleotides are methylated onthe cytosine base, and spontaneous deamination of methyl-Cresidues gives rise to T residues. (Spontaneous deamination ofordinary cytosine residues gives rise to uracil residues that arereadily recognized and repaired by the cell.) As a result, methyl-CpG dinucleotides steadily mutate to TpG dinucleotides. However,the genome contains many `CpG islands' in which CpG dinucleotidesare not methylated and occur at a frequency closer to thatpredicted by the local GC content. CpG islands are of particularinterest because many are associated with the 59 ends of genes 122±127 .We searched the draft genome sequence for CpG islands. Ideally,they should be de®ned by directly testing for the absence of cytosinemethylation, but that was not practical for this report. There areNATURE | VOL 409 | 15 FEBRUARY 2001 | www.nature.com © 2001 Macmillan Magazines Ltd877
articlesTable 10 Number of CpG islands by GC contentGC contentof islandNumberof islandsPercentageof islandsNucleotidesin islandsPercentage ofnucleotidesin islandsTotal 28,890 100 19,818,547 100.80% 22 0.08 5,916 0.0370±80% 5,884 20 3,111,965 1660±70% 18,779 65 13,110,924 6650±60% 4,205 15 3,589,742 18.............................................................................................................................................................................Potential CpG islands were identi®ed by searching the draft genome sequence one base at a time,scoring each dinucleotide (+17 for GC, -1 for others) and identifying maximally scoring segments.Each segment was then evaluated to determine GC content ($50%), length (.200) and ratio ofobserved proportion of GC dinucleotides to the expected proportion on the basis of the GC contentof the segment (.0.60), using a modi®cation of a program developed by G. Micklem (personalcommunication).various computer programs that attempt to identify CpG islands onthe basis of primary sequence alone. These programs differ in someimportant respects (such as how aggressively they subdivide longCpG-containing regions), and the precise correspondence withexperimentally undermethylated islands has not been validated.Nevertheless, there is a good correlation, and computational analysisthus provides a reasonable picture of the distribution of CpGislands in the genome.To identify CpG islands, we used the de®nition proposed byGardiner-Garden and Frommer 128 and embodied in a computerprogram. We searched the draft genome sequence for CpG islands,using both the full sequence and the sequence masked to eliminaterepeat sequences. The number of regions satisfying the de®nition ofa CpG island was 50,267 in the full sequence and 28,890 in therepeat-masked sequence. The difference re¯ects the fact that somerepeat elements (notably Alu) are GC-rich. Although some of theserepeat elements may function as control regions, it seems unlikelythat most of the apparent CpG islands in repeat sequences arefunctional. Accordingly, we focused on those in the non-repeatedsequence. The count of 28,890 CpG islands is reasonably close to theprevious estimate of about 35,000 (ref. 129, as modi®ed by ref. 130).Most of the islands are short, with 60±70% GC content (Table 10).More than 95% of the islands are less than 1,800 bp long, and morethan 75% are less than 850 bp. The longest CpG island (onchromosome 10) is 36,619 bp long, and 322 are longer than 3,000bp. Some of the larger islands contain ribosomal pseudogenes,although RNA genes and pseudogenes account for only a smallproportion of all islands (, 0.5%). The smaller islands are consistentwith their previously hypothesized function, but the role ofthese larger islands is uncertain.The density of CpG islands varies substantially among some ofthe chromosomes. Most chromosomes have 5±15 islands per Mb,with a mean of 10.5 islands per Mb. However, chromosome Y has anNumber of genes per Mb2520151050111 1514 6 9 12248 3207 105 2113 18X2217160 10 20 30 40 50Number of CpG islands per MbFigure 14 Number of CpG islands per Mb for each chromosome, plotted against thenumber of genes per Mb (the number of genes was taken from GeneMap98 (ref. 100)).Chromosomes 16, 17, 22 and particularly 19 are clear outliers, with a density of CpGislands that is even greater than would be expected from the high gene counts for thesefour chromosomes.19unusually low 2.9 islands per Mb, and chromosomes 16, 17 and 22have 19±22 islands per Mb. The extreme outlier is chromosome 19,with 43 islands per Mb. Similar trends are seen when considering thepercentage of bases contained in CpG islands. The relative density ofCpG islands correlates reasonably well with estimates of relativegene density on these chromosomes, based both on previousmapping studies involving ESTs (Fig. 14) and on the distributionof gene predictions discussed below.Comparison of genetic and physical distanceThe draft genome sequence makes it possible to compare geneticand physical distances and thereby to explore variation in the rate ofrecombination across the human chromosomes. We focus here onlarge-scale variation. Finer variation is examined in an accompanyingpaper 131 .The genetic and physical maps are integrated by 5,282 polymorphicloci from the Marsh®eld genetic map 102 , whose positionsare known in terms of centimorgans (cM) and Mb along thechromosomes. Figure 15 shows the comparison of the draftgenome sequence for chromosome 12 with the male, female andsex-averaged maps. One can calculate the approximate ratio of cMper Mb across a chromosome (re¯ected in the slopes in Fig. 15) andthe average recombination rate for each chromosome arm.Two striking features emerge from analysis of these data. First, theaverage recombination rate increases as the length of the chromosomearm decreases (Fig. 16). Long chromosome arms have anaverage recombination rate of about 1 cM per Mb, whereas theshortest arms are in the range of 2 cM per Mb. A similar trend hasbeen seen in the yeast genome 132,133 , despite the fact that the physicalscale is nearly 200 times as small. Moreover, experimental studieshave shown that lengthening or shortening yeast chromosomesresults in a compensatory change in recombination rate 132 .The second observation is that the recombination rate tends to besuppressed near the centromeres and higher in the distal portionsof most chromosomes, with the increase largely in the terminalDistance from centromere (cM)1401301201101009012q8070605040302010012p1020304050Sex-averagedMaleFemale600 10 20 30 40 50 60 70 80 90 100 110 120 130 140Centromere Position (Mb)Figure 15 Distance in cM along the genetic map of chromosome 12 plotted againstposition in Mb in the draft genome sequence. Female, male and sex-averaged maps areshown. Female recombination rates are much higher than male recombination rates. Theincreased slopes at either end of the chromosome re¯ect the increased rates ofrecombination per Mb near the telomeres. Conversely, the ¯atter slope near thecentromere shows decreased recombination there, especially in male meiosis. This istypical of the other chromosomes as well (see http://genome.ucsc.edu/goldenPath/mapPlots). Discordant markers may be map, marker placement or assembly errors.878 © 2001 Macmillan Magazines Ltd NATURE | VOL 409 | 15 FEBRUARY 2001 | www.nature.com
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