Chromosome 11, although average in size, is one of the most gene- and disease-rich chromosomes in the human genome. Initial gene annotation indicates an average gene density of 11.6 genes per megabase, including 1,524 protein-coding genes, some of which were identified using novel methods, and 765 pseudogenes. One-quarter of the protein-coding genes shows overlap with other genes. Of the 856 olfactory receptor genes in the human genome, more than 40% are located in 28 single- and multi-gene clusters along this chromosome. Out of the 171 disorders currently attributed to the chromosome, 86 remain for which the underlying molecular basis is not yet known, including several mendelian traits, cancer and susceptibility loci. The high-quality data presented here—nearly 134.5 million base pairs representing 99.8% coverage of the euchromatic sequence—provide scientists with a solid foundation for understanding the genetic basis of these disorders and other biological phenomena.
Human chromosome 11 (HSA11), which represents approximately 4.4% of the human genome1,2, has had a significant role in the history of molecular genetics, beginning long before its complete sequencing was undertaken. The haemoglobin beta gene, encoding one of the best-studied proteins, was one of the first genes mapped to the human genome (11p15.5) and was the first protein to have its crystal structure solved3. It is also the cause of sickle cell anaemia, the first human genetic disease for which a molecular basis was demonstrated4. Three megabases (Mb) distal lies the insulin gene, encoding the first fully-sequenced protein5, and the intensely studied imprinting region responsible for Beckwith–Wiedemann syndrome6. The physical map, high-quality finished sequence and gene catalogue presented here are but the latest landmark in an effort to understand the unique characteristics and functions of this chromosome.
The clone map and finished sequence
Chromosome 11 was sequenced using a clone-by-clone shotgun sequencing approach. The sequence is in eight finished contigs (Supplementary Tables S1–S3), the largest being 49.6 Mb, with seven gaps remaining, including one at 11p-tel (∼50 kilobases (kb)), one heterochromatic gap (207 kb) near 11p-cen and five small internal clone gaps (totalling ∼64.5 kb). Where possible, all of the gaps were size-estimated by fibre-fluorescence in situ hybridization (FISH) analysis. On 11q, we reached both the telomeric repeats and the centromeric alpha satellite repeats, and higher-order repeat structure was observed in clone AC126345 at 11p-cen. To ensure production of the most reliable data, sequence quality control checks were performed both internally (Supplementary Table S4) and externally7. In total, we finished 131,130,853 base pairs (bp) and estimate the total size of the chromosome, including the gaps and centromere, to be approximately 134.5 Mb (May 2004, NCBI build 35). The coverage of the euchromatic portion of the chromosome is an estimated 99.8%. Of the finished sequence, 60% was generated by RIKEN Genomic Sciences Center, 36% by the Broad Institute of MIT and Harvard, 3% by the Wellcome Trust Sanger Institute, and 1% by the Washington University School of Medicine Genome Sequencing Center.
The chromosome landscape
Figure 1 shows an overview of the chromosome 11 landscape. HSA11 is very gene rich and there are many clustered gene families located on the chromosome. According to a recent survey of the Ensembl genome browser8, HSA11 contains the fourth highest number of genes in the human genome, after human chromosomes 1, 2 (ref. 9) and 19 (ref. 10), respectively. These data show 10.6 protein-coding genes per Mb on HSA11, as compared to the genome-wide average of 7.3. In fact, manual annotation of the chromosome identifies a slightly higher gene density of 11.6 genes per Mb, with genes spaced an average of 86 kb apart. Both the repeat density (47.98%; Supplementary Table S5 and Supplementary Information) and G + C content (41.57%) are close to genome-wide averages. Table 1 lists various features of the chromosome.
The finished sequence of HSA11 shows strong concordance with existing physical and genetic maps. All sequence-tagged sites from the Généthon microsatellite-based genetic map11, the deCODE map12 and the Marshfield genetic maps13 are present in the HSA11 sequence (Supplemental Methods). We compared recombination rates in the deCODE female, male and sex-averaged meiotic maps (which average 1.53, 0.85 and 1.19 cM per Mb, respectively) with the physical distance as determined from the sequence assembly (Supplementary Fig. S1). Recombination statistics for HSA11 are similar to other human chromosomes, showing a relatively linear relationship between recombination rate and physical distance.
We annotated a total of 2,347 gene loci consisting of 1,524 potentially active protein-coding genes, 765 pseudogenes and 58 RNAs (Supplementary Table S6 and Supplementary Methods). The 1,524 protein-coding genes comprise 1,195 known genes (including 166 olfactory receptor genes), 104 novel coding sequences (CDSs), 221 novel transcripts and four putative genes. Some of these genes were identified by our ab initio gene prediction program DIGIT14, as described below. The 765 pseudogenes include at least three unprocessed pseudogenes and 203 olfactory receptor pseudogenes. In total, we annotated 230 previously unknown genes (that is, no RefSeq or Ensembl location, Supplementary Methods) consisting of 48 novel CDSs, 178 novel transcripts and four putative genes. These novel genes are scattered throughout the chromosome, with many located in potential disease candidate regions.
There are 296 single-exon genes, of which 168 belong to the olfactory receptor gene family. The remaining 1,228 multi-exon genes (80.53%) have an average of 9.39 exons per gene. In addition to the olfactory receptor gene clusters described later, we identified 142 genes in 37 clusters that belong to gene families with at least two members on HSA11 (Supplementary Table S7).
Co-transcribed or read-through genes do not appear to be a very common phenomenon in the human genome, but this could be due to the current lack of uniform genome-wide gene annotation. We found 12 cases on HSA11 (Supplementary Table S8), which are each supported by just one messenger RNA (and in a few cases by expressed sequence tags (ESTs)). Besides these examples, we found only a few other examples on chromosomes 17 and 22 (ref. 15) (Supplementary Methods). Of these, only two were found that probably result in a protein fusion product, TRIM6-TRIM34 and BSCL2-HNRPUL2. Whether or not these read-through transcripts should be considered as alternative transcripts or separate genes, with functions different from the two genes they connect, remains to be investigated. Because the supporting evidence for such read-through transcripts is usually minimal, additional experiments should first be carried out to determine whether or not they are real, or just represent cellular mistakes or artefacts.
For the protein-coding genes, we attempted to identify all possible splice variants using currently available mRNA data (and, in a few cases, EST information). We found that 805 (52.8%) of the genes have at least two or more variants, consisting of 738 known genes, 36 novel CDSs, 30 novel transcripts and one putative gene. The genes with at least two variants have an average of 3.73 variants per locus. The CTNND1 gene showed the largest number of variants with 28. In total, we identified 3,723 variants for the 1,524 expressed genes. Of these nearly 4,000 splice variants, there are many instances where the transcripts splice correctly but do not have definitive or long (> 100 amino acids) open reading frames and may be examples of incompletely spliced RNAs, incorrectly spliced RNAs or non-coding RNAs.
We explored whether there was any correlation between the presence of a CpG island and the number of variant transcripts for a gene (Supplementary Table S9). Interestingly, we found a significant correlation (χ2 = 224.29, P < 0.0001, 6 degrees of freedom). Out of the 894 genes with CpG islands, 650 (70%) have two or more variants. By contrast, of the 626 genes with no CpG islands, only 154 (24.6%) have two or more variants.
Olfactory receptor genes
Olfactory receptor genes comprise the largest multi-gene family in metazoans. All human chromosomes except HSA20 (ref. 16) and HSAY (ref. 17) contain olfactory receptor genes, but HSA11 is by far the richest. In human there are 856 olfactory receptor genes, 369 (43%) of which are located on HSA11 (ref. 18). These are mostly single-exon genes, with an average length of about 1 kb. Of the 369 loci on HSA11, 166 (45%) are protein-coding and the other 203 (55%) are pseudogenes; this is close to the genome-wide average (47% versus 53%). All but 10 of the olfactory receptor genes on HSA11 lie within 18 clusters, separated by at least 100 kb (Figs 1 and 2; see also Supplementary Table S10). The largest cluster contains 97 genes over a range of 1.5 Mb. The average distance between genes within a cluster is about 17 kb. The olfactory receptor genes on HSA11 are classified into 13 different families (having >40% protein identity), containing from as few as one to as many as 81 members. The olfactory receptor regions on HSA11 generally are rich in L1 repeats, poor in Alu repeats, CpG islands (Supplementary Table S11 and Supplementary Information) and predicted transcription starts (based on the Eponine program19), and have a G + C content of 40% or lower. Functional olfactory receptor genes are evenly distributed within the clusters.
Olfactory receptor genes are roughly classified into two classes: I and II. Class I olfactory receptor genes are known as fish-like olfactory receptors and are believed to be receptors for water-soluble ligands. They have expanded in mammalian lineages (Fig. 2) and many belong to one large cluster in mammalian genomes. In the human genome, all of the class I olfactory receptor genes are found in three closely spaced clusters on the subtelomeric region of 11p, from 4.1 to 6.2 Mb. Approximately 50% (54 out of 103) of these genes are intact in human, which is close to the genome-wide average for all olfactory receptors. The class I region is interrupted by a few genes including the beta-globin gene cluster and a TRIM gene cluster.
The most significant class II cluster is located around the centromere of HSA11. The corresponding clusters for the mouse20, rat21 and dog22 genomes are also the largest ones, and are comprised of many families of class II olfactory receptor genes. Notably, the human cluster has a significantly different structure from that of other mammals: the human cluster is divided by insertion of the centromere, a heterochromatic region and an intrachromosomal duplication. Despite the structural changes, and although some members of the cluster are on different chromosomes in rodents, analysis of conserved order of orthologous sequences suggests that they belonged to one large cluster in their last common ancestral genome.
Identification of weakly expressed novel genes
As mentioned above, we applied DIGIT14 (Methods), an ab initio gene-finder, to HSA11. The program predicted 65 novel protein-coding gene loci, with an average open-reading length of 366 amino acids, the genomic regions of which did not overlap at the time with human mRNAs from GenBank. We found experimental support for 34 (52%) of these predictions, based on reverse transcription polymerase chain reaction (RT–PCR) experiments that show evidence of the predicted splice junctions (including four full CDSs) (Supplementary Tables S12 and S13). Most (26 out of 34) of these genes appear to be expressed at an extremely low level (detectable only by nested PCR), which might explain why they had not been previously detected by any high-throughput EST or full-length cDNA sequencing strategy. Of the 34 genes with experimental support (Supplementary Table S14), 12 were identified only through this method because they have no orthologous sequence in any currently available genome (six also have no related human sequence, whereas six have related human sequence). Eight of the 34 genes may simply be extensions of nearby human genes. The remaining 14 genes either have orthologous sequence in other species or are highly similar to known human genes. Many of the 34 genes are predicted by the InterProScan23 program to contain a functional domain (Supplementary Table S15). Further experimental evidence to support the expression of these genes and to identify their full-length structures is necessary. In order to obtain a more complete catalogue of all protein-coding genes in the human genome, this type of analysis should ideally be extended to include all chromosomes, especially as some genes were only identified by this ‘ab initio plus experimental verification’ approach.
This work describes just a few of the interesting features of human chromosome 11. Notably, the chromosome is very rich in genes overall and disease genes in general (Supplementary Fig. S2). It contains many clustered gene families, the most significant being 369 members of the olfactory receptor gene family. Many medically important loci are associated with chromosome 11 for which the genetic cause of the disorder has yet to be elucidated (Supplementary Table S16). This includes various cancers, susceptibility genes and loci implicated in behavioural and psychiatric disease variation.
Some findings that stand out in our analysis include a significant correlation between the presence of CpG islands and the number of splice variants, a large number of overlapping genes (Supplementary Information) and genes sharing CpG islands, and genes that were only initially identified through ab initio methods. Although these phenomena may not necessarily be specific to chromosome 11, they do emphasize the need for further uniform analyses and annotation across the entire human genome. With the availability of the high-quality human genomic sequence as presented here, scientists have a solid foundation for identifying and understanding all of the genes and functional elements it holds.
Construction of the chromosome 11 large insert libraries
We prepared chromosome-specific bacterial artificial chromosome (BAC; CMB9) and fosmid (CMF9) libraries by using flow-sorted chromosomal DNA derived from human chromosomes 9–12 (these chromosomes cannot be separated by flow cytometry due to their similar size). For construction of the CMB9 library, sorted DNA derived from cultured lymphoblastoid cells was partially digested by SacI and the fragments were ligated into the pKS145 vector. Transformation was carried out by electroporation into Escherichia coli DH10B. The CMF9 library was prepared according to previously described methods24. We screened these two libraries, the RPCI-11 whole-genome BAC library, and a few other BAC and P1-derived artificial chromosome (PAC) whole-genome libraries (Supplementary Table S2). The chromosome-specific libraries proved especially useful during the gap-filling stage of the project and for identifying clones near the complex centromeric and telomeric regions.
Clone path construction
Initial seed clones were selected by using the restriction enzyme digest fingerprint data of WUGSC and MIT for HSA11p, and by screening the RPCI-11 BAC library with evenly spaced markers taken from a highly-integrated STS map of the whole human genome for HSA11q. These approaches allowed us to construct quickly a tiling path across most of the chromosome. The remaining gaps were filled by walking from clone end sequences and by re-screening of the clone libraries. The chromosomal locations for some clones in the minimum tiling path were confirmed by FISH analysis, and the lengths of the clone gaps were estimated by fibre-FISH according to previous methods25. The procedures for large-insert clone sequencing are described in Supplementary Methods.
Prediction of novel human genes
For exhaustive and efficient rare gene prediction we used DIGIT14, an ab initio gene-finder that finds genes by combining gene predictions from multiple ab initio gene-finders such as FGENESH26, GENSCAN27 and HMMgene28. The reason we used DIGIT is that ab initio gene-finders, which do not use sequence similarity, have the potential for exhaustive rare gene prediction. The most remarkable feature of ab initio gene-finders is their high sensitivity, especially at the nucleotide level. Conversely, ab initio gene-finders also predict many false-positive genes. DIGIT successfully discards many false-positive exons predicted by the individual gene-finders and yields remarkable improvements in specificity without lowering sensitivity as compared with the best accuracies achieved by any single gene-finder. For experimental verification of the candidate genes, RT–PCR was performed using primer sets designed from the predicted exon sequences with a single-strand cDNA library prepared from various human tissues. If, in the first round of RT–PCR, a product could not be detected, a second round of PCR using nested PCR primer sets with the diluted RT–PCR products was conducted. When a PCR product was amplified, sequence analysis was used to confirm that the cDNA fragment was located at the predicted genomic location.
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Thanks to the staff, past and present, at RIKEN Genomic Sciences Center and the Broad Institute. We also acknowledge Y. Arai and M. Ohki (mapping), M. Hirai, Y. Suto and Y. Kanoh (fibre-FISH analysis technical support), C. Kawagoe and T. Katayama (computational data management), R. Baertsch and J. Mudge (annotation), V. Heyningen (historical insights), K. Linblad-Toh (preliminary assembly of the Monodelphis domestica genome), and the HUGO Gene Nomenclature Committee: S. Povey (chair), T. A. Eyre, V. K. Khodiyar, R. C. Lovering, K. M. B. Sneddon, T. P. Sneddon, C. C. Talbot Jr and M. W. Wright (assignment of official gene symbols). The zebrafish sequence data (assembly Zv4) were produced by the Wellcome Trust Sanger Institute (http://www.sanger.ac.uk/Projects/D_rerio/wgs.shtml). The authors also acknowledge the Ministry of Education, Culture, Sports, Science and Technology (Japan), the National Human Genome Research Institute (USA) and the Wellcome Trust Sanger Institute (UK) for funding this work.
The entire sequence for the chromosome is deposited in DDBJ/EMBL/GenBank under accession numbers NT_035113, NT_009237, NT_035158, NT_033903, NT_078088, NT_033927, NT_008984 and NT_033899. Accession numbers for individual clones and genes identified in this study can be found in Supplementary Information. Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.
Supplementary Figure 1
Chromosome 11 recombination rate versus sequence-based physical distance. (PDF 515 kb)
Supplementary Figure 2
Gene and disorder distributions across the human genome. (PDF 497 kb)
Supplementary Figure 3
Figure S3: Sequence similarity and aligned bases of segmental duplications. (PDF 498 kb)
Supplementary Figure 4
Divergence of chromosome 11 segmental duplications. (PDF 574 kb)
Supplementary Figure 5
Pattern of chromosome 11 segmental duplications. (PDF 499 kb)
Supplementary Figure 6
Distribution of segmental duplications. (PDF 514 kb)
Supplementary Figure 7
Sequence identity of segmental duplications on chromosome 11. (PDF 543 kb)
Supplementary Figure 8
Multi-species comparative genome analysis for chromosome 11. (PDF 537 kb)
Supplementary Figure 9
Distribution of conserved non-coding regions along human chromosome 11. (PDF 601 kb)
Supplementary Figure 10
Segmentally duplicated region that was challenging to finish. (PDF 779 kb)
Supplementary Table 1
Minimum clone tiling path of human chromosome 11. (XLS 275 kb)
Supplementary Table 2
Physical/clone libraries screened during map construction. (XLS 18 kb)
Supplementary Table 3
Supplementary Table 3 nature04632-s13.xls Finished contigs and gaps on human chromosome 11. (XLS 16 kb)
Supplementary Table 4
Sequence quality information for RIKEN and WUGSC chromosome 11 clones. (XLS 21 kb)
Supplementary Table 5
Interspersed repetitive elements. (DOC 60 kb)
Supplementary Table 6
Gene catalog of human chromosome 11. (XLS 963 kb)
Supplementary Table 7
Non-OR clustered gene families on human chromosome 11. (XLS 31 kb)
Supplementary Table 8
Read-through transcripts found on human chromosome 11. (XLS 24 kb)
Supplementary Table 9
CpG islands versus number of variants in expressed genes. (XLS 16 kb)
Supplementary Table 10
Olfactory receptor gene clusters on chromosome 11. (DOC 101 kb)
Supplementary Table 11
Predicted CpG islands on human chromosome 11. (XLS 166 kb)
Supplementary Table 12
Gene expression analysis results for DIGIT predicted genes. (XLS 19 kb)
Supplementary Table 13
Table S13: Accession numbers for submitted DIGIT mRNA sequences. (XLS 25 kb)
Supplementary Table 14
Blast results for DIGIT genes versus the NCBI nt database. (XLS 77 kb)
Supplementary Table 15
InterProScan analysis of DIGIT verified genes. (XLS 48 kb)
Supplementary Table 16
OMIM disorders that have been associated with human chromosome 11 but for which no specific cause has yet been determined. (XLS 116 kb)
Supplementary Table 17
Gene deserts on human chromosome 11. (XLS 19 kb)
Supplementary Table 18
Imprinted genes on human chromosome 11. (DOC 47 kb)
Supplementary Table 19
Bases involved in segmental duplication and pairwise alignment. (XLS 14 kb)
Supplementary Table 20
Segmental duplication positions on human chromosome 11. (XLS 88 kb)
Supplementary Table 21
Segmental duplication in pericentromeric and telomeric regions. (XLS 15 kb)
Supplementary Table 22
RefSeq genes overlapped with segmental duplication. (XLS 29 kb)
Supplementary Table 23
Conservation blocks and segments between chromosome 11 and other genomes. (XLS 16 kb)
Supplementary Table 24
Conserved non-coding elements on human chromosome 11. (XLS 468 kb)
Supplementary Table 25
Sequencing gaps on human chromosome 11. (XLS 20 kb)
This file contains Supplementary Methods and additional references (DOC 91 kb)
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This file contains text to accompany the Supplementary Figures (DOC 61 kb)
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Taylor, T., Noguchi, H., Totoki, Y. et al. Human chromosome 11 DNA sequence and analysis including novel gene identification. Nature 440, 497–500 (2006). https://doi.org/10.1038/nature04632
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