Clustering of housekeeping genes provides a unified model of gene order in the human genome

It is often supposed that, except for tandem duplicates, genes are randomly distributed throughout the human genome. However, recent analyses suggest that when all the genes expressed in a given tissue (notably placenta and skeletal muscle) are examined, these genes do not map to random locations but instead resolve to clusters. We have asked three questions: (i) is this clustering true for most tissues, or are these the exceptions; (ii) is any clustering simply the result of the expression of tandem duplicates and (iii) how, if at all, does this relate to the observed clustering of genes with high expression rates? We provide a unified model of gene clustering that explains the previous observations. We examined Serial Analysis of Gene Expression (SAGE) data for 14 tissues and found significant clustering, in each tissue, that persists even after the removal of tandem duplicates. We confirmed clustering by analysis of independent expressed-sequence tag (EST) data. We then tested the possibility that the human genome is organized into subregions, each specializing in genes needed in a given tissue. By comparing genes expressed in different tissues, we show that this is not the case: those genes that seem to be tissue-specific in their expression do not, as a rule, cluster. We report that genes that are expressed in most tissues (housekeeping genes) show strong clustering. In addition, we show that the apparent clustering of genes with high expression rates is a consequence of the clustering of housekeeping genes.     

Fine-scale structural variation of the human genome

Inversions, deletions and insertions are important mediators of disease and disease susceptibility. We systematically compared the human genome reference sequence with a second genome (represented by fosmid paired-end sequences) to detect intermediate-sized structural variants >8 kb in length. We identified 297 sites of structural variation: 139 insertions, 102 deletions and 56 inversion breakpoints. Using combined literature, sequence and experimental analyses, we validated 112 of the structural variants, including several that are of biomedical relevance. These data provide a fine-scale structural variation map of the human genome and the requisite sequence precision for subsequent genetic studies of human disease.     

High-resolution haplotype structure in the human genome

Linkage disequilibrium (LD) analysis is traditionally based on individual genetic markers and often yields an erratic, non-monotonic picture, because the power to detect allelic associations depends on specific properties of each marker, such as frequency and population history. Ideally, LD analysis should be based directly on the underlying haplotype structure of the human genome, but this structure has remained poorly understood. Here we report a high-resolution analysis of the haplotype structure across 500 kilobases on chromosome 5q31 using 103 single-nucleotide polymorphisms (SNPs) in a European-derived population. The results show a picture of discrete haplotype blocks (of tens to hundreds of kilobases), each with limited diversity punctuated by apparent sites of recombination. In addition, we develop an analytical model for LD mapping based on such haplotype blocks. If our observed structure is general (and published data suggest that it may be), it offers a coherent framework for creating a haplotype map of the human genome.     

Common deletion polymorphisms in the human genome

The locations and properties of common deletion variants in the human genome are largely unknown. We describe a systematic method for using dense SNP genotype data to discover deletions and its application to data from the International HapMap Consortium to characterize and catalogue segregating deletion variants across the human genome. We identified 541 deletion variants (94% novel) ranging from 1 kb to 745 kb in size; 278 of these variants were observed in multiple, unrelated individuals, 120 in the homozygous state. The coding exons of ten expressed genes were found to be commonly deleted, including multiple genes with roles in sex steroid metabolism, olfaction and drug response. These common deletion polymorphisms typically represent ancestral mutations that are in linkage disequilibrium with nearby SNPs, meaning that their association to disease can often be evaluated in the course of SNP-based whole-genome association studies.     

A high-resolution recombination map of the human genome

Determination of recombination rates across the human genome has been constrained by the limited resolution and accuracy of existing genetic maps and the draft genome sequence. We have genotyped 5,136 microsatellite markers for 146 families, with a total of 1,257 meiotic events, to build a high-resolution genetic map meant to: (i) improve the genetic order of polymorphic markers; (ii) improve the precision of estimates of genetic distances; (iii) correct portions of the sequence assembly and SNP map of the human genome; and (iv) build a map of recombination rates. Recombination rates are significantly correlated with both cytogenetic structures (staining intensity of G bands) and sequence (GC content, CpG motifs and poly(A)/poly(T) stretches). Maternal and paternal chromosomes show many differences in locations of recombination maxima. We detected systematic differences in recombination rates between mothers and between gametes from the same mother, suggesting that there is some underlying component determined by both genetic and environmental factors that affects maternal recombination rates.     

Detection of large-scale variation in the human genome

We identified 255 loci across the human genome that contain genomic imbalances among unrelated individuals. Twenty-four variants are present in > 10% of the individuals that we examined. Half of these regions overlap with genes, and many coincide with segmental duplications or gaps in the human genome assembly. This previously unappreciated heterogeneity may underlie certain human phenotypic variation and susceptibility to disease and argues for a more dynamic human genome structure.     

An evaluation of the draft human genome sequence

The completed draft version of the human genome, comprised of multiple short contigs encompassing 85% or more of euchromatin, was announced in June of 2000 (ref. 1). The detailed findings of the sequencing consortium were reported several months later. The draft sequence has provided insight into global characteristics, such as the total number of genes and a more accurate definition of gene families. Also of importance are genome positional details such as local genome architecture, regional gene density and the location of transcribed units that are critical for disease gene identification. We carried out a series of mapping and computational experiments using a nonredundant collection of 925 expressed sequence tags (ESTs) and sections of the public draft genome sequence that were available at different timepoints between April 2000 and April 2001. We found discrepancies in both the reported coverage of the human genome and the accuracy of mapping of genomic clones, suggesting some limitations of the draft genome sequence in providing accurate positional information and detailed characterization of chromosomal subregions.     

A literature network of human genes for high-throughput analysis of gene expression

We have carried out automated extraction of explicit and implicit biomedical knowledge from publicly available gene and text databases to create a gene-to-gene co-citation network for 13,712 named human genes by automated analysis of titles and abstracts in over 10 million MEDLINE records. The associations between genes have been annotated by linking genes to terms from the medical subject heading (MeSH) index and terms from the gene ontology (GO) database. The extracted database and accompanying web tools for gene-expression analysis have collectively been named 'PubGene'. We validated the extracted networks by three large-scale experiments showing that co-occurrence reflects biologically meaningful relationships, thus providing an approach to extract and structure known biology. We validated the applicability of the tools by analyzing two publicly available microarray data sets.     

Homology-based annotation yields 1,042 new candidate genes in the Drosophila melanogaster genome

The approach to annotating a genome critically affects the number and accuracy of genes identified in the genome sequence. Genome annotation based on stringent gene identification is prone to underestimate the complement of genes encoded in a genome. In contrast, over-prediction of putative genes followed by exhaustive computational sequence, motif and structural homology search will find rarely expressed, possibly unique, new genes at the risk of including non-functional genes. We developed a two-stage approach that combines the merits of stringent genome annotation with the benefits of over-prediction. First we identify plausible genes regardless of matches with EST, cDNA or protein sequences from the organism (stage 1). In the second stage, proteins predicted from the plausible genes are compared at the protein level with EST, cDNA and protein sequences, and protein structures from other organisms (stage 2). Remote but biologically meaningful protein sequence or structure homologies provide supporting evidence for genuine genes. The method, applied to the Drosophila melanogaster genome, validated 1,042 novel candidate genes after filtering 19,410 plausible genes, of which 12,124 matched the original 13,601 annotated genes. This annotation strategy is applicable to genomes of all organisms, including human.     

A high-resolution survey of deletion polymorphism in the human genome

Recent work has shown that copy number polymorphism is an important class of genetic variation in human genomes. Here we report a new method that uses SNP genotype data from parent-offspring trios to identify polymorphic deletions. We applied this method to data from the International HapMap Project to produce the first high-resolution population surveys of deletion polymorphism. Approximately 100 of these deletions have been experimentally validated using comparative genome hybridization on tiling-resolution oligonucleotide microarrays. Our analysis identifies a total of 586 distinct regions that harbor deletion polymorphisms in one or more of the families. Notably, we estimate that typical individuals are hemizygous for roughly 30-50 deletions larger than 5 kb, totaling around 550-750 kb of euchromatic sequence across their genomes. The detected deletions span a total of 267 known and predicted genes. Overall, however, the deleted regions are relatively gene-poor, consistent with the action of purifying selection against deletions. Deletion polymorphisms may well have an important role in the genetics of complex traits; however, they are not directly observed in most current gene mapping studies. Our new method will permit the identification of deletion polymorphisms in high-density SNP surveys of trio or other family data.     

Structural genomics: beyond the human genome project.

With access to whole genome sequences for various organisms and imminent completion of the Human Genome Project, the entire process of discovery in molecular and cellular biology is poised to change. Massively parallel measurement strategies promise to revolutionize how we study and ultimately understand the complex biochemical circuitry responsible for controlling normal development, physiologic homeostasis and disease processes. This information explosion is also providing the foundation for an important new initiative in structural biology. We are about to embark on a program of high-throughput X-ray crystallography aimed at developing a comprehensive mechanistic understanding of normal and abnormal human and microbial physiology at the molecular level. We present the rationale for creation of a structural genomics initiative, recount the efforts of ongoing structural genomics pilot studies, and detail the lofty goals, technical challenges and pitfalls facing structural biologists.     

Mining the human genome using microarrays of open reading frames

To test the hypothesis that the human genome project will uncover many genes not previously discovered by sequencing of expressed sequence tags (ESTs), we designed and produced a set of microarrays using probes based on open reading frames (ORFs) in 350 Mb of finished and draft human sequence. Our approach aims to identify all genes directly from genomic sequence by querying gene expression. We analysed genomic sequence with a suite of ORF prediction programs, selected approximately one ORF per gene, amplified the ORFs from genomic DNA and arrayed the amplicons onto treated glass slides. Of the first 10,000 arrayed ORFs, 31% are completely novel and 29% are similar, but not identical, to sequences in public databases. Approximately one-half of these are expressed in the tissues we queried by microarray. Subsequent verification by other techniques confirmed expression of several of the novel genes. Expressed sequence tags (ESTs) have yielded vast amounts of data, but our results indicate that many genes in the human genome will only be found by genomic sequencing.     

Genome assembly comparison identifies structural variants in the human genome

Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs and intermediate-sized variants (ISVs). However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celera's R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.     

zA map for sequence analysis of the Arabidopsis thaliana genome.

Arabidopsis thaliana has emerged as a model system for studies of plant genetics and development, and its genome has been targeted for sequencing by an international consortium (the Arabidopsis Genome Initiative; http://genome-www. stanford.edu/Arabidopsis/agi.html). To support the genome-sequencing effort, we fingerprinted more than 20,000 BACs (ref. 2) from two high-quality publicly available libraries, generating an estimated 17-fold redundant coverage of the genome, and used the fingerprints to nucleate assembly of the data by computer. Subsequent manual revision of the assemblies resulted in the incorporation of 19,661 fingerprinted BACs into 169 ordered sets of overlapping clones ('contigs'), each containing at least 3 clones. These contigs are ideal for parallel selection of BACs for large-scale sequencing and have supported the generation of more than 5.8 Mb of finished genome sequence submitted to GenBank; analysis of the sequence has confirmed the integrity of contigs constructed using this fingerprint data. Placement of contigs onto chromosomes can now be performed, and is being pursued by groups involved in both sequencing and positional cloning studies. To our knowledge, these data provide the first example of whole-genome random BAC fingerprint analysis of a eucaryote, and have provided a model essential to efforts aimed at generating similar databases of fingerprint contigs to support sequencing of other complex genomes, including that of human.     

Computational identification of promoters and first exons in the human genome.

The identification of promoters and first exons has been one of the most difficult problems in gene-finding. We present a set of discriminant functions that can recognize structural and compositional features such as CpG islands, promoter regions and first splice-donor sites. We explain the implementation of the discriminant functions into a decision tree that constitutes a new program called FirstEF. By using different models to predict CpG-related and non-CpG-related first exons, we showed by cross-validation that the program could predict 86% of the first exons with 17% false positives. We also demonstrated the prediction accuracy of FirstEF at the genome level by applying it to the finished sequences of human chromosomes 21 and 22 as well as by comparing the predictions with the locations of the experimentally verified first exons. Finally, we present the analysis of the predicted first exons for all of the 24 chromosomes of the human genome.     

A tiling resolution DNA microarray with complete coverage of the human genome

We constructed a tiling resolution array consisting of 32,433 overlapping BAC clones covering the entire human genome. This increases our ability to identify genetic alterations and their boundaries throughout the genome in a single comparative genomic hybridization (CGH) experiment. At this tiling resolution, we identified minute DNA alterations not previously reported. These alterations include microamplifications and deletions containing oncogenes, tumor-suppressor genes and new genes that may be associated with multiple tumor types. Our findings show the need to move beyond conventional marker-based genome comparison approaches, that rely on inference of continuity between interval markers. Our submegabase resolution tiling set for array CGH (SMRT array) allows comprehensive assessment of genomic integrity and thereby the identification of new genes associated with disease.