A genomic view of alternative splicing.

Recent genome-wide analyses of alternative splicing indicate that 40-60% of human genes have alternative splice forms, suggesting that alternative splicing is one of the most significant components of the functional complexity of the human genome. Here we review these recent results from bioinformatics studies, assess their reliability and consider the impact of alternative splicing on biological functions. Although the 'big picture' of alternative splicing that is emerging from genomics is exciting, there are many challenges. High-throughput experimental verification of alternative splice forms, functional characterization, and regulation of alternative splicing are key directions for research. We recommend a community-based effort to discover and characterize alternative splice forms comprehensively throughout the human genome.     

Analysis of expressed sequence tags indicates 35,000 human genes

The number of protein-coding genes in an organism provides a useful first measure of its molecular complexity. Single-celled prokaryotes and eukaryotes typically have a few thousand genes; for example, Escherichia coli has 4,300 and Saccharomyces cerevisiae has 6,000. Evolution of multicellularity appears to have been accompanied by a several-fold increase in gene number, the invertebrates Caenorhabditis elegans and Drosophila melanogaster having 19,000 and 13,600 genes, respectively. Here we estimate the number of human genes by comparing a set of human expressed sequence tag (EST) contigs with human chromosome 22 and with a non-redundant set of mRNA sequences. The two comparisons give mutually consistent estimates of approximately 35,000 genes, substantially lower than most previous estimates. Evolution of the increased physiological complexity of vertebrates may therefore have depended more on the combinatorial diversification of regulatory networks or alternative splicing than on a substantial increase in gene number.     

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.     

A genome-wide RNA interference screen in Drosophila melanogaster cells for new components of the Hh signaling pathway

Members of the Hedgehog (Hh) family of signaling proteins are powerful regulators of developmental processes in many organisms and have been implicated in many human disease states. Here we report the results of a genome-wide RNA interference screen in Drosophila melanogaster cells for new components of the Hh signaling pathway. The screen identified hundreds of potential new regulators of Hh signaling, including many large protein complexes with pleiotropic effects, such as the coat protein complex I (COPI) complex, the ribosome and the proteasome. We identified the multimeric protein phosphatase 2A (PP2A) and two new kinases, the D. melanogaster orthologs of the vertebrate PITSLRE and cyclin-dependent kinase-9 (CDK9) kinases, as Hh regulators. We also identified a large group of constitutive and alternative splicing factors, two nucleoporins involved in mRNA export and several RNA-regulatory proteins as potent regulators of Hh signal transduction, indicating that splicing regulation and mRNA transport have a previously unrecognized role in Hh signaling. Finally, we showed that several of these genes have conserved roles in mammalian Hh signaling.     

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.     

Genome-wide variation and identification of vaccine targets in the Plasmodium falciparum genome

One goal in sequencing the Plasmodium falciparum genome, the agent of the most lethal form of malaria, is to discover vaccine and drug targets. However, identifying those targets in a genome in which approximately 60% of genes have unknown functions is an enormous challenge. Because the majority of known malaria antigens and drug-resistant genes are highly polymorphic and under various selective pressures, genome-wide analysis for signatures of selection may lead to discovery of new vaccine and drug candidates. Here we surveyed 3,539 P. falciparum genes ( approximately 65% of the predicted genes) for polymorphisms and identified various highly polymorphic loci and genes, some of which encode new antigens that we confirmed using human immune sera. Our collections of genome-wide SNPs ( approximately 65% nonsynonymous) and polymorphic microsatellites and indels provide a high-resolution map (one marker per approximately 4 kb) for mapping parasite traits and studying parasite populations. In addition, we report new antigens, providing urgently needed vaccine candidates for disease control.     

Nova regulates brain-specific splicing to shape the synapse

Alternative RNA splicing greatly increases proteome diversity and may thereby contribute to tissue-specific functions. We carried out genome-wide quantitative analysis of alternative splicing using a custom Affymetrix microarray to assess the role of the neuronal splicing factor Nova in the brain. We used a stringent algorithm to identify 591 exons that were differentially spliced in the brain relative to immune tissues, and 6.6% of these showed major splicing defects in the neocortex of Nova2-/- mice. We tested 49 exons with the largest predicted Nova-dependent splicing changes and validated all 49 by RT-PCR. We analyzed the encoded proteins and found that all those with defined brain functions acted in the synapse (34 of 40, including neurotransmitter receptors, cation channels, adhesion and scaffold proteins) or in axon guidance (8 of 40). Moreover, of the 35 proteins with known interaction partners, 74% (26) interact with each other. Validating a large set of Nova RNA targets has led us to identify a multi-tiered network in which Nova regulates the exon content of RNAs encoding proteins that interact in the synapse.     

Open-reading-frame sequence tags (OSTs) support the existence of at least 17,300 genes in C. elegans

The genome sequences of Caenorhabditis elegans, Drosophila melanogaster and Arabidopsis thaliana have been predicted to contain 19,000, 13,600 and 25,500 genes, respectively. Before this information can be fully used for evolutionary and functional studies, several issues need to be addressed. First, the gene number estimates obtained in silico and not yet supported by any experimental data need to be verified. For example, it seems biologically paradoxical that C. elegans would have 50% more genes than Drosophilia. Second, intron/exon predictions need to be tested experimentally. Third, complete sets of open reading frames (ORFs), or "ORFeomes," need to be cloned into various expression vectors. To address these issues simultaneously, we have designed and applied to C. elegans the following strategy. Predicted ORFs are amplified by PCR from a highly representative cDNA library using ORF-specific primers, cloned by Gateway recombination cloning and then sequenced to generate ORF sequence tags (OSTs) as a way to verify identity and splicing. In a sample (n=1,222) of the nearly 10,000 genes predicted ab initio (that is, for which no expressed sequence tag (EST) is available so far), at least 70% were verified by OSTs. We also observed that 27% of these experimentally confirmed genes have a structure different from that predicted by GeneFinder. We now have experimental evidence that supports the existence of at least 17,300 genes in C. elegans. Hence we suggest that gene counts based primarily on ESTs may underestimate the number of genes in human and in other organisms.     

Genome-wide association analysis identifies 20 loci that influence adult height

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.     

Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease

Integration of genome-wide expression profiling with linkage analysis is a new approach to identifying genes underlying complex traits. We applied this approach to the regulation of gene expression in the BXH/HXB panel of rat recombinant inbred strains, one of the largest available rodent recombinant inbred panels and a leading resource for genetic analysis of the highly prevalent metabolic syndrome. In two tissues important to the pathogenesis of the metabolic syndrome, we mapped cis- and trans-regulatory control elements for expression of thousands of genes across the genome. Many of the most highly linked expression quantitative trait loci are regulated in cis, are inherited essentially as monogenic traits and are good candidate genes for previously mapped physiological quantitative trait loci in the rat. By comparative mapping we generated a data set of 73 candidate genes for hypertension that merit testing in human populations. Mining of this publicly available data set is expected to lead to new insights into the genes and regulatory pathways underlying the extensive range of metabolic and cardiovascular disease phenotypes that segregate in these recombinant inbred strains.     

Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression

Variation in the CYP3A enzymes, which act in drug metabolism, influences circulating steroid levels and responses to half of all oxidatively metabolized drugs. CYP3A activity is the sum activity of the family of CYP3A genes, including CYP3A5, which is polymorphically expressed at high levels in a minority of Americans of European descent and Europeans (hereafter collectively referred to as 'Caucasians'). Only people with at least one CYP3A5*1 allele express large amounts of CYP3A5. Our findings show that single-nucleotide polymorphisms (SNPs) in CYP3A5*3 and CYP3A5*6 that cause alternative splicing and protein truncation result in the absence of CYP3A5 from tissues of some people. CYP3A5 was more frequently expressed in livers of African Americans (60%) than in those of Caucasians (33%). Because CYP3A5 represents at least 50% of the total hepatic CYP3A content in people polymorphically expressing CYP3A5, CYP3A5 may be the most important genetic contributor to interindividual and interracial differences in CYP3A-dependent drug clearance and in responses to many medicines.