Transcriptional regulation and function during the human cell cycle.

We report here the transcriptional profiling of the cell cycle on a genome-wide scale in human fibroblasts. We identified approximately 700 genes that display transcriptional fluctuation with a periodicity consistent with that of the cell cycle. Systematic analysis of these genes revealed functional organization within groups of coregulated transcripts. A diverse set of cytoskeletal reorganization genes exhibit cell-cycle-dependent regulation, indicating that biological pathways are redirected for the execution of cell division. Many genes involved in cell motility and remodeling of the extracellular matrix are expressed predominantly in M phase, indicating a mechanism for balancing proliferative and invasive cellular behavior. Transcripts upregulated during S phase displayed extensive overlap with genes induced by DNA damage; cell-cycle-regulated transcripts may therefore constitute coherent programs used in response to external stimuli. Our data also provide clues to biological function for hundreds of previously uncharacterized human genes.

A simple procedure for the analysis of single nucleotide polymorphisms facilitates map-based cloning in Arabidopsis.

We developed a modified allele-specific PCR procedure for assaying single nucleotide polymorphisms (SNPs) and used the procedure (called SNAP for single-nucleotide amplified polymorphisms) to generate 62 Arabidopsis mapping markers. SNAP primers contain a single base pair mismatch within three nucleotides from the 3' end of one allele (the specific allele) and in addition have a 3' mismatch with the nonspecific allele. A computer program called SNAPER was used to facilitate the design of primers that generate at least a 1,000-fold difference in the quantity of the amplification products from the specific and nonspecific SNP alleles. Because SNAP markers can be readily assayed by electrophoresis on standard agarose gels and because a public database of over 25,000 SNPs is available between the Arabidopsis Columbia and Landsberg erecta ecotypes, the SNAP method greatly facilitates the map-based cloning of Arabidopsis genes defined by a mutant phenotype.

Transcription, genomes, function.

Large-scale studies of mRNA expression have displayed the unusual ability to both challenge traditional biological paradigms and enjoy rapid adoption among a wide range of researchers. The proliferating applications of this technology are poised to exert heavy influence on the very way biologists conceptualize problems and ask questions in the post-genome era.

Genome-wide mapping with biallelic markers in Arabidopsis thaliana.

Single-nucleotide polymorphisms, as well as small insertions and deletions (here referred to collectively as simple nucleotide polymorphisms, or SNPs), comprise the largest set of sequence variants in most organisms. Positional cloning based on SNPs may accelerate the identification of human disease traits and a range of biologically informative mutations. The recent application of high-density oligonucleotide arrays to allele identification has made it feasible to genotype thousands of biallelic SNPs in a single experiment. It has yet to be established, however, whether SNP detection using oligonucleotide arrays can be used to accelerate the mapping of traits in diploid genomes. The cruciferous weed Arabidopsis thaliana is an attractive model system for the construction and use of biallelic SNP maps. Although important biological processes ranging from fertilization and cell fate determination to disease resistance have been modelled in A. thaliana, identifying mutations in this organism has been impeded by the lack of a high-density genetic map consisting of easily genotyped DNA markers. We report here the construction of a biallelic genetic map in A. thaliana with a resolution of 3.5 cM and its use in mapping Eds16, a gene involved in the defence response to the fungal pathogen Erysiphe orontii. Mapping of this trait involved the high-throughput generation of meiotic maps of F2 individuals using high-density oligonucleotide probe array-based genotyping. We developed a software package called InterMap and used it to automatically delimit Eds16 to a 7-cM interval on chromosome 1. These results are the first demonstration of biallelic mapping in diploid genomes and establish means for generalizing SNP-based maps to virtually any genetic organism.

Candidate regulatory sequence elements for cell cycle-dependent transcription in Saccharomyces cerevisiae.

Recent developments in genome-wide transcript monitoring have led to a rapid accumulation of data from gene expression studies. Such projects highlight the need for methods to predict the molecular basis of transcriptional coregulation. A microarray project identified the 420 yeast transcripts whose synthesis displays cell cycle-dependent periodicity. We present here a statistical technique we developed to identify the sequence elements that may be responsible for this cell cycle regulation. Because most gene regulatory sites contain a short string of highly conserved nucleotides, any such strings that are involved in gene regulation will occur frequently in the upstream regions of the genes that they regulate, and rarely in the upstream regions of other genes. Our strategy therefore utilizes statistical procedures to identify short oligomers, five or six nucleotides in length, that are over-represented in upstream regions of genes whose expression peaks at the same phase of the cell cycle. We report, with a high level of confidence, that 9 hexamers and 12 pentamers are over-represented in the upstream regions of genes whose expression peaks at the early G(1), late G(1), S, G(2), or M phase of the cell cycle. Some of these sequence elements show a preference for a particular orientation, and others, through a separate statistical test, for a particular position upstream of the ATG start codon. The finding that the majority of the statistically significant sequence elements are located in late G(1) upstream regions correlates with other experiments that identified the late G(1)/early S boundary as a vital cell cycle control point. Our results highlight the importance of MCB, an element implicated previously in late G(1)/early S gene regulation, as most of the late G(1) oligomers contain the MCB sequence or variations thereof. It is striking that most MCB-like sequences localize to a specific region upstream of the ATG start codon. Additional sequences that we have identified may be important for regulation at other phases of the cell cycle.

Systematic determination of genetic network architecture.

Technologies to measure whole-genome mRNA abundances and methods to organize and display such data are emerging as valuable tools for systems-level exploration of transcriptional regulatory networks. For instance, it has been shown that mRNA data from 118 genes, measured at several time points in the developing hindbrain of mice, can be hierarchically clustered into various patterns (or 'waves') whose members tend to participate in common processes. We have previously shown that hierarchical clustering can group together genes whose cis-regulatory elements are bound by the same proteins in vivo. Hierarchical clustering has also been used to organize genes into hierarchical dendograms on the basis of their expression across multiple growth conditions. The application of Fourier analysis to synchronized yeast mRNA expression data has identified cell-cycle periodic genes, many of which have expected cis-regulatory elements. Here we apply a systematic set of statistical algorithms, based on whole-genome mRNA data, partitional clustering and motif discovery, to identify transcriptional regulatory sub-networks in yeast-without any a priori knowledge of their structure or any assumptions about their dynamics. This approach uncovered new regulons (sets of co-regulated genes) and their putative cis-regulatory elements. We used statistical characterization of known regulons and motifs to derive criteria by which we infer the biological significance of newly discovered regulons and motifs. Our approach holds promise for the rapid elucidation of genetic network architecture in sequenced organisms in which little biology is known.

A genome-wide transcriptional analysis of the mitotic cell cycle.

Progression through the eukaryotic cell cycle is known to be both regulated and accompanied by periodic fluctuation in the expression levels of numerous genes. We report here the genome-wide characterization of mRNA transcript levels during the cell cycle of the budding yeast S. cerevisiae. Cell cycle-dependent periodicity was found for 416 of the 6220 monitored transcripts. More than 25% of the 416 genes were found directly adjacent to other genes in the genome that displayed induction in the same cell cycle phase, suggesting a mechanism for local chromosomal organization in global mRNA regulation. More than 60% of the characterized genes that displayed mRNA fluctuation have already been implicated in cell cycle period-specific biological roles. Because more than 20% of human proteins display significant homology to yeast proteins, these results also link a range of human genes to cell cycle period-specific biological functions.

Parallel analysis of genetic selections using whole genome oligonucleotide arrays.

Thousands of genes have recently been sequenced in organisms ranging from Escherichia coli to human. For the majority of these genes, however, available sequence does not define a biological role. Efficient functional characterization of these genes requires strategies for scaling genetic analyses to the whole genome level. Plasmid-based library selections are an established approach to the functional analysis of uncharacterized genes and can help elucidate biological function by identifying, for example, physical interactors for a gene and genetic enhancers and suppressors of mutant phenotypes. The application of these selections to every gene in a eukaryotic genome, however, is generally limited by the need to manipulate and sequence hundreds of DNA plasmids. We present an alternative approach in which identification of nucleic acids is accomplished by direct hybridization to high-density oligonucleotide arrays. Based on the complete sequence of Saccharomyces cerevisiae, high-density arrays containing oligonucleotides complementary to every gene in the yeast genome have been designed and synthesized. Two-hybrid protein-protein interaction screens were carried out for S. cerevisiae genes implicated in mRNA splicing and microtubule assembly. Hybridization of labeled DNA derived from positive clones is sufficient to characterize the results of a screen in a single experiment, allowing rapid determination of both established and previously unknown biological interactions. These results demonstrate the use of oligonucleotide arrays for the analysis of two-hybrid screens. This approach should be generally applicable to the analysis of a range of genetic selections.