We describe a straightforward PCR-based approach to the deletion, tagging, and overexpression of genes in their normal chromosomal locations in the fission yeast Schizosaccharomyces pombe. Using this approach and the S. pombe ura4+ gene as a marker, nine genes were deleted with efficiencies of homologous integration ranging from 6 to 63%. We also constructed a series of plasmids containing the kanMX6 module, which allows selection of G418-resistant cells and thus provides a new heterologous marker for use in S. pombe. The modular nature of these constructs allows a small number of PCR primers to be used for a wide variety of gene manipulations, including deletion, overexpression (using the regulatable nmt1 promoter), C- or N-terminal protein tagging (with HA, Myc, GST, or GFP), and partial C- or N-terminal deletions with or without tagging. Nine genes were manipulated using these kanMX6 constructs as templates for PCR. The PCR primers included 60 to 80 bp of flanking sequences homologous to target sequences in the genome. Transformants were screened for homologous integration by PCR. In most cases, the efficiency of homologous integration was > or = 50%, and the lowest efficiency encountered was 17%. The methodology and constructs described here should greatly facilitate analysis of gene function in S. pombe.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

We explored transcriptional responses of the fission yeast Schizosaccharomyces pombe to various environmental stresses. DNA microarrays were used to characterize changes in expression profiles of all known and predicted genes in response to five stress conditions: oxidative stress caused by hydrogen peroxide, heavy metal stress caused by cadmium, heat shock caused by temperature increase to 39°C, osmotic stress caused by sorbitol, and DNA damage caused by the alkylating agent methylmethane sulfonate. We define a core environmental stress response (CESR) common to all, or most, stresses. There was a substantial overlap between CESR genes of fission yeast and the genes of budding yeast that are stereotypically regulated during stress. CESR genes were controlled primarily by the stress-activated mitogen-activated protein kinase Sty1p and the transcription factor Atf1p. S. pombe also activated gene expression programs more specialized for a given stress or a subset of stresses. In general, these "stress-specific" responses were less dependent on the Sty1p mitogen-activated protein kinase pathway and may involve specific regulatory factors. Promoter motifs associated with some of the groups of coregulated genes were identified. We compare and contrast global regulation of stress genes in fission and budding yeasts and discuss evolutionary implications.

Organisms are constantly exposed to a wide range of environmental changes, including both short-term changes during their lifetime and longer-term changes across generations. Stress-related gene expression programmes, characterized by distinct transcriptional mechanisms and high levels of noise in their expression patterns, need to be balanced with growth-related gene expression programmes. A range of recent studies give fascinating insight into cellular strategies for keeping gene expression in tune with physiological needs dictated by the environment, promoting adaptation to both short- and long-term environmental changes. Not only do organisms show great resilience to external challenges, but emerging data suggest that they also exploit these challenges to fuel phenotypic variation and evolutionary innovation.

Recent data from several organisms indicate that the transcribed portions of genomes are larger and more complex than expected, and that many functional properties of transcripts are based not on coding sequences but on regulatory sequences in untranslated regions or non-coding RNAs. Alternative start and polyadenylation sites and regulation of intron splicing add additional dimensions to the rich transcriptional output. This transcriptional complexity has been sampled mainly using hybridization-based methods under one or few experimental conditions. Here we applied direct high-throughput sequencing of complementary DNAs (RNA-Seq), supplemented with data from high-density tiling arrays, to globally sample transcripts of the fission yeast Schizosaccharomyces pombe, independently from available gene annotations. We interrogated transcriptomes under multiple conditions, including rapid proliferation, meiotic differentiation and environmental stress, as well as in RNA processing mutants to reveal the dynamic plasticity of the transcriptional landscape as a function of environmental, developmental and genetic factors. High-throughput sequencing proved to be a powerful and quantitative method to sample transcriptomes deeply at maximal resolution. In contrast to hybridization, sequencing showed little, if any, background noise and was sensitive enough to detect widespread transcription in >90% of the genome, including traces of RNAs that were not robustly transcribed or rapidly degraded. The combined sequencing and strand-specific array data provide rich condition-specific information on novel, mostly non-coding transcripts, untranslated regions and gene structures, thus improving the existing genome annotation. Sequence reads spanning exon-exon or exon-intron junctions give unique insight into a surprising variability in splicing efficiency across introns, genes and conditions. Splicing efficiency was largely coordinated with transcript levels, and increased transcription led to increased splicing in test genes. Hundreds of introns showed such regulated splicing during cellular proliferation or differentiation.

Cell-cycle control of transcription seems to be universal, but little is known about its global conservation and biological significance. We report on the genome-wide transcriptional program of the Schizosaccharomyces pombe cell cycle, identifying 407 periodically expressed genes of which 136 show high-amplitude changes. These genes cluster in four major waves of expression. The forkhead protein Sep1p regulates mitotic genes in the first cluster, including Ace2p, which activates transcription in the second cluster during the M-G1 transition and cytokinesis. Other genes in the second cluster, which are required for G1-S progression, are regulated by the MBF complex independently of Sep1p and Ace2p. The third cluster coincides with S phase and a fourth cluster contains genes weakly regulated during G2 phase. Despite conserved cell-cycle transcription factors, differences in regulatory circuits between fission and budding yeasts are evident, revealing evolutionary plasticity of transcriptional control. Periodic transcription of most genes is not conserved between the two yeasts, except for a core set of approximately 40 genes that seem to be universally regulated during the eukaryotic cell cycle and may have key roles in cell-cycle progression.

Sexual reproduction requires meiosis to produce haploid gametes, which in turn can fuse to regenerate a diploid organism. We have studied the transcriptional program that drives this developmental process in Schizosaccharomyces pombe using DNA microarrays. Here we show that hundreds of genes are regulated in successive waves of transcription that correlate with major biological events of meiosis and sporulation. Each wave is associated with specific promoter motifs. Clusters of neighboring genes (mostly close to telomeres) are co-expressed early in the process, which reflects a more global control of these genes. We find that two Atf-like transcription factors are essential for the expression of late genes and formation of spores, and identify dozens of potential Atf target genes. Comparison with the meiotic program of the distantly related Saccharomyces cerevisiae reveals an unexpectedly small shared meiotic transcriptome, suggesting that the transcriptional regulation of meiosis evolved independently in both species.

SummaryData on absolute molecule numbers will empower the modeling, understanding, and comparison of cellular functions and biological systems. We quantified transcriptomes and proteomes in fission yeast during cellular proliferation and quiescence. This rich resource provides the first comprehensive reference for all RNA and most protein concentrations in a eukaryote under two key physiological conditions. The integrated data set supports quantitative biology and affords unique insights into cell regulation. Although mRNAs are typically expressed in a narrow range above 1 copy/cell, most long, noncoding RNAs, except for a distinct subset, are tightly repressed below 1 copy/cell. Cell-cycle-regulated transcription tunes mRNA numbers to phase-specific requirements but can also bring about more switch-like expression. Proteins greatly exceed mRNAs in abundance and dynamic range, and concentrations are regulated to functional demands. Upon transition to quiescence, the proteome changes substantially, but, in stark contrast to mRNAs, proteins do not uniformly decrease but scale with cell volume.