Jürg Bähler

Heterologous modules for efficient and versatile PCR-based gene targeting in Schizosaccharomyces pombe

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 ≥50%, and the lowest efficiency encountered was 17%. The methodology and constructs described here should greatly facilitate analysis of gene function in S. pombe.

Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution

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.

Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation

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.

Periodic gene expression program of the fission yeast cell cycle

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 ∼40 genes that seem to be universally regulated during the eukaryotic cell cycle and may have key roles in cell-cycle progression.

The transcriptional program of meiosis and sporulation in fission yeast

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.

RNA-seq: from technology to biology

Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

Quantitative Analysis of Fission Yeast Transcriptomes and Proteomes in Proliferating and Quiescent Cells

Summary Data 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.

Arginine methylation at histone H3R2 controls deposition of H3K4 trimethylation.

Modifications on histones control important biological processes through their effects on chromatin structure. Methylation at lysine 4 on histone H3 (H3K4) is found at the 5′ end of active genes and contributes to transcriptional activation by recruiting chromatin-remodelling enzymes. An adjacent arginine residue (H3R2) is also known to be asymmetrically dimethylated (H3R2me2a) in mammalian cells, but its location within genes and its function in transcription are unknown. Here we show that H3R2 is also methylated in budding yeast (Saccharomyces cerevisiae), and by using an antibody specific for H3R2me2a in a chromatin immunoprecipitation-on-chip analysis we determine the distribution of this modification on the entire yeast genome. We find that H3R2me2a is enriched throughout all heterochromatic loci and inactive euchromatic genes and is present at the 3′ end of moderately transcribed genes. In all cases the pattern of H3R2 methylation is mutually exclusive with the trimethyl form of H3K4 (H3K4me3). We show that methylation at H3R2 abrogates the trimethylation of H3K4 by the Set1 methyltransferase. The specific effect on H3K4me3 results from the occlusion of Spp1, a Set1 methyltransferase subunit necessary for trimethylation. Thus, the inability of Spp1 to recognize H3 methylated at R2 prevents Set1 from trimethylating H3K4. These results provide the first mechanistic insight into the function of arginine methylation on chromatin.

PomBase: a comprehensive online resource for fission yeast

PomBase (www.pombase.org) is a new model organism database established to provide access to comprehensive, accurate, and up-to-date molecular data and biological information for the fission yeast Schizosaccharomyces pombe to effectively support both exploratory and hypothesis-driven research. PomBase encompasses annotation of genomic sequence and features, comprehensive manual literature curation and genome-wide data sets, and supports sophisticated user-defined queries. The implementation of PomBase integrates a Chado relational database that houses manually curated data with Ensembl software that supports sequence-based annotation and web access. PomBase will provide user-friendly tools to promote curation by experts within the fission yeast community. This will make a key contribution to shaping its content and ensuring its comprehensiveness and long-term relevance.

Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data

BackgroundThe genome of the fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genomic era of this increasingly popular model organism. We have built fission yeast microarrays, optimised protocols to improve array performance, and carried out experiments to assess various characteristics of microarrays.ResultsWe designed PCR primers to amplify specific probes (180–500 bp) for all known and predicted fission yeast genes, which are printed in duplicate onto separate regions of glass slides together with control elements (~13,000 spots/slide). Fluorescence signal intensities depended on the size and intragenic position of the array elements, whereas the signal ratios were largely independent of element properties. Only the coding strand is covalently linked to the slides, and our array elements can discriminate transcriptional direction. The microarrays can distinguish sequences with up to 70% identity, above which cross-hybridisation contributes to the signal intensity. We tested the accuracy of signal ratios and measured the reproducibility of array data caused by biological and technical factors. Because the technical variability is lower, it is best to use samples prepared from independent biological experiments to obtain repeated measurements with swapping of fluorochromes to prevent dye bias. We also developed a script that discards unreliable data and performs a normalization to correct spatial artefacts.ConclusionsThis paper provides data for several microarray properties that are rarely measured. The results define critical parameters for microarray design and experiments and provide a framework to optimise and interpret array data. Our arrays give reproducible and accurate expression ratios with high sensitivity. The scripts for primer design and initial data processing as well as primer sequences and detailed protocols are available from our website.