Samuel Marguerat

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.

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.

A Network of Multiple Regulatory Layers Shapes Gene Expression in Fission Yeast

Summary Gene expression is controlled at multiple layers, and cells may integrate different regulatory steps for coherent production of proper protein levels. We applied various microarray-based approaches to determine key gene-expression intermediates in exponentially growing fission yeast, providing genome-wide data for translational profiles, mRNA steady-state levels, polyadenylation profiles, start-codon sequence context, mRNA half-lives, and RNA polymerase II occupancy. We uncovered widespread and unexpected relationships between distinct aspects of gene expression. Translation and polyadenylation are aligned on a global scale with both the lengths and levels of mRNAs: efficiently translated mRNAs have longer poly(A) tails and are shorter, more stable, and more efficiently transcribed on average. Transcription and translation may be independently but congruently optimized to streamline protein production. These rich data sets, all acquired under a standardized condition, reveal a substantial coordination between regulatory layers and provide a basis for a systems-level understanding of multilayered gene-expression programs.

Next-generation sequencing: applications beyond genomes

The development of DNA sequencing more than 30 years ago has profoundly impacted biological research. In the last couple of years, remarkable technological innovations have emerged that allow the direct and cost-effective sequencing of complex samples at unprecedented scale and speed. These next-generation technologies make it feasible to sequence not only static genomes, but also entire transcriptomes expressed under different conditions. These and other powerful applications of next-generation sequencing are rapidly revolutionizing the way genomic studies are carried out. Below, we provide a snapshot of these exciting new approaches to understanding the properties and functions of genomes. Given that sequencing-based assays may increasingly supersede microarray-based assays, we also compare and contrast data obtained from these distinct approaches.

Proportionality: A Valid Alternative to Correlation for Relative Data

In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative—or compositional—data, differential expression needs careful interpretation, and correlation—a statistical workhorse for analyzing pairwise relationships—is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic ϕ which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes.

A simple method for directional transcriptome sequencing using Illumina technology

High-throughput sequencing of cDNA has been used to study eukaryotic transcription on a genome-wide scale to single base pair resolution. In order to compensate for the high ribonuclease activity in bacterial cells, we have devised an equivalent technique optimized for studying complete prokaryotic transcriptomes that minimizes the manipulation of the RNA sample. This new approach uses Illumina technology to sequence single-stranded (ss) cDNA, generating information on both the direction and level of transcription throughout the genome. The protocol, and associated data analysis programs, are freely available from http://www.sanger.ac.uk/Projects/Pathogens/Transcriptome/. We have successfully applied this method to the bacterial pathogens Salmonella bongori and Streptococcus pneumoniae and the yeast Schizosaccharomyces pombe. This method enables experimental validation of genetic features predicted in silico and allows the easy identification of novel transcripts throughout the genome. We also show that there is a high correlation between the level of gene expression calculated from ss-cDNA and double-stranded-cDNA sequencing, indicting that ss-cDNA sequencing is both robust and appropriate for use in quantitative studies of transcription. Hence, this simple method should prove a useful tool in aiding genome annotation and gene expression studies in both prokaryotes and eukaryotes.

Fission yeast SWI/SNF and RSC complexes show compositional and functional differences from budding yeast.

SWI/SNF chromatin-remodeling complexes have crucial roles in transcription and other chromatin-related processes. The analysis of the two members of this class in Saccharomyces cerevisiae, SWI/SNF and RSC, has heavily contributed to our understanding of these complexes. To understand the in vivo functions of SWI/SNF and RSC in an evolutionarily distant organism, we have characterized these complexes in Schizosaccharomyces pombe. Although core components are conserved between the two yeasts, the compositions of S. pombe SWI/SNF and RSC differ from their S. cerevisiae counterparts and in some ways are more similar to metazoan complexes. Furthermore, several of the conserved proteins, including actin-like proteins, are markedly different between the two yeasts with respect to their requirement for viability. Finally, phenotypic and microarray analyses identified widespread requirements for SWI/SNF and RSC on transcription including strong evidence that SWI/SNF directly represses iron-transport genes.

A Pre-mRNA Degradation Pathway that Selectively Targets Intron-Containing Genes Requires the Nuclear Poly(A)-Binding Protein

General discard pathways eliminate unprocessed and irregular pre-mRNAs to control the quality of gene expression. In contrast to such general pre-mRNA decay, we describe here a nuclear pre-mRNA degradation pathway that controls the expression of select intron-containing genes. We show that the fission yeast nuclear poly(A)-binding protein, Pab2, and the nuclear exosome subunit, Rrp6, are the main factors involved in this polyadenylation-dependent pre-mRNA degradation pathway. Transcriptome analysis and intron swapping experiments revealed that inefficient splicing is important to dictate susceptibility to Pab2-dependent pre-mRNA decay. We also show that negative splicing regulation can promote the poor splicing efficiency required for this pre-mRNA decay pathway, and in doing so, we identified a mechanism of cross-regulation between paralogous ribosomal proteins through nuclear pre-mRNA decay. Our findings unveil a layer of regulation in the nucleus in which the turnover of specific pre-mRNAs, besides the turnover of mature mRNAs, is used to control gene expression.