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

Connecting growth with gene expression: of noise and numbers.

Growth is a dynamic process whereby cells accumulate mass. Growth rates of single cells are connected to RNA and protein synthesis rates, and therefore with biomolecule numbers. Noise in gene expression depends on these numbers, and is thus linked with cellular growth. Whether these global attributes of the cell participate in gene regulation is still largely unexplored. New experimental and modelling studies suggest that systemic variations in biomolecule numbers can coordinate cellular processes, including growth itself, through global regulatory feedback that acts in addition to genetic regulatory networks. Here, we review these findings and speculate on possible implications of this less appreciated layer of gene regulation for cellular physiology and adaptation to changing environments

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 coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes

Coarse-grained resource allocation models (C-GRAMs) are simple mathematical models of cell physiology, where large components of the macromolecular composition are abstracted into single entities. The dynamics and steady-state behaviour of such models provides insights on optimal allocation of cellular resources and have explained experimentally observed cellular growth laws, but current models do not account for the uptake of compound sources of carbon and nitrogen. Here, we formulate a C-GRAM with nitrogen and carbon pathways converging on biomass production, with parametrizations accounting for respirofermentative and purely respiratory growth. The model describes the effects of the uptake of sugars, ammonium and/or compound nutrients such as amino acids on the translational resource allocation towards proteome sectors that maximized the growth rate. It robustly recovers cellular growth laws including the Monod law and the ribosomal growth law. Furthermore, we show how the growth-maximizing balance between carbon uptake, recycling, and excretion depends on the nutrient environment. Lastly, we find a robust linear correlation between the ribosome fraction and the abundance of amino acid equivalents in the optimal cell, which supports the view that simple regulation of translational gene expression can enable cells to achieve an approximately optimal growth state

Fission yeast obeys a linear size law under nutrient titration

Steady-state cell size and geometry depend on growth conditions. Here, we use an experimental setup based on continuous culture and single-cell imaging to study how cell volume, length, width and surface-to-volume ratio vary across a range of growth conditions including nitrogen and carbon titration, the choice of nitrogen source, and translation inhibition. Overall, we find cell geometry is not fully determined by growth rate and depends on the specific mode of growth rate modulation. However, under nitrogen and carbon titrations, we observe that the cell volume and the growth rate follow the same linear scaling

Coordinating genome expression with cell size.

Cell size is highly variable; cells from various tissues differ in volume over orders of magnitudes, from tiny lymphocytes to giant neurons, and cells of a given type change size during the cell cycle. Larger cells need to produce and maintain higher amounts of RNA and protein to sustain biomass and function, although the genome content often remains constant. Available data indicate that the transcriptional and translational outputs scale with cell size at a genome-wide level, but how such remarkably coordinated regulation is achieved remains largely mysterious. With global and systems-level approaches becoming more widespread and quantitative, it is worth revisiting this fascinating problem. Here, we outline current knowledge of the fundamental relations between genome regulation and cell size, and highlight the biological implications and potential mechanisms of the global tuning of gene expression to cellular volume

Modelling capture efficiency of single-cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics

MOTIVATION: Gene expression is characterised by stochastic bursts of transcription that occur at brief and random periods of promoter activity. The kinetics of gene expression burstiness differs across the genome and is dependent on the promoter sequence, among other factors. Single-cell RNA sequencing (scRNA-seq) has made it possible to quantify the cell-to-cell variability in transcription at a global genome-wide level. However, scRNA-seq data is prone to technical variability, including low and variable capture efficiency of transcripts from individual cells. RESULTS: Here, we propose a novel mathematical theory for the observed variability in scRNA-seq data. Our method captures burst kinetics and variability in both the cell size and capture efficiency, which allows us to propose several likelihood-based and simulation-based methods for the inference of burst kinetics from scRNA-seq data. Using both synthetic and real data, we show that the simulation-based methods provide an accurate, robust and flexible tool for inferring burst kinetics from scRNA-seq data. In particular, in a supervised manner, a simulation-based inference method based on neural networks proves to be accurate and useful when applied to both allele and non-allele-specific scRNA-seq data. AVAILABILITY: The code for Neural Network and Approximate Bayesian Computation inference is available at https://github.com/WT215/nnRNA and https://github.com/WT215/Julia_ABC respectively. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

The DNA damage checkpoint pathway promotes extensive resection and nucleotide synthesis to facilitate homologous recombination repair and genome stability in fission yeast.

DNA double-strand breaks (DSBs) can cause chromosomal rearrangements and extensive loss of heterozygosity (LOH), hallmarks of cancer cells. Yet, how such events are normally suppressed is unclear. Here we identify roles for the DNA damage checkpoint pathway in facilitating homologous recombination (HR) repair and suppressing extensive LOH and chromosomal rearrangements in response to a DSB. Accordingly, deletion of Rad3(ATR), Rad26ATRIP, Crb2(53BP1) or Cdc25 overexpression leads to reduced HR and increased break-induced chromosome loss and rearrangements. We find the DNA damage checkpoint pathway facilitates HR, in part, by promoting break-induced Cdt2-dependent nucleotide synthesis. We also identify additional roles for Rad17, the 9-1-1 complex and Chk1 activation in facilitating break-induced extensive resection and chromosome loss, thereby suppressing extensive LOH. Loss of Rad17 or the 9-1-1 complex results in a striking increase in break-induced isochromosome formation and very low levels of chromosome loss, suggesting the 9-1-1 complex acts as a nuclease processivity factor to facilitate extensive resection. Further, our data suggest redundant roles for Rad3ATR and Exo1 in facilitating extensive resection. We propose that the DNA damage checkpoint pathway coordinates resection and nucleotide synthesis, thereby promoting efficient HR repair and genome stability

urg1: a uracil-regulatable promoter system for fission yeast with short induction and repression times.

BACKGROUND: The fission yeast Schizosaccharomyces pombe is a popular genetic model organism with powerful experimental tools. The thiamine-regulatable nmt1 promoter and derivatives, which take >15 hours for full induction, are most commonly used for controlled expression of ectopic genes. Given the short cell cycle of fission yeast, however, a promoter system that can be rapidly regulated, similar to the GAL system for budding yeast, would provide a key advantage for many experiments. METHODOLOGY/PRINCIPAL FINDINGS: We used S. pombe microarrays to identify three neighbouring genes (urg1, urg2, and urg3) whose transcript levels rapidly and strongly increased in response to uracil, a condition which otherwise had little effect on global gene expression. We cloned the promoter of urg1 (uracil-regulatable gene) to create several PCR-based gene targeting modules for replacing native promoters with the urg1 promoter (Purg1) in the normal chromosomal locations of genes of interest. The kanMX6 and natMX6 markers allow selection under urg1 induced and repressed conditions, respectively. Some modules also allow N-terminal tagging of gene products placed under urg1 control. Using pom1 as a proof-of-principle, we observed a maximal increase of Purg1-pom1 transcripts after uracil addition within less than 30 minutes, and a similarly rapid decrease after uracil removal. The induced and repressed transcriptional states remained stable over 24-hour periods. RT-PCR comparisons showed that both induced and repressed Purg1-pom1 transcript levels were lower than corresponding P3nmt1-pom1 levels (wild-type nmt1 promoter) but higher than P81nmt1-pom1 levels (weak nmt1 derivative). CONCLUSIONS/SIGNIFICANCE: We exploited the urg1 promoter system to rapidly induce pom1 expression at defined cell-cycle stages, showing that ectopic pom1 expression leads to cell branching in G2-phase but much less so in G1-phase. The high temporal resolution provided by the urg1 promoter should facilitate experimental design and improve the genetic toolbox for the fission yeast community

Genome-wide analysis of poly(A) site selection in schizosaccharomyces pombe,

Polyadenylation of pre-mRNAs, a critical step in eukaryotic gene expression, is mediated by cis elements collectively called the polyadenylation signal. Genome-wide analysis of such polyadenylation signals was missing in fission yeast, even though it is an important model organism. We demonstrate that the canonical AATAAA motif is the most frequent and functional polyadenylation signal in Schizosaccharomyces pombe. Using analysis of RNA-Seq data sets from cells grown under various physiological conditions, we identify 3′ UTRs for nearly 90% of the yeast genes. Heterogeneity of cleavage sites is common, as is alternative polyadenylation within and between conditions. We validated the computationally identified sequence elements likely to promote polyadenylation by functional assays, including qRT-PCR and 3′RACE analysis. The biological importance of the AATAAA motif is underlined by functional analysis of the genes containing it. Furthermore, it has been shown that convergent genes require trans elements, like cohesin for efficient transcription termination. Here we show that convergent genes lacking cohesin (on chromosome 2) are generally associated with longer overlapping mRNA transcripts. Our bioinformatic and experimental genome-wide results are summarized and can be accessed and customized in a user-friendly database Pomb(A)