AGAPE (Automated Genome Analysis PipelinE) for Pan-Genome Analysis of Saccharomyces cerevisiae

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community.     

The Network Architecture of the Saccharomyces cerevisiae Genome

We propose a network-based approach for surmising the spatial organization of genomes from high-throughput interaction data. Our strategy is based on methods for inferring architectural features of networks. Specifically, we employ a community detection algorithm to partition networks of genomic interactions. These community partitions represent an intuitive interpretation of genomic organization from interaction data. Furthermore, they are able to recapitulate known aspects of the spatial organization of the Saccharomyces cerevisiae genome, such as the rosette conformation of the genome, the clustering of centromeres, as well as tRNAs, and telomeres. We also demonstrate that simple architectural features of genomic interaction networks, such as cliques, can give meaningful insight into the functional role of the spatial organization of the genome. We show that there is a correlation between inter-chromosomal clique size and replication timing, as well as cohesin enrichment. Together, our network-based approach represents an effective and intuitive framework for interpreting high-throughput genomic interaction data. Importantly, there is a great potential for this strategy, given the rich literature and extensive set of existing tools in the field of network analysis.     

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H₂O₂), an oxidizing agent. In the experiment, yeast is grown for 48 hours in 1/2X YPD broth containing 3X glucose. The culture is split into a control and treated group. The experiment culture is treated with 0.5 mM H₂O₂ in Hanks Buffered Saline (HBSS) for 1 hour. The control culture is treated with HBSS only. Total RNA is extracted from both cultures and is converted to a biotin-labeled cRNA product through a multistep process. The final synthesis product is taken back to the UVM Microarray Core Facility and hybridized to the Affymetrix yeast GeneChips. The resulting gene expression data are uploaded into bioinformatics data analysis software.Download video file.^{(79M, mov)}     

Genome instability in rad54 mutants of Saccharomyces cerevisiae

The RAD54 gene of Saccharomyces cerevisiae encodes a conserved dsDNA-dependent ATPase of the Swi2/Snf2 family with a specialized function during recombinational DNA repair. Here we analyzed the consequences of the loss of Rad54 function in vegetative (mitotic) cells. Mutants in RAD54 exhibited drastically reduced rates of spontaneous intragenic recombination but were proficient for spontaneous intergenic recombinant formation. The intergenic recombinants likely arose by a RAD54-independent pathway of break-induced replication. Significantly increased rates of spontaneous chromosome loss for diploid rad54/rad54 cells were identified in several independent assays. Inter estingly, the increase in chromosome loss appeared to depend on the presence of a homolog. In addition, the rate of complex genetic events involving chromosome loss were drastically increased in diploid rad54/rad54 cells. Together, these data suggest a role for Rad54 protein in the repair of spontaneous damage, where in the absence of Rad54 protein, homologous recombination is initiated but not properly terminated, leading to misrepair and chromosome loss.     

Genome Duplication Increases Meiotic Recombination Frequency: A Saccharomyces cerevisiae Model

Genetic recombination characterized by reciprocal exchange of genes on paired homologous chromosomes is the most prominent event in meiosis of almost all sexually reproductive organisms. It contributes to genome stability by ensuring the balanced segregation of paired homologs in meiosis, and it is also the major driving factor in generating genetic variation for natural and artificial selection. Meiotic recombination is subjected to the control of a highly stringent and complex regulating process and meiotic recombination frequency (MRF) may be affected by biological and abiotic factors such as sex, gene density, nucleotide content, and chemical/temperature treatments, having motivated tremendous researches for artificially manipulating MRF. Whether genome polyploidization would lead to a significant change in MRF has attracted both historical and recent research interests; however, tackling this fundamental question is methodologically challenging due to the lack of appropriate methods for tetrasomic genetic analysis, thus has led to controversial conclusions in the literature. This article presents a comprehensive and rigorous survey of genome duplication-mediated change in MRF using Saccharomyces cerevisiae as a eukaryotic model. It demonstrates that genome duplication can lead to consistently significant increase in MRF and rate of crossovers across all 16 chromosomes of S. cerevisiae, including both cold and hot spots of MRF. This ploidy-driven change in MRF is associated with weakened recombination interference, enhanced double-strand break density, and loosened chromatin histone occupation. The study illuminates a significant evolutionary feature of genome duplication and opens an opportunity to accelerate response to artificial and natural selection through polyploidization.     

GC Content and Recombination: Reassessing the Causal Effects for the Saccharomyces cerevisiae Genome

Recombination plays a crucial role in the evolution of genomes. Among many chromosomal features, GC content is one of the most prominent variables that appear to be highly correlated with recombination. However, it is not yet clear (1) whether recombination drives GC content (as proposed, for example, in the biased gene conversion model) or the converse and (2) what are the length scales for mutual influences between GC content and recombination. Here we have reassessed these questions for the model genome Saccharomyces cerevisiae, for which the most refined recombination data are available. First, we confirmed a strong correlation between recombination rate and GC content at local scales (a few kilobases). Second, on the basis of alignments between S. cerevisiae, S. paradoxus, and S. mikatae sequences, we showed that the inferred AT/GC substitution patterns are not correlated with recombination, indicating that GC content is not driven by recombination in yeast. These results thus suggest that, in S. cerevisiae, recombination is determined either by the GC content or by a third parameter, also affecting the GC content. Third, we observed long-range correlations between GC and recombination for chromosome III (for which such correlations were reported experimentally and were the model for many structural studies). However, similar correlations were not detected in the other chromosomes, restraining thus the generality of the phenomenon. These results pave the way for further analyses aimed at the detailed untangling of drives involved in the evolutionary shaping of the yeast genome.THE architecture of genomes is the result of various evolutionary forces, which can exert concerted or opposing effects. Recombination is considered to represent one such fundamental drive. Indeed, correlations with recombination were reported for a large number of structural or functional properties, such as the length of genes, the length of introns for split genes (Comeron and Kreitman 2000; Prachumwat et al. 2004), or even gene order, with the clustering of essential genes in regions of low recombination (Pal and Hurst 2003). GC content represents perhaps the most prominent property for which strong correlations with recombination were reported for the genomes of many organisms including mammals, Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae (Gerton et al. 2000; Marais et al. 2001; Birdsell 2002; Kong et al. 2002; Meunier and Duret 2004). On the other hand it was recently demonstrated that in Arabidopsis thaliana rate of crossover and GC content are not correlated (Drouaud et al. 2006). However, despite these numerous results, it is not clear as yet (1) whether recombination drives GC content or the converse and (2) what are the length scales for the correlations between GC and recombination.Correlations between recombination and GC content have been detected both at local scales [typically in the kilobase range (see Gerton et al. 2000)] and at much larger ones (Kong et al. 2002). Arguments were advanced in favor of context-dependent recombinational activities, with the idea that such activities could be regulated, at least in part, by global features of chromosome structure, characterized more or less directly by the GC content (for a general overview, see, for example, Eyre-Walker and Hurst 2001). In this direction, in terms of evolutionary models, mutual influences between recombination and GC were even considered at the highest organizational levels, with the proposal that the large-scale organization of mammalian genomes in terms of GC-rich isochores could be accounted for to a large extent by the integral of past recombinational activities (Duret et al. 2006; Duret and Arndt 2008).Regarding the causality relationship between recombination and GC, the biased gene conversion model (see Eyre-Walker 1993 for original formulations) proposes that recombination represents a driving force for GC variations, from local to genomewide scales (in terms of isochore structures). In this model a basic role is attributed to allelic gene conversions during meiotic recombination, as a consequence of the repair of mismatches in heteroduplex DNA. This process is supposed to be biased toward GC, leading to an increase of overall GC contents in regions with high recombination activity (Brown and Jiricny 1989; Eyre-Walker 1993; Galtier et al. 2001; Marais et al. 2001; Birdsell 2002). On the contrary, with analyses mainly based on the Saccharomyces cerevisiae genome, the supporters of the opposite causality model have suggested that it is rather high GC content that promotes recombination (Gerton et al. 2000; Petes 2001; Blat et al. 2002; Petes and Merker 2002).In this general background we here reassess various questions concerning the relationships between recombination and GC for the S. cerevisiae model system. Surprisingly, whereas S. cerevisiae has served as the system of choice for many of the original questions and models concerning recombination, it appears that various questions, debated notably in the context of mammalian genomes, were not further put to test in the S. cerevisiae genome for which the most accurate recombination data of any system have become recently available (Blitzblau et al. 2007; Buhler et al. 2007; Mancera et al. 2008).We first addressed the causality question at local scales, using the same approach as the one that was implemented in the case of mammalian genomes. At such scales, with the new recombination data for S. cerevisiae, we confirmed the strong correlations between GC and recombination. We then analyzed the patterns of substitutions that occurred in the S. cerevisiae strain S288C lineage under two evolutionary perspectives: (1) after the divergence between the S288C lineage and the lineage of another strain of S. cerevisiae, YJM789, and (2) after the divergence between the S. cerevisiae and the S. paradoxus lineages. The rationale behind such substitution analyses (Meunier and Duret 2004; Webster et al. 2005; Khelifi et al. 2006; Duret and Arndt 2008) is to address the possible effect of recombination on GC content, through the determination of the relative rates of AT to GC and GC to AT substitutions. On the basis of such analyses, we found that recombination is not directly correlated to the patterns of AT/GC substitutions in S. cerevisiae, which indicates that recombination has no detectable influence on GC content in this case.Beyond the local scales, we then considered the ranges of mutual influences between recombination and GC content in S. cerevisiae. We first extended the substitution analyses at significantly larger scales, to test the possibility that the local result could hide long-range correlations. Indeed, results demonstrating the effect of recombination on GC content in the human genome could be observed only at the megabase scale (Duret and Arndt 2008). In S. cerevisiae, however, we found no evidence for a significant effect of recombination on GC content at any scale. Concerning the large-scale influences, we tested then a model developed by Petes and Merker (2002), following which, in S. cerevisiae, recombinational activity at one given locus could be determined by the GC content of the surrounding region, over large distances. This model was elaborated on the basis of the analysis of chromosome III, but our results did not allow us to validate the generality of the hypothesis for all S. cerevisiae chromosomes.     

Genome shuffling在酿酒酵母菌种选育中的应用

Genome shuffling(基因组改组)作为一种新型的菌种选育方法,与常见的育种方法相比,具有快速有效、简单易行和实用性强等特点,近年来不断应用于各种工业微生物菌种的改良研究中。论述了Genome shuf-fling的产生与原理、技术过程及其在酿酒酵母中的应用和发展前景。     

5-溴脱氧尿嘧啶核苷标记酵母基因组DNA的方法

胸腺嘧啶类似物5-溴脱氧尿嘧啶核苷(BrdU)标记技术是一种研究DNA复制、修复等生命过程的有效手段。由于酿酒酵母(Saccharomyces cerevisiae)中缺少胸腺嘧啶核苷酸补救途径,胞外BrdU不能有效的渗入到基因组中,使该技术在酿酒酵母中的应用受到极大制约。通过在基因组中引入单纯疱疹病毒胞苷激酶(HSV-TK)和人类平衡核苷转运蛋白(hENT1)基因,工作建立了BrdU标记酵母基因组DNA的方法。在生长对数中期加入0.2mg/ml BrdU,离体检测法检测发现,标记3h的荧光信号较1h、5h时强;胞内检测法结果显示,标记3h时55.3%的基因组DNA中能够渗入BrdU。该工作为酿酒酵母DNA复制、修复等方面提供了直接有效的研究方法。     

D-tyrosyl-tRNA(Tyr) metabolism in Saccharomyces cerevisiae

The Saccharomyces cerevisiae YDL219w (DTD1) gene, which codes for an amino acid sequence sharing 34% identity with the Escherichia coli D-Tyr-tRNA(Tyr) deacylase, was cloned, and its product was functionally characterized. Overexpression in the yeast of the DTD1 gene from a multicopy plasmid increased D-Tyr-tRNA(Tyr) deacylase activity in crude extracts by two orders of magnitude. Upon disruption of the chromosomal gene, deacylase activity was decreased by more than 90%, and the sensitivity to D-tyrosine of the growth of S. cerevisiae was exacerbated. The toxicity of D-tyrosine was also enhanced under conditions of nitrogen starvation, which stimulate the uptake of D-amino acids. In relation with these behaviors, the capacity of purified S. cerevisiae tyrosyl-tRNA synthetase to produce D-Tyr-tRNA(Tyr) could be shown. Finally, the phylogenetic distribution of genes homologous to DTD1 was examined in connection with L-tyrosine prototrophy or auxotrophy. In the auxotrophs, DTD1-like genes are systematically absent. In the prototrophs, the putative occurrence of a deacylase is variable. It possibly depends on the L-tyrosine anabolic pathway adopted by the cell.     

Genome Destabilizing Mutator Alleles Drive Specific Mutational Trajectories in Saccharomyces cerevisiae

In addition to environmental factors and intrinsic variations in base substitution rates, specific genome-destabilizing mutations can shape the mutational trajectory of genomes. How specific alleles influence the nature and position of accumulated mutations in a genomic context is largely unknown. Understanding the impact of genome-destabilizing alleles is particularly relevant to cancer genomes where biased mutational signatures are identifiable. We first created a more complete picture of cellular pathways that impact mutation rate using a primary screen to identify essential Saccharomyces cerevisiae gene mutations that cause mutator phenotypes. Drawing primarily on new alleles identified in this resource, we measure the impact of diverse mutator alleles on mutation patterns directly by whole-genome sequencing of 68 mutation-accumulation strains derived from wild-type and 11 parental mutator genotypes. The accumulated mutations differ across mutator strains, displaying base-substitution biases, allele-specific mutation hotspots, and break-associated mutation clustering. For example, in mutants of POLα and the Cdc13–Stn1–Ten1 complex, we find a distinct subtelomeric bias for mutations that we show is independent of the target sequence. Together our data suggest that specific genome-instability mutations are sufficient to drive discrete mutational signatures, some of which share properties with mutation patterns seen in tumors. Thus, in a population of cells, genome-instability mutations could influence clonal evolution by establishing discrete mutational trajectories for genomes.     

Sporulation of Saccharomyces cerevisiae in the Absence of a Functional Mitochondrial Genome

The role of the mitochondrial system during sporulation of Saccharomyces cerevisiae was studied. Addition of ethidium bromide (EthBr) to cells growing in acetate medium resulted in the quantitative (>98%) conversion of the culture to the petite genotype in one generation. The cells were respiratory active (derepressed) but contained no mitochondrial deoxyribonucleic acid (mtDNA) as demonstrated by analytical ultracentrifugation in CsCl. When transferred to acetate sporulation medium, the culture sporulated. Ascus production was only slightly below that of the control culture. Synthesis of mtDNA occurred during sporulation in the control but not in the EthBr-treated culture. Mitochondrial protein synthesis was virtually eliminated in the EthBr-treated culture. Therefore, completely derepressed cells can sporulate without a functional mitochondrial genetic system. When partially repressed cells were treated with EthBr, no ascus formation was observed after transfer to sporulation medium. Control cultures underwent respiratory adaptation in sporulation medium and then sporulated. Extensive derepression of the respiratory system is thus required for sporulation, and this adaptation is dependent on a functional mitochondrial system. Our results suggest that once the cells are fully derepressed no mitochondrial genetic information has to be expressed during meiosis and ascus formation.     

Longevity Regulation in Saccharomyces cerevisiae: Linking Metabolism, Genome Stability, and Heterochromatin

When it was first proposed that the budding yeast Saccharomyces cerevisiae might serve as a model for human aging in 1959, the suggestion was met with considerable skepticism. Although yeast had proved a valuable model for understanding basic cellular processes in humans, it was difficult to accept that such a simple unicellular organism could provide information about human aging, one of the most complex of biological phenomena. While it is true that causes of aging are likely to be multifarious, there is a growing realization that all eukaryotes possess surprisingly conserved longevity pathways that govern the pace of aging. This realization has come, in part, from studies of S. cerevisiae, which has emerged as a highly informative and respected model for the study of life span regulation. Genomic instability has been identified as a major cause of aging, and over a dozen longevity genes have now been identified that suppress it. Here we present the key discoveries in the yeast-aging field, regarding both the replicative and chronological measures of life span in this organism. We discuss the implications of these findings not only for mammalian longevity but also for other key aspects of cell biology, including cell survival, the relationship between chromatin structure and genome stability, and the effect of internal and external environments on cellular defense pathways. We focus on the regulation of replicative life span, since recent findings have shed considerable light on the mechanisms controlling this process. We also present the specific methods used to study aging and longevity regulation in S. cerevisiae.     

Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method

The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.     

Identification of low-dye-binding (ldb) mutants of Saccharomyces cerevisiae

We have completed the identification of Saccharomyces cerevisiae genes that are defective in previously isolated ldb (low-dye-binding) mutants. This was done by complementation of the mutant's phenotype with DNA fragments from a genomic library and by running standard tests of allelism with single-gene deletion mutants of similar phenotype. The results were as follows: LDB2 is allelic to ERD1; LDB4 to SPC72; LDB5 to RLR1; LDB6 to GON7/YJL184W; LDB7 to YBL006C; LDB9 to ELM1; LDB10 to CWH36; LDB11 to COG1; LDB12 to OCH1; LDB13 to VAN1; LDB14 to BUD32; and LDB15 to PHO85. Since the precise function of some of the genes is not known, these data may contribute to the functional characterization of the S. cerevisiae genome.     

菌落PCR快速扩增工业酿酒酵母基因组DNA片段

针对工业酿酒酵母细胞破壁难和提取基因酵母组DNA费时长(2-3 h/样品)的问题,研究了SDS-微珠涡旋破壁的方法。以破壁液上清为模板进行菌落PCR扩增酿酒酵母南阳K基因组中铜抗性蛋白基因(cup1)片段和rDNA片段。结果表明,在不需要提取酵母基因组前提下,利用该方法能有效地扩增酵母基因组DNA片段,同时该方法也适用于对转基因酿酒酵母进行菌落PCR从而实现对转化子的准确和快速地鉴定筛选,是一种成本低和易于操作的适于处理大量样品的方法。