Sequence variation in dispersed repetitive sequences in Saccharomyces cerevisiae

Two new dispersed repetitive DNA sequences related to the transposable element Tyl have been isolated from the genome of Saccharomyces cerevisiae. One sequence, designated Tyl-17, is present at about six copies per haploid genome, and one copy is located approximately 1000 base-pairs from the LEU2 locus on chromosome III. Tyl-17 is about the same size as Tyl (Cameron et al., 1979) and is flanked by δ sequences, but differs from Tyl by the presence of two large substitutions representing about 50% of the sequence. Tyl and Tyl-17 are found in a ‘head-to-head’ array in at least one cloned region of the yeast genome. Another sequence, designated Tyl-161, is situated about 9000 base-pairs from the PGK locus of chromosome III, and is structurally identical to Tyl except for the presence of a 1200 base-pair insertion near one end of the sequence element.     

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.     

Genome-wide analysis of nucleotide-level variation in commonly used Saccharomyces cerevisiae strains

Ten years have passed since the genome of Saccharomyces cerevisiae-more precisely, the S288c strain-was completely sequenced. However, experimental work in yeast is commonly performed using strains that are of unknown genetic relationship to S288c. Here, we characterized the nucleotide-level similarity between S288c and seven commonly used lab strains (A364A, W303, FL100, CEN.PK, summation 1278b, SK1 and BY4716) using 25mer oligonucleotide microarrays that provide complete and redundant coverage of the approximately 12 Mb Saccharomyces cerevisiae genome. Using these data, we assessed the frequency and distribution of nucleotide variation in comparison to the sequenced reference genome. These data allow us to infer the relationships between experimentally important strains of yeast and provide insight for experimental designs that are sensitive to sequence variation. We propose a rational approach for near complete sequencing of strains related to the reference using these data and directed re-sequencing. These data and new visualization tools are accessible online in a new resource: the Yeast SNPs Browser (YSB; http://gbrowse.princeton.edu/cgi-bin/gbrowse/yeast_strains_snps) that is available to all researchers.     

Differentiation of probiotic and environmental Saccharomyces cerevisiae strains in animal feed

Aims: To establish an identification system for probiotic Saccharomyces cerevisiae strains based on artificial neural network (ANN)–assisted Fourier‐transform infrared (FTIR) spectroscopy to improve quality control of animal feed. Methods and Results: The ANN‐based system for differentiating environmental from probiotic S. cerevisiae strains comprises five authorized feed additive strains plus environmental strains isolated from different habitats. A total of 108 isolates were used as reference strains to create the ANN. DHPLC analysis and δ‐PCR were used as reference methods to type probiotic yeast isolates. The performance of the FTIR‐ANN was tested in an internal validation using unknown spectra of each reference strain. This validation step yielded a classification rate of 99·1 %. For an external validation, a test data set comprising 965 spectra of 63 probiotic and environmental S. cerevisiae isolates unknown to the ANN was used, resulting in a classification rate of 98·2 %. Conclusions: Our results demonstrate that probiotic S. cerevisiae strains in feed can be differentiated successfully from environmental isolates using both genotypic approaches and ANN‐based FTIR spectroscopy. Significance and Impact of the Study: FTIR‐based artificial neural network analysis provides a rapid and inexpensive technique for yeast identification both at the species and at the strain level in routine diagnostic laboratories, using a single sample preparation.     

Buoyant density variation during the cell cycle of Saccharomyces cerevisiae

Cell buoyant densities of the budding yeast Saccharomyces cerevisiae were determined for rapidly growing asynchronous and synchronous cultures by equilibrium sedimentation in Percoll gradients. The average cell density in exponentially growing cultures was 1.1126 g/ml, with a range of density variation of 0.010 g/ml. Densities were highest for cells with buds about one-fourth the diameter of their mother cells and lowest when bud diameters were about the same as their mother cells. In synchronous cultures inoculated from the least-dense cells, there was no observable perturbation of cell growth: cell numbers increased without lag, and the doubling time (66 min) was the same as that for the parent culture. Starting from a low value at the beginning of the cycle, cell buoyant density oscillated between a maximum density near midcycle (0.4 generations) and a minimum near the end of the cycle (0.9 generations). The pattern of cyclic variation of buoyant density was quantitatively determined from density measurements for five cell classes, which were categorized by bud diameter. The observed variation in buoyant density during the cell cycle of S. cerevisiae contrasts sharply with the constancy in buoyant density observed for cells of Escherichia coli, Chinese hamster cells, and three murine cell lines.     

Effect of environmental stress on radiation response of Saccharomyces cerevisiae

We have investigated the effect of pH shock and oxidative stress (H2O2 effect) both separately and together on the response of Saccharomyces cerevisiae exposed to UV and gamma radiations for one hour. Exposure to these environmental stresses resulted in S. cerevisiae cells acquiring resistance to UV radiation. Presence of cycloheximide (a known protein synthesis inhibitor) during stress inhibited the acquired UV resistance. The increased UV resistance is apparently mediated through nucleotide excision repair as the stress exposure to rad3 mutants (defective in nucleotide excision repair) do not have any effect on UV response. Both types of stresses used probably follow the same path of induction of radioresistance as the effect of both of them is nonadditive. In the strains used in our study stress exposure does not have any significant effect on gamma radiation response.     

Information propagation within the Genetic Network of Saccharomyces cerevisiae

Background  

A gene network's capacity to process information, so as to bind past events to future actions, depends on its structure and logic. From previous and new microarray measurements in Saccharomyces cerevisiae following gene deletions and overexpressions, we identify a core gene regulatory network (GRN) of functional interactions between 328 genes and the transfer functions of each gene. Inferred connections are verified by gene enrichment.     

Genomic instability is associated with natural life span variation in Saccharomyces cerevisiae

Increasing genomic instability is associated with aging in eukaryotes, but the connection between genomic instability and natural variation in life span is unknown. We have quantified chronological life span and loss-of-heterozygosity (LOH) in 11 natural isolates of Saccharomyces cerevisiae. We show that genomic instability increases and mitotic asymmetry breaks down during chronological aging. The age-dependent increase of genomic instability generally lags behind the drop of viability and this delay accounts for approximately 50% of the observed natural variation of replicative life span in these yeast isolates. We conclude that the abilities of yeast strains to tolerate genomic instability co-vary with their replicative life spans. To the best of our knowledge, this is the first quantitative evidence that demonstrates a link between genomic instability and natural variation in life span.     

Saccharomyces cerevisiae

Yeast prions are infectious proteins that spread exclusively by mating. The frequency of prions in the wild therefore largely reflects the rate of spread by mating counterbalanced by prion growth slowing effects in the host. We recently showed that the frequency of outcross mating is about 1% of mitotic doublings with 23–46% of total matings being outcrosses. These findings imply that even the mildest forms of the [PSI+], [URE3] and [PIN+] prions impart > 1% growth/survival detriment on their hosts. Our estimate of outcrossing suggests that Saccharomyces cerevisiae is far more sexual than previously thought and would therefore be more responsive to the adaptive effects of natural selection compared with a strictly asexual yeast. Further, given its large effective population size, a growth/survival detriment of > 1% for yeast prions should strongly select against prion-infected strains in wild populations of Saccharomyces cerevisiae.     

Natural isolates of Saccharomyces cerevisiae display complex genetic variation in sporulation efficiency

Sporulation is a well-studied process executed with varying efficiency by diverse yeast strains. We developed a high-throughput method to quantify yeast sporulation efficiency and used this technique to analyze a line cross between a high-efficiency oak tree isolate and a low-efficiency wine strain. We find that natural variation in sporulation efficiency mirrors natural variation in higher eukaryotes: it shows divergence between isolated populations, arises from loci of major effect, and exhibits epistasis. We show that the lower sporulation efficiency of the wine strain results from a failure to initiate sporulation, rather than from slower kinetics of meiosis and spore formation. The two strains differentially regulate many genes involved in aerobic respiration, an essential pathway for sporulation, such that the oak tree strain appears better poised to generate energy from this pathway. We also report that a polymorphism in RME1 that affects sporulation efficiency in laboratory strains also cosegregates with significant phenotypic differences in our cross of natural isolates. These results lay the groundwork for the study of variation in sporulation efficiency among natural isolates of yeast.     

Isothermic variation of the specific growth rate of Saccharomyces cerevisiae in batch culture

The specific growth rate () of a respiration-deficient mutant of Saccharomyces cerevisiae growing under defined experimental conditions in batch culture (mineral medium plus glucose and vitamins at 25°C) varied from experiment to experiment over a wide range (0.10–0.24 h^-1) and showed a normal distribution. Neither the age of the culture, the history of the inoculum, nor experimental error accounted wholy for the variability of . The variation was positively correlated with the specific rate of glucose transfer and negatively with the specific rate of production of non-fermentative CO₂. The yield decreased with implying higher maintenance requirements in batch culture (4.7 mmoles g^-1 h^-1) than in continuous culture (0.8 mmoles g^-1 h^-1). It was concluded that the strain is capable of establishing any one of several steady states of growth under the same experimental conditions, each steady state displaying some buildin inertia with respect to change. The variations of the specific rates of glucose transfer and non-fermentative CO₂ production, and of the yield appeared to be consequences rather than causes of the variation of . The ultimate causes of the variation of remained unidentified.Part of a doctoral thesis submitted by J. Martinez-Peinado to the University of Navarra Spain     

G+C content variation along and among Saccharomyces cerevisiae chromosomes.

Past analyses of the genome of the yeast Saccharomyces cerevisiae have revealed substantial regional variation in G+C content. Important questions remain, though, as to the origin, nature, significance, and generality of this variation. We conducted an extensive analysis of the yeast genome to try to answer these questions. Our results indicate that open reading frames (ORFs) with similar G+C contents at silent codon positions are significantly clustered on chromosomes. This clustering can be explained by very short range correlations of silent-site G+C contents at neighboring ORFs. ORFs of high silent-site G+C content are disproportionately concentrated on shorter chromosomes, which causes a negative relationship between chromosome length and G+C content. Contrary to previous reports, there is no correlation between gene density and silent-site G+C content in yeast. Chromosome III is atypical in many regards, and possible reasons for this are discussed.     

Strain-dependent variation in carbon source regulation of nucleus-encoded mitochondrial proteins of Saccharomyces cerevisiae.

Nuclear genes encoding mitochondrial proteins are regulated by carbon source with significant heterogeneity among four Saccharomyces cerevisiae strains. This strain-dependent variation is seen both in respiratory capacity of the cells and in the expression of beta-galactosidase reporter fusions to the promoters of CYB2, CYC1, CYC3, MnSOD, and RPO41.