http://precedings.nature.com/tags/yeast Recently posted documents tagged with 'yeast' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3636.1 The contradiction between the long-term persistence of the chromosomal hotspots that initiate meiotic recombination and the self-destructive mechanism by which they act strongly suggests that our understanding of recombination is incomplete. To investigate the requirements for hotspot persistence, Rosemary Redfield and I developed a computer simulation model, hotspot, of their activity and its evolutionary consequences. http://dx.doi.org/10.1038/npre.2009.3636.1 Fri, 21 Aug 2009 20:17:03 UTC The joys and perils of recombination – The hotspot conversion paradox and the evolution of recombination doi:10.1038/npre.2009.3636.1 2009-08-21 Mario Pineda-Krch Nature Precedings 2009-08-21T20:17:03Z Presentation Genetics & Genomics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3637.1 The contradiction between the long-term persistence of the chromosomal hotspots that initiate meiotic recombination and the self-destructive mechanism by which they act strongly suggests that our understanding of recombination is incomplete. This “hotspot paradox” has been reinforced by the finding that biased gene conversion also removes active hotspots from human sperm. To investigate the requirements for hotspot persistence, we developed a detailed computer simulation model of their activity and its evolutionary consequences. With this model, unopposed hotspot activity could drive strong hotspots from 50% representation to extinction within 70 generations. Although the crossing over that hotspots cause can increase population fitness, this benefit was always too small to slow the loss of hotspots. Hotspots could not be maintained by plausible rates of de novo mutation, nor by crossover interference, which alters the frequency and/or spacing of crossovers. Competition among hotspots for activity-limiting factors also did not prevent their extinction, although the rate of hotspot loss was slowed. Key factors were the probability that the initiating hotspot allele is destroyed and the nonmeiotic contributions hotspots make to fitness. Experimental investigation of these deserves high priority, because until the paradox is resolved all components of the mechanism are open to doubt. http://dx.doi.org/10.1038/npre.2009.3637.1 Tue, 18 Aug 2009 20:29:58 UTC The hotspot conversion paradox doi:10.1038/npre.2009.3637.1 2009-08-18 Mario Pineda-Krch Nature Precedings 2009-08-18T20:29:58Z Presentation Genetics & Genomics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2311/version/1 BackgroundHigh throughput yeast functional genomics experiments are revealing associations among tens to hundreds of genes using numerous experimental conditions. To fully understand how the identified genes might be involved in the observed system, it is essential to consider the widest range of biological annotation possible. Biologists often start their search by collating the annotation provided for each protein within databases such as the Saccharomyces Genome Database, manually comparing them for similar features, and empirically assessing their significance. Such tasks can be automated, and more precise calculations of the significance can be determined using established probability measures. ResultsWe developed Yeast Features, an intuitive online tool to help establish the significance of finding a diverse set of shared features among a collection of yeast proteins. A total of 18,786 features from the Saccharomyces Genome Database are considered, including annotation based on the Gene Ontology’s molecular function, biological process and cellular compartment, as well as conserved domains, protein-protein and genetic interactions, complexes, metabolic pathways, phenotypes and publications. The significance of shared features is estimated using a hypergeometric probability, but novel options exist to improve the significance by adding background knowledge of the experimental system. For instance, increased statistical significance is achieved in gene deletion experiments because interactions with essential genes will never be observed. We further demonstrate the utility by suggesting the functional roles of the indirect targets of an aminoglycoside with a known mechanism of action, and also the targets of an herbal extract with a previously unknown mode of action. The identification of shared functional features may also be used to propose novel roles for proteins of unknown function, including a role in protein synthesis for YKL075C.ConclusionsYeast Features (YF) is an easy to use web-based application (http://software.dumontierlab.com/yeastfeatures/) which can identify and prioritize features that are shared among a set of yeast proteins. This approach is shown to be valuable in the analysis of complex data sets, in which the extracted associations revealed significant functional relationships among the gene products. http://precedings.nature.com/documents/2311/version/1 Fri, 19 Sep 2008 02:00:35 UTC Yeast Features: Identifying Significant Features Shared Among Yeast Proteins for Functional Genomics hdl:10101/npre.2008.2311.1 2008-09-19 Michel Dumontier Nature Precedings 2008-09-19T02:00:35Z Manuscript Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2288.1 The objective of the present study was to compare genetic and phenotypic variation of 103 Saccharomyces cerevisiae strains isolated from winemaking environments. We used bioinformatics approaches to identify genetically similary strains with specific phenotypes and to estimate a strain’s biotechnological potential. A S. cerevisiae collection, comprising 440 strains that were obtained from winemaking environments in Portugal has been constituted during the last years. All strains were genetically characterized by a set of eleven highly polymorphic microsatellites and showed unique allelic combinations. Using neural networks, a subset of 103 genetically most diverse strains was chosen for phenotypic analysis, that included growth in synthetic must media at various temperatures, utilization of carbon sources (glucose, ribose, arabinose, xylose, saccharose, galactose, rafinose, maltose, glycerol, potassium acetate and pyruvic acid), growth in ethanol containing media, evaluation of osmotic and oxidative stress resistance, H2S production and utilization of different nitrogen sources. Using supervised data mining approaches we have found that genotype represented with presence/absence of eleven microsatellites relates well with geographical location (performance evaluation using leave-out-out technique resulted in high performance scores; e.g., area under ROC curve was above 0.8 for a number of standard machine learning approaches tested). To find relations between phenotypes and genotypes, we used a two-step approach which first hierarchically clusters the strains according to their phenotype, and then tests if the resulting sub-clusters are identifiable using strain’s genetic data. Several groups of strains with similar phenotype profiles and common features in genotype were identified this way, and they are subject to further investigations. Financially supported by the programs POCI 2010 (FEDER/FCT, POCTI/AGR/56102/2004) and AGRO (ENOSAFE, Nº 762). http://dx.doi.org/10.1038/npre.2008.2288.1 Thu, 11 Sep 2008 22:17:00 UTC Bioinformatic approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection doi:10.1038/npre.2008.2288.1 2008-09-11 Dorit Schuller Nature Precedings 2008-09-11T22:17:00Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2182.1 Epistatic or genetic interactions, representing the effects of mutations on the phenotypes caused by other mutations, can be very helpful for uncovering functional relationships between genes. Recently, the Epistasis Miniarray Profile (E-MAP) method has emerged as a powerful approach for identifying such interactions systematically. As part of this approach, hierarchical clustering is used to partition genes into groups on the basis of the similarity between their global interaction profiles. Here we present an original biclustering algorithm for identifying groups of functionally related genes from E-MAP data in a manner that allows individual genes to be assigned to more than one functional group. This enables investigation of the pleiotropic nature of gene function, a goal that cannot be achieved with hierarchical clustering. The performance of our algorithm is illustrated by applying it to two E-MAP datasets and an E-MAP-like in silico dataset for the yeast S. cerevisiae. In addition to identifying the majority of the functional modules reported in these studies, our algorithm uncovers many recently documented and novel multi-functional relationships between genes and gene groups. http://dx.doi.org/10.1038/npre.2008.2182.1 Thu, 14 Aug 2008 21:45:30 UTC Analysis of Genetic Interaction Maps Reveals Functional Pleiotropy doi:10.1038/npre.2008.2182.1 2008-08-14 Shuye Pu Nature Precedings 2008-08-14T21:45:30Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2067/version/1 High throughput methods to measure protein-protein interactions will facilitate uncovering pairs of unknown interactions as well as designing new interactions. We have developed a platform to detect protein interactions on the surface of yeast, where one protein (bait) is covalently anchored to the cell wall and the other (prey) is expressed in secretory form. The prey is released either outside of the cells or remains on the cell surface by its binding to the bait. The strength of their interaction is measured by antibody binding to the epitope tag fused to the prey or direct readout of split fluorescence protein complementation. Our novel ‘yeast surface 2-hybrid’ system was found to differentiate 6-log difference in binding affinities between coiled coil associations and to measure specific interactions of antibodies and antigens. We demonstrate the use of YS2H in exploring activation allostery in integrins and isolating heavy chain only antibodies against botulinum neurotoxin. http://precedings.nature.com/documents/2067/version/1 Fri, 11 Jul 2008 09:17:25 UTC Yeast surface 2-hybrid to detect protein-protein interactions via the secretory pathway as a platform for antibody discovery hdl:10101/npre.2008.2067.1 2008-07-11 Moonsoo M. Jin Nature Precedings 2008-07-11T09:17:25Z Manuscript Biotechnology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1988/version/1 The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker’s yeast, Saccharomyces cerevisiae, and its closest relative, the wild S. paradoxus, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. S. paradoxus populations are well delineated along geographic boundaries while the variation among worldwide S. cerevisiae isolates show less differentiation and is comparable to a single S. paradoxus population. Rather than one or two domestication events leading to the extant baker’s yeasts, the population structure of S. cerevisiae shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation. http://precedings.nature.com/documents/1988/version/1 Fri, 20 Jun 2008 15:24:32 UTC Population genomics of domestic and wild yeasts hdl:10101/npre.2008.1988.1 2008-06-20 Edward Louis Nature Precedings 2008-06-20T15:24:32Z Manuscript Ecology Genetics & Genomics Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1543/version/1 The association between transcription and DNA repair is acknowledged as a player in the generation of mutations in a non-random fashion in prokaryotes and eukaryotes. Previous studies demonstrated that the transcription complex is capable of directing DNA repair to sites of transcription. This process is especially important to growth-arrested cells, in which many DNA repair capacities are diminished; it may also lead to mutations preferentially in transcribed genes. Using microarray analysis of growth-arrested yeast cultures, we demonstrated on a genomic scale, the co-localization of a DNA-turnover marker, indicative of DNA-repair-associated DNA synthesis, with genes persistently transcribed during stationary phase. This may serve as a clue regarding the non-random manner in which non-dividing cells may potentially mutate in the absence of replication, solely as a result of their inherent, transcriptional stress response. http://precedings.nature.com/documents/1543/version/1 Mon, 28 Jan 2008 15:35:26 UTC A Genome-Wide Analysis Reveals Significant Overlap of Transcription and DNA Repair in Stationary Phase Yeast hdl:10101/npre.2008.1543.1 2008-01-28 Aviv de Morgan Nature Precedings 2008-01-28T15:35:26Z Manuscript Genetics & Genomics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/