Detection, distribution and selection of microsatellites (SSRs) in the genome of the yeast Saccharomyces cerevisiae as molecular markers

Gallego, Francisco Javier; Martínez, Israel Borrajero; Hidalgo, P.

doi:10.1046/j.1472-765x.2001.01032.x

Cited by 64 publications

(59 citation statements)

References 18 publications

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“…RAPD-PCR-based analysis has been used to differentiate yeast strains and to determine the level of genetic polymorphism (3,12,18,33). Based on our previous results (15), the primers EI1 and LA1 were very efficient for strain delimitation; however, in the present study the profiles obtained for S. cerevisiae strains isolated from different distilleries were similar (Fig.…”

Section: Resultssupporting

confidence: 55%

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Biochemical and Molecular Characterization ofSaccharomyces cerevisiaeStrains Obtained from Sugar-Cane Juice Fermentations and Their Impact in Cachaça Production

Oliveira

Vicente

Fietto

et al. 2008

Appl Environ Microbiol

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Saccharomyces cerevisiae strains from different regions of Minas Gerais, Brazil, were isolated and characterized aiming at the selection of starter yeasts to be used in the production of cachaça, the Brazilian sugar cane spirit. The methodology established took into account the screening for biochemical traits desirable in a yeast cachaça producer, such as no H 2 S production, high tolerance to ethanol and high temperatures, high fermentative capacity, and the abilities to flocculate and to produce mycocins. Furthermore, the yeasts were exposed to drugs such as 5,5,5؆-trifluor-D,L-leucine and cerulenin to isolate those that potentially overproduce higher alcohols and esters. The utilization of a random amplified polymorphic DNA-PCR method with primers based on intron splicing sites flanking regions of the COX1 gene, as well as microsatellite analysis, was not sufficient to achieve good differentiation among selected strains. In contrast, karyotype analysis allowed a clear distinction among all strains. Two selected strains were experimentally evaluated as cachaça producers. The results suggest that the selection of strains as fermentation starters requires the combined use of biochemical and molecular criteria to ensure the isolation and identification of strains with potential characteristics to produce cachaça with a higher quality standard.Cachaça (pronounced "kha-sha-ssa"), the sugar cane spirit, is the most popular distilled beverage produced in Brazil. The annual production reaches 1.3 billion liters, with 15% being produced in more than 8,500 distilleries in the state of Minas Gerais.Traditional cachaça production relies on a spontaneous fermentative process that is mediated by the microbiota present in the cane juice wort and on the surface of equipments used in the productive process. It has been already demonstrated that in such systems there occurs a succession of yeasts, with Saccharomyces cerevisiae being the predominant species. Cachaça quality depends on the ecology of the microbial populations during an initial spontaneous fermentation (18,29,31,32,39). The fermentative process occurs through a continuously open fermentative process which is completed within 24 h and generally takes place from May to November, corresponding to the sugar cane harvesting period.Considering the conditions of production usually found in the cachaça distilleries, fermenting yeast populations have to face different types of stress (osmotic, high temperature, and high ethanol concentration). Besides, they might also present some characteristics such as a good fermentative power, no H 2 S production, killer activity, flocculation ability, and production of flavoring compounds. Taking all of these factors into account, we have developed a strategy to select yeast strains with appropriated characteristics to produce cachaça with potentially higher-quality standards (52). Parallel to the selection and development of S. cerevisiae strains toward ethanolic fermentations, molecular methods were developed and validated to study...

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Section: Resultssupporting

confidence: 55%

“…The forward primer of each pair was labeled with fluorescent dyes (FAM, HEX, or TET; MWG Biotech, Germany). The PCR products were amplified and analyzed in an ABI Prism 310 DNA sequencer (Applied Biosystems, Foster City, CA) and analyzed by using the corresponding Genescan software, as previously described (33,40).…”

Section: Methodsmentioning

confidence: 99%

Biochemical and Molecular Characterization ofSaccharomyces cerevisiaeStrains Obtained from Sugar-Cane Juice Fermentations and Their Impact in Cachaça Production

Oliveira

Vicente

Fietto

et al. 2008

Appl Environ Microbiol

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“…For each of them, a small amount of fresh colony was suspended in 50 l of Milli-Q water, and 7 l of this suspension was dropped on an FTA card for DNA preservation. The samples were then genotyped using 2 multiplex PCRs of 8 and 7 microsatellite loci, respectively, for mixtures 1 and 2 (see Table S3 in the supplemental material) (32)(33)(34)(35)(36)(37). Mixtures were prepared in a total volume of 84 l for 8 samples, with 50 l of 2ϫ Qiagen Multiplex PCR master mix, 15.5 l primers, and 18.5 l water.…”

Section: Methodsmentioning

confidence: 99%

Cellar-Associated Saccharomyces cerevisiae Population Structure Revealed High-Level Diversity and Perennial Persistence at Sauternes Wine Estates

Börlin

Venet

Claisse

et al. 2016

Appl Environ Microbiol

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Three wine estates (designated A, B, and C) were sampled in Sauternes, a typical appellation of the Bordeaux wine area producing sweet white wine. From those wine estates, 551 yeast strains were collected between 2012 and 2014, added to 102 older strains from 1992 to 2011 from wine estate C. All the strains were analyzed through 15 microsatellite markers, resulting in 503 unique Saccharomyces cerevisiae genotypes, revealing high genetic diversity and a low presence of commercial yeast starters. Population analysis performed using F st genetic distance or ancestry profiles revealed that the two closest wine estates, B and C, which have juxtaposed vineyard plots and common seasonal staff, share more related isolates with each other than with wine estate A, indicating exchange between estates. The characterization of isolates collected 23 years ago at wine estate C in relation to recent isolates obtained at wine estate B revealed the long-term persistence of isolates. Last, during the 2014 harvest period, a temporal succession of ancestral subpopulations related to the different batches associated with the selective picking of noble rotted grapes was highlighted. IMPORTANCEHigh genetic diversity of S. cerevisiae isolates from spontaneous fermentation on wine estates in the Sauternes appellation of Bordeaux was revealed. Only 7% of all Sauternes strains were considered genetically related to specific commercial strains. The long-term persistence (over 20 years) of S. cerevisiae profiles on a given wine estate is highlighted.

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“…Strains with identical mtDNA RFLP patterns were grouped and one representative strain was further characterised by analysis of 10 S. cerevisiae specific microsatellite loci [4,5]. The equivalent discriminatory power of mtDNA RFLP and microsatellite analysis has been previously reported [6].…”

Section: Molecular Molecular Identification Identificationmentioning

confidence: 92%

Bioinformatic approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection

et al. 2008

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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).

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Detection, distribution and selection of microsatellites (SSRs) in the genome of the yeast Saccharomyces cerevisiae as molecular markers

Abstract: The multiple analysis of microsatellites proved to be a powerful and agile tool for analysing the genome of S. cerevisiae populations.

Cited by 64 publications

References 18 publications

Biochemical and Molecular Characterization ofSaccharomyces cerevisiaeStrains Obtained from Sugar-Cane Juice Fermentations and Their Impact in Cachaça Production

Biochemical and Molecular Characterization ofSaccharomyces cerevisiaeStrains Obtained from Sugar-Cane Juice Fermentations and Their Impact in Cachaça Production

Cellar-Associated Saccharomyces cerevisiae Population Structure Revealed High-Level Diversity and Perennial Persistence at Sauternes Wine Estates

Bioinformatic approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection

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