Computational approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection
Computational approaches for the genetic and phenotypic characterization of a Saccharomyces cerevisiae wine yeast collection
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DOI：
10.1002/yea.1728
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发表时间：
2009-12-01
期刊：
影响因子：
2.6
通讯作者：
Schuller, D.
中科院分区：
文献类型：
--
作者：
Franco-Duarte, R.;Umek, L.;Schuller, D.
在这项研究中，我们已经使用了一套计算技术，涉及酿酒酵母的自然群体的基因型和表型，从11个微卫星位点的等位基因信息和24个表型测试的结果。从一个较大的S.酿酒酵母酿酒菌株的收集与自组织地图聚类。这些菌株的特征进一步关于其等位基因组合的11个微卫星和分析的表型筛选，包括分类标准（碳和氮同化试验，在不同温度下的生长）和测试与生物技术的相关性（乙醇抗性，硫化氢或芳香族前体的形成）。表型变异性相当高，每个菌株显示出独特的表型特征。生长22小时后，以光密度（A（640））表示的结果与分类学数据一致，尽管有一些例外，因为很少有菌株能够在很小程度上消耗阿拉伯糖和核糖。基于微卫星等位基因信息，朴素贝叶斯分类器正确地将大多数菌株分配（AUC = 0.81，p < 10（-8））到它们被分离的葡萄园，尽管它们的位置很近（50-100 km）。我们还鉴定了具有相似的表型特征值和微卫星等位基因模式（AUC >0.75）的菌株亚组。发现具有低乙醇抗性、在30 ℃下生长和在含有半乳糖、棉子糖或尿素的培养基中生长的菌株的亚组。结果表明，计算方法可用于建立基因型-表型关系，并对菌株的生物技术潜力进行预测。版权所有（C）2009约翰威利父子有限公司
Within this study, we have used a set of computational techniques to relate the genotypes and phenotypes of natural populations of Saccharomyces cerevisiae, using allelic information from 11 microsatellite loci and results from 24 phenotypic tests. A group of 103 strains was obtained from a larger S. cerevisiae winemaking strain collection by clustering with self-organizing maps. These strains were further characterized regarding their allelic combinations for 11 microsatellites and analysed in phenotypic screens that included taxonomic criteria (carbon and nitrogen assimilation tests, growth at different temperatures) and tests with biotechnological relevance (ethanol resistance, H2S or aromatic precursors formation). Phenotypic variability was rather high and each strain showed a unique phenotypic profile. The results, expressed as optical density (A(640)) after 22 h of growth, were in agreement with taxonomic data, although with some exceptions, since few strains were capable of consuming arabinose and ribose to a small extent. Based on microsatellite allellic information, naive Bayesian classifier correctly assigned (AUC = 0.81, p < 10(-8)) most of the strains to the vineyard from where they were isolated, despite their close location (50-100 km). We also identified subgroups of strains with similar values of a phenotypic feature and microsatellite allelic pattern (AUC >0.75). Subgroups were found for strains with low ethanol resistance, growth at 30 degrees C and growth in media containing galactose, raffinose or urea. The results demonstrate that computational approaches can be used to establish genotype-phenotype relations and to make predictions about a strain's biotechnological potential. Copyright (C) 2009 John Wiley & Sons, Ltd.