Application of Multi Locus Sequence Typing to the analysis of the biodiversity of indigenous Saccharomyces cerevisiae wine yeasts from Lebanon

被引：0
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作者：
Ayoub, M.-J. [1 ,2 ]
Legras, J.-L. [3 ]
Saliba, R. [2 ]
Gaillardin, C. [1 ,4 ]
机构：
[1] Collection de Levures d'Intérêt Biotechnologique, UMR INA-PG-INRA-CNRS Microbiologie Génétique Moléculaire, INA-PG, Thiverval-Grignon, France
[2] Département des Sciences et Technologies Agroalimentaires, Université Libanaise, Faculté d'Agronomie, Chouran, Beyrouth, Lebanon
[3] Santé de la Vigne et Qualité du Vin, UMR INRA-Université, Louis Pasteur Strasbourg-I, Colmar, France
[4] INA-PG, Microbiologie Génétique Moléculaire, F-78850 Thiverval-Grignon, France
来源：
Journal of Applied Microbiology | 2006年 / 100卷 / 04期
关键词：
Aims: To assess suitability of Multi Locus Sequence Typing (MLST) for investigating the biodiversity of wine yeast strains. This method was compared with established ones like microsatellite analysis or amplification of genomic regions flanked by repeated (delta) elements. Methods and Results: DNA fragments were amplified and sequenced for 26 loci representing housekeeping genes; open reading frames (ORFs) of unknown functions or intergenic regions. A set of seven loci was tested on 84 Saccharomyces cerevisiae strains; including 65 strains isolated from traditional wineries in Lebanon; commercial wine strains and Asian isolates. An overall sequence diversity of 2.05% was observed; consisting of single nucleotide polymorphisms; 60% of them occurring in a heterozygous state. The number of polymorphic sites per locus varied between 4 and 14. The same set of strains was analysed by microsatellite typing on six polymorphic loci and by interdelta amplification. Conclusions: Clustering of MLST profiles clearly differentiated the Asian group of strains from Lebanese and European commercial strains that appear closely related. The current MLST scheme appears less discriminatory (92.27%) on closely related wine yeasts than microsatellite or interdelta typing (>99%). Significance and Impact of the Study: MLST is a highly reliable method for relatedness inference and promising for wine yeast typing. © 2006 The Society for Applied Microbiology;
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页码：699 / 711
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