Quantifying separation and similarity in a Saccharomyces cerevisiae metapopulation.
Quantifying separation and similarity in a Saccharomyces cerevisiae metapopulation.
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DOI：
10.1038/ismej.2014.132
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发表时间：
2015-02
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影响因子：
--
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真核微生物是关键的生态系统驱动因素;然而，我们几乎没有理论和数据来阐明影响其观察到的种群模式的过程。在这里，我们提供了一个深入的定量分析的人口分离和相似性的酵母酿酒酵母的目的是提供一个更详细的说明发生在微生物的人口过程。从新西兰1000公里范围内的6个主要地区的原生植物、葡萄园和自然发酵的水果中收集了10000多个分离株。从这些，数以百计的S。获得了酿酒酵母的基因型，并使用一套分析方法，我们提供了全面的定量估计人口结构和基因流或迁移率。在地理区域内没有发现遗传分化，即使是居住在原始森林和葡萄园的种群之间也是如此。然而，我们确实揭示了一幅全国人口结构的图景，其规模超过100公里，其中较偏远的纳尔逊和奥塔哥中部地区的人口特征主要对此做出了贡献。此外，观察到区域人口之间的连通性程度不同，并与新西兰葡萄酒行业的水果运动相关。这表明一些人为的影响，这些观察到的人口格局。
Eukaryotic microbes are key ecosystem drivers; however, we have little theory and few data elucidating the processes influencing their observed population patterns. Here we provide an in-depth quantitative analysis of population separation and similarity in the yeast Saccharomyces cerevisiae with the aim of providing a more detailed account of the population processes occurring in microbes. Over 10 000 individual isolates were collected from native plants, vineyards and spontaneous ferments of fruit from six major regions spanning 1000 km across New Zealand. From these, hundreds of S. cerevisiae genotypes were obtained, and using a suite of analytical methods we provide comprehensive quantitative estimates for both population structure and rates of gene flow or migration. No genetic differentiation was detected within geographic regions, even between populations inhabiting native forests and vineyards. We do, however, reveal a picture of national population structure at scales above ∼100 km with distinctive populations in the more remote Nelson and Central Otago regions primarily contributing to this. In addition, differential degrees of connectivity between regional populations are observed and correlate with the movement of fruit by the New Zealand wine industry. This suggests some anthropogenic influence on these observed population patterns.
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影响因子：
3.3
作者：
Francesca, Nicola;Canale, Domenica E.;Moschetti, Giancarlo
通讯作者：
Moschetti, Giancarlo
影响因子：
4.8
作者：
Goddard, Matthew R.
通讯作者：
Goddard, Matthew R.
影响因子：
5.1
作者：
Goddard, Matthew R.;Anfang, Nicole;Jun, Casey
通讯作者：
Jun, Casey
影响因子：
2.4
作者：
de Melo Pereira, G. V.;Ramos, C. L.;Schwan, R. F.
通讯作者：
Schwan, R. F.
影响因子：
5.8
作者：
Beerli, P
通讯作者：
Beerli, P