Diversity measurement is important for understanding community structure and dynamics, but has been particularly challenging for microorganisms. Microbial community characterization using small subunit rRNA (SSU rRNA) gene sequences has revealed an extensive, previously unsuspected diversity that we are only now beginning to understand, especially now that advanced sequencing technologies are producing datasets containing hundreds of thousands of sequences from hundreds of samples. Efforts to quantify microbial diversity often use taxon-based methods that ignore the fact that not all species are equally related, which can therefore obscure important patterns in the data. For example, alpha-diversity (diversity within communities) is often estimated as the number of species in a community (species richness), and beta-diversity (partitioning of diversity among communities) is often based on the number of shared species. Methods for measuring alpha- and beta-diversity that account for different levels of divergence between individuals have recently been more widely applied. These methods are more powerful than taxon-based methods because microorganisms in a community differ dramatically in sequence similarity, which also often correlates with phenotypic similarity in key features such as metabolic capabilities. Consequently, divergence-based methods are providing new insights into microbial community structure and function.

中文翻译：

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物种分化和微生物多样性的测量。

多样性测量对于了解群落结构和动态非常重要，但对于微生物来说尤其具有挑战性。使用小亚基 rRNA (SSU rRNA) 基因序列进行的微生物群落表征揭示了一种广泛的、以前未曾预料到的多样性，我们现在才刚刚开始了解这种多样性，特别是现在先进的测序技术正在生成包含来自数百个样本的数十万个序列的数据集。量化微生物多样性的努力通常使用基于分类单元的方法，这些方法忽略了并非所有物种都同等相关的事实，因此可能会掩盖数据中的重要模式。例如，α-多样性（群落内的多样性）通常被估计为群落中的物种数量（物种丰富度），而β-多样性（群落之间多样性的划分）通常基于共享物种的数量。测量α和β多样性的方法最近得到了更广泛的应用，这些方法可以解释个体之间不同程度的差异。这些方法比基于分类单元的方法更强大，因为群落中的微生物在序列相似性方面存在显着差异，这通常也与代谢能力等关键特征的表型相似性相关。因此，基于分歧的方法为微生物群落结构和功能提供了新的见解。