Estimating intraspecific genetic diversity from community DNA metabarcoding data
Estimating intraspecific genetic diversity from community DNA metabarcoding data
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DOI：
10.7717/peerj.4644
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发表时间：
2018-04-09
期刊：
影响因子：
2.7
通讯作者：
Leese, Florian
中科院分区：
文献类型：
--
作者：
Elbrecht, Vasco;Vamos, Ecaterina Edith;Leese, Florian
背景：DNA元条形码被用于生成整个群落的物种组成数据。然而，高通量测序仪器中的测序错误是相当常见的，通常需要将读段聚类到操作分类单元（OTU）中，从而在该过程中丢失关于种内多样性的信息。虽然细胞色素c氧化酶亚基I（COI）I单倍型的信息是有限的，在解决种内多样性，但它往往是有用的，例如在一个地理环境，有助于制定假设分类群的分布和dispersion.Methods：本研究结合序列去噪策略，通常应用于微生物的研究，额外的丰度为基础的过滤提取单倍型信息从淡水大型无脊椎动物metabarcoding数据集。这种新的方法被添加到R包JAMP”中，并且可以应用于COI扩增子数据集。我们测试了我们的单倍型测序方法（i）一个单一物种的模拟社区组成的31个人，15个不同的单倍型跨越三个数量级的生物量和（ii）18个监测样品，每个扩增与四个不同的引物集和两个PCR replications.Results：我们检测到所有15个单倍型的模拟社区中的单一标本与宽松的过滤和去噪设置。然而，在两次重复中仍有多达480个额外的非预期单倍型。严格过滤去除了大多数意想不到的单倍型，但也可以丢弃主要来自小样本的预期单倍型。在监测样品中，不同引物组检测到177-200个OTU，每个OTU平均含有2.40-3.30个单倍型。衍生的种内多样性数据表明，重复之间的一致性和相似的引物对之间的人口结构，但分辨率取决于引物长度。仔细观察数据集中丰富的分类群，可以发现不同的种群遗传模式，例如石蛾Taeniopteryx nebulosa和石蛾Hydropsyche pellucidula在单倍型分布方面表现出明显的南北向倾向，而甲虫Oulimnius tuberculatus和等足类Asellus aquaticus没有显示出明确的种群模式，但遗传多样性不同。我们开发了一种策略来推断种内遗传多样性从散装无脊椎动物元基因编码数据。需要强调的是，在这一点上，由于样本大小的变化、引物偏倚和低丰度序列变异的丢失，这种元条形码信息的单倍型分型不能捕获这些样本中存在的全部多样性。然而，对于大量的物种种内多样性恢复，确定潜在的孤立的人口和类群，进一步更详细的地理分布调查。虽然我们目前缺乏大规模的metabarcoding数据集来充分利用我们的新方法，但metabarcoding-informed haplotyping具有很大的希望或生物监测工作，不仅寻求有关物种多样性的信息，还寻求潜在的遗传多样性。
Background: DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high-throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTUs), losing information on intraspecific diversity in the process. While Cytochrome c oxidase subunit I (COI) Ihaplotype information is limited in resolving intraspecific diversity it is nevertheless often useful e.g. in a phylogeographic context, helping to formulate hypotheses on taxon distribution and dispersal.Methods: This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotype information from freshwater macroinvertebrate metabarcoding datasets. This novel approach was added to the R package JAMP" and can be applied to COI amplicon datasets. We tested our haplotyping method by sequencing (i) a single-species mock community composed of 31 individuals with 15 different haplotypes spanning three orders of magnitude in biomass and (ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates.Results: We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177-200 OTUs, each containing an average of 2.40-3.30 haplotypes per OTU. The derived intraspecific diversity data showed population structures that were consistent between replicates and similar between primer pairs but resolution depended on the primer length. A closer look at abundant taxa in the dataset revealed various population genetic patterns, e.g. the stonefly Taeniopteryx nebulosa and the caddisfly Hydropsyche pellucidula showed a distinct north south cline with respect to haplotype distribution, while the beetle Oulimnius tuberculatus and the isopod Asellus aquaticus displayed no clear population pattern but differed in genetic diversity.Discussion: We developed a strategy to infer intraspecific genetic diversityfrom bulk invertebrate metabarcoding data. It needs to be stressed that at this point this metabarcoding-informed haplotyping is not capable of capturing the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and taxa for further more detailed phylogeographic investigation. While we are currently,' lacking large-scale metabarcoding datasets to fully take advantage f f our new approach, metabarcoding-informed haplotyping holds great promise or biomonitoring efforts that not only seek information about species diversity but also underlying genetic diversity.