Taylor D Lee, Walters William A, Lennon Niall J, Bochicchio James, Krohn Andrew, Caporaso J Gregory, Pennanen Taina
Department of Biology, University of New Mexico, Albuquerque, New Mexico, USA
Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA.
Appl Environ Microbiol. 2016 Nov 21;82(24):7217-7226. doi: 10.1128/AEM.02576-16. Print 2016 Dec 15.
While high-throughput sequencing methods are revolutionizing fungal ecology, recovering accurate estimates of species richness and abundance has proven elusive. We sought to design internal transcribed spacer (ITS) primers and an Illumina protocol that would maximize coverage of the kingdom Fungi while minimizing nontarget eukaryotes. We inspected alignments of the 5.8S and large subunit (LSU) ribosomal genes and evaluated potential primers using PrimerProspector. We tested the resulting primers using tiered-abundance mock communities and five previously characterized soil samples. We recovered operational taxonomic units (OTUs) belonging to all 8 members in both mock communities, despite DNA abundances spanning 3 orders of magnitude. The expected and observed read counts were strongly correlated (r = 0.94 to 0.97). However, several taxa were consistently over- or underrepresented, likely due to variation in rRNA gene copy numbers. The Illumina data resulted in clustering of soil samples identical to that obtained with Sanger sequence clone library data using different primers. Furthermore, the two methods produced distance matrices with a Mantel correlation of 0.92. Nonfungal sequences comprised less than 0.5% of the soil data set, with most attributable to vascular plants. Our results suggest that high-throughput methods can produce fairly accurate estimates of fungal abundances in complex communities. Further improvements might be achieved through corrections for rRNA copy number and utilization of standardized mock communities.
Fungi play numerous important roles in the environment. Improvements in sequencing methods are providing revolutionary insights into fungal biodiversity, yet accurate estimates of the number of fungal species (i.e., richness) and their relative abundances in an environmental sample (e.g., soil, roots, water, etc.) remain difficult to obtain. We present improved methods for high-throughput Illumina sequencing of the species-diagnostic fungal ribosomal marker gene that improve the accuracy of richness and abundance estimates. The improvements include new PCR primers and library preparation, validation using a known mock community, and bioinformatic parameter tuning.
虽然高通量测序方法正在彻底改变真菌生态学,但要获得物种丰富度和丰度的准确估计值却一直难以实现。我们试图设计内部转录间隔区(ITS)引物和一种Illumina方案,以最大限度地覆盖真菌界,同时尽量减少非目标真核生物。我们检查了5.8S和大亚基(LSU)核糖体基因的比对情况,并使用PrimerProspector评估潜在引物。我们使用分层丰度模拟群落和五个先前已表征的土壤样本测试了所得引物。尽管DNA丰度跨越3个数量级,但我们在两个模拟群落中都回收了属于所有8个成员的可操作分类单元(OTU)。预期读数和观察到的读数高度相关(r = 0.94至0.97)。然而,由于rRNA基因拷贝数的变化,几个分类群的代表性一直过高或过低。Illumina数据导致土壤样本的聚类与使用不同引物的桑格序列克隆文库数据获得的聚类相同。此外,这两种方法产生的距离矩阵的Mantel相关性为0.92。非真菌序列占土壤数据集的比例不到0.5%,大部分归因于维管植物。我们的结果表明,高通量方法可以对复杂群落中的真菌丰度进行相当准确的估计。通过对rRNA拷贝数进行校正和使用标准化模拟群落,可能会实现进一步的改进。
真菌在环境中发挥着许多重要作用。测序方法的改进为真菌生物多样性提供了革命性的见解,但要准确估计环境样本(如土壤、根系、水等)中真菌物种的数量(即丰富度)及其相对丰度仍然很难。我们提出了改进的高通量Illumina测序方法,用于物种诊断真菌核糖体标记基因,提高了丰富度和丰度估计的准确性。改进包括新的PCR引物和文库制备、使用已知模拟群落进行验证以及生物信息学参数调整。