背景:DNA元编码应用高通量测序方法从混合样品池中生成大量DNA条形码,用于大量物种鉴定和群落表征。迄今为止,然而,大多数元编码研究采用第二代测序平台,如Illumina,这是由短的读取长度和较长的周转时间的限制。虽然诸如MinION(牛津纳米孔技术)之类的第三代平台可以对更长的读数甚至实时进行排序,可能由于相对较高的读取错误率以及用于处理此类读取的专用软件的缺乏,这些平台用于元编码的应用仍然有限。
结果:我们通过执行基于纳米孔的方法表明情况不再如此,细胞色素C氧化酶亚基I(COI)在34个浮游动物散装样品上的代谢编码,并将结果与常规IlluminaMiSeq测序进行基准测试。纳米孔R10.3测序化学和超精确(SUP)碱基判定模型将原始读取错误率降低到约4%,和使用amplicon_sorter的共识调用(没有进一步的纠错)生成的元条形码错误≤1%。尽管Illumina恢复了比纳米孔测序更多的分子操作分类单位(MOTU)(589vs.471),我们发现测序平台之间推断的浮游动物群落没有显着差异。重要的是,Illumina和纳米孔之间的444个共享MOTU中的406个(91.4%)也被发现没有插入错误,测序仅12-15小时,就可以恢复85%的浮游动物丰富度。
结论:我们的结果表明,纳米孔测序可以产生具有Illumina-like准确性的元条形码,我们是第一个研究表明纳米孔元码几乎总是无内德尔的。我们还表明,纳米孔代谢编码对于快速表征物种丰富的群落是可行的,并且无论使用何种测序平台,都可以获得相同的生态结论。总的来说,我们的研究激发了人们对纳米孔测序的信心,并为纳米孔技术在各种元编码应用中的更大利用铺平了道路.
BACKGROUND: DNA metabarcoding applies high-throughput sequencing approaches to generate numerous DNA barcodes from mixed sample pools for mass species identification and community characterisation. To date, however, most metabarcoding studies employ second-generation sequencing platforms like Illumina, which are limited by short read lengths and longer turnaround times. While third-generation platforms such as the MinION (Oxford Nanopore Technologies) can sequence longer reads and even in real-time, application of these platforms for metabarcoding has remained limited possibly due to the relatively high read error rates as well as the paucity of specialised software for processing such reads.
RESULTS: We show that this is no longer the case by performing nanopore-based, cytochrome c oxidase subunit I (COI) metabarcoding on 34 zooplankton bulk samples, and benchmarking the results against conventional Illumina MiSeq sequencing. Nanopore R10.3 sequencing chemistry and super accurate (SUP) basecalling model reduced raw read error rates to ~ 4%, and
consensus calling with amplicon_sorter (without further error correction) generated metabarcodes that were ≤ 1% erroneous. Although Illumina recovered a higher number of molecular operational taxonomic units (MOTUs) than nanopore sequencing (589 vs. 471), we found no significant differences in the zooplankton communities inferred between the sequencing platforms. Importantly, 406 of 444 (91.4%) shared MOTUs between Illumina and nanopore were also found to be free of indel errors, and 85% of the zooplankton richness could be recovered after just 12-15 h of sequencing.
CONCLUSIONS: Our results demonstrate that nanopore sequencing can generate metabarcodes with Illumina-like accuracy, and we are the first study to show that nanopore metabarcodes are almost always indel-free. We also show that nanopore metabarcoding is viable for characterising species-rich communities rapidly, and that the same ecological conclusions can be obtained regardless of the sequencing platform used. Collectively, our study inspires confidence in nanopore sequencing and paves the way for greater utilisation of nanopore technology in various metabarcoding applications.