Article ; Online: Haplotype-level metabarcoding of freshwater macroinvertebrate species: A prospective tool for population genetic analysis.
2023 Volume 18, Issue 7, Page(s) e0289056
Abstract: Metabarcoding is a molecular-based tool capable of large quantity high-throughput species identification from bulk samples that is a faster and more cost-effective alternative to conventional DNA-sequencing approaches. Still, further exploration and ... ...
| Abstract | Metabarcoding is a molecular-based tool capable of large quantity high-throughput species identification from bulk samples that is a faster and more cost-effective alternative to conventional DNA-sequencing approaches. Still, further exploration and assessment of the laboratory and bioinformatics strategies are required to unlock the potential of metabarcoding-based inference of haplotype information. In this study, we assessed the inference of freshwater macroinvertebrate haplotypes from metabarcoding data in a mock sample. We also examined the influence of DNA template concentration and PCR cycle on detecting true and spurious haplotypes. We tested this strategy on a mock sample containing twenty individuals from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. We recovered fourteen zero-radius operational taxonomic units (zOTUs) of 421-bp length, with twelve zOTUs having a 100% match with the Sanger haplotype sequences. High-quality reads relatively increased with increasing PCR cycles, and the relative abundance of each zOTU was consistent for each cycle. This suggests that increasing the PCR cycles from 24 to 64 did not affect the relative abundance of each zOTU. As metabarcoding becomes more established and laboratory protocols and bioinformatic pipelines are continuously being developed, our study demonstrated the method's ability to infer intraspecific variability while highlighting the challenges that must be addressed before its eventual application for population genetic studies. |
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| MeSH term(s) | Humans ; Haplotypes ; Computational Biology ; Fresh Water ; Genetics, Population ; DNA |
| Chemical Substances | DNA (9007-49-2) |
| Language | English |
| Publishing date | 2023-07-24 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2267670-3 |
| ISSN | 1932-6203 ; 1932-6203 |
| ISSN (online) | 1932-6203 |
| ISSN | 1932-6203 |
| DOI | 10.1371/journal.pone.0289056 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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