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Amplicon | Whole genome | |
|---|---|---|
Dataset size | Very small | Medium to very large |
Computational resources | Small | Medium to very large |
Price | Low | Medium to high |
Taxonomic resolution | Mostly genus | Species or strain |
Functional analysis | Limited | Greater detail |
Database curation | Detailed | Minimal |
Taxonomic coverage | Specific (e.g. 16s = bacteria) | All taxa |
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Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing
Our study demonstrates that whole genome shotgun sequencing has multiple advantages compared with the 16S amplicon method including enhanced detection of bacterial species, increased detection of diversity and increased prediction of genes. In addition, increased length, either due to longer reads or the assembly of contigs, improved the accuracy of species detection.
Full length amplicon vs hypervariable regions
Typically The 16S rRNA gene is about 1,500 bases in length. Illumina reads are much shorter than this, therefore amplicon analysis typically involves sequencing 2-3 ‘hypervariable’ 16S regions.
https://nf-co.re/ampliseq/2.9.0/docs/usage#taxonomic-classificationwww.nature.com/articles/s41598-023-30764-z
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Different groups of bacteria are better represented by specific regions.
With the development of 3rd generation long read sequencing, such as Nanopore and PacBio, the full 16S length can be sequenced. This reduces bias and improves taxonomic resolution.
https://www.nature.com/articles/s41598-020-80826-9
NOTE: For eukaryotic (e.g. fungi) metagenomic amplicon sequencing, ITS (Internal transcribed spacer) regions are used.
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https://data.eresearchqut.net/paulw/public/mahsa_manuscript2/index.html
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The OTU method typically can identify 97% similarity (with any accuracy) whereas the ASV method can identify even single base-pair differences. This enables a finer resolution of taxa down to the genus and species level. Note that there is increasing ‘fuzziness’ toward the lower taxonomic levels, as the diversity within some taxa is greater than the diversity between this and other taxa (in other words, even with ASV, not all taxa can be resolved to lower taxonomic levels and this is highly depedant dependent on the taxonomic group involved).
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It’s important to note that a significant difference between 2nd and 3rd generation technology is accuracy. The error rate (i.e. the number of bases with low sequencing quality scores) of 3nd 3rd gen has been considerably higher than 2nd gen, with typically ~0.1% error rate for Illumina sequences and >5% error rate for Nanopore. The Nanopore error rate has improved dramatically in recent years though, but still is considerably lower than Illumina. This higher error rate can cause issues, such as in metagenomics when identifying species that differ by a small number of base pairs.
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