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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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image-20240527-224247.pngImage Added

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

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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://www.nature.com/articles/s41598-023-30764-z

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Different groups of bacteria are better represented by specific regions.

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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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