Combining 16S rDNA and Metagenomic data

Hi QIIME2 users, we are currently working with 16S rDNA sequencing (v3-v4) to evaluate the oral microbiota, but now we are planning to shift and use metagenomic instead, but my question refers to, is there a way to combine these two approaches for a better end result?

Hi @Anders,


It’s pretty well recoganized (an open secret? A badly kept secret?) that 16S and metagenomic data give different views of the community and are compositionally different. While you’ll typically see similar arrangement in beta diversity if you apply a procrustes analysis or mantel test and compare the two communities, they’ll correlate the actual composition will be slightly different. With 16S, you tend to have primer bias and copy number variation that play a larger role. It’s pretty difficult to directly combine 16S and shotgun in my experience, they essentially become two different datasets that you need to combine and force to make sense. So, I think one question to consider is whether there’s a specific hypothesis that metagenomics answers in a way that 16S doesn’t and what the pipeline is to get there. If there isn’t a good reason to switch for this specific project, I would try to either finish it out with 16S or re-analyze everything with shotgun.

And, if I did have to combine things, GTDB has both a 16S and kraken database for annotation that might be worth looking into.