So, generally people apply 97% similarity cut-off for species/OTUs in 16S based metagenomics. As far as I know, the 97% cut-off became standard practice with full 16S sequences. However, in 16S amplicon metagenomics we usually inspect just partial 16S sequences (~200-400 bp) from some variable region. In such cases, would it not make more sense to apply a higher cut-off value for clustering. I've noticed that with our data, increasing the cut-off from 97% to 99% increases OTU count some 5-10 fold. Our samples are from deep underground, so there's little literature to go on what would be a sensible species count for a given sample, but somehow I have a feeling that e.g. 500 OTUs is more realistic than 50 OTUs. Any thoughts?
-
savetherhino.org -
What platform are you sequencing on? I would like to see other's responses to this... I am sequencing on Ion Torrent PGM and the difference between 94, 97 and 99% is significant. I believe even within species, sometimes you only have 97% identity, or less. I don't know if I agree with you about your sensible species count. It sounds like your environment (deep underground) would not be an ideal place for speciation to occur, or a diverse population to develop-- too little movement, very static environment. So I would think it would be unlikely that too many species would develop to fill such a small niche as you are looking at... but maybe I'm wrong.
-
Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?
Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating...10-14-2026, 09:55 AM -
Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.
We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing...
Comment