2.4 Sequence data processing
The raw FASTQ files were subject to a series of standard processing
including demultiplexing, read merging, quality filtering and chimeric
removal using DADA2 (version
1.20.0)(Callahan et al., 2016). A relative
abundance microbial profile was generated at the level of amplicon
sequence variant (ASV). The taxonomic information for each ASV was
determined using the Ribosomal Database Project (RDP) Classifier
(http://rdp.cme.msu.edu)(Cole
et al., 2009) with a confidence interval of 80%.
The ”Rarefy” function in the
”GuniFrac” package is used to rarefy the microbial profile to a same
sequencing depth before further statistical analyses were carried out.
All analyses were completed in R v 4.1.2.
Microbial ASVs were classified into two different categories, including
abundant and the rare taxa, according to their relative abundance and/or
frequency(Bickel & Or, 2021). Here, ASVs
with an average relative abundance of <0.01% across all
samples were defined as rare taxa, whereas the remaining ones were
defined as abundant ASVs. Notably, different criteria were used to
define abundant and rare taxa in different
studies(Jiao, Chen, & Wei, 2017;
Y. Xue et al., 2018). Since only 72 ASVs
were not rare, we classified all of them as abundant, without
considering more precise concept such as occasional taxa.
For all ASVs, indices including niche breadth and niche overlap were
calculated to see how well they may adapt to the environment. The niche
breadth was evaluated using the Levins’ standardized niche breadth
index(Feinsinger, Spears, & Poole,
1981). The niche overlap was calculated using Pianka’s niche overlap
index equation, with the value of Pianka’s index between 0 and
1(Pianka, 1974). The R package ”spaa” was
employed to calculate niche breadth and niche overlap indices.