Supplementary text
Overview of sequencing statistics. The V4-V5 regions of the 16S rRNA genes were
amplified using a conserved primer pair, which was tagged with a short
oligonucleotide sequence of 6 bp (i.e. barcodes) (Table S1). These samples were
sequenced with one pyrosequencing run, and a total of 52.2 mbp sequences with
213,329 reads were obtained. Since both forward and reverse primers were tagged,
sequences from both strands were obtained. Although PCR amplification with this
primer set generated ~400 bp fragments, only the first 240 bp after the proximal PCR
primer was used for analysis due to sequence quality problem. The sequences from
both forward and reverse primers were analyzed separately or combined together. A
total of 178,148 raw sequencing reads were obtained, ranging from 1,637 to 8,275
sequences per sample prior to sequence preprocessing (Table S7-C). After removing
low quality reads as described in the Materials and Methods section, a total of
115,741 sequence reads were obtained (24 samples, 56 tags). About 6% (p=0.049
based on Mann-Whitney U test) more sequence reads were obtained with the forward
primer (52.8%) than reverse primer (47.2%). The number of total pyrosequencing
reads varied considerably among different tags,
ranging from 432 to 2,999 with an
average of 1,091 reads for the forward primers (Table S7-A), and from 487 to 3,158
with an average of 976 reads for the reverse primers (Table S7-B). These results are
similar to other pyrosequencing results (Campbell et al., 2010; Hollister et al., 2010;
Acosta-Martinez et al., 2008; Koopman et al., 2010; Middelbos et al., 2010).
All pyrosequencing reads from all samples were aligned using the RDP
Infernal Aligner and the complete linkage clustering method was used to define OTUs
using 97% sequence identity as a cutoff. A total of 17,218 OTUs were obtained.
About 17% (p<0.001) more OTUs were obtained with the forward primer (58.6%)
than reverse (41.4%). The numbers of OTUs from different tags vary significantly,
ranging from 306 to 1,480, with an average of 633 OTUs per tag, for the forward
primer (Table S7-A), and 235 to 1,358, with an average of 502 OTUs per tag, for the
reverse primer (Table S7-B).
Rarefaction analysis of microbial community diversity. To understand whether
the OTUs obtained via pyrosequencing represent the diversity of the abundant
populations of microbial communities, rarefaction analysis was carried out based on
individual primers, combined primers, individual plots, treatments and the
experimental site as a whole. The majority (91.1%) of the experimental data fitted
well with a nonlinear exponential model, y = ax (1 – exp (-b*x) (Zhou et al., 2004) (r2
= 0.9727 - 0.9999). Most of the rarefaction curves (plots of the cumulative number of
OTUs as a function of sequence number) approached saturation (Fig. S3 and data not
shown), suggesting that sampling efforts were reasonably sufficient to reflect the
diversity of the communities examined. Based on the rarefaction curves, predicted
OTU numbers for each sequencing tag were obtained. Overall, about 57±7.2% of the
predicted OTUs were sampled with different tags for the forward primers (Table
S7-A), 64±6.0% for reverse primers (Table S7-B) and 51±6.4% for both combined
(Table S7-C, p values: F/R, <0.001; F/FR, <0.001; R/FR, <0.001). Also, based on
Chao1 estimation, about 37±4.5% of the predicted OTUs were sampled with different
tags for forward primers (Table S7-A), 41±4.9% for reverse primers (Table S7-B) and
32.6±4.2% for both combined (Table S7-C, p values: F/R, <0.001; F/FR, <0.001;
R/FR, <0.001). In addition,
a total of 16,825 OTUs were observed by pooling all
sequences together, which was 96.8% of the OTUs predicted by rarefaction analysis
(17,370), and 85.2% of the OTUs based on Chao1 (19,746) (Table S7-C), indicating
that the diversity of the abundant populations in these communities was recovered in
this study.
Key issues for improving data comparability. To make a meaningful biological
comparison across different experimental conditions from noisy data, the simplest
way to improve the data comparability is to increase sequencing efforts and generate
sufficient number of sequences from each sample. Nevertheless, this can be difficult
due to the complexity of soil microbial communities and experimental cost. Another
improvement is to remove less confident sequence data, such as singleton sequences
and/or less representative OTUs (e.g., OTUs present only once or twice across
samples) (He et al., 2010). In addition, increasing biological replicates should also be
an effective improvement. In the following, we systematically examined the effects of
these various strategies on improving data comparability using the data from this
experimental site.
Previous studies demonstrated that experimental warming at this site markedly
affected plant growth and phenology (Luo et al. 2007; Sherry et al., 2008), as well as
microbial community structure based on fatty acid analysis (Zhang et al., 2005) and
functional gene arrays (Zhou et al, unpublished). The aboveground community
structures also differ between clipping and non-clipping. It is thus reasonable to
believe that warming or clipping will significantly shift microbial community
phylogenetic composition and structure. Therefore, we assessed the effectiveness of
various data preprocessing strategies for improving data comparability by simply
judging whether they can provide better differentiation (resolution) of microbial
community phylogenetic structure between warming and unwarming, or between
clipping and unclipping.
In this study, some of the samples (plots) were sequenced with 2 tags and the others
with 3 tags. This data can be combined in two ways to represent the community
composition and structure of a sample. One is to add all OTUs together by treating the
sequencing with these tags as a continuous sampling event, which leads to increased
sequencing effort. The alternative way is to calculate the average numbers of OTUs
identified with these tags by considering the sequencing with different tags as
replicate sampling events. The latter could lead to increased sequencing efforts, but to
lesser extent. Thus, the former approach is generally preferred. In addition, since the
sequence number of individual OTUs obtained varied significantly among different
samples, the relative proportions of sequence numbers were used for community
comparison. The main results based on the above considerations were described in the
main text.
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