l. japonicus nfr5 , lhk1-1 nin-2 - pnas€¦ · materials and methods soil and plant material....
TRANSCRIPT
Materials and Methods
Soil and plant material.
Seeds of L. japonicus WT, ecotype Gifu B-129 and the corresponding symbiosis-deficient
mutants nfr5-2, nfr5-3, lhk1-1 and nin-2 were grown in soil batches collected from an
agricultural field located at the Max Planck Institute for Plant Breeding Research in Cologne,
Germany (50.958N, 6.865E) in the following seasons: CAS8-spring 2013, CAS9-fall 2013,
CAS10-spring 2014. The field was not cultivated in past years, no fertiliser or pesticide
treatment was administered at the harvesting site. For each genotype and soil batch, 3
biological replicas were obtained, and the samples were harvested from 10 weeks -old plants
grown in the greenhouse (day/night cycle 16/8h, light intensity 6000 LUX, temperature: 20
°C, relative humidity: 60%). Optional supplementation of the soil with potassium nitrate was
done by addition of KNO3 to a final concentration of 10 mM to the tap water used for plant
watering. For nitrogen supplementation experiment, plants were grown in CAS11 soil,
collected in fall 2015 from a location described before.
Sample and 16S library preparations.
Fragments of the root systems (4 cm-long starting 1 cm below hypocotyl) were washed and
ultrasound treated to separate the rhizosphere, root and nodule compartments. First wash
containing the root-adhering soil layer defined the rhizosphere compartment. Nodules and
visible primordia, were separated from washed root fragments of nodulating genotypes (WT
and lhk1-1) with a scalpel. Root samples were exposed to 10 cycles of 30” ultrasound
treatment, and the nodules to 3 cycles in order to avoid tissue out-burst. Homogenized
samples were transferred to lysis buffer and DNA extraction was performed following the
manufacturer’s protocol (MP Bioproducts). DNA concentrations were measured
fluorometrically (Quant-iT™ PicoGreen dsDNA assay kit, Life Technologies, Darmstadt,
Germany), and finally adjusted to 3,5 ng/μl. Primers targeting the variable V5-V7 regions of
bacterial 16S rRNA genes (799F and 1193R) (1, 2) were used for amplification. For each
sample, triplicate amplifications were performed using three independent PCR mixtures (9
replicates per sample in total, along with no template controls). Amplification products were
purified, combined and subjected to 454 sequencing.
Quantitative RT-PCR.
WT and mutant root samples were used for mRNA isolation using oligodT DYNA beads
following the protocol of the manufacturer (Invitrogen). The mRNA was subsequently used
as template for cDNA synthesis using an oligodT primer. The same cDNA pool was used for
amplification of all tested transcripts in each sample. Quantitative PCR was performed on
the LightCycler (Roche Molecular Biochemicals) using FastStart DNA master SYBR greenI kit
(Roche). The relative quantification software (Roche) was used to determine the efficiency-
corrected relative transcript concentration, normalized to a calibrator sample. ATP, UBC,
PP2A were used as housekeeping genes. For each genotype, normalized relative ratios of the
target genes and the three independent housekeeping genes have been calculated using the
Relative Quantification Software (Quant) from Roche. The geometric mean of the relative
expression ratios for the three biological and three technical replicates and the
corresponding 95% intervals of confidence have been calculated. Primers used for transcript
amplification are presented in Dataset S3.
Computational analyses.
The 16S rRNA gene sequences were processed using a combination of custom scripts as well
as tools from the QIIME (3) and USEARCH (4) pipelines (QIIIME-ready mapping files are
provided in the Dataset S4 and S5). First, reads were truncated to an even length (290 bp)
using the truncate_fasta_qual_files.py QIIME script. Libraries were demultiplexed
(split_libraries.py) and only reads with a quality score Q > 25 were retained for subsequent
analysis. After dereplication and removal of singletons we conducted de novo clustering of
sequences into OTUs using the UPARSE algorithm (5) at 97% identity. Next, chimeric
sequences were filtered using the UCHIME algorithm (6) implemented in the USEARCH
pipeline and the ‘gold’ database (http://drive5.com/uchime/gold.fa) as a reference. An
additional filtering step was performed by first aligning all OTU representative sequences to
the greengenes database (7) using PyNAST (8; align_seqs.py script in QIIME) and
subsequently discarding sequences not aligned to the database at least at 75% identity. OTU
representative sequences were classified taxonomically using the RDP classifier (9) and the
uclust algorithm (4) trained on the greengenes database. The resulting OTU table was used
in all subsequent statistical analyses of differentially abundant taxa as well analyses of alpha -
and beta-diversity.
Indices of α-diversity (Shannon, chao1 and number of observed OTUs) were calculated after
subsampling to an even depth of 1000 reads (QIIME script alpha_diversity.py). Measures of
β-diversity (Bray-Curtis and weighted and unweighted UniFrac; 10) were calculated on a
normalized OTU table (CSS method with QIIME script function beta_diversity.py). Principle
Coordinate Analysis (PCoA) was done by classical multidimensional scaling of β -diversity
distance matrices using the cmdscale function in R. Canonical Analysis of Principle
Coordinates (11; CAP) was computed using the capscale function implemented in the vegan
R library (12), by constraining for the variable of interest and conditioning for the remaining
factors. Statistical significance was determined using a permutation-based ANOVA test
implemented in anova.cca function using 5,000 permutations. Statistical analyses of
differentially abundant OTUs were performed using the edgeR library (13). Briefly, we first
obtained normalization factors using the function calcNormFactors and subsequently
estimated common and tag-wise dispersions for a Negative Binomial Generalized Linear
Model (GLM) using the estimateGLMCommonDisp and estimateGLMTagwiseDisp functions,
respectively. In order to test for differential OTU abundances, we then fit a negative
binomial generalized log-linear model to the read counts for OTU using the glmFit function.
P values were corrected for multiple tests using the approach of (14) with α=0.05.
Metabolite analysis
Root nitrate contents were determined by ion chromatography method as previously
described (15). Approximately 20 mg plant tissue was homogenized and extracted in 1 mL of
sterile water for 1 hour at 4°C. The extracts were heated for 15 min at 95°C and centrifuged
for 15 min at 13,000 rpm. Ten µL of the extracts were analysed on Dionex IonPac AS22 RFIC
4x250 mm analytical column (Thermo Scientific) using a carbonate buffer (4.5 mM Na2CO3,
1.4 mM NaHCO3) as eluent at 1 mL/min in an isocratic mode and a Dionex ICS-1100 ion
chromatography system. Proteins were extracted in 10 mM Tris/HCl buffer, pH 8 and
determined with a Bio-Rad Protein Assay Kit using bovine serum albumin as standard.
References
1. Bulgarelli D, et al. (2012) Revealing structure and assembly cues for Arabidopsis root-
inhabiting bacterial microbiota. Nature 488(7409):91-95.
2. Chelius MK, Triplett EW (2001) The Diversity of Archaea and bacteria in association
with the roots of Zea Mays. Microb. Ecol. 41:252-263
3. Caporaso JG, et al. (2010) PyNAST: a flexible tool for aligning sequences to a template
alignment. Bioinformatics 26(2):266-267.
4. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST.
Bioinformatics 26(19):2460-2461.
5. Edgar RC (2013) UPARSE: highly accurate OTU sequences from microbial amplicon
reads. Nature methods 10(10):996-998.
6. Edgar RC, Haas BJ, Clemente JC, Quince C, & Knight R (2011) UCHIME improves
sensitivity and speed of chimera detection. Bioinformatics 27(16):2194-2200.
7. DeSantis TZ, et al. (2006) Greengenes, a chimera-checked 16S rRNA gene database
and workbench compatible with ARB. Applied and environmental microbiology 72(7):5069-
5072.
8. Caporaso JG, et al. (2010) QIIME allows analysis of high-throughput community
sequencing data. Nature methods 7(5):335-336.
9. Wang Q, Garrity GM, Tiedje JM, & Cole JR (2007) Naive Bayesian classifier for rapid
assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microb
73(16):5261-5267.
10. Lozupone C, Lladser ME, Knights D, Stombaugh J, & Knight R (2011) UniFrac: an
effective distance metric for microbial community comparison. The ISME journal 5(2):169-
172.
11. Anderson MJ & Willis TJ (2003) Canonical analysis of principal coordinates: A useful
method of constrained ordination for ecology. Ecology 84(2):511-525.
12. Oksanen J, et al. (2015) R Package ‘vegan’ 2.3-3. Community Ecology Package.
13. Robinson MD, McCarthy DJ, & Smyth GK (2010) edgeR: a Bioconductor package for
differential expression analysis of digital gene expression data. Bioinformatics 26(1): 139-
140.
14. Benjamini Y & Hochberg Y (1995) Controlling the false discovery rate - a practical and
powerful approach to multiple testing. J Roy Stat Soc B Met 57(1):289-300.
15. Koprivova A, Harper AL, Trick M, Bancroft I, Kopriva S (2014) Dissection of control of
anion homeostasis by associative transcriptomics in Brassica napus. Plant Physiol,
166(1):442-450.
Fig. S1. Harvesting procedures applied for compartment separation of nodulating (a)and non-nodulating (b) genotypes of Lotus japonicus.
a
b
DNA
extra
ctio
nRhizosphere of Roots
Roots 16S
rRN
A C
omm
unity
Pro
flin
g
Isolation andWashing
Sonication
Isolation andWashing
Compartmentseparation DN
A ex
tract
ion
Rhizosphere of Rootsand Nodules
Pooled Nodules
Roots without Nodules
16S
rRN
A C
omm
unity
Pro
flin
g
Sonication
Fig. S2. Analisys of α-diversity (within sample diversity) based on the Shannon indexin the soil (n=27), rhizosphere (n=38), root (n=62) and nodule (n=18) compartments.Each dot corresponds to an individual sample, colored by compartment and each hostgenotype is represented by a different shape. Each sample was rarefied to an depth of1,000 reads before the analysis.
2
4
6
8
Soil Rhizosphere Root Nodule
Sh
an
no
n i
nd
ex
rhizosphereroot
soil
compartment
nodule
genotype
lhk1-1
soil
nfr5-3
nin-2
gifu (wild-type)
nfr5-2
−0.2
0.0
0.2
−0.4 −0.2 0.0 0.2PCoA 1 (26.62%)
PC
oA
2 (
11
.27
%)
genotype
nfr5-2
gifu (wild-type)
rhizosphereroot
soil
compartment
−0.2
0.0
0.2
0.4
−0.4 −0.2 0.0 0.2PCoA 1 (31.38%)
PC
oA
2 (
13
.67
%)
genotype
nfr5-2
gifu (wild-type)
rhizosphereroot
soil
compartment
−0.2
0.0
0.2
−0.50 −0.25 0.00 0.25PCoA 1 (31.64%)
PC
oA
2 (
9.7
99
%)
genotype
hit1-1
soil
nfr5-3
nin-2
gifu (wild-type)
rhizosphereroot
soil
compartment
CAS10
CAS9
CAS8
Fig. S3. PCoA plots of Bray-Curtis distances for samples from each soil batch(a, CAS8, n=63; b, CAS9, n=31 and c, CAS10, n=72). Each point corresponds to a differentsample, colored by compartment. Host genotype is represented by different shapes.
a
b
c
Fig. S4. Constrained PCoA plot of Bray-Curtis distances constrained by genotype after in silicodepletion of nodule-enriched OTUs (9.72% of variance explained, P<0.001; n=164). Eachpoint corresponds to a different sample, colored by compartment and each host genotypeis represented by a different shape. The percentage of variation indicated in each axiscorresponds to the fraction of the total variance explained by the projection.
−0.2
−0.1
0.0
0.1
0.2
−0.2 −0.1 0.0 0.1CPCoA 1 (83.52%)
CP
Co
A 2
(1
6.4
8%
)
genotype
lhk1-1
soil
nfr5-3
nin2
gifu (wild-type)
nfr5-2
rhizosphereroot
soil
compartment
9.72 % of variance (P<0.001)
Wild-type
Root Rhizosphere
Soil
nfr5−2
Root Rhizosphere
Soil
Fig. S5. Ternary plots depicting compartment relative abundance of all OTUs (>5 ‰) for wild-type samples (a, gifu) and mutant samples (b, nfr5-2) in CAS8 soil. Each point corresponds to an OTU and its position represents its relative abundance with respectto each compartment. Colored circles represent OTUs enriched in one compartmentcompared to the others (green in root, orange in rhizosphere and brown in root samples).
a b
Soil
Rhizosphere
Root
Enriched OTUs
Soil
Rhizosphere
Root
Enriched OTUs
Wild-type
Root Rhizosphere
Soil
nfr5−2
Root Rhizosphere
Soil
Fig. S6. Ternary plots depicting compartment relative abundance of all OTUs (>5 ‰) for wildtype samples (a, gifu) and mutant samples (b, nfr5-2) in CAS9 soil. Each point corresponds to an OTU and its position represents its relative abundance with respectto each compartment. Colored circles represent OTUs enriched in one compartmentcompared to the others (green in root, orange in rhizosphere and brown in root samples).
a b
Soil
Rhizosphere
Root
Enriched OTUs
Soil
Rhizosphere
Root
Enriched OTUs
nfr5−3Wild-type
Root Rhizosphere
Soil
Root Rhizosphere
Soil
Fig. S7. Ternary plots depicting compartment relative abundance of all OTUs (>5 ‰) for wildtype samples (a, gifu) and mutant samples (b, nfr5-3) in CAS10 soil. Each point corresponds to an OTU and its position represents its relative abundance with respectto each compartment. Colored circles represent OTUs enriched in one compartmentcompared to the others (green in root, orange in rhizosphere and brown in root samples).
a b
Soil
Rhizosphere
Root
Enriched OTUs
Soil
Rhizosphere
Root
Enriched OTUs
Root Rhizosphere
Soil
Root Rhizosphere
Soil
lhk1-1Wild-type
Fig. S8. Ternary plots depicting compartment relative abundance of all OTUs (> 5 ‰) for wildtype samples (a, gifu) and mutant samples (b, lhk1-1) in CAS10 soil. Each point corresponds to an OTU and its position represents its relative abundance with respectto each compartment. Colored circles represent OTUs enriched in one compartmentcompared to the others (green in root, orange in rhizosphere and brown in root samples).
a b
Soil
Rhizosphere
Root
Enriched OTUs
Soil
Rhizosphere
Root
Enriched OTUs
nin-2Wild-type
Root Rhizosphere
Soil
Root Rhizosphere
Soil
Fig. S9. Ternary plots depicting compartment relative abundance of all OTUs (> 5 ‰) for wildtype samples (a, gifu) and mutant samples (b, nin-2) in CAS10 soil. Each point corresponds to an OTU and its position represents its relative abundance with respectto each compartment. Colored circles represent OTUs enriched in one compartmentcompared to the others (green in root, orange in rhizosphere and brown in root samples).
a b
Soil
Rhizosphere
Root
Enriched OTUs
Soil
Rhizosphere
Root
Enriched OTUs
1 2 3
a b c a b c a b c
1 2 3
a b c a b c a b c
1 2 3
a b c a b c a b c
1 2 3
a b c a b c a b c
Wild-type nfr5-3 nin-2 lhk1-1O
TU
s en
rich
ed in
gifu
ro
ots
OT
Us
enric
hed
in m
utan
ts r
oots
[0,0.01)
[0.01,0.05)
[0.05,0.1)
[0.1,0.5)
[0.5,1)
[1,2)
[2,4)
[6,8)
[8,100)
R.A (%)
Fig. S10. (a) Heatmaps showing relative abundances of all OTUs found to be significantlyenriched in the root samples of wild-type plants grown in CAS10 soil with respect to themutants (top panel) or significantly enriched in the root samples of the mutants comparedto wild-type (bottom panel). (b) Heatmaps showing relative abundances of all OTUs foundto be significantly enriched in the rhizosphere samples of wild-type plants grown in CAS10soil with respect to the symbiosis- impaired mutants (top panel) or significantly enriched inthe rhizosphere samples of the mutants compared to wild-type (bottom panel). Labels at thebottom of each column correspond to biological (numbers) and technical replicates (letters).Enrichment tests were performed using the negative binomial generalized log-linear modeland P-values were FDR adjusted.
1 2 3
a b c a b c a b c
1 2
a b c a b c
1 2 3
a b c a b c a b c
1 2 3
a b a a
Wild-type nfr5-3 nin-2 lhk1-1
OT
Us
enric
hed
in g
ifu r
hiz
osph
ere
mut
ants
[0,0.01)
[0.01,0.05)
[0.05,0.1)
[0.1,0.5)
[0.5,1)
[1,2)
[2,4)
[6,8)
[8,100)
R.A (%)
a
b
0
20
40
60
−log10(P)
wild
-typ
e ro
ots
a
0
20
40
60
−log10(P)
mut
ant r
oots
b
0
20
40
60
−log10(P)
wild
-typ
e rh
izos
phe
re
c
0
20
40
60
−log10(P)
mut
ant r
hizo
sphe
re
d
0.001 0.04 0.08 0.12 0.16
relative abundance (%)significantly enriched n.s.
Gp1
ThermotogalesNeisseriales
ChlamydialesGemmatimonadales
Bacillales
XanthomonadalesPseudomonadales
MyxococcalesBurkholderiales
Sphingomonadales
Rhizobiales
Nitrospirales
Actinobacteridae
LegionellalesSphingobacterialesFlavobacteriales
Gp10Thiotrichales
OTUs enriched in wild-type roots with respect to mutant roots
FlavobacterialesXanthomonadalesBurkholderialesActinobacteridae Sphingobacteriales
FlavobacterialesCytophagales
OTUs enriched in mutant roots with respect to wilt-type roots
ThermotogalesMyxococcales
RhodocyclalesThermoleophilalesRubrobacteridae
Gp1Thermotogales
Gemmatimonadales XanthomonadalesPseudomonadales
BurkholderialesRhizobialesNitrospirales
Actinobacteridae FlavobacterialesGp22
Methylophilales / Neisseriales
OTUs enriched in wild-type rhizosphere with respect to mutant rhizosphere
SphingomonadalesSphingobacteriales
BurkholderialesActinobacteridae
OTUs enriched in mutant rhizospherewith respect to wilt-type rhizosphere
Fig. S11. Manhattan plots showing OTUs enriched in wild-type root compared to mutant rootsamples (a), depleted in the wild-type with respect to the mutants (b), enriched in the wild-typerhizosphere compared with respect to the mutants (c) or depleted in gifu rhizosphere withrespect to the mutant rhizosphere (d). Significantly enriched OTUs are depicted as full circles.The dashed line corresponds to the FDR corrected P-value threshold of significance (α=0.05).The color of each dot represents the different taxonomic affiliation of the OTUs (order level)and their sizes to their relative abundances in their respective samples (a, wild-type rootsamples; b, mutant root samples). Grey boxes are used to denote the different taxonomicgroups (order level).
Fig. S12. Relative abundances aggregated to the phylum taxonomic level showing acomparison between wild-type and the mutant root (a; n=74) and rhizosphere (b; n=63)samples.
Root
Rhizosphere
a
b
Mutant
Wild-type
Mutant
Wild-type
●●
● ●● ●● ●●
●
● ●
●●
Other
Firmicutes
Bacteroidetes
Actinobacteria
Proteobacteria
0% 20% 40% 60% 80%relative abundance
●●●
●●
Other
Firmicutes
Bacteroidetes
Actinobacteria
Proteobacteria
0% 20% 40% 60% 80%relative abundance
Fig. S13. Soil-grown wild-type and symbiotic mutants differ in the expression of earlysymbiotic genes, but show comparable immune- and symbiosis-related metabolic responses.Relative transcript levels of (a) immune-response genes (LjPR1b, LjErf1, LjMyc2 LjNpr1,Ljwrky70, LjJar1, LjIcs1, LjCoi1), (b) symbiosis-related metabolic responses (LjInv1, LjNod26,LjNod70, LjSut4) and (c) early symbiotic genes (LjNin, LjPeroxidase, LjThaumatin, LjPR1a).
a
b
cLj2g3v3373100.1_LjNin Lj0g3v0207139.1_LjThaumatin LjSGA_029184_LjPR1a
Lj6g3v2170750.1_LjPR1b
chr6.CM0314.280.nc_LjPeroxidase
Lj5g3v1167370.1_LjERF1
0
1
2
3
4
5
6
WT lhk1-1 nin2 nfr5-2
Lj0g3v0343449.1_LjMYC2
0
1
2
3
4
5
WT lhk1-1 nin2 nfr5-2
Lj6g3v1692500.1_LjNPR1
0
1
2
3
4
WT lhk1-1 nin2 nfr5-2
Lj1g3v1134120.1_LjWRKY70
0
0,5
1
1,5
2
WT lhk1-1 nin2 nfr5-2
Lj1g3v5033420.1_LjJAR1
0
0,1
0,2
0,3
WT lhk1-1 nin2 nfr5-2
Lj3g3v1970100_LjICS1
0
0,5
1
1,5
WT lhk1-1 nin2 nfr5-2
Lj0g3v0011599.1_LjCOI1
0
0,2
0,4
0,6
0,8
1
1,2
WT lhk1-1 nin2 nfr5-2
Lj5g3v1853130.1_LjINV1
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
WT lhk1-1 nin2 nfr5-2
Lj5g3v0878400.1_LjNod26
0
0,005
0,01
0,015
0,02
0,025
0,03
WT lhk1-1 nin2 nfr5-2
Lj0g3v0003829.1_LjNod70
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
WT lhk1-1 nin2 nfr5-2
Lj1g3v2096190.1_LjSut4
0
0,05
0,1
0,15
0,2
0,25
0,3
WT lhk1-1 nin2 nfr5-20
1
2
3
WT lhk1-1 nin2 nfr5-2
0
0,05
0,1
0,15
0,2
0,25
WT lhk1-1 nin2 nfr5-2
0
1
2
3
4
5
WT lhk1-1 nin2 nfr5-20
1
2
3
4
5
6
7
8
9
10
WT lhk1-1 nin2 nfr5-20
5
10
15
20
25
30
35
40
45
50
WT lhk1-1 nin2 nfr5-2
Fig. S14. Roots of soil-grown wild-type and symbiotic mutants have the same proteinconcentration but differ in nitrate pool. Concentration of (a) soluble proteins and (b) nitratein roots across Lotus genotypes. Bars correspond to the standard deviation between samples.
nmol
/ m
g F
W
μg
/ mg
FW
wild-ty
pe
(n=6
) lhk1-
1
(n=1
0)nfr5
-2
(n=8
)nfr5
-3
(n=1
0) nin2
(n=1
0)
wild-ty
pe
(n=3
) lhk1-
1
(n=5
)nfr5
-2
(n=4
)nfr5
-3
(n=5
) nin2
(n=5
)
Fig. S15. (a) Images depicting L. japonicus wild-type (a) and root nodule symbiosis-deficientmutant plants lhk1-1 (b) nfr5-2 (c) and nfr5-3 (d) and nin2 (e) grown in natural soil. The lowerpanels display an identical set of genotypes, wild-type (f), hit1-1 (g), nfr5-2 (h), nfr5-3 (i) andnin2 (j), grown in natural soil supplemented with 10 mM potassium nitrate. Scale barscorrespond to 1cm. (k) differences in nitrate concentrations in the roots of wild-type and Lotusmutants under both conditions. Differences in fresh weight of wild-type Lotus and mutantplants grown in natural soil (l) and in natural soil supplemented with potassium nitrate (m).
k l m
0
5
10
15
20
25
30
35
+ 0 mM KNO3 + 10 mM KNO3
nm
ol/m
g f
resh
mass
gifu nfr5-3nfr5-2 nin2 lhk1-10.00
0.25
0.50
0.75
1.00
1.25
fre
sh
we
igh
t
wild-type
mutant
+ 0 mM KNO3
q
q
q
0.00
0.25
0.50
0.75
1.00
1.25
fre
sh
we
igh
t
+ 10mM KNO3
wild-type
mutant
gifu nfr5-3nfr5-2 nin2lhk1-1 gifu nfr5-3nfr5-2 nin2lhk1-1
Fig. S16. (a) Constrained PCoA plot of Bray-Curtis distances between samples from KNO3treated CAS11 soil constrained by genotype (21.2% of variance, P>0.001; n=61).(b) Contrained PCoA plot of Bray-Curtis distances between CAS11 untreated samplesconstrained by genotype (21.8% of variance explained, P<0.001; n=58). Each pointcorresponds to a different sample, colored by compartment and each host genotype isrepresented by a different shape. The percentage of variation indicated in each axiscorresponds to the fraction of the total variance explained by the projection.
a
b KNO3-
PCoA constrained by genotype
21.8 % of variance (P<0.001)
KNO3+
PCoA constrained by genotype
21.2 % of variance (P<0.001)
−0.3
−0.2
−0.1
0.0
0.1
0.2
−0.1 0.0 0.1 0.2 0.3CPCoA 1 (86.09%)
CP
Co
A2
(13
.91
%)
−0.3
−0.2
−0.1
0.0
0.1
0.2
−0.1 0.0 0.1 0.2 0.3CPCoA 1 (88.52%)
CP
Co
A2
(11
.48
%)
genotype
soil
nfr5-3
gifu (wild-type)
nfr5-2
genotype
soil
nfr5-3
gifu (wild-type)
nfr5-2
rhizosphereroot
soil
compartment
rhizosphereroot
soil
compartment