Abstract
The aim of this study was to determine the effects and underlying
molecular mechanisms of humic acid (HA) on foxtail millet (Setaria
italica Beauv.) under drought conditions. The rainless climate of the
Shanxi Province (37°42'N, 112°58'E) in China provides a natural
simulation of drought conditions. Two foxtail millet cultivars, Jingu21
and Zhangza10, were cultivated in Shanxi for two consecutive years
(2017–2018) based on a split-plot design. Plant growth, grain quality,
and mineral elements were analyzed in foxtail millet treated with HA
(50, 100, 200, 300, and 400 mg L^-1) and those treated with clear
water. Transcriptome sequencing followed by bioinformatics analysis was
performed on plants in the normal control (CK), drought treatment (D),
and drought + HA treatment (DHA) groups. Results were verified using
real-time quantitative PCR (RT-qPCR). HA at a concentration of 100–200
mg L^-1 caused a significant increase in the yield of foxtail millet
and had a positive effect on dry weight and root-shoot ratio. HA also
significantly increased P, Fe, Cu, Zn, and Mg content in grains.
Moreover, a total of 1098 and 409 differentially expressed genes (DEGs)
were identified in group D vs. CK and D vs. DHA, respectively. A
protein-protein interaction network and two modules were constructed
based on DEGs (such as SETIT_016654mg) between groups D and DHA. These
DEGs were mainly enriched in the metabolic pathway. In conclusion, HA
(100 mg L^-1) was found to promote the growth of foxtail millet under
drought conditions. Furthermore, SETIT_016654mg may play a role in the
effect of HA on foxtail millet via control of the metabolic pathway.
This study lays the foundation for research into the molecular
mechanisms that underlie the alleviating effects of HA on foxtail
millet under drought conditions.
Introduction
Foxtail millet (Setaria italica Beauv.) is a grain crop that grows in
arid and semi-arid regions. It is an important crop in many areas of
Africa and Asia due to its ability to grow in harsh environments
[[36]1], and is the dominant food crop in many provinces of China,
including Shanxi [[37]1]. Shanxi Province has a typical continental
arid climate with annual rainfall ranging between 400–650 mm, which is
below standard irrigation conditions [[38]2]. It is therefore of great
practical importance to investigate the drought-resistant growth
mechanisms of foxtail millet and identify ways to increase its yield in
arid and semi-arid conditions.
Humic Acid (HA) is a natural organic polymer compound and a major
component of humus, which plays an important role in crop quality,
yield, and stress resistance [[39]3, [40]4]. According to recent
reports, HA affects plant quality in two major ways: helping to resist
stress by controlling the amount of reactive oxygen species present
[[41]5], and promoting growth, photosynthesis, nitrogen assimilation,
and amino acid metabolism [[42]4, [43]6]. Parađiković et al. found that
using a mixture of biostimulants containing HA increased the yield of
yellow pepper crops. Peptides and amino acids contained in this mixed
preparation promoted high temperature resistance in the peppers, and
stimulated root growth and development, while vitamins and HA supported
fruit growth [[44]7]. A study showed that high concentrations of HA had
a significant positive effect on the morphological characteristics of
cucumber, including plant height, leaf number, and fresh weight and
yield. Additionally, the percentage of total chemical components
[nitrogenium (N), phosphorus (P), potassium kalium (K), calcium (Ca),
and magnesium (Mg)] in the leaves of cucumber plants increased as HA
concentration increased [[45]8]. Maji et al. showed that HA facilitates
plant growth by improving the microbial community structure of soil and
increasing mycorrhizal colonization in the roots of Pisum sativum
[[46]9], while another study found that foliar-applied HA improved dry
weight and mineral nutrient uptake [such as manganese (Mn), copper
(Cu), zinc (Zn), and calcium (Ca)] of maize [[47]10]. HA has also been
shown to stimulate nitrogen assimilation and amino acid metabolism in
maize at both the physiological and molecular level [[48]6]. Olaetxea
et al. demonstrated that root hydraulic conductivity and
aquaporin-related gene expression are important for plant shoot
outgrowth induced by HA [[49]11], and Kuşvuran et al. described the
effects of different HA treatments on yield and performance in common
millet. Together, these results indicate that HA treatment can
significantly improve plant yield and quality [[50]12]. However,
despite all of these promising reports, the effects of HA on foxtail
millet, and the underlying molecular mechanisms, remain unknown
In the present study, we utilized the natural drought conditions in
Shanxi Province to investigate the effects of HA on crop yield and
quality of foxtail millet. The optimal HA concentration was determined
by measuring growth and nutritional indicators in foxtail millet
samples after different periods of HA treatment. Moreover,
high-throughput sequencing analysis was used to assess changes in gene
expression related to photosynthetic assimilation and nutrient
indicators. This allowed the molecular mechanisms that underlie the
effects of HA on dry matter and nutrient accumulation in foxtail millet
to be further elucidated.
Materials and methods
Test material
Test materials were selected from ordinary high-quality foxtail millet
Jingu21 (Shanxi Academy of Agricultural Sciences Economic Crops
Research Institute, China) and hybrid high-yield foxtail millet
Zhangza10 (Zhangjiakou City Academy of Agricultural Sciences, Hebei
Province, China).
Field experiments
From 2017 to 2018, field experiments were conducted at the agricultural
research station of Shanxi Agricultural University (37°42'N, 112°58'E).
This region is dry and has very little rainfall, thus naturally
simulating a drought environment. Crops from the previous season were
not foxtail millet, and continuous cropping was therefore avoided.
A split-plot design was adopted for this study. Briefly, clear water
was used as a blank control for the main plot, while HA at
concentrations of 50, 100, 200, 300, and 400 mg L^-1 (T1, T2, T3, T4,
and T5, respectively) was used for the secondary plot. Both water and
HA were sprayed onto the leaves of the foxtail millet at the jointing
and filling stages (800 L ha^-1). The experiment was repeated three
times in all 36 districts (10 m^2 district^-1).
Plant quality evaluation
The foxtail millet was harvested on October 13, 2017, and October 1,
2018. The ear, stem, leaf, and root from three representative mature
plants were baked at 105°C for 30 min, followed by 80°C for 24–48 h,
then the dry weight was measured. Plant height, stem diameter, ear
length, ear diameter, ear yardage, and 1000-grain weight were measured
on three representative mature plants. Grain ears were manually
threshed, shelled, comminuted (0.5 mm sieve), and dried. Protein
content was determined using an MPA Fourier transform near-infrared
spectrometer (Bruke, Germany). Total P and K content was determined via
the molybdenum antimony colorimetric method and flame photometry.
Presence of mineral elements, such as iron (Fe), Mn, Cu, Zn, Ca, and
Magnesium (Mg), was determined using the diethylenetriaminepentaacetic
acid (DTPA) extraction inductively-coupled plasma spectroscopy (ICP)
method.
HA treatment evaluation based on the membership function method
The yield and quality of foxtail millet Jingu21 and Zhangza10 after
treatment with different HA concentrations were comprehensively
analyzed using the membership function method in fuzzy mathematics
[[51]13]. The membership function formula is:
[MATH: U(Xi)=(Xi‑Xmin)/<
/mo>(Xmax‑Xmin)(indicatortraitpositivelycorrelateswithnutrientuptakeandyield) :MATH]
[MATH: U(Xi)=1‑(Xi‑Xmin)/<
/mo>(Xmax‑Xmin)(indicatortraitnegativelycorrelateswithnutrientuptakeandyield) :MATH]
where U (X[i]) is the membership function value; X[i] is the measured
value of an index at each processing level; X[max] and X[min] are the
maximum and minimum values within an indicator at all processing
levels, respectively.
Grouping for molecular analysis
Leaves from 3–5 leaf potted foxtail millet seedlings were sequenced to
ensure accuracy of the test. Sequencing samples (Jingu21) were divided
into three groups; normal control group (CK), drought treatment group
(D), and drought + HA treatment group (DHA). Plants in the CK group
were cultured under normal conditions. Culture conditions for plants in
groups D and DHA were in accordance with field trials. The optimal HA
concentration identified during field trials was used as the default
concentration for HA treatment (100 mg L^-1). Seedlings in groups D and
DHA were harvested and analyzed after five days of drought.
Transcriptome sequencing
Total RNA was extracted from samples from all groups using the
TRIzol-based method (RNAiso Plus, TaKaRa, 9109). RNA quantification and
purity were determined using diethyl phosphorocyanidate (DEPC) H[2]O as
the blank control. Transcriptome sequencing was then performed based on
Illumina high throughput sequencing. The design and detailed operation
for sequencing were validated by Beijing Novogene Technology Co., Ltd
(Project Number: P101SC18122767-01). Sequencing data were retained for
subsequent analysis.
Quality control and preprocessing
Quality control and preprocessing were performed on the original
sequencing data. A clean read was obtained by filtering joint and
low-quality sequences. Quality control of the clean reads was performed
using fastqc (version: 0.11.5,
[52]http://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
[[53]14]. TopHat software (version: 2.1.0,
[54]http://ccb.jhu.edu/software/tophat/) [[55]15] was used to locate
clean reads on the reference genome Setaria_italica_v2.0 (version:
Ensembl Plants) [[56]16] for foxtail millet. Finally, the featureCounts
tool (version: 1.6.0, [57]http://subread.sourceforge.net/) [[58]17] was
used to annotate the samples with a Gens genome annotation file
(Ensembl Plants), and read information for each gene alignment was
obtained.
DEGs analysis
According to the RNA read count data, the read count was pretreated
using the TMM (trimmed mean of M values) normalization method within
the edgeR package in R software [[59]18, [60]19]. DEGs between D vs. CK
and D vs. DHA were then revealed using the quasi-likelihood (QL) F-test
in the edgeR package. Results were visualized via a heat map using
pheatmap software
([61]https://cran.r-project.org/web/packages/pheatmap). DEGs in both
the D vs. CK and D vs. DHA groups were then visualized using a Venn
diagram generated using VENNY software
([62]http://bioinfogp.cnb.csic.es/tools/venny/index.html) [[63]20].
PPI network construction and module analysis
Protein interaction information was obtained according to the search
tool for the retrieval of interacting genes (STING) database (version:
11.0, [64]http://www.string-db.org/) [[65]21], and PPI pairs among DEGs
between groups D and DHA were predicted with median confidence (score)
= 0.4. Next, a PPI network was constructed using Cytoscape software
(version: 3.7.0, [66]http://www.cytoscape.org/) [[67]22], and molecular
complex detection (MCODE, Version1.5.1
[68]http://apps.cytoscape.org/apps/MCODE) [[69]23], a plug-in of
Cytoscape software, was used to screen significantly enriched modules
from the PPI network with a module score ≥ 4.
Pathway enrichment analysis of the DEGs
KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway [[70]24]
enrichment analyses of DEGs between groups D and DHA were performed
using KOBAS software (version: 3.0, [71]http://kobas.cbi.pku.edu.cn/)
[[72]25]. p < 0.05 was considered the cut-off for significant
enrichment.
Real-time quantitative PCR
RT-qPCR was used to verify DEGs obtained in this study. Expression of
SETIT_009509mg, SETIT_021707mg, SETIT_016840mg, SETIT_015030mg,
SETIT_004913mg, and SETIT_016654mg was assessed by qPCR. Briefly, total
RNA was extracted from samples from each group (CK1, CK2, CK3, D1, D2,
D3, DHA1, DHA2, and DHA3) using TRIzol reagent (RNAiso Plus, TaKaRa,
9109) and quantified. Reverse transcription was performed using
5×primeScript RT Master Mix (Perfect Real Time, TAKARA, RR036A). Actin
was used as a reference. Primers are listed in [73]S1 Table. Reaction
conditions were as follows: 50°C for 3 min, 95°C for 3 min, 40 cycles
at 95°C for 10 s, and 60°C for 30 s. A fluorescence signal was recorded
at the end of each cycle, and an amplification curve was generated.
Relative expression of candidate genes was calculated using the 2^-ΔΔCT
method [[74]26].
Statistical analysis
Statistical analysis was carried out using SPSS 16.0 (Inc., Chicago,
IL, USA) and GraphPad Prism 5 software (GraphPad Software, San Diego,
CA). Results from field trials were processed and plotted using
Microsoft Excel 2010, and data are presented as mean ± standard error
(SE). RT-qPCR results are presented as mean ± standard deviation (SD).
p < 0.05 and p < 0.01 were the screening criteria for significant and
extremely significant differences, respectively.
Results
Effect of HA on growth and yield characteristics of foxtail millet
As the HA concentration increased, the stem diameter of Zhangza10
initially increased then decreased, and this was true for samples
collected in both 2017 and 2018. The effects of HA on plant height and
stem diameter of Jingu21, and plant height of Zhangza10, were not
significant (all p > 0.05) ([75]Fig 1). In 2017, the underground dry
weight of Jingu21 and Zhangza10 initially increased then decreased with
increasing HA concentrations ([76]S2 Table). Jingu21 reached its
maximum root-to-shoot ratio with T3 in 2017 and 2018, while Zhangza10
reached its maximum root-to-shoot ratio with T2 in both years. These
results show that HA at a concentration of 100–200 mg L^-1
significantly improved the dry weight and root-shoot ratio of foxtail
millet.
Fig 1. Effect of humic acid on plant height and stem diameter of foxtail
millet in the years 2017 and 2018.
Fig 1
[77]Open in a new tab
X-axis represents different cultivars of foxtail millet; y-axis
represents different plant traits. CK, T1, T2, T3, T4, and T5 represent
different concentrations of HA (0 mg L^-1, 50 mg L^-1, 100 mg L^-1, 200
mg L^-1, 300 mg L^-1, and 400 mg L^-1). Lowercase letters in the same
column indicate significant differences at the 0.05 level.
Moreover, there was an initial increase in ear yardage, ear weight, and
yield in both Jingu21 and Zhangza10 as HA concentration increased, but
they then decreased ([78]Table 1). Jingu21 had the largest ear diameter
and yield with T3 in 2017 and with T2 in 2018, while Zhangza10 had the
largest ear diameter and yield with T3 in 2017. In 2018, the maximum
ear diameter of Zhangza10 was recorded with T2, while the maximum yield
occurred with T3, and this treatment also resulted in the maximum ear
length. The yield of Jingu21 increased by 16.96% (two-year average)
with T3 and T2, compared to CK. Meanwhile, Zhangza10 yield increased by
14.48% (two-year average) with T3, compared to CK. These results show
that HA at a concentration of 100–200 mg L^-1 causes a significant
increase in foxtail millet yield, and has a positive effect on dry
weight and root-shoot ratio. The correlation coefficients between
growth indicators and yield traits are listed in [79]Table 2. There was
a strong negative correlation between yield, plant height and
aboveground dry weight (p < 0.01), and a positive correlation between
yield and root-shoot ratio (p < 0.01). Thousand kernel weight showed a
strong positive correlation with stem diameter and underground dry
weight (p < 0.01).
Table 1. Effect of HA on yield and yield composition of foxtail millet in
2017 and 2018.
Cultivar Treatment Ear length(cm) Ear diameter(mm) Ear yardage Ear
weight(g) 1000-grain weight(g) Yield / kg·ha^-1
CK 24.61±0.48^ab 32.38±0.92^a 102.3±1.5^b 21.06±1.07^b 3.112±0.096^a
3928.2±28.7^c
Jingu21 T1 23.67±0.19^b 31.50±1.16^a 106.6±2.8^b 21.75±1.65^b
3.201±0.018^a 3595.5±36.8^d
(2017) T2 24.50±0.35^ab 32.33±0.33^a 117.8±3.5^a 27.86±1.32^a
3.264±0.073^a 3351.7±47.6^e
T3 25.00±0.75^ab 34.23±0.70^a 114.9±1.6^a 28.60±2.61^a 3.252±0.003^a
4463.5±53.4^a
T4 23.83±0.19^ab 33.78±1.24^a 105.4±1.2^b 23.21±0.73^ab 3.270±0.072^a
4238.4±63.4^b
T5 25.44±0.78^a 32.82±0.64^a 105.7±3.2^b 25.53±1.87^ab 3.215±0.065^a
3982.0±43.3^c
CK 27.23±0.26^a 26.53±0.70^ab 100.6±4.9^b 25.06±0.37^b 2.452±0.109^ab
3741.5±17.8^c
Jingu21 T1 26.77±0.30^ab 27.50±0.60^a 110.3±3.2^ab 22.48±0.56^c
2.651±0.029^a 3572.6±51.1^c
(2018) T2 26.13±0.24^b 28.67±0.68^a 109.4±4.3^ab 26.28±0.51^ab
2.506±0.082^ab 4500.2±67.2^a
T3 26.43±0.20^ab 28.43±0.60^a 117.7±4.8^a 27.30±0.54^a 2.301±0.124^b
4158.3±50.5^b
T4 25.87±0.37^b 27.77±0.53^a 116.6±3.9^a 20.91±0.42^d 2.392±0.068^ab
4195.8±41.6^b
T5 26.13±0.39^b 24.56±0.72^b 105.4±3.5^ab 20.37±0.58^d 2.504±0.101^ab
3604.7±70.9^c
CK 26.08±0.14^a 29.71±0.98^a 107.0±4.1^abc 29.89±3.06^abc
2.957±0.057^ab 5160.1±47.9^b
Zhangza10 T1 24.67±0.44^b 30.48±0.93^a 98.9±2.1^c 31.67±2.91^ab
2.968±0.062^ab 5149.4±61.7^b
(2017) T2 25.17±0.42^ab 31.69±0.10^a 104.4±2.4^bc 32.22±0.78^a
3.038±0.023^a 5414.0±10.1^a
T3 25.94±0.24^a 32.17±1.03^a 110.3±2.1^ab 33.67±1.93^a 3.005±0.024^a
5447.7±40.2^a
T4 25.22±0.49^ab 30.86±1.01^a 116.6±3.8^a 23.67±0.58^c 2.987±0.031^a
5123.4±57.2^b
T5 25.44±0.31^ab 31.29±1.11^a 106.4±2.8^bc 24.78±2.32^bc 2.848±0.008^b
4674.4±72.3^c
CK 32.29±0.22^ab 33.36±0.54^ab 103.9±3.6^a 26.94±0.46^b 2.609±0.042^a
3828.0±40.0^c
Zhangza10 T1 31.21±0.41^b 32.00±0.84^b 100.9±2.6^a 24.06±0.88^c
2.655±0.031^a 3761.4±76.3^c
(2018) T2 30.92±0.66^b 35.12±0.54^a 104.9±3.5^a 28.08±0.52^ab
2.651±0.035^a 4401.7±73.5^b
T3 33.19±0.75^a 32.61±0.99^b 104.9±1.8^a 29.17±0.55^a 2.549±0.050^a
4723.3±89.7^a
T4 30.77±0.70^b 32.90±0.86^ab 100.0±1.2^a 22.45±0.42^cd 2.542±0.028^a
4601.3±76.6^ab
T5 32.08±0.60^ab 31.54±0.31^b 101.6±4.0^a 21.82±0.35^d 2.636±0.039^a
3523.1±38.8^d
[80]Open in a new tab
CK, T1, T2, T3, T4 and T5 represent HA concentrations (0 mg L^-1, 50
mg/L, 100 mg L^-1, 200 mg L^-1, 300 mg L^-1 and 400 mg L^-1);
superscript lowercase letters in the same column indicated significant
differences at 0.05 level.
Table 2. Correlation coefficients between growth indicators and yield traits.
Yield traits Plant height (cm) Stem diameter (mm) Aboveground dry
weight (g) Underground dry weight (g) Root-shoot ratio (%)
Ear length (cm) -0.15 -0.37 -0.50[81]^* -0.62[82]^** 0
Ear diameter (mm) -0.50[83]^* 0.49[84]^* -0.08 0.41[85]^* 0.35
Ear yardage 0.36 0.28 0.35 0.48[86]^* -0.04
Ear weight (g) -0.47[87]^* -0.15 -0.42[88]^* 0.15 0.63[89]^**
1000-grain weight (g) -0.34 0.69[90]^** 0.34 0.75[91]^** 0.24
Yield (kg·ha^-1) -0.64[92]^** -0.2 -0.61[93]^** 0.1 0.80[94]^**
[95]Open in a new tab
* and ** denote significant correlation at 5% and 1% probability
levels, respectively.
Seed quality and membership function evaluation
As HA concentration increased, the protein content of Jingu21 and
Zhangza10 grains initially increased and then decreased, in both 2017
and 2018 ([96]Fig 2). Results of the membership function and
comprehensive evaluation are shown in [97]Table 3, and reveal an
initial increase and subsequent decrease in nutrient uptake and yield
in foxtail millet treated with HA. The order of action concentration
for Jingu21 was T3 > T2 > T1 > T4 > T5, and for Zhangza10 was T2 > T3 >
T1 > T4 > T5. The average membership function with T2 was 0.65 for
Jingu21 and 0.80 for Zhangza10, and with T3 was 0.81 for Jingu21 and
0.69 for Zhangza10. The comprehensive analysis showed that the order of
HA concentrations that improved foxtail millet yield and quality was T3
> T2 > T1 > T4 > T5.
Fig 2. Effect of humic acid on protein content of foxtail millet in the years
2017 and 2018.
Fig 2
[98]Open in a new tab
CK, T1, T2, T3, T4, and T5 on the x-axis represent HA concentrations (0
mg L^-1, 50 mg L^-1, 100 mg L^-1, 200 mg L^-1, 300 mg L^-1, and 400 mg
L^-1); y-axis represents protein content. Lowercase letters in the same
column indicate significant differences at the 0.05 level.
Table 3. Membership function value of humic acid action on foxtail millet and
comprehensive evaluation.
Cultivars Treatment Protein content (%) P (g·kg^-1) K (g·kg^-1) Fe
(mg·kg^-1) Mn (mg·kg^-1) Cu (mg·kg^-1) Zn (mg·kg^-1) Ca (mg·kg^-1) Mg
(mg·kg^-1) Yield (kg·ha^-1) Mean
value Sort
Jingu21 CK 0.27 0.00 0.81 0.10 0.78 0.00 0.00 0.82 0.00 0.34 0.31 6
T1 0.57 0.50 0.61 0.04 0.98 0.57 0.15 1.00 0.73 0.00 0.51 3
T2 1.00 0.40 0.91 0.00 1.00 1.00 0.23 0.56 0.99 0.47 0.65 2
T3 0.90 1.00 1.00 0.63 0.95 0.39 0.96 0.25 1.00 1.00 0.81 1
T4 0.26 0.00 0.00 0.72 0.00 0.50 1.00 0.23 0.72 0.87 0.43 4
T5 0.00 0.07 0.63 1.00 0.09 0.46 0.16 0.00 0.46 0.29 0.32 5
Zhangza10 CK 0.00 0.00 0.36 0.00 1.00 0.00 0.03 0.58 0.00 0.40 0.24 5
T1 0.49 0.50 0.00 0.23 0.76 0.55 0.62 1.00 0.52 0.36 0.50 3
T2 0.98 1.00 1.00 0.29 0.33 1.00 1.00 0.76 0.78 0.82 0.80 1
T3 1.00 0.55 0.61 0.58 0.02 0.65 0.90 0.65 1.00 1.00 0.69 2
T4 0.19 0.36 0.29 0.69 0.23 0.58 0.00 0.00 0.35 0.77 0.35 4
T5 0.08 0.33 0.07 1.00 0.00 0.43 0.00 0.04 0.13 0.00 0.21 6
[99]Open in a new tab
CK, T1, T2, T3, T4 and T5 represent HA concentrations (0 mg L^-1, 50 mg
L^-1, 100 mg L^-1, 200 mg L^-1, 300 mg L^-1 and 400 mg L^-1).
DEG analysis based on mRNA sequencing data
Sequencing data identified 453 genes that were up- regulated and 645
that were down-regulated between groups D and CK. Meanwhile, a total of
272 up-regulated and 137 down-regulated genes were identified between
groups D and DHA. A heat map for the union of the two groups is shown
in [100]Fig 3A, and indicates the relative expression values of DEGs
among samples in different groups. Furthermore, a Venn plot analysis
was performed on all DEGs ([101]Fig 3B), and revealed 79 common DEGs in
both D vs. CK and D vs. DHA. Meanwhile, 1019 and 330 DEGs were
identified for D vs. CK and D vs. DHA, respectively. Three hundred and
thirty DEGs between groups D and DHA were selected for further
investigation into the molecular mechanisms that underlie the effect of
HA on dry matter and nutrient accumulation in foxtail millet.
Fig 3. Differential gene expression in foxtail millet after HA treatment.
[102]Fig 3
[103]Open in a new tab
A) heat map for DEGs among different groups; different colors represent
different groups; values at p < 0.05 and |log2FC| > 0.585 were
considered significantly different. B) Venn plot analysis for genes in
all samples.
PPI network and module investigation
A PPI network was constructed based on DEGs between groups D and DHA
([104]Fig 4A) with a combined score of 0.4. Moreover, with score ≥ 0.4,
two modules, A (score = 4.8, six nodes, twelve interactions) and B
(score = 4, four nodes, six interactions), were found to form the
current PPI network ([105]Fig 4B). Characteristic genes with top ten
degrees were within the PPI network (such as SETIT_026527mg), module A
(such as SETIT_001087MG), and module B (such as SETIT_025844mg).
Fig 4. Protein-protein interaction network of differentially expressed genes.
[106]Fig 4
[107]Open in a new tab
A, PPI network constructed from DEGs between groups D and DHA. B, two
modules obtained from the PPI network. Red circles represent
up-regulated DEGs; purple circles represent down-regulated DEGs. Gray
lines represent protein interaction relationships. The larger the node,
the higher the degree of interaction.
Enrichment analysis based on DEGs
A KEGG pathway enrichment analysis was performed on DEGs between groups
D and DHA ([108]Fig 5). Results show that the DEGs are mainly enriched
in metabolic pathways (sita01100, genes: SETIT_009509mg,
SETIT_017919mg, and SETIT_021617mg), secondary metabolite biosynthesis
(sita01110, genes: SETIT_014105mg, SETIT_017811mg, and SETIT_022131mg),
and starch and sucrose metabolism (sita00500, genes: SETIT_009543mg,
SETIT_034299mg, and SETIT_009543mg).
Fig 5. Pathway enrichment analysis of differentially expressed genes between
groups D and DHA.
[109]Fig 5
[110]Open in a new tab
Y-axis represents pathway annotation information; x-axis represents
number of genes enriched in the pathway. The -log10 (p-value) is
represented as an inflection point of the broken line.
Gene expression analysis
Expression of human SETIT_009509mg, SETIT_021707mg, SETIT_016840mg,
SETIT_015030mg, SETIT_004913mg, and SETIT_016654mg genes was analyzed
by RT-qPCR. Results show that SETIT_016654mg was significantly
up-regulated in group D compared with the CK group (p < 0.05).
Moreover, SETIT_021707mg, SETIT_016840mg, and SETIT_015030mg were
significantly up-regulated, while SETIT_004913mg and SETIT_016654mg
were significantly down-regulated in the DHA group compared with group
D (all p < 0.05) ([111]Fig 6). Finally, SETIT-009509mg was
significantly up-regulated in the DHA group compared to groups CK and D
(all p < 0.05).
Fig 6. RT-qPCR analysis of gene expression in different HA treatment groups.
Fig 6
[112]Open in a new tab
X-axis represents different groups; y-axis represents relative gene
expression. *, p < 0.05 when compared with the CK group; #, p < 0.05
when compared with the D group.
Discussion
Organic HA contains macronutrients and micronutrients, growth-promoting
substances, vitamins, and beneficial microorganisms, all of which are
important for maximizing plant yield. Previous research showed that HA
treatment resulted in an increase in grain yield in wheat [[113]27].
For the two varieties of millet in the present study, there was no
difference in P content between CK and the T4 treatment, whereas other
concentrations of HA resulted in an increase in P content. This
increase in phosphorus after HA treatment could be due its forming a
complex with iron (Fe) [[114]28]. Some trace elements, including Fe,
have low solubility in soil at higher pH values, which can result in Fe
deficiency in plants. The addition of HA can reduce the soil pH
[[115]29], which in turn would not only promote the growth of crops,
but could also increase nutrient absorption from the soil [[116]27].
Humic acid can either activate or inhibit enzyme activity by promoting
the absorption of underground soil nutrients by the plant, thus
altering cell membrane permeability, which in turn leads to protein
synthesis and stimulates growth, ultimately increasing the yield.
In the current study, HA was found to alleviate drought stress in
foxtail millet. More specifically, treatment with 100–200 mg L^-1 HA
had a positive effect on underground dry weight and root-shoot ratio.,
and also increased the yield. There was a strong positive correlation
between root-shoot ratio and yield (p < 0.01). An increase in
underground dry weight is an indication of enhanced root growth, which
could be a good way to alleviate moisture loss in the soil [[117]30].
It has been shown that addition of HA to soil increases proliferation
and branching of root hairs [[118]31], which could in part explain the
enhanced nutrient absorption and increased yield observed in the
present study. HA treatment had little influence on ear length, ear
diameter or ear yardage of millet, which could be because the HA was
applied during the jointing and filling stages, when these ear
characteristics are already defined [[119]32].
Drought stress is one of the major abiotic stresses known to affect
crop production worldwide. In order to understand the mechanism by
which plants cope with water deficiency, it is necessary to study
natural drought-tolerant plants and identify the molecular mechanisms
that underlie their drought stress tolerance. The biological function
of HA is commonly studied in terms of regulation at either the gene or
molecular level [[120]33]. In the present study, 330 DEGs were
identified between groups D and DHA, and were found to be enriched
mainly in metabolic pathways (SETIT_009509mg, SETIT_017919mg, and
SETIT_021617mg), secondary metabolite biosynthesis (SETIT_014105mg,
SETIT_017811mg, and SETIT_022131mg), and starch and sucrose metabolism
(SETIT_009543mg, SETIT_034299mg, and SETIT_009543mg) [[121]34,
[122]35], indicating that these pathways are dominant when the plant is
under drought stress. The expression of six genes, which are involved
in important metabolic pathways and with high degrees of interaction in
a PPI network, were verified by RTqPCR. Of these, SETIT_016654mg was
significantly up-regulated in group D compared to groups CK and DHA (p
< 0.0001). SETIT_016654mg encodes arginine decarboxylase 2 (ADC2),
which has been shown to be induced by drought stress in Arabidopsis
thaliana [[123]36]. Under high permeability conditions, such as after
treatment with mannitol, ADC activity was found to be increased in the
leaves and roots of wheat. Furthermore, putrescine is known to play an
important role in salt tolerance in plants [[124]37], and levels of
putrescine and spermine were increased in the leaves and roots of
plants treated with mannitol,.
Conclusions
In conclusion, HA at a concentration of 100 mg L^-1 can increase the
yield and protein and mineral content of foxtail millet grain under
drought conditions. Moreover, SETIT_016654mg may play an important role
in the effect of HA on foxtail millet by regulating metabolic pathways.
This study identified the treatment dose of HA that should be used in
millet under drought conditions, and lays the foundation for research
into the molecular mechanisms that underlie the alleviating effects of
HA on foxtail millet under drought conditions.
Supporting information
S1 Table. Primers used for RT-qPCR.
(DOCX)
[125]Click here for additional data file.^ (16.4KB, docx)
S2 Table. Effect of humic acid on growth indicators of foxtail millet
in the years 2017 and 2018.
(DOCX)
[126]Click here for additional data file.^ (16.8KB, docx)
Data Availability
Transcriptome data is deposited to NCBI under accession number
PRJNA601233 ([127]https://www.ncbi.nlm.nih.gov/sra/PRJNA601233).
Funding Statement
This study was funded by Scientific and Technological Innovation
Project of Colleges and Universities in Shanxi Province (grant number
201802056) to JS; Program for the Technical System of National Foxtail
Millet and Sorghum Industry in the 13th Five-Year (grant number
CARS-06-13.5-A28) to XY; Key Scientific and Technological Project of
Shanxi Province (grant number 2015-TN-09) to PG; and the Key Innovation
Team of “1331” Project from Shanxi Province to PG.
References