healthmedicinet

Effects of salt stress on growth parameters

After treated with 50 mM NaCl for 7 days, there was no significant difference in M-81E
(Fig. 1a), while growth of Roma was significantly inhibited (Fig. 1b). In the presence of 150 mM NaCl, the growth of both genotypes was inhibited, but
it was more severe in Roma. Leaf length of M-81E was not affected by 50 mM NaCl treatment,
but slightly decreased 15.6 % at 150 mM NaCl treatment. Leaf length of Roma decreased
27.2 % at 50 mM NaCl treatment and 41.6 % at 150 mM NaCl treatment (Additional file
1: Figure S1). Leaf numbers of M-81E and Roma were not affected by 50 mM NaCl, but
decreased 23.2 and 31.3 %, respectively, when treated with 150 mM NaCl (Additional
file1: Figure S1). Fresh weight (FW) of leaves of both genotypes gradually decreased
with an increase in NaCl concentration. The reductions were more severe at 150 mM,
particularly for Roma (Additional file 2: Figure S2) in which values decreased 43.1 and 68.6 % for 50 and 150 mM NaCl concentrations,
respectively. Dry weight (DW) of leaves also decreased with an increase in NaCl concentration.
The highest reduction in Roma was 62.9 % at 150 mM NaCl (Additional file 2: Figure S2). There was no significant effect on water content during NaCl treatment.
(Additional file 2: Figure S2).

Fig. 1. The phenotype of M-81E (a) and Roma (b) treated with different concentrations of NaCl (0, 50 and 150 mM) for 7 days

Effects of salt stress on ion concentration

After treated with 50 mM NaCl for 7 days, there were no significant changes in Na
⁺
concentrations in leaves of both genotypes compared to control plants (Additional
file 3: Figure S3). When a higher concentration of salt (150 mM) was applied, Na
⁺
concentration increased significantly, especially for Roma. The K
⁺
concentration in leaves gradually decreased in response to NaCl. At the 150 mM NaCl
treatment, K
⁺
concentration of M-81E and Roma decreased 30.6 and 41.6 %, respectively (Additional
file 3: Figure S3). The K
⁺
/Na
⁺
ratio in leaves of M-81E increased under 50 mM NaCl treatment and then decreased when
treated by 150 mM NaCl. While the K
⁺
/Na
⁺
ratio in leaves of Roma decreased under the NaCl treatment. At 150 mM NaCl treatment,
the K
⁺
/Na
⁺
ratio in Roma decreased by a factor of fourteen times (Additional file 3: Figure S3).

Effects of salt stress on PSII photochemical efficiency

In both genotypes the potential efficiency of PSII photochemistry (Fv/Fm) was reduced
with increasing NaCl concentration (Fig. 2). After treated with 50 mM NaCl for 7 days, Fv/Fm of M-81E and Roma decreased 3.6
and 11.1 %, respectively. For 150 mM NaCl, Fv/Fm of M-81E and Roma decreased 4.2 and
20.8 %, respectively (Fig. 2). The actual PSII efficiency (?PSII) decreased in both genotypes after treated with
NaCl. ?PSII of M-81E treated with 50 and 150 mM NaCl decreased 10.7 and 14.4 %, respectively.
In Roma, ?PSII decreased 36.6 and 50.7 % for 50 and 150 mM NaCl treatment, respectively.

Fig. 2. Effect of salt stress (0, 50 and 150 mM) on Fv/Fm and ?PSII in leaves of M-81E and
Roma. Fv/Fm and ?PSII were measured after treated with NaCl for 7 days. Values are
means?±?SD of five measurements for each of five plants. Bars with the different letters
are significantly different at p?=?0.05 according to Duncan’s multiple range test. Bars with same letter are not significantly
different

Effects of salt stress on chlorophyll content

The effects of increasing level of NaCl salinity on chlorophyll contents in the two
genotypes were determined after 7 day exposure to salinity (Fig. 3). Chlorophyll content in M-81E was not changed significantly by 50 mM NaCl but decreased
46.5 % under 150 mM NaCl treatment. On the other hand, in Roma, chlorophyll content
decreased gradually with the increasing NaCl treatments. Chlorophyll content of Roma
treated with 50 and 150 mM NaCl decreased 37.6 and 68.4 %, respectively.

Fig. 3. Chlorophyll content of M-81E and Roma treated with different concentrations of NaCl
(0, 50 and 150 mM) for 7 days. Values are means?±?SD of five replicates. Bars with
the different letters are significantly different at p?=?0.05 according to Duncan’s multiple range test. Bars with same letter are not significantly
different

Effects of salt stress on photosynthesis

There were no significant changes in photosynthetic rate, stomatal conductance and
intercellular CO
₂
concentration in M-81E under salt stress. However, photosynthesis in Roma was significantly
influenced by salt stress (Fig. 4). The photosynthetic rate of Roma was inhibited after treated with NaCl for 7 days.
The reduction percentage of photosynthetic rate of Roma was 45.1 and 67.5 % for 50 mM
and 150 mM NaCl treatment, respectively. Stomatal conductance of Roma decreased 35.5
and 60.9 % after treated with 50 mM and 150 mM NaCl, respectively. Intercellular CO
₂
concentration of Roma decreased 23.0 % under 50 mM NaCl. While after treated with
150 mM NaCl for 7 days, the intercellular CO
₂
concentration of Roma increased 3.9 %.

Fig. 4. Photosynthetic rate, stomatal conductance and intercellular CO
₂
concentration of M-81E and Roma treated with different concentrations of NaCl (0,
50 and 150 mM) for 7 days. Values are means?±?SD of five replicates. Bars with the
different letters are significantly different at p?=?0.05 according to Duncan’s multiple range test. Bars with same letter are not significantly
different

Effects of salt stress on sugar content

The effects of increasing level of NaCl salinity on sugar contents in the two genotypes
were determined after 7 days exposure to salinity. After treated for 7 days, the sugar
content of M-81E increased 15.6 and 99.7 % under 50 mM and 150 mM NaCl, respectively.
While, there was no significant change in sugar content of Roma under 50 mM NaCl.
Under 150 mM NaCl, the sugar content of Roma decreased 30.5 % (Fig. 5).

Fig. 5. Sugar content of M-81E and Roma treated with different concentrations of NaCl (0,
50 and 150 mM) for 7 days. Values are means?±?SD of five replicates. Bars with the
different letters are significantly different at p?=?0.05 according to Duncan’s multiple range test

Sequencing output and assembly

In order to investigate the molecular mechanisms of high sugar content under salt
stress in sweet sorghum, libraries (MC, MS, RC and RS) were designed for RNA-seq.
MC and MS libraries were used for leaves of M-81E treated with 0 mM and 150 mM NaCl,
respectively. RC and RS libraries were used for leaves of Roma treated with 0 mM and
150 mM NaCl, respectively. In total, 78.41 million reads were generated. After trimming
adapters and filtering out low quality reads, more than 67.08 million clean reads
were retained for assembly and further analysis. Among all the reads, more than 94 %
had Phred-like quality scores at the Q30 level (an error probability of 0.1 %) (Additional
file 4: Table S1). All these data showed that the throughput and sequencing quality were
high enough for further analysis. The reads produced in this study have been deposited
in the National Center for Biotechnology Information (NCBI) SRA database and accession
number was shown in “Availability of supporting data”.

Exploration of DEGs in response to salt stress

In the absence of salt, 3342 genes showed differential expression levels when comparing
M-81E vs. Roma. While in the presence of salt, the DEGs between them were 2265. For
M-81E, 864 genes were differentially expressed between control plants and those subjected
to salt. Among these DEGs, 236 genes were up-regulated in leaves under salt stress.
For Roma, 930 genes were differentially expressed between control plants and those
subjected to salt. Among these DEGs, 442 genes were up-regulated in leaves under salt
stress (Fig. 6). All of these DEGs were selected for further analysis.

Fig. 6. Numbers of DEGs of different genotypes affected by salt stress

Functional categorization of stress-regulated genes

Functional classification by GO

In order to assign functional information to the DEGs between control plants and those
treated with NaCl, Gene Ontology (GO) 23] analysis was carried out. This analysis provides a dynamic, controlled vocabulary
and also hierarchical relationships for the representation of information on biological
processes, molecular function, and cellular components, forming a coherent annotation
of various gene products 23]. In M-81E, there were 812 unique transcripts assigned to 48 level-2 GO terms, which
were summarized under three main GO categories, including 13 for cellular component,
12 for molecular function and 23 for biological process, respectively. In Roma, there
were 878 unique transcripts assigned to 47 level-2 GO terms including 13 for cellular
component, 12 for molecular function and 22 for biological process, respectively.
For the cellular group, in both M-81E and Roma, the most represented category was
cell part, cell and organelle. For molecular function, the category of binding was
the most represented GO term, followed second by the category of catalytic activity.
Regarding biological process, NCBI UniGene for cellular process and metabolic process
were highly represented (Fig. 7).

Fig. 7. Functional annotation of assembled sequences based on gene ontology (GO) categorization.
Results are summarized for three main Go categories: Biological Process, Molecular
Function, and Cellular Component

Functional classification by COG

In addition, all the DEGs were subjected to a search against the Clusters of Orthologous
Groups (COG) 24] classification. Among the 864 DEGs, 349 sequences showed a COG classification in
M-81E (Additional file 5: Figure S4A). Among the 25 COG categories, the cluster for “general function prediction
only” was the largest group, followed by “secondary metabolites biosynthesis, transport
and catabolism”, “amino acid transport and metabolism”, “carbohydrate transport and
metabolism” and “transcription”. The categories “chromatin structure and dynamics”,
“extracellular structure” and “nuclear structure” had no corresponding genes. The
360 sequences of the 930 sequences could be assigned to COG classifications in Roma
(Additional file 5: Figure S4B). The cluster for “general function prediction only” represented the
largest group, followed by “signal transduction mechanisms”, “transcription”, “replication,
recombination and repair” and “carbohydrate transport and metabolism”. Whereas no
unigenes were assigned to “extracellular structure”, “nuclear structure”, “cell motility”
and “intracellular trafficking, secretion, and vesicular transport”.

Functional classification by KEGG

Kyoto Encyclopedia of Genes and Genomes database (KEGG) 25] was used to identify potential biological pathways represented in the sweet sorghum
transcriptome. There were 150 DEGs of M-81E and 174 DEGs of Roma assigned to 70 and
63 KEGG pathways, respectively. The majority of these DEGs mapped to “photosynthesis”,
“photosynthesis-antenna proteins”, “carbon fixation in photosynthetic organisms” and
“starch and sucrose metabolism” categories (Fig. 8, Table 1), which indicated that salt stress mainly affected photosynthesis and carbohydrate
metabolism in leaves of sweet sorghum.

Fig. 8. The heat map display of DEGs assigned to different KEGG pathways. The numbers in the
scale bar show the percentage of the number of DEGs assigned to a certain KEGG pathway
in which assigned to all KEGG pathways. Red indicates that more genes are enriched
in this pathway

Table 1. DEGs mapped to KEGG pathways related with sugar content

Photosynthesis-antenna proteins

In the first steps of photosynthesis, light energy is captured and converted into
chemical energy. A large part of the light is absorbed by the outer light-harvesting
complexes (LHCs), which contain most of the chlorophyll and carotenoid pigments and
are peripherally associated with PSI and PSII 26], 27]. These LHC proteins are encoded by nuclear genes of the LHC multi-gene family coding
for proteins that contain one to four trans-membrane helices and share a number of
conserved chlorophyll- and xanthophyll-binding motifs 28]. In higher plants, 14 different types of LHC proteins (Lhca1–Lhca6 and Lhcb1–Lhcb8)
are expressed 29]. Lhca-type proteins are organized into two heterodimeric domains (Lhca1/Lhca4 and
Lhca2/Lhca3) as an external antenna with the PSI core. The reaction center of PSII
is surrounded by Lhcb-type proteins. In the present study, 8 DEGs of M-81E and 14
DEGs of Roma were mapped to the antenna proteins, respectively. In comparison with
the untreated control, the expression of DEGs encoding Lhca1 and Lhcb1-5 were down-regulated
in both of the two genotypes under salt stress. However, the expression level of DEGs
encoding Lcha2-4 and Lchb6 dropped under salt stress in Roma but did not change in
M-81E (Additional file 6: Figure S5).

Photosynthesis

Photosynthesis is one of the most important metabolic processes in plants. Salt stress
significantly impacts the photosynthetic rate 30], 31]. The four protein components of the photosynthetic electron transport chain responsible
for the electron transfer from water to NADP
⁺
are Photosystem II (PSII), Photosystem I (PSI), cytochrome (Cytb6f) complex, and ATP
synthase. There were 11 and 20 DEGs of M-81E and Roma, respectively, that mapped to
the photosynthesis pathway, which led to changes in the structure and function of
the four protein components (Fig. 9, Table 1).

Fig. 9. KEGG map of the photosynthesis pathway. It’s an analysis of DEGs, comparing salt-treated
samples to untreated control. Boxes with a red frame indicate the corresponding DEGs
were up-regulated in the salt-treated samples, boxes with a green frame indicate the
corresponding DEGs were down-regulated in the salt-treated samples, boxes with blue
frame indicate some of the corresponding DEGs were down-regulated and others were
up-regulated, and those without any colored frame indicate the expression level of
corresponding genes were not changed, as determined by RNA-seq

Photosystem II is a protein complex consisting of several different types of chlorophyll
binding components. The function of these components is to organize chlorophylls for
light harvesting and to harbor the electron transport intermediates as well as cofactors
needed for the oxidation of water 32]. After treated with NaCl, DEGs encoding PsbQ, which is necessary for regulation of
activity and assembly 33], 34] of PSII in both M-81E and Roma, were down-regulated. PsbR has been proved to be an
important link in the PSII core complex to permit stable assembly of the oxygen-evolving
complex proteins PsbP and PsbQ 35]. DEGs encoding PsbR were up-regulated in M-81E after treated with 150 mM NaCl for
48 h. DEGs encoding PsbW, which stabilize the supramolecular organization of photosystem
II, were down-regulated only in Roma. These results suggested that salt stress reduced
the binding stability of several subunits of PSII. However, we predict that M-81E
may protect important connective structures from being destroyed by increasing expression
of specific genes.

Photosystem I (PSI) from higher plants is a supramolecular complex which catalyzes
the light-driven electron transfer from plastocyanin to ferredoxin and is composed
of a chlorophyll binding core complex and a chlorophyll a/b binding peripheral antenna
called LHCI 36]. After treated with NaCl for 48 h, the expression of DEGs encoding PsaK, PsaH and
PsaO decreased in both genotypes. All of these three subunits are involved in the
interaction between the light-harvesting complex (LHC) and Photosystem I 37]–39], suggesting that salt stress weakened the connection between LHCs and PSI and reduced
the conversion of light energy to chemical energy. PsaD, PsaE, PsaF, PsaG, PsaL and
PsaN encoding genes were down-regulated only in Roma. Among them, four subunits (PsaD,
PsaE, PsaF, PsaN) are considered to be important for the interaction with ferredoxin
or plastocyanin 40], 41], indicating that the electron transport mechanism was inhibited by salt stress in
Roma. These observations agreed fairly well with the down-regulation of petE and petF in Roma after treated with salt. Moreover, expression of Sb04g027810, a gene encoding the ATP synthase delta chain, decreased in both genotypes when treated
with 150 mM NaCl, while the gene encoding the ATP synthase gamma chain was only down-regulated
in Roma.

Carbon fixation in photosynthetic organisms

There were 6 and 8 DEGs of M-81E and Roma, respectively, mapped to the carbon fixation
in photosynthetic organisms pathway. Ribulose-bisphosphate carboxylase (rubisco, EC:
4.1.1.39), phosphoenolpyruvate carboxylase (PEPC, EC:4.1.1.31) and pyruvate orthophosphate
dikinase (PPDK, EC:2.7.9.1) are considered as key enzymes in the process of carbon
fixation. Rubisco catalyzes the incorporation of CO
₂
into ribulose 1,5-bisphosphate 42]. Under salt stress for 48 h, the expression of DEGs encoding rubisco decreased while
the PPDK and PEPC encoding genes remained unchanged in both genotypes based on our
RNA-seq data. Surprisingly, the expression of DEGs encoding transketolase (EC:2.2.1.1)
and NADP
⁺
-malate dehydrogenase (NADP-ME, 1.1.1.40) in M-81E were extremely enhanced by salt
stress (Additional file 7: Figure S6).

Starch and sucrose metabolism

Sucrose phosphate synthetase (SPS, EC:3.1.3.24), sucrose synthetase (SS, EC:2.4.1.13)
and invertase (INV, EC:3.2.1.26) are considered to be key enzymes in sucrose metabolism.
SS is known to play a role in sucrose synthesis using uridine diphosphate (UDP)-glucose
and fructose as substrates and its activity is high in source tissues such as leaves
43]. After a 48 h treatment with NaCl, the expression of DEGs encoding SS were enhanced
in M-81E but unchanged in Roma. INV plays the most important role in the decomposition
of sucrose. In the present study, the expression of DEGs encoding INV decreased in
M-81E but increased in Roma during salt stress (Additional file 8: Figure S7).

Verification of RNA-seq data

We performed quantitative real-time PCR on 14 randomly selected DEGs to validate the
RNA-seq gene expression analysis. As shown in Fig. 10, a high correlation (R
²
?=?0.93) between RNA-seq and qRT-PCR was observed. Also, three genes (Sb03g034280,
Sb06g023760 and Sb01g035890) which may play important roles in improving sugar content
in sweet sorghum were confirmed by qPCR, too. As shown in Fig. 11, a high correlation (R
²
?=?0.92) was observed, confirming the reliability of the RNA-seq data.

Fig. 10. Validation of RNA-seq results by RT-qPCR. Expression levels of 14 randomly selected
genes in the four samples used in this study were detected by RT-qPCR. R
²
represents the correlation coefficient value between the two platforms. The numbers
in the scale bar stand for RPKM values in RNA-seq and ??Ct in qRT-PCR, which were
used to evaluate the correlation (R
²
). Primers are listed in (Additional file 9: Table S2)

Fig. 11. Validation of RNA-seq results by RT-qPCR. Expression levels of 3 genes involved in
sucrose synthesis and metabolism pathways were detected by RT-qPCR. R
²
represents the correlation coefficient value between the two platforms. The numbers
in the scale bar stand for RPKM values in RNA-seq and ??Ct in qRT-PCR, which were
used to evaluate the correlation (R
²
). Primers are listed in (Additional file 9: Table S2)