Figure 4. Identification of isoflavone-related candidate genes
through transcriptome profile analysis. Normalized FPKM values are
depicted on the Z-Score scale, gray indicates no expression data of the
target gene in the database.
3. Discussion
The isoflavone content of soybean seeds is a quantitative trait that is
determined by multiple QTLs and environmental factors [42]. Ideally,
breeders would like to introduce multiple genes into elite soybean
cultivars to produce a superior variety with high yield and high
isoflavone content in seeds. Achieving this goal through traditional
methods has proven to be a challenge due to long breeding cycles.
Identification of QTLs would provide the much-needed tools for efficient
selection of high isoflavone content [43]. The RILs described here,
as a permanent isolated population, provided good material for genetic
map construction and QTL mapping. Using an RIL population of 178 F2:6
and 52 SSR molecular markers, we assembled a genetic linkage map
covering 11 chromosomes. This yielded a total of 22 QTLs related to
isoflavone content. The sequence of SSR markers on the linkage groups
was mostly consistent with previously reported maps. Among the detected
sites, 5, 7 and 6 were associated with daidzin, genistin and glycitin
content, respectively. Four QTLs were found to be associated with total
isoflavones, two which corresponded to genistin QTLs, and one to a
glycitin QTL. Referring to the 2003 soybean public genetic map
(GmComposite 2003), 15 QTLs were classified corresponded to those in the
SoyBase database (https://www.soybase.org), and 7 new ones were
identified including qDaidzin-2-1, qGlycitin-11-1, qGlycitin-16-1,
Genistin-8-1, qGenistin-9-1, qGenistin-14-1 and qGenistin-19-2.
Of the candidate genes identified (Table S1), many were involved in
phenypropanoid metabolism (Table 3). This included many genes involved
in lignin biosynthesis, including eight laccases associated with five
different QTL. Given their use of common precursors, it can be expected
that downregulation of lignin biosynthesis could enhance the production
of flavonoids. Indeed, previous research revealed a significant increase
of flavonoids in Laccase 1 RNAi lines in cotton (Gossypium hirsutum)
[44]. Similarly, decreasing lignin levels through downregulation of
other lignin biosynthetic genes was shown to result in flavonoid
accumulation in both Arabidopsis thaliana and Medicago sativa
[45-47]. On the other hand, it was shown, using a population of
inbred Brassica napus lines, that lines with high seed lignin showed
increased expression of both lignin and flavonoid biosynthesis genes,
suggesting that concordant regulation of these pathways can also occur
[48]. Homologs of two arabidopsis phenypropanoid-related
transcriptional regulators were also identified as candidates. One of
these was a homolog of MYB20, a transcription factor that promotes
expression of lignin biosynthesis genes in arabidopsis. In addition to
activating lignin biosynthetic genes, MYB20 was shown to directly
activate transcriptional repressors of flavonoid biosynthesis genes,
which was reflected in increased flavonoid levels in the myb20 mutant
[49]. Another candidate was homologous to MEDIATOR 23, a
transcriptional regulator that was shown to regulate the production of
phenylpropanoids [50]. Another candidate is homologous to
Cinnamoyl CoA reductase 6 (CCR6), which potentially encodes an enzyme
responsible for the final step in monolignol biosynthesis and that was
previously linked to a QTL for lignin content in arabidopsis [51].
More research is needed to determine whether the QTLs described here can
be explained through perturbation of lignin metabolism.
Several other candidates are predicted to be flavonoid-related,
including a homolog of BANYULS, and its regulators. BANYULS a negative
regulator of flavonoid synthesis in A. thaliana , that inhibits
the production of proanthocyanidins in the seed coat [52] BANYULS
expression is positively regulated by the so-called MBW transcriptional
complex, which is comprised of the R2R3-MYB TRANSPARENT TESTA 1 (TT2)
[53,54], the bHLH protein TT8 [55], and the WD40-repeat protein
TRANSPARENT TESTA GLABROUS 1 (TTG1) [32,56]. Our study found that
homologs of BANYULS and all three MBW complex members are associated
with isoflavonoid QTLs. As discussed above for lignins, this could be
explained by changes in proanthocyanidin synthesis affecting levels of
common precursors required for production isoflavonoids. Two QTL were
associated with CHS, the key branchpoint enzyme directing carbon flux
from general phenylpropanoid metabolism to the flavonoid pathway.
In total, five of the 22 isoflavonoid QTL identified were found to be
linked to homologs of ‘transparent testa’ genes. The TT genes were
identified as having reduced seed coat pigments due to lower levels of
proanthocyanidins [57] and hence are all expressed in the seed coat.
For example, one candidate is homologous to TT10/Laccase 15, a gene
expressed in developing testa, where it colocalizes with the flavonoid
end products proanthocyanidins and flavonols [35]. Our data suggests
that competition with lignin and other flavonoids for precursors could
be a major factors affecting isoflavonoid production in seeds. This work
highlights two research avenues that deserve further investigation: the
identification or creation of lines with a) reduced lignin production to
divert precursors to the flavonoid branch or b) increased
proanthocyanidin biosynthesis, which may be associated with a general
increase in flavonoid content.
4. Materials and Methods
4.1. Plant materials and field experiments
An F2:6 recombinant inbred line (RIL) population consisting of 178 lines
was derived from the cross of the parental genotypes Jinong 17 and
Jinong 18 that differed significantly in the composition and total
content of isoflavones in soybean seeds. Jinong 17 was used as the
female parent and contains higher daidzin, glycitin, genistin and total
isoflavones than Jinong 18, the male parent.
The field experiment was conducted in the experimental field of Jilin
Agricultural University in Changchun, Jilin Province (43°13′N,
125°19′E), China. The experiment was laid out in a randomized complete
block design (RCBD) with three replications. Parents and RIL populations
were planted with a row length of 4.5 meters, a distance between rows of
0.65 meters, 2 rows for each RIL material, and the planting density was
180,000-200,000 plants per hectare. Seeds were sampled after full
maturity for further phenotypic characterization.
4.2. Soybean seed isoflavone extraction and determination
Soybean seed isoflavones were extracted and characterized as follows:
Soybean seeds were ground into powder and were sifted through a 40-mesh
screen. The soybean powder obtained was degreased with petroleum ether
at 65℃ for 2 hours, and then was dried at 37℃ until reaching a constant
weight. The skimmed powder (250 mg) was dissolved in 10 mL 80% methanol
at room temperature for 2 hours and then distilled at 80°C for 12 hours.
The supernatant was collected by centrifugation at 12000 rpm for 15
minutes. 1 mL of supernatant solution was filtered into a separate HPLC
vial using a glass syringe equipped with a 0.45 µm nylon filter (Amicon,
USA) for further isoflavones determination. The standards (genistein,
genistin, daidzein, glycitein, glycitin and daidzin with purity more
than 98%, Sigma-Aldrich, USA) were dissolved in methanol to a
concentration of 100mg/L. Then the isoflavones standard solutions were
serially diluted to 2 mg/L, 5 mg/L and 10mg/L for the calibration
curves. An internal standard (2-methoxyflavone, Sigma-Aldrich, USA)
solution (5 mg/mL) was also prepared in the same solvent.
A high-performance liquid chromatography (HPLC, Shimadzu, Japan) system
was employed with a Shim-pack VP-DOS column (150mm×4.6mm, Shimadzu,
Japan) and a mobile phase of methanol-water (a cubage ratio of 30:70).
The column temperature was set at 40℃, the wave length was 254nm, the
flow rate was 1mL/min, and the filling amount was 10μL. Analytes were
quantified on the basis of the internal standard method. All samples
were analyzed in triplicates.
4.3. Genotype analysis and construction of Genetic Maps
Fresh leaves of soybean plants at the three-leaf stage were used for
total genome DNA extraction with the cetyltrimethylammonium bromide
(CTAB) method [58]. DNA was dissolved in ddH2O to a concentration
100ng/ml with RNAase A (Thermo Fisher Scientific, USA)added. All primer
sequences were obtained from Soybase database
(https://www.soybase.org ). A total of 274 primers from 14 linkage
groups were used to detect polymorphism of SSR loci in the parents (in
the parents), and 58 of them were available and synthesized.
PCR amplification was performed using the 2×Taq PCR StarMix kit (Genstar
Kangrun Bio, Beijing, China). The PCR reactions used 1.0 µg template
DNA, 1.0 µL of 10 µM forward and reverse primers, 10 µL of 2×Taq PCR
Star Mix, and 7 µL of ddH2O. PCR was carried out as follows: 94℃
pre-denaturation for 5 min, 94℃ denaturation for 30 s, 53℃ renaturations
for 30 s, 72℃ extension for 30 s, repeated 35 cycles, and 5min final
extension at 72℃ after the last cycle. The ICIMapping v4.0 software was
used to identify the QTLs related to isoflavone contents and
composition. A LOD value of 2.5 was used as a minimum to declare the
detection of a QTL in a particular region.
5. Conclusions
The present study used an RIL
population derived two parents with different isoflavones components,
Jinong 17 and Jinong 18, to detect QTLs as well as mine possible
candidate genes controlling soybean isoflavones content in multiple
environments. A total of 22 QTLs were found, and 7 of these were novel.
61 candidate genes were identified based on the annotations. 10 genes
were identified through integration of the QTL analysis, gene annotation
and gene expression profile analysis. These three genes were not only in
the isoflavones-related QTL region, but also highly expressed when
isoflavones accumulated rapidly in soybean seeds. These results advance
our understanding of the genetic basis of isoflavones synthesis and
accumulation in soybeans.
Author Contributions: X.L., Jun.Z., L.C., C.Y., X.H., S.Y. were
involved in the manuscript writing and methodology; Y.S., D.Y., S.F.
J.M., Jian Z. were involved in manuscript refinement, data analysis,
visualization and important intellectual content discussion; Jun Z.,
Jian Z. helpe to obtaine funding; J.M, Jian.Z helped frame the paper
Funding: This research was supported by Science and Technology
Project of Jilin Provincial Department of Education (JJKH20210348KJ),
Jilin Provincial Science and Technology Department of Science and
Technology Development Project (20210202113NC), Science and Technology
Project of Jilin Provincial Department of Education (JJKH20180658KJ) and
Jilin Agricultural University high level researcher grant
(JAUHLRG20102006).
Conflicts of Interest: The authors declare no conflict of
interest.