Graphical abstract
graphic file with name fx1.jpg
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Highlights
* •
Global methylation identified significantly different proportions
of mCs in hybrid
* •
Of common DMRs, 33.08% showed different methylation in hybrid from
the mid-parental value
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Negatively correlated DEG pDMR-genes were enriched in metabolic
pathways
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Significant higher expression of metabolites and DE-Gs were
identified in the F[1] hybrid
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Biological sciences; Natural sciences; Plant biology; Plant Genetics.
Introduction
The Capsicum (2n = 2x = 24) crop, which belongs to the family
Solanaceae, is one of the most important vegetable crops. Although more
than 38 species are reported under the Capsicum genus, only Capsium
annuum, C. frutescens, C. chinense, C. pubescens and C. baccatum are
cultivated ([36]Bosland and Votava, 2000; [37]Ibiza et al., 2012).
Besides their use as a spice, Capsicum, commonly known as chilli
peppers contains several important secondary metabolites and other
phytochemicals compounds which makes them an economically important
crop with high industrial and pharmacological potential ([38]Ramchiary
et al., 2014; [39]Sarpras et al., 2020; [40]Sricharoen et al., 2017;
[41]Sinisgalli et al., 2020; [42]Olatunji and Afolayan, 2019;
[43]Baenas et al., 2019). For instance, the naturally found compounds
such as phenolics, flavonoids, carotenoids, capsaicinoids, vitamins,
and alkaloids in Capsicum can be used for multipurpose industry usage
viz. in increasing food shelf-life, improving the sensory properties,
seasoning, and coloring of foods, in cosmetic and pharma industry
([44]Baenas et al., 2019). Several studies reported the presence of
intra and interspecific diversity of fruit traits, metabolites content,
and other agronomic traits in Capsicum species ([45]Ahmad et al.,
2021a, [46]2021b; [47]Araceli et al., 2009; [48]Chhapekar et al., 2020;
[49]Liu et al., 2020; [50]Sarpras et al., 2016; [51]Sarpras et al.,
2019). Furthermore, many studies on marker development, QTL/gene(s)
mapping of economically important traits, whole transcriptome, and
genome sequencing have been reported on Capsicum species ([52]Ahn
et al., 2014; [53]Chhapekar et al., 2021; [54]Dubey et al., 2019;
[55]Jaiswal et al., 2020; [56]Kim et al., 2020; [57]Liu et al., 2019;
[58]Martínez et al., 2021; [59]Razo-Mendivil et al., 2021). Few studies
reported that inter- and intraspecific hybrids of cultivated Capsicum
species i.e. C. annuum, C. frutescens, C. chinense, C. baccatum, and
C. pubescence, showed vigor for different traits like fruit yield,
plant growth, and earliness ([60]Sood and Kumar, 2010; [61]Shrestha
et al., 2011; [62]Singh et al., 2014; [63]Gözen et al., 2018).
Heterosis breeding has been extensively used in Capsicum crop to
increase the production of economically important traits ([64]Herath
et al., 2021). A recent study reported the expression of higher
capsaicinoids and sugars in heterotic hybrid (derived from crossing
between C. chinense x C. frutescens) as compared to their parental
lines ([65]Zamljen et al., 2020). Also, the higher accumulation of
several metabolites such as sugars (viz. glucose, fructose, and
sucrose) and primary metabolites like citric acid was observed in
leaves of Capsicum hybrids compared to the parents at lower
temperatures ([66]Shiragaki et al., 2021). These observations in
different studies suggest that the higher expression of genes and
metabolites in F[1] hybrids compared to the parental lines might have a
direct role in the manifestation of heterosis in F[1] hybrids.
Furthermore, it was reported that DNA methylation plays an important
role in the regulation of the expression of genes, which would
eventually influence the biosynthesis of metabolites ([67]Sinha et al.,
2020; [68]Lauss et al., 2018), thereby, suggesting further the need for
integrated analysis of DNA methylation, and expression of genes and
metabolites content for detail understanding of the manifestation of
heterosis, as no such study is reported in Capsicum crops until date.
Although, primarily, DNA methylation causes the silencing of the
gene(s) ([69]He et al., 2011, [70]2021); however, a few studies also
reported higher expression of genes despite methylation found in the
gene body ([71]Arechederra et al., 2018), and the exact mechanism is
still not understood. In plants, DNA methylation occurs in three
contexts: CG, CHG, and CHH (where H is any nucleotide other than G) and
are maintained by MET1, CM3, and DRM2, respectively ([72]He et al.,
2021). Studies have also found that DNA methylation also inherits
loyally across the generations ([73]Becker et al., 2011; [74]Schmitz
et al., 2011) when progenies are derived by selfing. However, the
inheritance trend of DNA methylations may be deferred in hybrid
genotypes derived by crossing ([75]He et al., 2010; [76]Chodavarapu
et al., 2012); and the degree of differential methylation pattern is
directly proportional to the divergence of parental genotypes. These
allelic and epi-allelic variations and their corresponding effect on
the expression of genes in hybrids are considered one of the major
causes of heterosis ([77]Lauss et al., 2018).
Recently, a number of studies were conducted to explore the DNA
methylation pattern and their possible role in heterosis in model
plants ([78]Greaves et al., 2012; [79]Shen et al., 2012; [80]Chen,
2013; [81]Groszmann et al., 2013; [82]Dapp et al., 2015; [83]Zhang
et al., 2016; [84]Lauss et al., 2018) as well as important crops
([85]He et al., 2010, [86]2013; [87]Shen et al., 2017; [88]Li et al.,
2018; [89]Sinha et al., 2020; [90]Zhou et al., 2021). In pigeon pea,
the global DNA methylation and transcriptome study identified an
overall increase in the methylation in F[1] hybrids ([91]Sinha et al.,
2020). The same study reported the differential expression of genes
involved in phytohormone signaling, defense response and growth. More
than 65% of differentially expressed genes (DE-Gs) were also found to
be differentially methylated in hybrids, thereby indicating the active
role of DNA methylations in gene expression and ultimately hybrid vigor
in F[1] ([92]Sinha et al., 2020). Similarly, in the case of Brassica,
higher methylation was also observed in F[1]s than their respective
parents ([93]Shen et al., 2017; [94]Li et al., 2018). In Brassica napus
(allotetraploid), the DNA methylation was also associated with higher
expression of small RNA clusters of that region and was also involved
in mechanisms of active growth and flower development ([95]Shen et al.,
2017). In B. oleracea, differential DNA methylations were found to
contribute to curd yield heterosis ([96]Li et al., 2018). Likewise,
efforts were also made to understand the role of DNA methylations in
hybrids in other major food crops like rice ([97]He et al., 2010;
[98]Zhou et al., 2021), maize ([99]He et al., 2013) and so forth.
However, despite the availability of whole genome sequences of Capsicum
spp. ([100]Kim et al., 2014, [101]2017; [102]Qin et al., 2014), the
integrated analysis of global DNA methylome and its correlation with
gene(s) and metabolites expression are not studied in Capsicum hybrids,
although few studies explored the role of epigenetics in fruit
development and ripening using whole genome methylome ([103]Rawoof
et al., 2020; [104]Xiao et al., 2020) and small RNA sequencing
([105]Lopez-Ortiz et al., 2021; [106]Chhapekar et al., 2021), and
observed that the co-networking/correlation of methylome and small RNAs
were potential players in fruit development. Keeping this knowledge gap
in mind, in this study for the first time we report the integrated
analysis wherein we observed significant correlations of DNA
methylation with the expression of genes and metabolites in heterotic
F[1] Capsicum hybrid and their parental lines at the early plant growth
stage. Furthermore, our study revealed the complex and dynamic
relationships of the genomes of two Capsicum spp. and their inheritance
in the interspecific F[1] hybrid.
Results
Phenotypic analysis of F[1] hybrid and parental lines
The interspecific Capsicum F[1] hybrid derived from crossing between
two contrasting Capsicum species, C. chinense (Choco, female parent)
and C. frutescens (Frut4, pollen donor) was evaluated for heterotic
traits along with their parental lines. The parent C. chinense bears
large fruits and with extreme pungency, while the C. frutescens bears
small and a large number of fruits, with robust plant type and medium
pungency. Since the performance of the plants is determined by the
early establishment and robust growth of plants from the seedling
stage, we chose 60 days old plants for the present study. The developed
F[1] hybrid plants showed heterosis over the parental genotypes for
phenotypic traits studied ([107]Figure 1A). The F[1] plants showed
vigorous performance from early seedlings compared to the plants of
parental genotypes. For example, 29.7% mid-parent heterosis (MPH) and
20.0% better parent heterosis (BHP) were observed for leaf lengths
(LL). In hybrids, leaves were broader than parental genotypes with high
value of heterosis (MPH = 63.2%, BHP = 60.1%) ([108]Figures 1B and 1C).
Furthermore, at the time of the flowering height of parents was 31.5
(Choco) and 53.2 cm (Frut4), respectively, however, hybrids reached to
a height of 83.6 cm with 97.6% MPH and 56.6% BPH. Similarly, for plant
width (PW), upto 80 and 58.8% MPH and BPH, respectively, were observed
in hybrids. At the time of flowering, vigourisity were also observed
for leaf traits like number of leaves (NL; MPH = 95.5%, BPH = 79.2%),
leaf length (LL; MPH = 75.5%, BPH = 52.6%), leaf width (LW; MPH =
84.9%, BPH = 63.7%) in hybrids. These results emphasized that the
heterosis in plants was manifested from the early seedling stage. Thus
we used DNA/RNA from two-month-old plant stage for methylome and
transcriptome analysis.
Figure 1.
[109]Figure 1
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Trait variation observed in F[1] hybrid and their parents
(A) Phenotypic variability observed in adult plants.
(B and C) Phenotypic variability in young plants (two months old). Blue
line showing mid parent value. PH = plant height, PW = plant width,
NBS = number of secondary branches, NL = number of leaves, LL = leaf
length, LW = leaf width, TCC = total chlorophyll content. MPH = mid
parent heterosis, BPH = better parent heterosis.
Whole-genome bisulfite and RNA sequencing of Capsicum hybrid and its parents
It is expected that the methylation of two distinct parental lines
belonging to different Capsicum species might potentially contribute to
the methylome of their F[1] hybrid. Therefore, to obtain an in-depth
understanding of the global dynamics of cytosine methylation/epigenetic
regulation owing to DNA methylation during hybrid formation at
single-base resolution, whole-genome bisulfite sequencing of parental
lines and their hybrid was performed. A total of 1660 million (∼553
million/library including biological replicates) of length 150 bp clean
bisulfite sequencing reads were obtained from parental lines and their
hybrid. Around 1038 million reads from all samples were aligned to the
reference genome with an average mapping rate of 62.54%. Overall,
384825557, 278031457, and 375544686 reads from Choco, Frut4, and hybrid
were uniquely mapped to the C. chinense reference genome, respectively,
thereby providing more than 10X coverage ([111]Table S2A). The
reproducibility of the results was also tested using Pearson
correlation analysis and a high correlation (0.9–0.95) among the
biological replicates of each sample was found ([112]Figure S1). An
average of 0.4–0.5% mapping efficiency of each sample against lambda
DNA reference genome indicated >99% bisulfite conversion efficiency of
sample replicates from parents and hybrids ([113]Table S2B). In
addition, to understand gene(s) expression changes along with methylome
dynamics in the hybrid compared to its parents, RNA sequencing (RNAseq)
was performed using the same leaf tissue used in WGBS. Approximately
476 million of 150 bp clean reads (∼159 million/library including
replicates) were obtained from parents and their hybrid was aligned to
the C. chinense reference genome. On an average, 84.5% reads of Choco,
93.8% of Frut4, and 96.8% reads of the hybrid aligned to the
C. chinense reference genome. ([114]Table S2C).
Global methylation landscape in Capsicum hybrid and its parental lines
The genome-wide dynamics of cytosine methylation at CG, CHG, and CHH
context varied in parental line and their hybrid. Choco showed the
highest global methylation in all three contexts as compared to hybrid
and Frut4. The hybrid showed higher global average methylation in CG
and CHG contexts and lower methylations in the CHH context compared to
parent Frut4 ([115]Figure 2A). Also, the frequencies of mCs in Capsicum
hybrid and its parental lines ranged from 32.8% to 36.02%
([116]Table S3). In particular context, the fraction of mCs observed
was approximately 22.5–24.9%, 31.7–34.9% and 40–45.7% at CG, CHG, and
CHH, respectively, in three genotypes ([117]Figure 2B). Notably,
compared to both the parents, hybrid showed 1.2-fold higher mCs
proportion (24.9 and 34.9%, respectively) at symmetric (CG, CHG)
context, while contrasting to this, it showed 1.12-fold lower mCs
proportion in asymmetric (CHH) context ([118]Figure 2B). Segmentation
of chromosome-wise average methylation showed higher methylation at
symmetric CG and CHG context than asymmetric context throughout the 12
chromosomes in all three genotypes ([119]Figure 2C). Also, at segments
of chromosome (chr) chr2 to chr5, chr7, and chr11, both hybrid and
Frut4 showed slightly higher methylation than Choco. Howbeit, the same
chromosomes in hybrid showed slight decrease in methylation than Frut4
([120]Figure 2C).
Figure 2.
[121]Figure 2
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Global DNA methylation profile observed in hybrid and parental lines
Choco and Frut4
(A) Average methylation, (B) methylated cytosine (mCs) proportion, and
(C) average methylation distribution across 12 Capsicum chromosomes at
CG, CHG, and CHH methylation context.
Methylation pattern at various genomic regions and transposable elements
The pattern of mCs at different genomic regions/elements was analyzed
in hybrid and its parental line ([123]Figures 3 and [124]S2). Both
parental line and hybrid showed the highest average gene-body
methylation (GBM) at CG followed by the CHG context, while lowest at
the CHH context ([125]Figure 3A). At CG context, the level of GBM
looked similar to that in the 2 kb flanking region and was highest in
Choco, followed by hybrid, and lowest in the case of Frut4. The GBM at
CHG and CHH context showed notably less methylation as compared to the
2 kb flanking region of genes. Unexpectedly, the average GBM at CHG and
CHH context was lowest in the hybrid; however, both parental lines
showed similar methylation frequencies ([126]Figure 3A). To avoid the
potential noise (arising owing to transposable elements), the GBM was
segmented into exonic and intronic regions. We observed that
methylation at exon body was lower than its flanking regions, while it
was higher at intron body than its flanking region at both symmetric
and asymmetric methylation contexts in three genotypes
([127]Figures S2A and S2B). On comparing methylations at three
different contexts in hybrid and parents, we found that at CHG and CHH
contexts, both exonic and intronic body methylations were lower in
hybrid than its parents. However, methylation in CG context was at par
with Frut4 in exon, lower and higher than Choco and Frut4, respectively
in intronic regions ([128]Figures S2A and S2B). Genome-wide
proportion/distribution of cytosine methylation was analyzed at
different genomic regions including exons, introns, intergenic, and
promoter regions across 4 different methylation bins categorized based
on percent methylation, i.e. <20%, 20–50%, 50–80%, and >80% DNA
methylation ([129]Figure S2C). At CG, these genomic regions showed a
higher proportion of mCs with >80% methylation in Choco and hybrid than
Frut4. However, with <20% methylation, the hybrid showed a slightly
higher methylation proportion than its parental line across all genomic
elements. Also, within 50–80% methylation bin at CG and CHG context,
both hybrid and Frut4 showed a higher proportion of mCs than Choco
([130]Figure S2C).
Figure 3.
[131]Figure 3
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Metaplots representing methylation distribution at genomic elements and
their flanking regions
(A) gene-body, (B–F) transposable-elements (TEs) body including copia,
gypsy, LINE, SINE, and DNA-elements, respectively, along with their 1.5
kb flanking regions. Methylation at gene/TE -body and flanking regions
was analyzed across 20 and 30 bins, respectively.
In addition, methylation pattern within transposable-elements body
(TE-body) and their 2kb flanking regions was analyzed for long terminal
repeats (LTRs; copia and gypsy), non-LTRs (LINEs and SINEs) and
DNA-elements ([133]Figures 3B–3F). Overall, higher TE-body methylation
than its flanking region was observed at both symmetric (CG, CHG) and
asymmetric (CHH) contexts in parental lines and their hybrid. The
methylation in LTRs at both TE-body and flanking regions was
consistently higher at all contexts ([134]Figures 3B and 3C), while in
non-LTRs and DNA-elements, it was preferentially higher at TE-body than
their flanking regions ([135]Figures 3D–3F and [136]S2D). Across all TE
methylation, at both CG and CHG contexts, hybrid showed lower
methylations than Choco and higher methylation than Frut4, while in the
CHH context, hybrid showed peculiarly lowest TE methylation
([137]Figures 3B–3F). Likewise, in hybrid, at CHG context, SINE
(non-LTRs) and at CHH context all TE (LTRs, non-LTRs, and DNA-elements)
were hypo-methylated than its two parents ([138]Figure S2E).
Altogether, as far as the CG context is concerned, the hybrid had lower
methylation than Choco and higher methylation than Frut4 in all the
genomic regions (GBM, TEs, DNA elements); however, in the CHH context,
hybrid had lower methylations than both the parents. In the case of the
CHG context, hybrid has lower methylations than both the parents in GBM
and SINE, and in COPIA, GYPSY, LINE, DNA elements, and hybrid had lower
and higher methylations than Choco and Frut4, respectively.
Differentially methylated regions in Capsicum parental lines and their hybrid
Analysis of differentially methylated regions (DMRs) between parental
lines (Choco, Frut4) and their hybrid led to the identification of a
total of 70597, 108797, and 38418 unique DMRs at CG, CHG, and CHH
methylation context, respectively ([139]Tables S4, [140]S5, and [141]S6
and [142]Figure S3A). In Choco vs hybrid and Frut4 vs hybrid, around
8.8–9.2% and 10.1–11.2% DMRs in symmetric CG and CHG context,
respectively while, 19.9% DMRs in the CHH context, were uniquely
methylated ([143]Figures S3B–S3D; [144]Table S7A). It was noted that,
in both symmetric contexts, Frut4 had a high number of hypo-methylated
DMRs, while in the CHH context; it had high hyper-methylated DMRs
compared to hybrid and Choco ([145]Figure S3A). Also, hybrid had a low
contribution of DMRs, i.e. 27.7%, 28.3 and 13.9% from CG, CHG, and CHH
context respectively when compared to Choco, indicating hybrid was
hypo-methylated than parent Choco. However, when compared to the other
parent Frut4, hybrid showed an increased contribution of DMRs, i.e.
80.8%, 75.2%, and 15.8% from CG, CHG, and CHH context, respectively,
indicating that hybrid is hyper-methylated than parent Frut4
([146]Table S7B). Then the density of DMRs in hybrid and its parents
was checked across 12 Capsicum chromosomes. It was observed that at CG
and CHG context, the density of hyper DMR was more in Choco vs hybrid,
while it was low in Frut4 vs hybrid and Frut4 vs Choco
([147]Figures S4A–S4C). However, when analyzed at the individual
chromosome level, low-density of hypo DMRs was observed in Choco vs
hybrid across segments of chr2 to chr5, chr7, and chr11 at both
symmetric contexts ([148]Figure S4A). But in Frut4 vs hybrid at CG and
CHG context and in Frut4 vs Choco at CG, CHG, and CHH context, the same
aforementioned chromosome segments showed increased density of
hypo-methylated DMRs ([149]Figures S4B and S4C). After this, the
genomic annotation/distribution of these DMRs was analyzed and observed
that most of the DMRs in hybrid and its parents were from intergenic
regions of the genome ([150]Figures 4A–4C and [151]Table S7C). Of total
DMRs in Choco vs hybrid, around 81.9–87.12%, 3.8–6.7%, and 6.8–11.3%
DMRs were from intergenic, intragenic, and promoter regions
respectively ([152]Figure 4A and [153]Table S7C). Similarly, in Frut4
vs hybrid, of total DMRs, 81.4–89.3%, 3.6–7.7%, and 5.8–10.8% were from
intergenic, intragenic, and promoter regions, respectively
([154]Figure 4B and [155]Table S7C). Also, in Choco vs hybrid, all
intergenic, intragenic, and promoter DMRs were hyper-methylated at all
three methylation contexts ([156]Figures 4A and [157]S5A). However, in
Frut4 vs hybrid and Frut4 vs Choco at CG and CHG context, the
intergenic DMRs were hypo-methylated ([158]Figures 4B, 4C, [159]S5B,
and S5C).
Figure 4.
[160]Figure 4
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Genomic distribution of differentially methylated regions (DMRs) at
three methylation context
Barplots representing DMRs distribution at intergenic, intragenic, and
promoter regions in (A) Choco vs hybrid, (B) Frut4 vs hybrid, and (C)
Frut 4 vs Choco.
Furthermore, we identified a total of 4891 (2206 CG, 2353 CHG, and 332
CHH) common DMRs between hybrids and both of its parents
([162]Table S8.). Based on common DMRs, the predictive level of
methylation in hybrid was estimated against the mean average parental
methylation level or mid-parental methylation values (MPMV). Of common
DMRs, only 33.08% (1618) showed significant different methylation (p
value < 0.01; FDR<0.05) in hybrid from MPMV and DMRs in hybrid having
higher methylation than MPMV were categorized as trans-chromosomal
methylation (TCM), while those having methylation less than MPMV were
categorized as trans-chromosomal demethylation (TCdM). Most of these
DMRs (86.5%) were located in intergenic regions ([163]Table S8).
Furthermore, the percent methylation contribution of both parents in
hybrid as well as newly originated mCs in hybrid were identified. A
total of 77994412 mCs in hybrid were from both parents out of which
78.92% (61551482 mCs) were from Choco and 21.08% (16442930 mCs) were
from Frut4 ([164]Tables S9A and S9B). Also, around 76.5–76.7% mCHH
sites in hybrid were contributed by both parents, while only 8.8–9.1%
mCG and 14.4–14.5% mCHG sites arose from both parental lines.
Additionally, a total of 15523997 new mCs originated in hybrid, which
contributed to 76.99% mCHH, 13.94% mCHG, and 9.07% mCG sites
([165]Tables S9A and S9B).
Allele-specific methylation variations
The significantly methylated alleles (ASM) at single nucleotide
positions were analyzed across the DMRs spanned over various genomic
regions in parental lines and their F[1] hybrid. Around 8803–11379 CG,
10964–13966 CHG, and 4901–7299 CHH SNVs associated with pDMRs
negatively correlated with their corresponding gene expressions were
identified from Capsicum F[1] hybrid and its parental lines. Of these
SNVs, 1449–2338 in Choco, 1310–1783 in Frut4, and 1468–2315 in hybrid
were significantly methylated ASM (adjusted p value <0.05) and were
associated with 523, 753, and 734 pDMRs genes at CG, CHG, and CHH
context, respectively ([166]Figure 5A and [167]Tables S10A–S10C). In
addition, significant methylated ASMs (adjusted p value <0.05)
associated with TCM and TCdM DMRs were also identified in Choco (404
CG, 605 CHG, 282 CHH), Frut4 (1236 CG, 1098 CHG, 244 CHH) and their
F[1]hybrid (3240 CG, 3686 CHG, 340 CHH, [168]Figure 5B and
[169]Tables S10D–S10F). Furthermore, when comparing the ASM between the
hybrid and its parents, a total of 3577 CG, 5130 CHG, and 3916 CHH ASM
associated with promoter DMRs were identified collectively
([170]Figure 5C), while, a total of 4669 CG, 5163 CHG and 680 CHH ASM
associated with TCM and TCdM DMRs were collectively identified from the
parental lines and hybrid ([171]Figure 5D). Furthermore, at CG and CHG
context, the majority of ASM associated with TCM and TCdM DMRs were
from intergenic regions and both parents had comparatively lower number
of ASM than hybrid ([172]Figures 5E and 5F). Although, at CHH context,
the number of intergenic ASMs associated with TCM DMRs was lower than
TCdM DMRs in both parental lines and their F[1] hybrid
([173]Figure 5G). Besides, the ASM showed a differential methylation
pattern between both Capsicum parental lines and their F[1] hybrid. For
instance, ASM with G>A/T alleles in the promoter region of gene
BC332_22173 showed preferentially high methylation in the hybrid
compared to both parents and it was observed that methylation in hybrid
was preferentially affected by the A/T allele from parent Frut4
([174]Figure 6A). Also, the expression of the gene showed the overall
negative correlation with the promoter methylation ([175]Figure 6D).
Another genes such as BC332_29730, BC332_09755, BC332_14352,
BC332_20263 and BC332_23927 with ASM having C>T allele showed
preferential contribution of methylation in hybrid from parental lines
([176]Figures 6B–6F). The ASM associated with the promoter of
BC332_20263 and BC332_23927 genes from the glyoxylate and dicarboxylate
metabolism pathway showed low or no methylation for allele T in parent
Frut4. Also, in hybrid overall methylation for allele T was slightly
lower than mid-parent methylation, while the expression of gene was
also preferentially high in hybrid than in parent Frut4
([177]Figure 6G). Additionally, ASM associated with TCM and TCdM DMRs
showed preferential methylation and demethylation ([178]Figure 7). For
example, in TCdM associated ASM with G>T allele at chr 9
([179]CM008439.1:4821650), the allele T was hypo methylated in hybrid
compared to parent Frut4 ([180]Figure 7A), while in ASM with G>A allele
at chr 10 ([181]CM008440.1:221199113), the allele G was hypo methylated
in hybrid compared to parent Frut4, and the methylation at allele A was
transferred to hybrid from parent Choco ([182]Figure 7B). Similarly, in
TCM-associated ASM with C>T allele, allele T showed hypo-methylation in
both hybrid and parent Frut4 compared to other parent Choco, while
allele C was preferentially hyper-methylated in hybrid compared to both
parental lines ([183]Figure 7C).
Figure 5.
[184]Figure 5
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Summary of allele-specific methylation (ASM) and single nucleotide
variants (SNV) identified in Capsicum F[1] hybrid and its parental
lines at CG, CHG, and CHH methylation context
SNV and identified significant ASM associated with (A) Promoter DMRs
(pDMRs), and (B) trans chromosomal methylation (TCM) and demethylation
(TCdM) DMRs, common and unique ASM from (C) pDMRs and (D) TCM/TCdM
DMRs, (E, F, and G) ASM distribution across the genomic region
(promoter, intragenic and intergenic) at three different methylation
context between the F[1] hybrid and its parental lines.
Figure 6.
[186]Figure 6
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Allele-specific methylation (ASM) associated with promoter
differentially methylated regions (pDMR) genes in Capsicum F[1] hybrid
and its parental lines.
(A–F) Representative ASM locus at CG context associated with
heterozygous SNV sites in DMRs located in promoters region of genes and
(G) expression pattern of genes in both parental lines Choco and Frut4
with respect to F[1] hybrid.
Figure 7.
[188]Figure 7
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Allele-specific methylation (ASM) associated with non-additive trans
chromosomal methylation and demethylation (TCM and TCdM) differentially
methylated regions (DMRs).
Representative heterozygous ASM locus with (A) G>T allele and (B) G>A
allele associated with TCdM DMRs while (C) C>T allele associated with
TCM DMRs in Capsicum F[1] hybrid and its parental lines.
Expression profiling in Capsicum hybrid and its parents
The expression profiling of transcripts and differential expression of
genes between the Capsicum hybrid and its parents (Choco and Frut4) was
analyzed using RNAseq data. A total of 6875 genes were significantly (p
value < 0.001 and FDR <0.01) differentially expressed (DE-Gs) between
hybrid and its parents. A total of 2003 (1083 up-regulated; 920
down-regulated) genes were DE-Gs between Choco vs hybrid and 4815 DE-Gs
(2187 up-regulated; 2628 down-regulated) in Frut4 vs Hybrid, while 4316
DE-Gs (1924 up-regulated; 2392 down-regulated) in Frut4 vs Choco, were
significantly expressed ([190]Table S11). Furthermore, it was observed
that these DE-Gs were significantly enriched (adjusted p value < 0.01)
in different pathways, including photosynthesis (ko00195), glyoxylate
and dicarboxylate metabolism (ko00630), photosynthesis-antenna proteins
(ko00196), carbon metabolism (ko01200), retinol metabolism (ko00830),
and ubiquinone and other terpenoid-quinone biosynthesis (ko00130)
([191]Table S12A). Also, gene ontology (GO) terms from biological
processes (BP) such as photosynthesis and light harvesting (GO:0009765,
GO:0015979), transport of inorganic anion (GO:0015698), precursor
metabolites and energy generation (GO:0006091) and organic acid
catabolic process (GO:0016054) were found to be significantly enriched.
Although GO terms related to the photosystem I and II (GO:0009521,
GO:0009523, GO:0009522) under cellular component (CC) and GO terms such
as those related to binding of carbohydrate, chlorophyll,
monosaccharide (GO:0030246, GO:0016168, GO:0048029) and related to
protein serine/threonine kinase activity (GO:0004674) were
significantly enriched (p value < 0.01; FDR<0.05) under molecular
function (MF) category ([192]Table S12B).
Correlation between methylation instances and expression of genes
Karl Pearson’s correlation analysis was performed to understand the
correlations between the overall expression of genes and their average
methylation in Capsicum hybrid and its parents Choco and Frut4.
Overall, a significant negative correlation (R = −0.16 to −0.22; p
value < 0.001) between the expression of genes and their CG and CHG
methylation instances was observed in all the samples ([193]Figures 8A
and 8B). However, no negative correlation was observed at CHH
methylation ([194]Figure 8C). Furthermore, pDMRs were screened for
their associated genes, and a total of 4332, 4782, and 4127 pDMRs
underlying in 3154, 3476, and 3213 genes were identified at CG, CHG,
and CHH context, respectively, between hybrid and its parental lines
([195]Tables S13, [196]S14, and [197]S15). Furthermore, 15.3–24.25%
pDMR-Genes at CG, 13.8–21.64% pDMR-Genes at CHG and 15.54–25.62%
pDMR-Genes were significant DE-Gs between hybrid and its parental
lines. Also, only 55 CG, 49 CHG, and 3 CHH pDMRs were common in hybrid
and its parental lines ([198]Figures 8D–8F). Out of total pDMRs, 1052
(662 hyper, 390 hypo) CG, 1122 (598 hyper, 524 hypo) CHG, and 1123 (846
hyper, 277 hypo) CHH pDMRs were identified in Choco vs Hybrid
([199]Table S7C). In Frut4 vs hybrid, a total of 1459 (453 hyper, 1006
hypo) CG, 1622 (826 hyper, 796 hypo) CHG, and 1307 (973 hyper, 334
hypo) CHH pDMRs were identified, while, in parents (Frut4 vs Choco), a
total of 2940 (809 hyper, 2131 hypo) CG, 3151 (1252 hyper, 1899 hypo)
CHG and 2379 (1190 hyper, 1189 hypo) CHH pDMRs were identified
([200]Tables S13, [201]S14, and [202]S15). Additionally, a total of
1854 (496 with DE-Gs) CG pDMRs, 1960 (532 with DE-Gs) CHG pDMRs, and
1800 (463 with DE-Gs) CHH pDMRs showed a negative correlation with the
expression of genes between Choco vs hybrid, Frut4 vs hybrid and Frut4
vs Choco comparisons ([203]Tables S13, [204]S14, and [205]S15 and
[206]Figures S6A–S6C), respectively. Moreover, these negatively
correlated DEG pDMR-Genes were significantly enriched (adjusted p
value < 0.01) in pathways ([207]Table S16A), including photosynthesis
(ko00195), oxidative phosphorylation (ko00190) as well as were
significantly enriched (p value < 0.01; FDR<0.05) in several GO terms
such as those related to hydrogen and proton transports (GO:0006818,
GO:0015992, GO:1902600) under BP, transmembrane transporter activity of
monovalent inorganic cation and hydrogen ions (GO:0015077, GO:0015078)
under MF and mitochondrial inner membrane (GO:0005743), organelle
envelope (GO:0031967) under CC ([208]Figures S7 and [209]S8A–S8C;
[210]Table S16B).
Figure 8.
[211]Figure 8
[212]Open in a new tab
The correlation of promoter methylation with gene(s) expression
Scatter plot showing a correlation between promoter methylation and
gene expression in (A) Choco, (B) Frut4 and (C) hybrid at CG, CHG, and
CHH context. Venn diagram representing common and unique promoter DMRs
along with their gene count (in red text) among at (D) CG, (E) CHG and
(F) CHH methylation context.
qRT-PCR expression analysis
The expression of 24 DE-Gs which showed a negative correlation with
their promoter methylation at CG, CHG, and CHH context was validated
using qRT-PCR in hybrid and its parental lines. Of the 24 genes, 22
(91.66%) showed similar expression patterns with their respective
RNAseq expression data ([213]Figure 9A). The expression of these genes
was higher while promoter methylation was lower in hybrid than both
parents Choco and Frut4. Genes such as Cellulose synthase A catalytic
subunit 9 (BC332_17838), Nudix hydrolase 8 (BC332_20283), Dead-box
ATP-dependent RNA helicase 9 (BC332_18776), and Glycerol-3-phosphate
dehydrogenase (BC332_12420) at CG context, Bifunctional
aspartokinase/homoserine dehydrogenase 1 (BC332_02193), ATP-dependent
zinc metalloprotease FtsH (BC332_10767), Photosystem II reaction center
W protein (BC332_17671), Eceriferum 3 (BC332_18054), hypothetical
protein BC332_20287, Chlorophyll a-b binding protein 3C (BC332_21229),
hypothetical protein BC332_22614, Bifunctional enolase
2/transcriptional activator (BC332_22856), Diacylglycerol kinase 5
(BC332_25145), hypothetical protein BC332_28523, and Elongation factor
1-gamma 2 (BC332_29084) at CHG context, while Leucine-rich repeat
receptor-like protein kinase PXL2 (BC332_03097), protein AUXIN
SIGNALING F BOX 3 (BC332_04750), Chlorophyll a-b binding protein of
LHCII type III (BC332_07524), 3-ketoacyl-CoA synthase 11 (BC332_10084),
protein ASPARTIC PROTEASE IN GUARD CELL 2 (BC332_12969), putative
peroxygenase 5 (BC332_13123), CBL-interacting protein kinase 5
(BC332_17800), and NAD(P)H-quinone oxidoreductase subunit H
(BC332_27111) at CHH context, had significantly (q-value <0.001) high
promoter methylation in both Choco and Frut4 compared to hybrid. Also,
genes such as Photosystem II protein D1 (BC332_02125) at CG and CHG
context, Chlorophyll a-b binding protein of LHCII type III
(BC332_07524) at CHH context, had significantly (q-value <0.001) high
promoter methylation in Frut4 compared to Choco. The qRT-PCR expression
trend of these genes (except BC332_17838, BC332_17671 at CG and CHG in
Frut4 vs Hybrid) between hybrid and both parents was similar to their
RNAseq expression data. Also, the qRT-PCR expression of all genes was
significantly different (p value < 0.05, p value < 0.01 and p
value < 0.001) among samples, except for genes BC332_27111 in Choco vs
hybrid, BC332_29084 in Frut4 vs hybrid and BC332_2125 in Frut4 vs Choco
- which did not show a significant difference in their expression
([214]Figure 9A).
Figure 9.
[215]Figure 9
[216]Open in a new tab
Gene expression observed in quantitative real-time (qRT) PCR analysis
(A) Twenty-four (24) significantly (p value <0.01) differentially
expressed genes (DE-Gs) showing negative correlation with promoter
methylation in parental line Choco, Frut4 and their hybrid. Genes
showing qRT-PCR expression similar to their RNAseq data were
represented in blue boxes. LFC represents expression in log2 fold
change and significant p values were denoted by ∗ <0.05; ∗∗ <0.01; ∗∗∗
<0.001.
(B) Differential expression pattern of DNA methyltransferase and
demethylase genes in parental lines Choco and Frut4 compared to F[1]
heterotic hybrids analyzed using RNA sequencing (RNA-seq) and qRT-PCR
expression data. Letters a, b, and c shown on bar indicate the
significant expression difference of a gene between each parent and
hybrid with p value less than 0.001, 0.01, and 0.05, respectively.
Additionally, we have examined the expression patterns of 10 genes
belonging to enzymes including DNA methyltransferases (METs),
chromomethylases (CMTs), demeter-like (DML), and domain rearranged
methyltransferases (DRMs) using qRT-PCR and RNA-seq analysis
([217]Figure 9B). We observed similar expression patterns of 8 out of
10 genes in both the expression analysis. The expression pattern of
genes such as CcMET1 (BC332_12132) and CcDRM5-like 1 (BC332_03361) was
higher in parental lines compared to F[1] hybrid and was significantly
different between Choco-vs hybrid and Frut4-vs-hybrid (p value <0.001;
p value <0.01). Similarly, but opposite expression pattern (low in
parental lines than hybrid) of genes including CcDRM6-like
(BC332_13992), CcDML1-like (BC332_22864), CcCMT2-like (BC332_20529) and
CcCMT3-like (BC332_33051) was observed.
Significant metabolites in hybrid
Our GC-MS analysis identified more than 100 metabolites, of which only
71 were found in both parents and hybrid were used for further
analysis. The overall changes in metabolic content between parents and
their hybrid were analyzed in term of log2 fold change or ratio of
normalized area. Most commonly altered metabolites in hybrid compared
to parental genotypes were amino acids and their derivatives, and
carboxylic acid and sugar derivatives groups. For instance, L-proline,
L-serine, L-threonine, L-5-oxoproline, 1-amino-propan-2—Ol and
4-aminobutanoic acid from the amino group, 1,2,3-propanetricarboxylic
acid from the carboxylic group and galactinol from sugar derivatives
were significantly different in hybrid compared to parents
([218]Figure 10). Also, metabolites such as octanoic acid, sucrose,
palmitic acid, quininic acid, cyclohexane, D-fructose, and silanol were
significantly higher (p > 0.001) in the parent Choco than the hybrid,
while most of the sugar and its derivatives including D-fructose,
D-glucitol, sucrose, D-psicofuranose, and amino acid L-threonine were
significantly higher in hybrid compared to the parent Frut4
([219]Figure 10A). Moreover, we have observed that two pathways namely
glyoxylate and dicarboxylate metabolism and glycine, serine, and
threonine metabolism were most significantly (p value <0.01) enriched
([220]Figures 10B and 10C). In hybrid, metabolites such as glycine,
L-threonine, succinate, and 2-oxoglutarate showed significantly (p
value < 0.05 & p value < 0.01) high response ratio compared to both the
parental genotypes, while metabolites L-serine, glyceric acid, and
D-glycerate showed low response ratio than in both the parental
genotypes ([221]Figures 10D–10J). In addition, few metabolites showed
slightly higher content in the F[1] hybrid compared to both parents but
were not significantly different from either or both of the parental
genotypes. For example, the content of 2-ketoglutaric acid
(2-oxoglutarate) was higher in hybrid compared to both parents but was
not significantly different ([222]Figures 10A and 10J). Likewise, the
content of metabolite butanedioic acid (succinate) was higher in the F1
hybrid than both parental genotypes but was only significantly
different (p value <0.01) compared to parent Choco ([223]Figures 10A
and 10I).
Figure 10.
[224]Figure 10
[225]Open in a new tab
Global metabolite profiling in hybrid and parental genotypes
(A) Heatmap representing metabolite changes in term of log2 fold change
(ratio) of normalized area, (B) pathway enrichment of metabolites
commonly identified in hybrid and parental genotypes, (C) pathway map
of significantly enriched pathways, and (D–J) metabolites with
significantly high and low response ratio compared to both parents
Choco and Frut4. Metabolite response difference between Choco vs.
hybrid, Frut4 vs hybrid and Fru4 vs. Choco are represented as a, b, and
c, respectively and the significant level are indicated as ∗ for p
value <0.5, ∗∗ for p value <0.01 and ∗∗∗ for p value <0.001.
Correlation analysis of promoter methylation with the expression of genes and
metabolites
The integrated analysis between significant DE-Gs with their promoter
methylation and metabolites biosynthesis pathway was performed to find
the plausible impact of expression of genes and/or promoter methylation
in Capsicum hybrid and parental genotypes. Our analysis observed the
expression of 43 significant DE-Gs which were enriched in glyoxylate
and dicarboxylate metabolism pathways. Of the total, 28 and 31 DE-Gs
showed increased or higher expression in F[1] hybrid than parent Choco
and Frut4, respectively ([226]Figure S9). Also, the expression of 28
DE-Gs was higher in hybrid than the mid-parent expression value. Few
genes including Glycerate dehydrogenase, Glutamine synthetase, Glycine
cleavage system H protein, Aminomethyltransferase, Aconitate hydratase,
and Serine hydroxymethyltransferase showed 1-3 fold higher expression
than mid-parent expression values, while genes such as ribulose
bisphosphate carboxylase, and Malate dehydrogenase showed 2-47 fold
higher expression than mid-parental expression value. Furthermore, the
promoter regions of these genes was scrutinized for methylated cytosine
which revealed that the upstream promoter regions of 14 genes including
Glutamine synthetase, Glycine cleavage system H protein, Serine
hydroxymethyltransferase, ribulose bisphosphate carboxylase, and Malate
dehydrogenase were less/low methylated than mid-parental methylation
value (MPMV) and hence showed higher gene expression of those genes
compared to the mid-parent expression values ([227]Figure S9).
Discussion
Hybrid breeding is one of the most preferred methods in many crop
plants owing to its heterotic performance and higher yield, among many
advantages. However, the detailed mechanism of the heterotic
performance of F[1] hybrids compared to parental lines is not still
understood well especially with respect to the DNA methylation and its
correlation with the expression of genes and metabolites. In this
study, we developed an interspecific hybrid by crossing genotypes
(Choco and Frut4) belonging to two different Capsicum species and found
heterosis in the developed hybrid ([228]Figure 1). Through earlier,
different genetic models like dominance and overdominance hypothesis
have been proposed to explain hybrid vigour/heterosis in F[1] hybrids
([229]Jones, 1917; [230]Crow, 1948, [231]1999; [232]Schnable and
Springer, 2013); however, these models do not provide sufficient
explanation or prediction of heterosis. Recently, the role of DNA
methylation in hybrid vigour has also been reported in several
important plants, including Arabidopsis ([233]Shen et al., 2012;
[234]Kawanabe et al., 2016), tomato ([235]Raza et al., 2017), rice
([236]He et al., 2010; [237]Chodavarapu et al., 2012), pigeon pea
([238]Junaid et al., 2018; [239]Sinha et al., 2020), and Populus
([240]Gao et al., 2014). Using methylation-sensitive amplified
polymorphism (MSAP) analysis, [241]Xu et al. (2015) reported the
adjustment of methylation patterns in heterotic reciprocal heterotic
hybrids of two hot peppers. In the present study, we conducted an
integrated high-resolution mapping of genome-wide DNA methylation at
single-base resolution in interspecific Capsicum hybrid and its
parental genotypes. This study also identified gene(s) expression
signatures and showed expression correlation with their promoter
methylation in both parental lines and their F[1] hybrid. Therefore,
this study may prove to be a useful asset for research and
investigations of molecular mechanisms influencing the heterotic
phenomenon in Capsicum.
DNA methylations are highly variable in three different contexts i.e.
CG, CHG, and CHH across the different plant species ([242]Alonso
et al., 2015; [243]Niederhuth et al., 2016; [244]Takuno et al., 2016).
For instance, B. vulgaris showed maximum (∼81%) methylations at CHG;
however, Eutrema salsugineum showed the lowest (9.3%) methylation at
CHG context ([245]Niederhuth et al., 2016). In the case of tomato, CG
methylations were prominent (71.6–72.8%) followed by CHG (52.5–53.0%)
and CHH (10.7–12.5%) methylations ([246]Zuo et al., 2018). Earlier
82.8–89.6% CG, 77.8–83.9% CHG, and 22.4–25% CHH methylation was
reported in fruits of three different Capsicum species, i.e. Capsicum
annuum, C. chinense, and C. frutescens ([247]Rawoof et al., 2020). The
present study also identified similar methylation i.e. 87.9–90.6% CG,
78–83.7% CHG and 17.2–21.1% CHH methylation context in leaves of hybrid
and its parental lines ([248]Figure 2A). In Arabidopsis, it was
reported that CMT2 and RNA-directed DNA methylation (RdDM) facilitate
and maintain methylation in the CHH context ([249]Zemach et al., 2013).
In hybrid, it was observed that the fractional proportion of CHH
methylation was the lowest than both Choco and Frut4 parental lines,
which suggested that CMT2 and RdDM mediated CHH methylation instances
were less active in Capsicum hybrid ([250]Figure 2B). Patterns of DNA
methylation are ubiquitous in nature and occur throughout the genome,
including genic regions, inter-genetic regions, transposable elements;
DNA elements and so forth and their density/distribution across these
regions may provide biological information regarding functional
processes and methylation regulation ([251]Takuno and Gaut, 2012,
[252]2013). Furthermore, it was reported that promoter methylation
affects the expression/transcription of genes. Also, high CHG and CHH
methylation in flanking regions than gene-body was reported in fruits
of Capsicum ([253]Rawoof et al., 2020). In Arabidopsis and rice, high
CHG methylation at GBM along with flanking regions was observed with
low transcript/gene expression ([254]Saze et al., 2008; [255]Zemach
et al., 2010; [256]Klosinska et al., 2016). A similar GBM pattern was
observed in Capsicum hybrid and its parental lines Choco and Frut4
([257]Figure 3A). However, in pur study, the hybrid showed the lowest
CHG and CHH GBM compared to both parental lines, suggesting methylation
via RdDM pathway is less active in the Capsicum hybrid. One of the most
important functions of DNA methylation is to stabilize transposable
elements (TEs) ([258]Chan et al., 2005; [259]Law and Jacobsen, 2010).
In this study, it was found that TE body along with flanking region of
the majority of TEs including LTRs, non-LTRs, and DNA elements were
densely methylated ([260]Figures 3B–3F and [261]S3), suggesting their
possible role in genome stability. Methylation at both TE-body and TE
flanking regions regulates transposon silencing ([262]Inagaki and
Kakutani, 2012). It was observed that TE-body methylation was higher
than GBM ([263]Figures 3 and [264]S3), which was similar to earlier
studies ([265]Rawoof et al., 2020; [266]Sinha et al., 2020); however,
at CHH context, methylation in both GBM and TEs is lower in Capsicum
hybrid than its parents Choco and Frut4, suggesting that de novo
maintenance of CHH methylation instances in TEs and GBM via CMT2
pathway is less active in Capsicum hybrid.
The interaction between parental genomes and epigenomes within the
nuclei of hybrid alters the cytosine methylation patterns
([267]Chodavarapu et al., 2012; [268]Greaves et al., 2012; [269]Shen
et al., 2012). These alterations of mCs occur at particular chromosomal
segments/regions which are differentially methylated (DMRs) between
hybrid and parents ([270]Greaves et al., 2014). In this study, we
observed that at CG and CHG context, hypo and hypermethylated DMRs were
the most abundant in hybrid when compared with parent Choco and Frut4,
respectively ([271]Figures S3 and [272]S4), while at the CHH context,
hybrid had a higher abundance of hypo DMRs than both parents
([273]Figures S3 and [274]S4). It was reported that DNA methylations
are associated with regulatory function and are more prominent in
intergenic regions than in genic regions ([275]He et al., 2010). In
this study, the genomic distribution of DMRs showed that the majority
of DMRs in Capsicum hybrid and its parental lines belonged to the
intergenic regions, followed by promoter regions and genic regions
([276]Figures 4 and [277]S5), which indicated their potential role in
gene regulation and heterosis ([278]Zhao et al., 2007; [279]Jin et al.,
2008; [280]He et al., 2010; [281]Greaves et al., 2012; [282]Sinha
et al., 2020).
There are two types of genetic regulators, first consisting of
cis-acting regulators including promoter sequences, and the other being
trans-acting regulators like transcription factors ([283]Springer and
Stupar, 2007). It has been suggested that trans-acting elements are
mainly involved in non-additive variations; however, additive
variations may be caused by both cis- and trans-acting elements
([284]Swanson-Wagner et al., 2006; [285]Springer and Stupar, 2007;
[286]Guo et al., 2008; [287]He et al., 2010). The non-additive
methylation changes in Capsicum hybrid were attributed to TCM and TCdM
whereas compared to the parental segments; methylation in hybrid was
higher in case of TCM and lower in case of TCdM ([288]Greaves et al.,
2014). Both TCM and TCdM are considered major epigenetic factors
driving wide changes in hybrid methylome; however, their possible role
in transcript expression regulations in heterotic hybrids remained
unclear ([289]Greaves et al., 2014). During the present study, 4891 TCM
(2272) and TCdM (2619), majorly located in intergenic regions of the
genome, were identified in Capsicum hybrid, and only 33.08% (1618) were
significantly different from mid-parent-methylation ([290]Table S8),
suggesting significant trans-acting effects in Capsicum hybrid that may
play an important role in heterosis.
In plants, the methylation of the DMRs in the promoter of genes not
only involved in the alteration of gene expression but is also used to
understand the maintenance of parental variations in hybrid
([291]Zemach et al., 2010; [292]Ma et al., 2021). This study identified
several allelic methylation associated with pDMR gene which was
preferentially methylated in heterotic Capsicum hybrid ([293]Figures 5,
[294]6, and [295]7). It was reported that the genetic diversity of
parental genomes even at single nucleotide polymorphism might impact
the expression of functional genes in hyrbid owing to the expression of
either of the parental allele and thus may contribute to heterosis
([296]Botet and Keurentjes, 2020; [297]Zebell, 2021). This study
observed that the expression of Malate dehydrogenase (BC332_23927) gene
from glyoxylate and dicarboxylate metabolism pathway in F[1] hyrbid was
higher than mid-parent expression, while its promoter region was
hypo-methylated than mid-parent methylation ([298]Figures 6F and
[299]S9). Additionally, the allele T with ASM (C>T) was preferentially
high methylated than one of the parental alleles from Frut4
([300]Figure 6F). Likewise, another gene Glycine cleavage system H
protein (BC332_20263) showed significantly higher expression in hybrid
than both the parental lines ([301]Figure 6G), while in its promoter
region, methylation of allele T with ASM (C>T) was contributed from
parental allele from Choco ([302]Figure 6E), suggesting that parental
allele associated with pDMRs with their corresponding gene expression
might be involved in heterosis, however, its molecular mechanism
remains elusive. Earlier in rice, it was reported that parental alleles
associated with CG and CHG DMRs were stably transferred in hybrid
([303]Ma et al., 2021). Therefore, to get insight into the conservation
and transfer of the parental DMRs (TCM & TcdM) in the Capsicum hybrid,
this study analyzed the methylation at the single base allele (ASM)
associated with these TCM and TCdM DMRs in hybrid and its parental
lines ([304]Figures 7A–7G). This study observed that at both CG and CHG
contexts, high number of ASM were associated with TCM and TCdM DMRs,
suggesting that the variations at CG and CHG methylation contexts are
substantially maintained for parental alleles in F[1] Capsicum hybrids,
which is in concordance with the previous finding.
The stability of newly formed methylation instances in F[1] hybrid and
the inheritance of methylated cytosines from parental lines to
successive generations can be assessed using WGBS at single base
resolution ([305]Becker et al., 2011; [306]Schmitz et al., 2011;
[307]Van Der Graaf et al., 2015). In Arabidopsis, the inheritance of
∼45% of newly methylated sites was stable and maintained between
generations ([308]Hofmeister et al., 2017). In Capsicum hybrid, the
majority of mCs (78.9%) were inherited from parent Choco, while only
21.1% were inherited from Frut4 ([309]Table S9), suggesting major mCs
in hybrid were inherited from parent Choco. The use of Choco as female
parent in the development of hybrid could be one of the reasons for the
higher proportion of mCs (78.9%) from Choco than Frut4. Furthermore,
only a small fraction (9% of total inherited mCs) of newly formed
methylated sites was identified in hybrid and of which ∼76% of newly
formed mCs belonged to the CHH context and only ∼23% mCs originated at
CG and CHG context ([310]Table S9). Altogether, our data suggested that
although the majority of methylations are stanchly inherited across the
generations as suggested previously ([311]Zhang et al., 2008;
[312]Becker et al., 2011; [313]Van Der Graaf et al., 2015;
[314]Hofmeister et al., 2017), however, newly formed methylations and
demethylation events in hybrid may play a possible role in providing
heterosis to the plants which need to be further confirmed.
Hitherto, a number of studies have suggested that DNA methylation may
differently regulate the transcript expression in hybrids and may
contribute to the heterosis ([315]Greaves et al., 2015; [316]Zhang
et al., 2016; [317]Raza et al., 2017; [318]Shen et al., 2017;
[319]Junaid et al., 2018; [320]Sinha et al., 2020). Therefore, to
understand the role of DNA methylations on gene expressions, we
developed a complex of dynamic methylome and transcriptome and the
associated gene functions; and thus conducted transcriptome analysis of
the same samples. In Capsicum hybrid, ∼46% significant DE-Gs were
up-regulated compared to parent Choco, while ∼55–56% significant DE-Gs
were up-regulated in both hybrid and Choco compared to the other parent
Frut4 ([321]Table S11). Also, it was observed that several DE-Gs with
higher expression in hybrid were having low promoter methylation than
both parental genotypes, suggesting methylation may involve in
expression regulation during the manifestation of heterosis in
Capsicum. For instance, in hybrid DEG DEAD-box ATP-dependent RNA
helicase which was reported to be involved in plant development and
abiotic stress responses ([322]Liu and Imai, 2018; [323]Macovei et al.,
2012) was observed with higher expression. Similarly, DEG D. kinase
(DGK) which is a key enzyme involved in lipid signaling, signal
transduction from hormones, growth factors, and in build-up metabolic
network in responses to several stresses ([324]Kue Foka et al., 2020),
was also found to be highly expressed in Capsicum F[1] hybrid in both
parental genotypes. Likewise, in hybrid around 2-fold increased
expression of DEG B. enolase 2/transcriptional activator which is
important for plant growth and development ([325]Eremina et al., 2015)
was observed than both parents ([326]Figure 9A). In Arabidopsis,
heterotic phenotypes showed an increment in the total amount of
photosynthesis than parental lines ([327]Fujimoto et al., 2012;
[328]Kawanabe et al., 2016). This study observed that
photosynthesis-related gene Chlorophyll a/b binding protein of
Light-Harvesting Complex (LHC) II was highly expressed in hybrid (4–11
LFC) than both parents and at the same time it showed low promoter
methylation than MPMV of both parents suggesting increased
photosynthesis in heterotic F1 hybrid with promoter methylation may
interplay during heterosis in Capsicum ([329]Figure 9A). The enrichment
analysis showed that DE-Gs in Capsicum hybrid and parental lines were
significantly enriched in pathways and GO terms related to
photosynthesis, glyoxylate and dicarboxylate metabolism, and metabolite
biosynthesis ([330]Table S12), which was similar to earlier reports in
hybrids ([331]Fujimoto et al., 2012; [332]Kong et al., 2020; [333]Li
et al., 2020a, [334]2020b).
In this study, we also observed significant enrichment of several
metabolites from sugar and sugar derivatives, amino acid and their
derivatives, and carboxylic acid group between hybrid and parental
genotypes ([335]Figure 10). A similar observation was reported by
recent studies on Capsicum hybrids wherein they observed the increased
metabolite (mainly sugar, citric acid, and capsaicinoids) content in
hybrids compared to parental genotypes ([336]Zamljen et al., 2020;
[337]Shiragaki et al., 2021). Also, our metabolite profiling analysis
showed that metabolites related to glyoxylate and dicarboxylate
metabolism pathway were most enriched (p value < 0.01) between Capsicum
hybrid and parents ([338]Figure S8; [339]Table S12), and it was
observed that the expression of genes (∼65–72% of enriched genes)
related to this pathway were also higher in F[1] hybrid than mid-parent
average expression values of parental genotypes ([340]Figure S9). The
promoter methylation analysis showed that around 32.6% of total
significant DE-Gs enriched in glyoxylate and dicarboxylate pathway were
having low promoter methylation than MPMV and increased expression than
both parental genotypes ([341]Figure S9), which suggested that,
methylation in hybrid might potentially involve in the regulation of
gene expression thereby increasing certain metabolite content in hybrid
leading to early heterosis in Capsicum F[1] hybrid.
Additionally, the overall significant negative correlation of promoter
methylations with gene expression ([342]Figure 8) suggested the overall
repressive nature of DNA methylations which is also widely reported in
different plant species ([343]Zilberman et al., 2007; [344]Zemach
et al., 2010; [345]Lang et al., 2017; [346]Raza et al., 2017). Earlier,
it was reported that promoter CHH methylation positively correlated
with the gene expression ([347]Bhatia et al., 2018; [348]Rawoof et al.,
2020) and similar results were observed in Capsicum hybrid and parental
lines; however, the molecular mechanism behind this correlation is
still unknown. To get insight into the regulation of expression in
hybrid, we investigated the promoter DMR (pDMR) of genes and observed
that the majority of genes showing increased expression had
low/decreased promoter methylation in the hybrid compared to their
parents ([349]Figure S6). Also, these pDMR DE-Gs were significantly
enriched in photosynthesis and oxidative phosphorylation-related
pathways ([350]Table S16; [351]Figures S7 and [352]S8), suggesting DNA
methylation in Capsicum hybrid may be involved in enhanced
photosynthesis and may contribute to heterosis, which further needs to
be investigated. Furthermore, we have validated the expression of
randomly selected 24 DE-Gs which notably have low promoter methylation
and high expression in hybrid compared to both parental lines
([353]Figure 9A). The qRT-PCR expression analysis also showed that most
of these genes had significant differential expression in hybrid, which
was much more than that observed in both parental lines and suggested
that promoter methylation in Capsicum hybrid is correlated with altered
expression of genes.
In plants, the establishment of DNA methylation at all context is
carried out by DNA methyltransferase Domain Rearranged
Methyltransferase 2 (DRM2) via siRNA-guided RdDM pathways, while,
methylation maintenance at CG, CHG, and CHH context is carried out by
DNA methyltransferase 1 (MET1), chromomethylase 3 (CMT3), and CMT2,
respectively. Additionally, the demethylation of methylated cytosine is
actively arbitrated by several DNA demethylases including demeter
(DME), demeter-like (DML), and repressor of silencing 1 (ROS1)
([354]Liang et al., 2019). Therefore, to understand the expression
dynamics of the DNA methylase and demethylase genes, we have analyzed
the expression of 10 different genes (1 MET1, 3 DRM, 3 DML, and 3 CMT)
using RNA-seq and qRT-PCR analysis ([355]Figure 9B). Of these, 8 genes
including CcMET1-like (BC332_12132), CcDRM5-like 1 (BC332_03361),
CcDRM6-like (BC332_26991), CcDML1-like (BC332_22863), CcDML3-like
(BC332_29933), CcCMT2-like (BC332_20529), CcCMT3-like (BC332_33051),
and CcCMT4-like (BC332_01667) showed similar expression trends among
the samples in both RNA-seq and qRT-PCR analysis. We observed that
compared to F[1] hybrid, both the parents (Choco and Frut4) showed the
upregulation of CcMET1-like, while CcCMT4-like was upregulated in
parent Choco and downregulated in Frut4 compared F[1] hybrid. Also, in
Arabidopsis hybrids generated from met1-RNAi knockdown, it was observed
that MET1 is not involved in heterosis ([356]Kawanabe et al., 2016). In
this study, we observed that the high expression of MET1 and CMT4 with
relatively low CG and CHG methylation in F[1] hybrid than parental
lines and their role in heterosis needs further investigation.
Furthermore, the increased expression of CcCMT2-like than the
mid-parent expression and additional newly formed mCs (9% of total
inherited mCs), chiefly from CHH context was observed in the F[1]
hybrid ([357]Table S9). Previously, it was reported that in addition to
CHH methylation maintenance via RdDM, CMT2 along with a decrease in DNA
methylation1 (DDM1) can alternatively also be involved in the
generation of new methylation marks ([358]Greaves et al., 2015;
[359]Zemach et al., 2013) and in corroboration with, our observation
suggests that CMT2 plausibly might be involved in the establishment of
new mCs partially in F[1] Capsicum hybrid, which in turn might lead to
heterosis.
In conclusion, the present study identified the inheritance pattern of
DNA methylation marks from parent to hybrids. Some of the regions were
hyper/hypo methylated with significant MPMV in hybrids as compared to
parental genotypes. Expression dynamics and global metabolite profiling
suggested the potential role of cross-talk between the three components
(methylation, expression of genes, and metabolites) in the development
of early heterosis in the F[1] hybrid of Capsicum. The expression
analysis of genes identified a significant number of DE-Gs in hybrids
which overall showed negative correlations with the promoter
methylation. Furthermore, our metabolite profiling showed significantly
higher expression of metabolites such as glycine, carboxylic acid,
D-fructose, D-glucitol, sucrose, D-psicofuranose, and L-threonine in
hybrid. Glyoxylate and dicarboxylate metabolism pathway was
significantly enriched for metabolites and DE-Gs in F[1] hybrid and
parental lines. Of the total, 65–72% enriched genes in this pathway
showed overall increased expression (of these 32.6% with low promoter
methylation than MPMV) in F[1] hybrid than mid-parent value.
Altogether, the present study provided insightful dimensions into the
plausible integrated role of DNA methylation, and expression of genes
and metabolites toward the early heterosis in Capsicum hybrid.
Limitations of the study
Out of two Capsicum spp used to develop hybrid, the reference genome
was available only for C. chinense, and thus present study might escape
the detection of some essential epigenomic regions associated with
heterosis that varies among both parental genomes (such as SNP/InDels)
can be explored in future on the availability of reference genome of
C. frutescens. Secondly, the present study focused on early-stage
heterosis, however, hybrid vigor for fruit characters is also a
potential area to be explored.
STAR★Methods
Key resources table
REAGENT or RESOURCE SOURCE IDENTIFIER
Biological samples
__________________________________________________________________
Capsicum chinense (Choco) This study N/A
Capsicum frutescens (Frut4) This study N/A
Capsicum F1 Hybrid (Choco X Frut4) This study N/A
__________________________________________________________________
Chemicals, peptides, and recombinant proteins
__________________________________________________________________
Acetone Sigma-Aldrich 34850
CTAB Sigma-Aldrich H5882
Zymo EZ-DNA Methylation-Gold Kit Zymo Research D5005
NucleoSpin RNA plant Kit Macherey-Nagel 740949.50
Illumina TruSeq RNA sample preparation kit Illumina RS-930-2001
PrimeScript IV 1^st strand cDNA Synthesis Mix TaKaRa Bio 6215A
TB Green Premix Ex Taq II Master Mix TaKaRa Bio RR820L
Methanol Sigma-Aldrich 34860
Adonitol (Adonite, Ribitol) Sigma-Aldrich A5502
Methoxyamine hydrochloride MP Biomedicals 02155405-CF
Pyridine Sigma-Aldrich 360570
N-Methyl-N-(trimethylsilyl) trifluoroacetamide Sigma-Aldrich 69479
__________________________________________________________________
Deposited data
__________________________________________________________________
Raw Data for WGBS and RNA sequencing This study PRJNA770309
Capsicum chinense reference genome ASM227189v2 NCBI ([360]Kim et al.,
2017)
[361]https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/271/895/GCA_00227
1895.2_ASM227189v2/
__________________________________________________________________
Oligonucleotides
__________________________________________________________________
Gene specific Primers for qRT-PCR analysis, see [362]Table S1 This
study N/A
__________________________________________________________________
Software and algorithms
__________________________________________________________________
FastQC tool [363]Andrews (2010)
[364]https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
TrimGalore N/A [365]https://github.com/FelixKrueger/TrimGalore
Bismark [366]Krueger and Andrews (2011)
[367]https://github.com/FelixKrueger/Bismark
Hisat2 [368]Kim et al. (2019)
[369]http://daehwankimlab.github.io/hisat2/
featureCounts(v1.5.1) [370]Liao et al. (2014)
[371]http://subread.sourceforge.net/
methylKit [372]Akalin et al. (2012)
[373]https://bioconductor.org/packages/methylKit/
edgeR [374]Robinson et al. (2010)
[375]https://bioconductor.org/packages/edgeR/
Circlize [376]Gu et al. (2014)
[377]https://github.com/jokergoo/circlize
GenomicFeatures [378]Lawrence et al. (2013)
[379]https://bioconductor.org/packages/GenomicFeatures/
CGmapTools [380]Guo et al. (2018) [381]https://cgmaptools.github.io/
Pheatmap [382]Kolde (2019)
[383]https://CRAN.R-project.org/package=pheatmap
agriGO tool [384]Tian et al. (2017)
[385]http://systemsbiology.cau.edu.cn/agriGOv2/
clusterProfiler [386]Yu et al. (2012)
[387]https://github.com/YuLab-SMU/clusterProfiler
Primer3 [388]Untergasser et al. (2012) [389]https://primer3.ut.ee/
GC-MS Shimadzu GCMS-QP2010 Plus
Reference mass spectral library databases NIST14
[390]https://www.nist.gov/
Reference mass spectral library databases Wiley 9
[391]https://www.sisweb.com/software/ms/wiley.htm
MetaboAnalystR [392]Pang et al. (2021)
[393]https://www.metaboanalyst.ca/docs/RTutorial.xhtml
__________________________________________________________________
Other
__________________________________________________________________
CFX96 Touch Real-Time PCR Detection System Bio-Rad CFX96
HiSeq X Ten Sequencing System Illumina N/A
HiSeq 4000 Sequencing System Illumina N/A
[394]Open in a new tab
Resource availability
Lead contact
Further information and requests for resources and reagents should be
directed to and will be fulfilled by the lead contacts, Vandana Jaiswal
([395]vandana.jaiswal2009@gmail.com).
Materials availability
This study did not generate new unique reagents or material.
Method details
Plant material and phenotyping
To generate Capsicum hybrid, two Capsicum accessions Choco and Frut4
(pollen donor) belonging to Capsicum chinense and C. frutescens,
respectively, were crossed by hand pollination. The resultant F[1]
seeds were collected, sown and allowed to grow at standard growth
conditions (day/night temperature: 27°C/19°C and 16 h/day light) in the
greenhouse of the School of Life Sciences, Jawaharlal Nehru University,
New Delhi, India. Then leaf samples were collected from two months old
plants from two parents and hybrid, each with two biological
replicates. Leaves from each sample were immediately frozen and
preserved in liquid nitrogen and used for DNA/RNA extraction and
metabolome profiling.
Hybrids and their parents were phenotyped for seven traits at the time
of flowering each with five replicates. These traits include plant
height (cm), plant width (cm), number of secondary branches, number of
leaves, leaf length (cm), leaf width (cm), and total chlorophyll
content (μg/mg). The total chlorophyll content was estimated according
to the method of [396]Arnon (1949). Fresh leaves were taken, washed,
blotted in tissue paper to dry the external moisture and the leaf
weight of the material was recorded. Approximately, 100 mg leaf samples
were homogenized in a pre-chilled mortar using cold 80% acetone and
tissue was pulverized completely. The homogenate was centrifuged at
3200 rpm for 30 min and the supernatant was collected. 80% acetone was
taken as blank and the optical density of the acetone extract was
measured at 645 and 663 nm in a spectrophotometer (Thermo Scientific).
Total chlorophyll content was calculated from three biological
replicates using the following formula:
[MATH: TotalChlorophyll=20.1XO.D.(at645nm)+8.02XO.D(at663nm)
:MATH]
Mid parent heterosis (MPH) and better parent heterosis (BPH) were also
calculated for these seven traits using following formula-
[MATH: MPH=[(
F1−MP)/MP]×100 :MATH]
[MATH: BPH=[(
F1−BP)/BP]×100 :MATH]
where, MP and BP are mid parent and better parent trait values
respectively.
Whole-genome bisulfite sequencing and data processing
From each sample, high molecular weight genomic DNA was extracted using
the cetyltrimethylammonium bromide (CTAB) method. Around 50–100 ng of
DNA was used for bisulfite conversion using Zymo EZ-DNA
Methylation-Gold kit (Zymo Research, Irvine, USA), following
manufacturer’s protocol. Briefly, fragmented DNA of 100–300 bp size was
subjected to anneal to random primers having tagged sequences,
providing ssDNA copy. Then, using ssDNA as a template, dsDNA was
synthesized using terminal tagging oligo (TTO) with 3′ end blocked.
Further, polymerase chain reaction (PCR) was performed with Illumina
TruSeq indices followed by assessment of fragment size, concentration
and library size using Agilent 2200 TapeStation. At last, six
2 × 150 bp paired-end libraries from three samples (Choco, Frut4 and
hybrid; each with two biological replicates) were constructed on
Illumina’s HiSeq X Ten platform (Illumina, San Diego, USA).
Each sample’s raw sequencing reads were converted to FASTQ format and
quality was checked using FastQC tool ([397]Andrews, 2010). Adaptor
sequences and reads with low quality scores were filtered out using
TrimGalore ([398]https://github.com/FelixKrueger/TrimGalore). The clean
reads were then aligned to bismark-transformed C. chinense ([399]Kim
et al., 2017) reference genome using Bismark ([400]Krueger and Andrews,
2011) and genome-wide CG, CHG and CHH methylation at single-base
resolution were identified using criteria as described earlier by
([401]Rawoof et al., 2020). Bisulfite conversion efficiency was
determined using spiked-in un-methylated 1% lambda DNA (GenBank:
[402]J02459.1). Average methylation at 12 Capsicum chromosomes was
represented across bins of equal 1MB length using the R circlize
package ([403]Gu et al., 2014).
RNA sequencing and data processing
Total RNA from each sample was extracted using NucleoSpin RNA plant Kit
(Macherey-Nagel, Germany) following standard protocol. The quality and
integrity of RNA were checked using an Agilent bioanalyzer and then RNA
with RNA integrity number (RIN) > 8 was sequenced as described earlier
([404]Rawoof et al., 2020; [405]Islam et al., 2021). Briefly, an equal
amount of total RNA (5–10 μg) from each sample was used for library
preparation using Illumina TruSeq RNA sample preparation kit (Illumina,
San Diego, CA) following manufacturer’s protocols and paired-end
sequencing was performed on Illumina HiSeq 4000 to develop 150 bp
paired-end reads from three samples (two biological replicate of each
sample). The raw RNAseq were subjected for quality check and then
adapter sequences, as well as reads with quality score <30, were
filtered out. Further, clean reads were aligned to the C. chinense
reference genome ([406]Kim et al., 2017) using Hisat2 ([407]Kim et al.,
2019) program with default parameters. Read counts of transcripts were
quantified using the featureCounts (v1.5.1) ([408]Liao et al., 2014).
Raw read counts were normalized using TMM methods ([409]Robinson and
Oshlack, 2010), and differentially expressed genes (DE-Gs) between two
sample comparisons were identified using the glmQLFit and glmQLFTest
functions in the edgeR package ([410]Robinson et al., 2010). Genes with
p value < 0.01 and false discovery rate (FDR) < 0.01 were considered
significantly differentially expressed between the two samples.
Analysis of differential methylation levels and their correlation with gene
expression
For the identification of differentially methylated regions (DMRs) at
each methylation context and their genomic annotation, parameters
earlier described by [411]Rawoof et al. (2020) were used. In brief,
differential methylation analysis was performed using a sliding window
of 100bp with 50 bp step size and overlapping DMRs were merged, and
methylation information of each DMR was assessed using the R methylKit
package ([412]Akalin et al., 2012) with parameters including Fisher’s
exact test, sliding linear model for q-values and p values. Also, each
window having bases >10X coverage, with at-least 3 mCs for CG, CHG and
CHH context along with methylation difference (meth.diff) > 25% with
q-values <0.01 were considered as significant DMRs. For common DMRs
between hybrid and its parents, all samples were analyzed together.
Then for additive methylation level in hybrid, mid-parental methylation
values (MPMV) were calculated and common DMRs with higher methylation
than MPMV were categorized as trans-chromosomal methylation (TCM),
while lower than MPMV were categorized as trans-chromosomal
demethylation (TCdM). A significance test was performed using pairwise
t-test with both FDR and p value <0.01. DMRs were annotated using an
in-house built txdb SQLite database of C. chinense using R
GenomicFeatures ([413]Lawrence et al., 2013) and were categorised as
intergenic, intragenic and promoter DMRs. Repeat-elements information
as reported by ([414]Rawoof et al., 2020) was used for methylation
analysis at transposable elements (TEs). Gene-body methylation (GBM)
and TE methylation were analyzed using CGmapTools ([415]Guo et al.,
2018). Moreover, to avoid noise from TEs at GBM, methylation at exonic
and intronic levels along with 2 kb flanking regions were also
analyzed. Methylation and gene expression correlation was performed
using Pearson correlation analysis between the RNAseq expression of
total C. chinense genes and their promoter methylation at each
methylation context, and correlations with p value <0.001 were
considered as significant. Additionally, promoter-DMR genes (PDG)
having differential expression between parents and hybrids were
investigated for methylation and their correlation with expression was
represented as a heatmap using R pheatmap package ([416]Kolde, 2019).
Analysis of allele-specific methylation (ASM) associated with DMRs
To analyze allele specific methylation, single nucleotide variants
(SNVs) were identified using CGmapTools snv function ([417]Guo et al.,
2018). The SNVs detection was performed using bismark mapped methylated
reads (>10x coverage) from hybrid and parental lines against
C. chinense reference genome with BayesWC mode and dynamic p value
cut-off vale of <0.001. Prior to ASM calling, the SNVs associated with
TCM, TCdM and promoter DMRs were filtered out using vcftools --recode
function. These DMRs specific SNVs were further used for ASM calling
using asm mode of CGmapTools with filter criteria of minimum 5 reads
for each allele linked sites, adjusted p value < 0.05 and high
methylation threshold ≥0.8 to identify significant ASM associated with
DMRs at CG, CHG and CHH methylation context. The tanghulu plots
representing ASM were visualized using CGmapTools.
Gene ontology and pathway enrichment analysis
Gene ontology (GO) analysis of DE-Gs between hybrid and parental lines
and DE-Gs having a negative correlation between their expression and
promoter methylation, was performed using agriGO tool ([418]Tian
et al., 2017). For GO information, a hypergeometric test with p value
<0.01 and FDR <0.01 was used. For pathway enrichment analysis,
SQLite-based custom annotation package for C. chinense was prepared in
R, and then enrichment analysis was performed using R clusterProfiler
([419]Yu et al., 2012). GO terms and pathways with adjusted p values
<0.01 were considered as significant.
qRT-PCR expression validation of DE-Gs negatively correlated with promoter
methylation
At least 24 DE-Gs genes that negatively correlated with promoter
methylation were selected for qRT-PCR validation, and gene-specific
primers ([420]Table S1) were designed using Primer3 ([421]Untergasser
et al., 2012). RNA was extracted from leaves of hybrid and parental
lines (same samples used in WGBS and RNAseq) using NucleoSpin RNA plant
kit (Macherey-Nagel, Germany) following manufacturer’s protocol. The
quality and integrity of extracted RNA was checked using NanoDrop 1000
(Thermo Scientific) and 1% Agarose gel, respectively. Equally, ∼1 μg of
total RNA was used to synthesize cDNA using PrimeScript IV 1 st strand
cDNA Synthesis Mix (Takara). The real-time PCR reaction was set up
using TB Green Premix Ex Taq II Master Mix (Clontech, USA) and run on
the Bio-Rad CFX96 Real-Time System (Bio-Rad, USA) using the thermal
profile of initial denaturation at 95°C for 30 s, followed by
amplification step with 40 cycles of 95°C for 5 s and 60°C for 30 s.
Then final amplification was completed at 65°C for 5 s, as described
earlier ([422]Dubey et al., 2019; [423]Ahmad et al., 2021b). Further,
qRT-PCR expression was compared with in silico RNAseq expression data.
EF1-alpha was used as internal control, and significant expression
difference was analyzed using two-way ANOVA test.
Untargeted GC-MS based metabolomics analysis
The global metabolome of hybrid and parental genotypes, three
biological replicates each, was analyzed using gas chromatography
coupled with mass spectrometry (GC-MS) following the method described
by [424]Lisec et al. (2006) and [425]Ahmad et al. (2021b) with slight
modification. Briefly, 100 mg of each leaf sample was homogenized with
mortar and pestle using liquid nitrogen and then 1400 μL of pure
methanol (chilled) was added. For internal quantitative standard, 60 μL
of ribitol (0.2 mg mL^−1) was added and kept for shaking for 10 min at
70°C, followed by vortexing at 11000g for 10 min. Further, 750 μL of
chloroform and 1500μL of dH[2]O were added and centrifuged for 15 min
at 2,200g. Finally, the supernatant of each sample was dried in a
vacuum concentrator without heating. For derivatization, 40μL of
methoxyamine hydrochloride (20 mg mL^−1) in pyridine was added in all
samples, vortexed and kept in a shaker for 2 h at 37°C. For
trimethylsilylation, 70 μL of N-Methyl-N-(trimethylsilyl)
trifluoroacetamide (MSTFA) as a silylating agent was added and then
vortexed and incubated with shaking for 30 min at 37°C. The GC-MS
running conditions includes: oven temperature – 100°C for 2 min
followed by increment in oven temperature upto 250°C at the rate of 5°C
per min, then finally 280°C at the rate of 2°C per min. Further, 1μL of
derivatised sample was injected at 10:1 split ratio into a GC-MS
(Shimadzu QP2010 Plus), equipped with a Rtx- 5 MS capillary column
(0.25 mm film thickness, 0.25 mm internal diameter, and 30 m in length)
with helium as the carrier gas with flow-rate of 1.2 mL/min. The
quantification of detected metabolites was analyzed using GCMS post run
Analysis Program (Shimadzu Scientific Instruments) following criteria
described by [426]Ahmad et al. (2021b). In short, metabolites were
identified by MS detector via full scan mode using their distinct peak
fragmentation pattern and peaks of identified metabolites were compared
with retention indices and mass spectra from reference mass spectral
library databases (NIST14 and Wiley 9). At last, relative
quantification was based on peak area ratio of analyte to internal
standard ribitol. The metabolites in hybrid were assessed by relative
changes in abundance as response ratios compared to its parents. The
response ratio was calculated by dividing the average metabolite
concentration from both parents (Choco and Frut4) by the average
metabolite concentration from the hybrid. Metabolite differences
between parents and hybrid with fold change >2 and p value < 0.05 were
considered significant. Pathway enrichment of metabolites were analyzed
using MetaboAnalystR ([427]Pang et al., 2021) and pathways number of
metabolites >3 and pathway impact >0.2 along with p value <0.01 were
considered as significantly enriched.
Acknowledgments