(2021) 12:510
Sekita et al. Stem Cell Res Ther
https://doi.org/10.1186/s13287-021-02578-1

Open Access

RESEARCH

AKT signaling is associated with epigenetic
reprogramming via the upregulation of TET
and its cofactor, alpha‑ketoglutarate during iPSC
generation
Yoichi Sekita1, Yuki Sugiura2, Akari Matsumoto1, Yuki Kawasaki3, Kazuya Akasaka1, Ryo Konno4,
Momoka Shimizu1, Toshiaki Ito1, Eiji Sugiyama2, Terushi Yamazaki1, Eriko Kanai1, Toshinobu Nakamura5,
Makoto Suematsu2, Fumitoshi Ishino3, Yoshio Kodera4,6, Takashi Kohda3,7 and Tohru Kimura1*

Abstract
Background: Phosphoinositide-3 kinase (PI3K)/AKT signaling participates in cellular proliferation, survival andtumorigenesis. The activation of AKT signaling promotes the cellular reprogramming including generation of induced
pluripotent stem cells (iPSCs) and dedifferentiation of primordial germ cells (PGCs). Previous studies suggested that
AKT promotes reprogramming by activating proliferation and glycolysis. Here we report a line of evidence that supports the notion that AKT signaling is involved in TET-mediated DNA demethylation during iPSC induction.
Methods: AKT signaling was activated in mouse embryonic fibroblasts (MEFs) that were transduced with OCT4,
SOX2 and KLF4. Multiomics analyses were conducted in this system to examine the effects of AKT activation on cells
undergoing reprogramming.
Results: We revealed that cells undergoing reprogramming with artificially activated AKT exhibit enhanced anabolic
glucose metabolism and accordingly increased level of cytosolic α-ketoglutarate (αKG), which is an essential cofactor
for the enzymatic activity of the 5-methylcytosine (5mC) dioxygenase TET. Additionally, the level of TET is upregulated.
Consistent with the upregulation of αKG production and TET, we observed a genome-wide increase in 5-hydroxymethylcytosine (5hmC), which is an intermediate in DNA demethylation. Moreover, the DNA methylation level of ES-cellsuper-enhancers of pluripotency-related genes is significantly decreased, leading to the upregulation of associatedgenes. Finally, the transduction of TET and the administration of cell-permeable αKG to somatic cells synergisticallyenhance cell reprogramming by Yamanaka factors.
Conclusion: These results suggest the possibility that the activation of AKT during somatic cell reprogramming promotes epigenetic reprogramming through the hyperactivation of TET at the transcriptional and catalytic levels.
Keywords: AKT signal, TET, αKG, DNA demethylation, Reprogramming, iPS cells*Correspondence: tkimura@kitasato-u.ac.jp
1
Laboratory of Stem Cell Biology, Department of Biosciences, Kitasato
University School of Science, 1‑15‑1 Kitasato, Minami‑ku, Sagamihara‑shi,Kanagawa 252‑0373, Japan
Full list of author information is available at the end of the article

BackgroundPI3K/AKT signaling is activated downstream of extracellular stimuli such as growth factors and hormones
via receptor tyrosine kinases and G-protein-coupled
receptors [1]. Activated AKT phosphorylates serine
and threonine residues of multiple target proteins, and© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Sekita et al. Stem Cell Res Ther

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cellular survival, proliferation, metabolism and growth
are promoted as downstream effects of target phosphorylation. Research from our laboratory and others has
shown that AKT activation enhances cellular reprogramming or dedifferentiation in vivo and in vitro [2].
Germ cell-specific Pten-deficient mice, which display
constitutively activated AKT in germ cells, develop testicular teratomas that emerge from dedifferentiated primordial germ cells (PGCs) at the neonatal stage [3]. We
have also shown that AKT activation in PGCs increases
the efficiency of their dedifferentiation to pluripotent
embryonic germ cells (EGCs) in vitro and that AKT caneven replace bFGF, a cytokine required for EGC induction under the conventional protocol [4]. AKT activation also improves the efficiency of iPSC production[5].
In the process of iPSC induction, many functions ofcellular physiology (e.g., metabolism, the epigenetic
state associated with transcriptional networks, morphology and proliferation rates) dramatically change
during the shift from a somatic cell state to a pluripotent stem cell state. Among these changes, metabolic
remodeling occurs during the very early stage of reprogramming [6, 7]. Within 2 days following the transduction of Yamanaka factors (OCT4, SOX2 and KLF4;
OSK), terminally differentiated cells with low glycolytic
activity and an intermediate level of mitochondrial
oxidative phosphorylation activity show a shift their
metabolic state toward high glycolytic and oxidative
phosphorylation activities, known as an OXPHOS
burst. Recently, cellular metabolic remodeling has beenrecognized as an important mechanism controlling thepluripotency state by providing not only energy andcellular building blocks but also rate-limiting substrates
for enzymes regulating epigenetic modifications, such
as αKG and acetyl-CoA [8–11]. Epigenetic reprogramming occurs during the intermediate stage of iPSC generation. Genome-wide DNA hypomethylation activates
pluripotency-associated genes, followed by the reestablishment of DNA methylation to repress cell typespecific genes [12]. TET family dioxygenases catalyze
the sequential oxidation of 5mC to 5hmC, 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC), ultimately
leading to DNA demethylation. Thus, TETs play anessential role in epigenetic reprogramming during iPSC
generation [13–15].
In this study, we observed molecular events in cells
undergoing reprogramming with activated AKT in thecontext of cellular metabolism and DNA methylationand hydroxymethylation. Our results illustrate the association of epigenome reprogramming promoted by PI3K/
AKT signaling with metabolic remodeling during iPSC
generation.

Page 2 of 15

Methods
Mice

C57BL/6 mice for maintaining the Oct4-EGFP transgenic mouse line [16, 17] and KSN/Slc nude mice for the
teratoma formation assay (see below) were purchasedfrom Japan SLC. All animal care and experimental procedures were carried out in accordance with the Guidelines for Animal Experiments of Kitasato University andwere approved by the Institutional Animal Care and Use
Committee of Kitasato University (Approval number:
SAS2004). The study was carried out in compliance with
the ARRIVE guidelines (https://​arriv​eguid​elines.​org).
Mouse embryonic fibroblast derivation

MEFs were isolated from Oct4-EGFP transgenic mice
[16, 17]. Multiple E13.5 male embryos were mixed andcultured in DMEM supplemented with high glucose(Nacalai Tesque), penicillin–streptomycin (Nacalai
Tesque) and 10% FBS (Equitech-Bio).
Plasmid construction

To construct pMYs-AKT-Mer, the BamHI-XhoI fragment from the pCAGGS-myr-AKT-Mer-IRES-EGFPpA
plasmid [18] was cloned into the pMYs retroviral vector, which was linearized, and subjected to IRES-GFP
cassette removal by BamHI and SalI digestion (pMYsIRES-GFP was kindly provided by Dr. Kitamura [3, 19]).
To construct the pMYs-Idh1 retroviral vector, Idh1 wasamplified from a cDNA library synthesized using inhouse-cultured ES cells (c57bl/6 and DBA/2-mixed
background) by RT-PCR (forward primer: 5′-AGT​
TAA​T TA​AGG​ATC​C AC​C AT​GTC​C AG​A AA​A AT​C CA​
AGG-3′; reverse primer: 5′-TTA​TTT​TAT​CGT​CGA​CTT​
AAA​GTT​TGG​CCT​GAG​CTA​-3′). Then, the RT-PCR
amplicon was digested with BamHI and SalI, followedby ligation to the pMYs retroviral vector, linearization
and removal of the IRES-GFP cassette by BamHI and
SalI digestion. We performed site-directed mutagenesis
to produce the IDH1-R132H mutant retroviral vector
from pMYs-Idh1 using a mutagenesis primer set (forward primer: 5′-CCA​TCA​TCA​TTG​GCC​ACCAT​GCA​
TAT​GGG​GAC-3′; reverse primer: 5′-GTC​CCC​ATA​
TGC​ATG​GTGGC​CAA​TGA​TGA​TGG-3′). pMYs-FlagTET2CD was kindly provided by Dr. Xu of the Chinese
Academy of Sciences.
Retroviral infection and iPSC derivation

The retroviral transduction of the Yamanaka factors(OSK) along with AKT-Mer, IDH1 or IDH1(R132H)
was performed following the original protocol withsome modifications [20]. Briefly, 3 × ­106 plat-E cells
were plated in a 60-mm dish 1 day before transfection
with 4.5 µg of the pMXs-Oct4, pMXs-Sox2, pMXs-Klf4,

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pMYs-AKT-Mer, pMYs-Idh1, pMYs-Idh1(R132H) or
pMYs-Flag-TET2CD plasmid using X-tremeGENE 9(Merck), following the manufacturer’s instructions. At
48 h posttransfection, the retroviruses in plat-E medium
were collected, mixed and filtered via PVDF filters with
a 0.45 µm pore size (Merck, Cat# SLHVR33RS). Next,
OE-MEFs that had been plated at 3 × ­105 cells per 60-mm
dish the day before were infected with retroviruses supplemented with 4 µg/mL polybrene (Sigma-Aldrich, Cat#
H9268). At 3 dpi, the transfected cells were replated in
a 6-well plate with LIF containing ES medium-DMEM(Nacalai Tesque Cat# 08459-64) supplemented with 10%
FCS (Gibco, Cat# 10270, Lot# 42Q3056K), 0.1 mM nonessential amino acids (Nacalai Tesque Cat# 06344-56),
2 mM L-glutamine (Nacalai Tesque Cat# 16948-04), 0.1%
2-mercaptoethanol, 100 U/mL LIF (made in the laboratory) and streptomycin/penicillin (Nacalai Tesque Cat#
09367-34). At the same time, 4OHT (Sigma-Aldrich,Cat# H7904) (final concentration, 1 µM) was added tothree wells to activate AKT, and ethanol (vehicle control)
was added to another 3 wells for the AKT-nonactivatedcontrols. AOA (Sigma-Aldrich, Cat# C13408) (final concentration, 1 mM) or DM-αKG (Sigma-Aldrich, Cat#
349631) (final concentration, 0.8 mM) was added to theculture medium beginning at either 3 dpi, to examine thelevels of αKG and 5hmC (Fig. 4f, g) or 7 dpi, to determine
reprogramming efficiency (Fig. 4h, i).
Teratoma formation assay

Established iPSCs (1 × ­106) were subcutaneously injected
into the dorsal flank of nude mice (Japan SLC). At
4–5 weeks after transplantation, the tumors were dissected from the mice. The teratomas were fixed with 4%paraformaldehyde in PBS and embedded in OCT compound (Sakura Finetek Japan). Sections (7 µm thick) were
stained with hematoxylin and eosin.
Cell cycle analysis

At 7, 8, 9 and 10 dpi, 1 × ­106 cells undergoing reprogramming were harvested in tubes, fixed with 1% PFA for
15 min at room temperature, washed with PBS and resuspended in 100 µL PBS. A total of 900 µL of 70% ethanol
chilled at − 30 °C was added, with mixing by tapping, followed by 50 µL RNase (50 µg/µL) and 200 µL propidium
iodide (100 µg/mL). Next, the mixture was incubated for
30 min at room temperature. The cells were collectedby centrifugation (960 × g for 5 min), resuspended in
1% FCS in PBS and passed through a mesh. Fluorescein
was measured with a Gallios flow cytometer (Beckman
Coulter) and analyzed with Kaluza software (Beckman
Coulter).

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Proteomic analysis

Three wells per experimental group were analyzed
independently. Cells were harvested at 10 dpi by trypsinization and washed with PBS. The cell pellet wasstored at − 80 °C until protein extraction. The methods
used for protein extraction and trypsin digestion havebeen described previously [21]. See Additional file 5 forfurther methodological details.
Ion chromatography–tandem mass spectrometry
for anionic metabolites

Cells from each experimental group were plated inthree wells of 6-well plates and analyzed independently
as follows. The culture medium from cells undergoing
reprogramming at 10 dpi was replaced with DMEM
without glucose (Nacalai Tesque) supplemented with
4.5 g/L D-glucose-13C6 (Sigma-Aldrich), followed byincubation with 5% C
­ O2 for 1 h at 37 °C. Then, themedium was aspirated, and the cells were washed in
ice-cold PBS three times with chilling, followed bysnap freezing in liquid nitrogen. The plates were storedat − 80 °C until metabolite extraction. The methods
used for metabolite extraction and cytosolic fractionation to remove mitochondria from cell lysates havebeen described previously [22, 23]. See Additional file 5
for further details.
Microarray analysis

Total RNA was extracted using the miRNeasy Mini Kit(QIAGEN) according to the manufacturer’s instructions. Cyanine-3 (Cy3)-labeled cRNA was prepared from
100 ng RNA using the Low Input Quick Amp Labeling
Kit (Agilent) according to the manufacturer’s instructions, followed by RNeasy column purification (QIAGEN). Dye incorporation and the cRNA yield werechecked with a NanoDrop ND-1000 spectrophotometer. Slides were scanned immediately after washing onan Agilent DNA Microarray Scanner (G2565CA) using
the one-color scan setting for 8 × 60 k array slides (scanarea 61 × 21.6 mm, scan resolution 3 µm, dye channel set
to green, green PMT set to 100% and TIFF file dynamic
range of 20 bits). The scanned images were analyzed with
Feature Extraction Software 10.7.3.1 (Agilent) using thedefault parameters to obtain background-subtracted andspatially detrended processed signal intensities.
Immunoblotting

Proteins were extracted using RIPA buffer (50 mM
HEPES pH 7.9, 150 mM NaCl, 1% NP-40, 0.5% sodium
deoxycholate, 0.1% SDS), followed by protein concentration measurement using a Pierce BCA Protein Assay Kit

Sekita et al. Stem Cell Res Ther

(2021) 12:510(Thermo Fisher Scientific). For SDS-PAGE, 20 µg protein
was applied per lane. Proteins were detected with antiTET2 (diluted to 1:1000) (Cell Signaling Technology) andanti-β-ACTIN (diluted to 1:1000) primary antibodies
using ImageQuant LAS 4000 (GE Healthcare).
RNA sequencing

Total RNA was isolated from cells using the AllPrep
DNA/RNA Mini Kit (QIAGEN) according to the manufacturer’s instructions. Standard polyA libraries wereprepared using the KAPA Stranded mRNA-Seq Kit for
Illumina (Kapa Biosystems) according to the manufacturer’s protocol. Libraries were subjected to 50-bp singleend sequencing on the Illumina HiSeq 1500 platform.
The sequence data were trimmed using Trim Galore(https://​www.​bioin​for matics.babraham.ac.uk/projects/
trim_galore/) and mapped against the mouse referencetranscriptome using Salmon [24].
qRT‑PCR

Total RNA was isolated from cells using the RNeasy Mini
Kit (QIAGEN) according to the manufacturer’s instructions. Reverse transcription was performed by using a
ThermoScript RT-PCR System (Invitrogen) and an oligo(dT) primer. Gene expression levels were measured with
Stratagene MX3000P (Agilent Technologies) using FastStart Universal SYBR Green Master Mix (Rox) (Roche).
See Additional file 5: Table S1 for the primers.

Page 4 of 15

in blocking reagent (BlockingOne, Nacalai Tesque) for
1 h at room temperature, washed briefly with TBS with
0.1% Tween-20 (TBST), incubated with a polyclonal anti5hmC antibody (Activemotif, cat # 39069) diluted 1:5000
with Can Get Signal Solution 1 (Toyobo Life Science) at
4 °C overnight, washed with TBST three times for 10 min
each, incubated with an HRP-linked anti-rabbit IgG antibody (GE Healthcare, cat # NA934) for 1 h at room temperature and washed with TBST three times for 10 min
each. The resulting signals were detected by ECL chemiluminescence (Nacalai Tesque) using ImageQuant LAS
4000 (GE Healthcare). The signal intensity of the dots
was quantified using ImageJ software. To plot a standard curve of the dot signal intensity versus the amount of
5hmC, we used a synthesized oligonucleotide consistingof 57 nucleotides including seven 5hmCs (5′-AGAAT[X1]
GGT​ TAT​ AGG[X 2]GGG​ AGA​ C AT​ AGA​ A AC​ TGC​ [ X 3]
G[X4]GTG[X5]GTG[X6]GTC​CAC​[X7]GAAAC-3′, [X];5hmC). Twofold dilutions of the oligonucleotide wereprepared starting from the highest 5hmC concentration of 400 fmol/µL and treated in the same way as the
genomic samples described above.
Statistical analysis

Genomic DNA was isolated from cells using the Cica
Geneus Total DNA Prep Kit (Kanto Chemical) according to the manufacturer’s instructions. The isolated DNA
was subjected to the bisulfite reaction as described previously with some modifications [25, 26]. The automatedshell scripts and the read me text are available in Additional files 2, 3 and 4 [27]. See Additional file 5 for further
details.

To evaluate reprogramming efficiency, iPSCs from eachgroup were plated in three wells of 6-well plates. Then,the GFP-positive colonies in each well were counted. For
dot blotting, transcriptomic, proteomic and metabolomic
analyses, qRT-PCR, and bisulfite sequencing, cells fromthe three wells per experimental group were assessedindependently. Statistical analyses of the iPSC generation
assay, dot blot analysis, metabolomic analysis, qRT-PCR
and methylation analysis data were performed using theunpaired Student’s t-test. Statistical analyses of the RNA
sequencing data were performed using the edgeR package [28], and p values were calculated after adjusting forthe false discovery rate. Data are shown as the means,
and error bars represent standard deviations.

Dot blot assay

Data and software availability

Total DNA was extracted from cells by RNase and protease digestion, followed by phenol/chloroform purification. The DNA concentration was measured using a
Qubit system (Thermo Fisher Scientific) and diluted to
100 ng/µL with distilled and deionized water. To denature the genomic DNA, 0.5 µL of 1 N NaOH was added
to 4.5 µL of DNA solution, after which the mixture washeated to 95 °C for 10 min and neutralized by adding 0.75
µL of 5 M ammonium acetate. The genomic DNA (1.5µL) was blotted onto a nylon membrane (Hybond-N + ,GE Healthcare) (i.e., 117 ng genomic DNA per spot). The
membrane was incubated at 80 °C for 30 min and UV
cross-linked at 70 mJ. The blotting membrane was soaked

The accession numbers of the RNA-seq data andthe microarray data reported in this paper are GEO:
GSE161344 and GEO: GSE161399, respectively. The
accession number of the proteomic analysis reported inthis paper Japan ProteOme Standard Repository (JPOST;
https://​repos​itory.​jpost​db.​org/) is PXD014856. The
metabolomic analysis data reported in this paper areavailable in Additional file 1.

Bisulfite sequencing

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Results
Conditional activation of AKT enhances iPSC induction
efficiency

To investigate the role of activated AKT during iPSC
induction, we employed a fusion protein of myristoylated AKT and a modified estrogen receptor (AKTMER) [4]. In this system, AKT can be conditionallyactivated by administering the MER ligand 4-hydroxytamoxifen (4OHT). For the induction of cell reprogramming, we used mouse embryonic fibroblasts(MEFs) carrying a transgene encoding enhanced green
fluorescent protein gene (EGFP) under the control of
the Oct4 promoter and enhancer (OE-MEFs) [16, 17].
The OE-MEFs enabled us to identify cells undergoing
reprogramming by observing EGFP fluorescence. We
transduced the OE-MEFs with AKT-MER in combination with OSK (OSKA) via retroviral vector infection (Day 0). At 3 days postinfection (dpi), we split
the cells into two groups, which were cultured with
(OSKA + 4OHT: AKT activation) or without 4OHT
(OSKA − 4OHT: AKT nonactivation) (Fig. 1a). We
assessed the effect of AKT activation on iPSC induction by counting the number of GFP-positive colonies at 7 and 10 dpi. At 7 dpi, the average number of
GFP-positive colonies in the OSKA + 4OHT groupwas 450 ± 179.5 (i.e., the reprogramming efficiency
was 0.15 ± 0.06% when the number of infected cells
was 3 × ­105), whereas no GFP-positive colonies wereobserved in the OSKA − 4OHT group (n = 3, p = 0.045,
Student’s t-test) (Fig. 1b). At 10 dpi, there were1094 ± 33.3 GFP-positive colonies (reprogramming
efficiency: 0.36 ± 0.01%) in the OSKA + 4OHT groupcompared with 295 ± 65.0 (reprogramming efficiency:
0.10 ± 0.02%) in the OSKA − 4OHT group (n = 3,
p = 0.00033, Student’s t-test) (Fig. 1b). The effects of
4OHT on the cells that were not transduced with AKTMER were limited in terms of iPSC induction efficiency
and gene expression (Figs. 1b and Additional file 5: Fig.
S1). We established iPSC lines from GFP-positive colonies in the OSKA + 4OHT group and confirmed theirpluripotent ability to differentiate into the three germlayers using a teratoma formation assay (Fig. 1c). The
results indicated that the conditional activation of AKT
greatly accelerates the timing and improves the efficiency of somatic cell reprogramming by Yamanaka
factors.
We examined cell cycle progression with or without
AKT activation from 7 to 10 dpi using fluorescenceactivated cell sorting to measure DNA contents following propidium iodide (PI) staining. It has beenreported that an accelerated cell cycle rate is importantfor somatic cell reprogramming [29, 30]. Additionally,
one of the major effects of AKT on cell physiology is

Page 5 of 15

to promote proliferation by phosphorylating the cell
cycle checkpoint proteins p21 and p27 [1]. The proportion of G1-phase cells was significantly lower at
all assessed time points, whereas that of S-phase cells
was significantly higher among AKT-activated cells(OSKA + 4OHT) than nonactivated cells (OSK withand without 4OHT: OSK − 4OHT and OSK + 4OHT,
respectively, and OSKA − 4OHT) at 8 dpi (Fig. 1d).
These results indicate that activated AKT promotes theG1-to-S phase transition, thereby accelerating the cell
cycle during iPSC induction.
Expanded glucose anabolism during iPSC induction
with activated AKT

As AKT participates in glucose metabolism by regulating GSK and FOXO, we performed a metabolomic pathway tracing analysis by adding 13C-labeled glucose to thecell culture medium at 10 dpi. This experiment enabled
us to understand how the carbon flows derived from thelabeled glucose were modified in each metabolic pathway, where non-13C-labeled molecules corresponded tometabolites derived from intracellularly accumulated
substrates or extracellular nonglucose substrates. The
volcano plot showed an overall increasing trend of theanionic metabolites that we measured (Fig. 2a). Among
313 metabolites, 103 metabolites showed a statisticallysignificant increase, whereas only 5 metabolites showeda statistically significant decrease in AKT-activated cells
relative to AKT-nonactivated cells. The flow of glucose carbon into the glycolysis pathway and the pentose
phosphate pathway was significantly increased in AKTactivated cells (Additional file 5: Fig. S2a,b). De novo
nucleotide synthesis for genome replication, represented
by inosine monophosphate (IMP) and deoxynucleotide
triphosphates (dGTP, dATP, dCTP and TTP), was notably elevated (Additional file 5: Fig. S2c,d). The carbon
flow into the TCA cycle was also significantly increased(Fig. 2b). The levels of intermediates of the TCA cycle,
including citrate, cis-aconitate, isocitrate and αKG,
significantly altered in AKT-activated cells. Because
glucose-derived citrate is exclusively produced in mitochondria, this result suggests a higher level of mitochondrial activity. Importantly, these molecules are involvedin fatty acid and amino acid synthesis.
Consistent with the metabolomic analysis, a proteomic
analysis at 10 dpi followed by KEGG pathway analysis
revealed that proteins involved in glycolysis and the pentose phosphate pathway as well as fatty acid metabolism,
amino acid biosynthesis and carbon metabolism weresignificantly enriched among the proteins upregulated
in AKT-activated cells (Additional file 5: Figs S2a,b andS3a,b). Overall, the metabolomic and proteomic analyses
showed that iPSC induction with AKT activation shifts

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Page 6 of 15

Fig. 1 Enhancement of iPSC induction by conditional AKT activation. a A schematic representation of conditional AKT activation during iPSC
induction. OE-MEFs were transduced with reprogramming factors (OSK) and AKT-Mer (A). Cells were plated in 6-well plates at 3 dpi. Next, 4OHT(the Mer ligand) was added to three wells to activate AKT, and vehicle (ethanol) was added to the remaining three wells as a control. GFP-positive
colonies were counted at 7 and 10 dpi. b The numbers of GFP-positive colonies at 7 and 10 dpi. Cells without AKT-Mer transduction (OSK − 4OHTand OSK + 4OHT) were observed to record the intrinsic effects of 4OHT on reprogramming (n = 3). c Representative images of GFP-positive colonies
and histological sections illustrating the three germ layers that differentiated from AKT-activated iPSCs transplanted into nude mice. The epidermis,
muscle and mucosal gland correspond to the ectoderm, mesoderm and endoderm, respectively. d Cell cycle analysis by DNA content quantitation,as assessed by PI staining and flow cytometry between 7 and 10 dpi (n = 3). *p < 0.05; **p < 0.01; ***p < 0.001 by the unpaired Student’s t-test

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Page 7 of 15(See figure on next page.)
Fig. 2 Effects of AKT activation on metabolic pathways during iPSC induction, as assessed by metabolomic analyses. a Volcano plot representing
all metabolites quantified by ion chromatography–tandem mass spectrometry. For every metabolite, the l­og2 fold change of AKT-activated versus
AKT-nonactivated cells was plotted against the − ­log10 false discovery rate adjusted p value (n = 3). Colored and black dots depict significantly
higher or lower levels of metabolites in AKT-activated cells than in AKT-nonactivated cells, and gray dots represent metabolites showing no
significant difference (p < 0.05). Each color represents a metabolic process related to processes such as glycolysis, the pentose phosphate pathway,
the TCA cycle or nucleotide biosynthesis, as indicated on the upper right. b Fold changes in metabolites involved in the TCA cycle, as quantified
by ion chromatography–tandem mass spectrometry (n = 3). Metabolites not containing 13C were derived from intracellularly accumulated
substrates or extracellular nonglucose substrates, whereas 13C-containing metabolites were derived from extracellular glucose. The levels of
non-13C-containing and 13C-containing metabolites in AKT-nonactivated cells (− 4OHT) were set to 1. c Fold change in cytosolic αKG, as quantified
by ion chromatography–tandem mass spectrometry (Rep 1–4; 4 independent experiments). Western blots with antibodies against HSP60(mitochondrial marker) and α-tubulin (cytosolic marker) indicated the successful exclusion of mitochondria from the cytoplasmic fraction (c) of thewhole-cell lysate (w)the glucose metabolic state toward anabolic processes
supplying cellular building blocks (e.g., nucleotides andfatty acids), which could support an accelerated cell cycle
rate (Fig. 1d).
Enhanced epigenetic reprogramming during iPSC
induction with activated AKT

Next, we performed RNA sequencing at 10 dpi. A total of559 genes were significantly upregulated, and 429 genes
were significantly downregulated in the OSKA + 4OHTgroup relative to the OSKA − 4OHT group (foldchange > 2, adjusted p value < 0.05, n = 3). KEGG pathway analysis revealed that genes involved in metabolism-related pathways, infection responses and cell cycle
regulation were significantly enriched among the genes
upregulated in AKT-activated cells (Fig. 3a). On theother hand, genes involved in cell adhesion, motility, thecytoskeleton, cancer and TGF-b signaling were enrichedamong the downregulated genes (Fig. 3a). The downregulation of TGF-b signaling, which enhances epithelialto-mesenchymal transition (EMT), suggests that AKT
promotes mesenchymal-to-epithelial transition (MET),
which is a critical step in reprogramming [31]. Accordingly, Snai2, a transcription factor that represses key epithelial regulators, was downregulated in AKT-activatedcells (0.67-fold, p = 0.04) [31].
Among the differentially expressed RNAs, we focusedon the transcriptional upregulation of Tet1 (5.4-fold,p = 0.02) and Tet2 (2.9-fold, p = 9.1 × ­10−5) in AKTactivated cells (Fig. 3b). This was because in addition tothe overexpression of these genes, the elevation of αKG
in AKT-activated cells (Fig. 2b,c) led us to speculate that
AKT has epigenetic effects, as αKG is an essential cofactor of αKG- and Fe(II)-dependent dioxygenases, including TET enzymes. Consistent with the observed RNA
overexpression, an elevated level of the TET2 protein wasobserved (Fig. 3b).
We investigated the genome-wide level of 5hmC
at 10 dpi in bulk cells and GFP-negative cells in theintermediate stage of reprogramming (Fig. 3c). Quantitative dot blot analysis using an anti-5hmC antibody
and standards consisting of known amounts of 5hmCcontaining oligonucleotides revealed a 3.7-fold increasein the 5hmC level in OSKA + 4OHT bulk cells (n = 3,
p = 0.015, Student’s t-test; Fig. 3c). We observed a similar upregulation (3.6-fold) of 5hmC in GFP-negative cells
collected by fluorescent activated cell sorting (FACS)(n = 3, p = 0.0008, Student’s t-test), indicating that theincrease in the 5hmC level preceded the activation of the
Oct4-EGFP reporter gene.
We also investigated the DNA methylation levels of
cis-regulatory elements (i.e., promoters and enhancers)of three pluripotency-related genes, Nanog, Zfp42 andpri-miR290-295. These genes were significantly upregulated by AKT activation (Nanog, 16.4-fold, p = 0.006;
Zfp42, 8.1-fold, p = 0.003; pri-miR290-295, 6.4-fold,p = 2.2 × ­10−5; Fig. 3d) [32–34]. We collected GFP-negative cells at 10 dpi by FACS and performed bisulfite
sequencing by adapting PCR amplicon sequencing using
a next-generation sequencer. By comparing the percentage of methylated CpGs in each PCR amplicon, we founda robust decrease in DNA methylation in AKT-activatedcells in the ESC super-enhancers of the genes assessed,
rather than in their promoter regions (n = 3 for eachgroup; Fig. 3e). Notably, multiple CpGs were observed tobe significantly hypomethylated at a single-CpG resolution, whereas no CpGs were significantly hypermethylated in AKT-activated cells (Additional file 5: Fig. S5).
Taken together with the TET-mediated genome-wide
increase in 5hmC, these findings indicate that pluripotency-related genes are upregulated in AKT-activatedcells relative to AKT-nonactivated cells by promoting
DNA demethylation at cis-regulatory regions.
Involvement of increased αKG levels in epigenetic
reprogramming during iPSC induction

To determine whether the elevated levels of 5hmC in
AKT-activated cells were associated with TET activity

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Fig. 2 (See legend on previous page.)and pluripotency acquisition, we transduced mutant
isocitrate dehydrogenase 1 (IDH1-R132H) together with
OSKA to inhibit TET activity. IDH1 functions in thecytosol, and normal IDH1 (IDH1-WT) converts isocitrate into αKG, whereas IDH1-R132H converts αKG into

2-hydroxyglutarate (2HG), which inhibits TET activity[35] (Fig. 4a). We measured cellular αKG and 2HG andgenome-wide 5hmC levels at 10 dpi. We also assessed the
reprogramming efficiency at 10 and 14 dpi. The level ofαKG was not affected by IDH1-WT but was significantly

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Page 9 of 15(See figure on next page.)
Fig. 3 Enhanced DNA methylation reprogramming in AKT-activated cells during reprogramming. a RNA-seq followed by the DAVID functionalannotation tool used with the KEGG pathway dataset showed that 16 and 32 biological processes were significantly associated with theupregulated and downregulated RNAs, respectively. b Transcriptional upregulation of Tet1 (p = 4.9 × ­10−8) and Tet2 (p = 2.2 × ­10−19) (n = 3 for eachgroup) by AKT activation at 10 dpi shown by RNA sequencing (left). Upregulation of TET2 at the protein level shown by western blotting (right).
c Elevated 5hmC levels induced by AKT activation at 10 dpi shown by dot blot analysis. For quantitative analysis, synthesized oligonucleotides
containing 5hmC in a known molar amount were plotted. Genomic DNA was extracted from total cells (Total), GFP-negative cells (GFP −) collectedby FACS and nontransduced MEFs to measure 5hmC levels (middle and right). The blot was stained with methylene blue after 5hmC detection
to assess the total amount of DNA (middle lower panel). d Expression levels of pluripotency-related genes measured by RNA sequencing (Nanog
and Zfp42) or qRT-PCR (pri-miR290-295) (n = 3). Pri-miR290-295 expression was normalized to Arbp expression, and the level of OSKA − 4OHT was
set to 1. e DNA methylation levels in cis-regulatory regions around Nanog (left column), Zfp42 (center column) and pri-miR-290–295 (right column)
assayed by bisulfite sequencing adapting PCR amplicon sequencing. The results are presented as the average percentage of methylated CpGs
in all sequenced CpGs for each PCR amplicon (n = 3 for each). The top and middle rows are IGV snapshots of the whole regions (top row) andthe targeted regions (middle row) depicting publicly available datasets of histone H3K27 acetylation (H3K27Ac) (SRX4178803), the occupancyof the pluripotent stem cell-specific transcription factors Oct4 (SRX950710), Sox2 (SRX1342337) and Klf4 (SRX2441333) and a component ofmediator complex Med1 (SRX657147) in ESCs or iPSCs [47]. Blue shading indicates cis-regulatory regions. Bisulfite PCR sites are indicated by boldlines under the IGV snapshots, and the numbers of CpGs involved in each bisulfite PCR amplicon are indicated in parentheses. Abbreviations, SE;super-enhancer, E; enhancer, P; promoter, n; Nanog, z; Zfp42, m; pri-miR290-295

reduced by IDH1-R132H (Fig. 4b). Conversely, the levelof 2HG was greatly increased in IDH1-R132H-transduced cells (Fig. 4c). The level of 5hmC was not affectedby IDH1-WT but was decreased in IDH1-R132H-transduced cells (Fig. 4d). The reprogramming efficiency
assessed by the number of GFP-positive colonies was significantly decreased by IDH1-R132H at both 10 and 14
dpi (Fig. 4e). The number of GFP-positive colonies wasdecreased by IDH1-WT at 10 dpi but had recovered by
14 dpi, suggesting that IDH1-WT altered the timing,
rather than the efficiency, of somatic cell reprogramming (Fig. 4e). These data indicate that elevated levels of 5hmC depend on TET activity and are associatedwith an increased reprogramming efficiency. In addition,
cell reprogramming with activated AKT increases cytosolic αKG during iPSC induction because IDH1-R132H,
which functions in the cytosol but not in mitochondria,
prevents the increase in the αKG level induced by AKT
activation [36] (Fig. 4b). This was confirmed by measuring αKG in the cytosolic fraction without mitochondria(Fig. 2c).
Because TET2 is indispensable for iPSC generation
and TET1 or TET2 overexpression during iPSC induction improves the reprogramming efficiency, the elevated expression of Tet1 and Tet2 in cells undergoing
OSKA + 4OHT-induced reprogramming is potentiallyinvolved in the enhanced reprogramming efficiency [13,37, 38]. Additionally, it is highly possible that the elevatedproduction of αKG is critical for enhanced reprogramming in the OSKA + 4OHT group. To investigate thispossibility, we evaluated aminooxyacetic acid (AOA),
which is an inhibitor of aminotransferases and decreases
cellular αKG levels [10]. AOA administration beginningat 3 dpi prevented the increase in the αKG level in AKTactivated cells (OSKA + 4OHT) in a dose-dependent

manner (Fig. 4f ). We also found that the increase in
5hmC in the OSKA + 4OHT group was suppressedby AOA administration in a dose-dependent manner(Fig. 4g). Taken together, these data show a strong correlation between αKG levels and genome-wide 5hmC levels. To assess the effect of AOA on the reprogramming
efficiency, we administered AOA to cells at 7 dpi because
its administration at 3 dpi interfered with cell proliferation. AOA administration significantly decreased thenumber of GFP-positive colonies at 10 dpi (Fig. 4h). Thisdecrease was rescued by the simultaneous administrationof dimethyl-αKG (DM-αKG), a cell membrane-permeable
αKG derivative (Fig. 4h). However, DM-αKG administration in AKT-nonactivated cells (OSKA − 4OHT) did not
improve the reprogramming efficiency (Fig. 4h), suggesting that an increase in the αKG level in conjunction withthe upregulation of TET genes is critical for promoting
reprogramming. Therefore, we investigated the effect ofDM-αKG in cells undergoing reprogramming with TET2
catalytic domain (TET2CD) overexpression (OSKT2).
The OSKT2 group showed a higher reprogramming efficiency than the OSK group at 14 dpi (Fig. 4i). Moreover,
DM-αKG administration in the OSKT2 group beginningat 3 dpi significantly improved the reprogramming efficiency (Fig. 4i). Taken together, these results suggest thatenhanced 5hmC production and the consequent promotion of somatic cell reprogramming are associated withthe synergistic effect of TET overexpression and αKG
overproduction in AKT-activated cells.

Discussion
In this study, we found that glycolysis was enhanced
in AKT-activated cells undergoing reprogramming,
leading to the accumulation of the downstream TCA
cycle metabolite αKG during iPSC induction by OSK.

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Fig. 3 (See legend on previous page.)

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Page 11 of 15(See figure on next page.)
Fig. 4 Epigenetic reprogramming promoted by αKG dose-dependent TET activity in AKT-activated cells during reprogramming. a A schematic
representation of the 5mC-to-5hmC conversion step, including related enzymes (filled shapes) and metabolites (unfilled shapes). αKG is an
essential cofactor for TET activity; conversely, 2HG is a TET activity-inhibitory metabolite. b-e Requirement of TET-enzymatic activity for an enhanced
reprogramming efficiency in AKT-activated cells, as revealed by a decrease in reprogramming resulting from TET inhibition due to 2HG production
by IDH1 R132H. Cellular αKG (b) and 2HG (c) levels in cells undergoing reprogramming induced by OSKA, OSKA + IDH1 and OSKA + IDH1 R132H
were quantified by ion chromatography–tandem mass spectrometry at 10 dpi. Genome-wide 5hmC levels were quantified by dot blot analysis (d).
GFP-positive colonies were counted at 10 and 14 dpi (e). f and g Correlation between αKG levels and genome-wide 5hmC levels at 10 dpi. AOA
administration at 3 dpi reduced αKG levels in AKT-activated cells in a dose-dependent manner, as quantified by ion chromatography–tandem mass
spectrometry (f). Genome-wide 5hmC levels of cells undergoing reprogramming with or without AOA administration at 3 dpi were quantified by
dot blot analysis (g). h Requirement for upregulated αKG production for an enhanced reprogramming efficiency in AKT-activated cells. GFP-positive
colonies were counted at 10 dpi. AOA administration at 7 dpi reduced the reprogramming efficiency, but the simultaneous administration of
DM-αKG rescued the reprogramming efficiency. i Effects of DM-αKG on the reprogramming efficiency with or without TET2CD overexpression.
GFP-positive colonies were counted at 14 dpi. The dot blot images shown in Figs. 3 and 4 are from the same membrane as shown in Additional
file 5: Fig. S4. Therefore, the ‘total’ in Fig. 3b, ‘IDH1-’ in d and ‘AOA-’ in g are the same as ‘OSKA’ shown in Additional file 5: Fig. S4

Additionally, while it has been reported that Tet1 andTet2 expression is induced during iPSC induction, we
observed higher expression of Tet1 and Tet2 in AKTactivated cells than in AKT-nonactivated cells [13, 39].
We speculate that the increases in αKG and TET at least
partly account for the genome-wide elevation of 5hmC as
well as DNA hypomethylation at ESC super-enhancers,
for the following reasons. First, the levels of αKG werecorrelated with the genome-wide 5hmC levels, suggesting that αKG may play a role in DNA demethylation during somatic cell reprogramming. Second, the inhibition ofαKG production abrogated iPSC induction. Furthermore,
we showed that simultaneous TET2CD transduction
and DM-αKG administration synergistically enhanced
the reprogramming efficiency; thus, they partially reproduced the effect of AKT activation on reprogramming.
In addition, these results support the idea that AKT
signaling is involved in the enhanced production of TET
and αKG. The possible mechanisms of this effect include
the following. First, TET overexpression may be induced
by introducing Yamanaka factors, as Tet1 and Tet2 havesuper-enhancers with OCT4 binding sites [40], and it
has been reported that the AKT-mediated phosphorylation of OCT4, SOX2 and KLF4 upregulates their activity [41, 42]. Second, αKG overproduction involves the
AKT-FOXO1 axis [5]. AKT inactivates FOXO1 throughdirect phosphorylation, which activates glycolysis andmitochondrial function and may result in αKG overproduction [43]. Alternatively, because TET expression was
found to be upregulated in cells undergoing reprogramming, these observations might reflect the consequencesof an increase in reprogramming mediated by AKT. Further studies are required to reveal the direct and/or indirect linkages among AKT activation, TET expression and
αKG production.
Which pathway is responsible for the overproductionof cytosolic αKG is another intriguing question (Fig. 2c).

In this study, we used labeled glucose to show that the
glucose-derived αKG level was elevated. Glucose-derived
αKG accumulates in the cytosol via two pathways: (1)cytosolic citrate transferred from the mitochondria via
citrate carrier proteins expressed on the mitochondrial
membrane is metabolized to αKG by IDH1, and (2) αKG
produced as a TCA cycle intermediate in the mitochondria is transferred to the cytosol via the malate–aspartate
shuttle, in which aspartate and αKG are transferred frommitochondria to the cytosol instead of malate and glutamate being transferred from the cytosol to mitochondria. Although it is unknown which of these mechanisms
is responsible for the increased level of cytosolic αKG
induced in AKT-activated cells, mitochondrial activity is
obviously important in both cases. It has been proposedthat the balance between glycolysis and mitochondrial
activity (e.g., OXPHOS burst) is critical for somatic cell
reprogramming [7]. However, the role of mitochondria incell reprogramming remains unclear [44]. Our findings
suggest that mitochondrial activity is important for αKG
production because the metabolites of the initial stepsof the TCA cycle, especially citrate, were observed to be
increased in AKT-activated cells. As the next step, it will
be important to elucidate the mechanisms whereby AKT
enhances αKG production during reprogramming.
On the other hand, the impact of activated AKT on the
reprogramming efficiency is greater than that of the synergistic effect of TET2CD and DM-αKG, indicating that
another effect of AKT activation on epigenetic regulation is involved in reprogramming enhancement. It has
been proposed that cells with an accelerated cell cycle
are dominantly reprogrammed [30]. In this study, we
revealed an accelerated G1–S transition. The metabolic
shift toward anabolic processes facilitates this phenomenon by providing the cellular building blocks necessary
for cell division (i.e., nucleotides for DNA synthesis andphospholipids as a component of the plasma membrane).

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Fig. 4 (See legend on previous page.)

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Moreover, AKT suppresses Chk1, p21 and p27, which arenegative regulators of the cell cycle via phosphorylation,and phosphorylates Mdm2 to repress p53 [1]. ThroughRNA-seq followed by pathway analysis, we also foundthat MET is promoted in AKT-activated cells, whichis associated with the improvement of the reprogramming efficiency by AKT [31]. Several other roles of AKT
in cellular reprogramming and pluripotency, including
apoptosis inhibition and the respiratory shift mediatedby activated AKT in mitochondria, have also been proposed[45, 46]. Altogether, our results showing the role of
AKT in epigenetic reprogramming associated with metabolic remodeling add new insight into the wide-ranging
roles of AKT signaling in cellular reprogramming.

Conclusion
In summary, we performed a multiomics analysis toobserve the effects of AKT activation on somatic cell
reprogramming. These findings may provide novel
insights into the dynamic link between AKT signaling
and epigenetic regulation mediated by metabolic remodeling in pluripotency acquisition.
Abbreviations
PI3K: Phsophoinositide-3 kinase; iPSCs: Induced pluripotent stem cells; PGCs:
Primordial germ cells; MEFs: Mouse embryonic fibroblasts; EGFP: Enhanced
green fluorescent protein; OE-MEFs: Mouse embryonic fibroblasts carrying
Oct4-EGFP transgene; dpi: Days postinfection; FACS: Fluorescent activatedcell sorting; αKG: α-Ketoglutarate; DM-αKG: Dimethyl-α-ketoglutarate; 5mC:
5-Methylcytosine; 5hmC: 5-Hydoxymethylcytosine; 5fC: 5-Formylcytosine;
5caC: 5-Carboxylcytosine; 4OHT: 4-Hydroxytamoxyfen; OSK: OCT4, SOX2 andKLF4; AKT-MER: Fusion protein of myristoylated AKT and modified estrogen
receptor; OSKA: OCT4, SOX2, KLF4 and AKT-MER; TET2CD: TET2-catalytic
domain; OSKT2: OCT4, SOX2, KLF4 and TET2-catalytic domain; IDH1: Isocitrate
dehydrogenase 1; 2HG: 2-Hydroxyglutarate; AOA: Aminooxyacetic acid.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s13287-​021-​02578-1.
Additional file 1: Data 1 : Metabolome data for OSKA − 4OHT and
OSKA + 4OHT at 10 dpi.

Additional file 2: Auto ma ted shell scr ipt used for quantification of DNA
methylation.
Additional file 3: Automated shell script used for quantification of DNA
methylation for Linux.
Additional file 4: Read me for automated shell script used for quantification of DNA m ethylation.
Additional file 5: Supplementary Methods, References, Tables andFigures.
Acknowledgements
We thank Dr. Guoliang Xu for pMYs-Flag-TET2CD plasmid, Kazuko Fujitani forhelp with sequencing and Keita Fujikawa for help with iPSC generation.

Page 13 of 15

Authors’ contributions
Yo.S. contributed to the design and performance of most of the experiments
and wrote the manuscript. Yu.S. and E.S. performed and analyzed the metabolomic data. A.M. performed most of the experiments. Yu.K. performed the dot
blot analysis and analyzed the results. R.K. performed the proteomic analysis.
K.A. and M.S. performed the bisulfite sequencing analysis. T.I. performed thewestern blot analysis. T.Y. analyzed the transcriptomic data. E.K. performed
the qRT-PCR. T.N., M.S. and F.I. held collaborative discussions on the data. Yo.K.
performed the proteomic analysis and analyzed the data. Ta.K. performed the
dot blot analysis and the RNA sequencing analysis and analyzed the results.
To.K. initiated, designed and led the study and wrote the manuscript, with all
authors contributing to the final version.
Funding
This work was supported by a JSPS Grant-in-Aid for Young Scientists (B)(JP15K18458), a JSPS Grant-in-Aid for Scientific Research (C) (20K07577),
Takeda Science Foundation, Kitasato University Research Grant for Young
Researchers, Nanken-Kyoten Tokyo Medical and Dental University, andthe MEXT Joint Usage/Research Center Program at the Advanced Medical
Research Center, Yokohama City University to Yo.S., and JSPS Grant-in-Aid for
Scientific Research (B) (JP24390097) to To.K.
Availability of data and materials
The datasets used and/or analyzed during the current study are available
from public databases (see Methods), supplementary information and thecorresponding author on reasonable request.

Declarations
Ethic approval and consent to participate
This study does not report on or involve the use of human data or tissue. All
animal care and experiments were carried out in accordance with Guidelines of Animal Experiments of Kitasato University and were approved by
Institutional Animal Care and Use Committee of Kitasato University (Approval
number: SAS2004). The study was carried out in compliance with the ARRIVE
guidelines (https://​arriv​eguid​elines.​org).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing financial and non-financial interests.
Author details
1
Laboratory of Stem Cell Biology, Department of Biosciences, Kitasato
University School of Science, 1‑15‑1 Kitasato, Minami‑ku, Sagamihara‑shi,Kanagawa 252‑0373, Japan. 2 Department of Biochemistry, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku‑ku, Tokyo 160‑8582, Japan.
3
Department of Epigenetics, Medical Research Institute, Tokyo Medical
and Dental University, 1‑5‑45 Yushima, Bunkyo‑ku, Tokyo 113‑8510, Japan.
4
Department of Physics, Kitasato University School of Science, 1‑15‑1 Kitasato, Minami‑ku, Sagamihara‑shi, Kanagawa 252‑0373, Japan. 5 Laboratory
for Epigenetic Regulation, Nagahama Institute of Bio-Science and Technology,
1266 Tamura‑cho, Nagahama‑shi, Shiga 526‑0829, Japan. 6 Center for Disease
Proteomics, Kitasato University School of Science, 1‑15‑1 Kitasato, Minami‑ku,
Sagamihara‑shi, Kanagawa 252‑0373, Japan. 7 Laboratory of Embryology
and Genomics, Department of Biotechnology, Faculty of Life and Environmental Sciences, University of Yamanashi, 4‑4‑37 Takeda, Kofu‑shi, Yamanashi 400‑8510, Japan.
Received: 11 May 2021 Accepted: 31 August 2021

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