Advance Publication by J-STAGE Journal of Reproduction and Development
Accepted for publication: February 16, 2017 Published online: March 31, 2017
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High-resolution profiles of gene expression and DNA methylation highlight mitochondrial
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modifications during early embryonic development
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Likun Ren1)*, Chao Zhang1)*, Li Tao1)*, Jing Hao1), Kun Tan1), Kai Miao1), Yong Yu1), Linlin Sui1),
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Zhonghong Wu1), Jianhui Tian 1), Lei An1)
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1) Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture,
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National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology,
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China Agricultural University, Beijing 100193, P. R. China
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* Likun Ren and Chao Zhang contributed equally to this work.
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Running head: Mitochondrial modifications in embryos
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Corresponding author: Lei An (email:
[email protected])
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Abstract
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Well-organized mitochondrial functions and dynamics are critical for early embryonic development
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and are operated via a large number of mitochondria-related genes (MtGs) encoded by both the
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nuclear and the mitochondrial genome. However, the mechanisms underlying mitochondrial
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modifications during the critical window between blastocyst implantation and postimplantation
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organogenesis are poorly understood. Herein, we performed high-resolution dynamic profiling of
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MtGs to acquire a more detailed understanding of mitochondrial modifications during early
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development. Our data suggest that the resumption of mitochondrial mass growth is not only
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facilitated by increased mitochondrial biogenesis and mitochondrial DNA (mtDNA) replication, but
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also by the appropriate balance between mitochondrial fission and fusion. In addition, increased levels
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of reactive oxygen species (ROS) resulting from enhanced mitochondrial functions may be the critical
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inducer for activating the glutathione (GSH)-based stress response system in early embryos. The
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appropriate balance between the mitochondrial stress response and apoptosis appears to be significant
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for cell differentiation and early organogenesis. Furthermore, we found that most MtGs undergo de
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novo promoter methylation, which may have functional consequences on mitochondrial functions and
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dynamics during early development. We also report that mtDNA methylation can be observed as early
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as soon after implantation. DNMT1, the predominant enzyme for maintaining DNA methylation,
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localized to the mitochondria and bound to mtDNA by the implantation stage. Our study provides a
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new insight into the involvement of mitochondria in early mammalian embryogenesis. We also
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propose that the epigenetic modifications during early development are significant for modulating
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mitochondrial functions and dynamics.
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Key words: Mitochondria, Early embryos, Reactive oxygen species, Glutathione, DNA methylation
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Introduction
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Mitochondria not only provide the energy required to maintain cellular survival and growth but
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also participate in a number of pathways that maintain cellular homeostasis, including ion homeostasis,
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amino acid metabolism, glycolysis, fatty acid metabolism, signal transduction, and apoptosis [1].
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Well-organized mitochondrial dynamics and functions are of prime importance for early embryonic
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development. During the period between the blastocyst and the postimplantation stages, which
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overlaps with implantation and organogenesis initiation, the mitochondrion undergoes dramatic
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modifications, including mitochondrial biogenesis and mitochondrial DNA (mtDNA) replication, a
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shift from anaerobic to aerobic metabolism, and changes in the mitochondrial ultrastructure [2]. These
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mitochondrial modifications are essential for successful implantation and survival. However, the
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comprehensive mechanism underlying mitochondrial dynamics during this critical developmental
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period remains largely elusive.
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The orchestrated mitochondrial functions and dynamics are highly regulated by both the nuclear
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(nDNA) and mitochondrial genomes (nuclear-mitochondrial cross-talk). In addition to the 37
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mtDNA-encoded genes, it is estimated that approximately 1200 proteins encoded by nDNA can enter
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the mouse mitochondrial matrix or bind to its membrane [3]. These mitochondria-related genes (MtGs)
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have been targeted in high-resolution gene expression analysis to evaluate the involvement of
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mitochondrial dysfunctions in cardiac pathology [4] and cancer [5]. Recently, our own studies
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suggested that mitochondrial dysfunction may be the determining factor of impaired development of
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in vitro fertilized (IVF) embryos through disturbed oxidative phosphorylation (OXPHOS), reduced
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mitochondrial biogenesis, and dysregulated responses to oxidative stress [6].
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In this study, we performed a dynamic high-resolution expression profiling of MtGs during early
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embryonic development, using samples from E3.5 blastocysts, epiblasts from E7.5 embryos (E7.5
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epiblasts), and E10.5 embryos. The targeted profiling of a specific gene set leads to a more efficient
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enrichment of the involved mitochondrial functions, thereby providing a more detailed and
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comprehensive understanding of mitochondrial dynamics and functions during early development.
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In addition to the expression profiling, we also highlighted the DNA methylation dynamics of
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MtGs for the period between the blastocyst and the postimplantation stages. One of the most important
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epigenetic events during this critical developmental period is the re-establishment of DNA methylation
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patterns, termed de novo DNA methylation. The progression of this. epigenetic event highly coincides
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with the mitochondrial modifications taking place by the implantation stage, such as the ‘embryonic
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shift’ from anaerobic to aerobic metabolism and the resumption of mitochondrial biogenesis. In
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addition, previous studies demonstrated that the DNA methylation status of nDNA-encoded MtGs
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underlies tissue- or cell type-dependent mitochondrial functions and dynamics [7, 8] as well as
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mitochondrial pathology [9-11]. These facts lead us to investigate whether de novo DNA methylation
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may play a regulatory role in the mitochondria during early development.
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Materials and Methods
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Animal preparation
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F1 female mice (ICR, 5–6 weeks old) and F1 male mice (ICR, 8–9 weeks old) were fed ad
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libitum and housed in a room with a controlled light cycle (12L:12D). F1 females were naturally
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mated with F1 males. All studies were specifically approved by and performed in accordance with the
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guidelines of the Institutional Animal Care and Use Committee of China Agricultural University.
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Embryo preparation and collection
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The criteria for sampling embryos were based on developmental progress and morphology.
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Embryos showing typical morphological features according to the well-established landmarks [12]
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were sampled for further analyses. All sampled embryos for RNA and DNA isolation were serially
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washed with phosphate-buffered saline (PBS; GIBCO, Life Technologies, NY, USA) and immediately
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stored in liquid nitrogen for future use. In addition, to avoid cross-contamination between embryonic
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and extraembryonic tissues, we controlled the efficiency of the dissection procedure by detecting the
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expression of markers specific to the extraembryonic ectoderm (ETS-related transcription factor, Elf5),
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ectoplacental cone (Achaete-scute like 2, ASCL2, also known as Mash2), and epiblasts (fibroblast
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growth factor 5, Fgf5) at E7.5 [13].
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In vitro fertilization and culture
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To generate in vitro fertilized embryos, female ICR mice were superovulated by an
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intraperitoneal (i.p.) injection of 5 IU pregnant mare serum gonadotropin (PMSG; Ningbo Hormone
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Product Co., Ltd., Ningbo, China), followed by an i.p. injection of 5 IU human chorionic gonadotropin
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(hCG; Ningbo Hormone Product Co., Ltd.) 48 h later. At 14 h after hCG treatment, cumulus-enclosed
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oocyte complexes were recovered from oviducts and cumulus cells were removed by digestion with
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hyaluronidase (Sigma-Aldrich, St. Louis, MO, USA) for 3–5 min. The oocytes were rinsed in human
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tubal fluid (HTF) medium (Sage, Bedminster, NJ, USA), and placed into 60 μl drops of HTF medium
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covered with paraffin oil, before being equilibrated overnight at 37°C and 5% CO2. Sperm was
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collected from the cauda epididymis and capacitated for 1 h in HTF medium at 37°C and 5% CO2.
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Oocytes were inseminated 15 h post-hCG with 106 spermatozoa. After 4 h in the incubator, oocytes
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and zygotes were washed several times in potassium simplex optimization medium containing amino
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acids (KSOM + AA; Millipore, Billerica, MA, USA) and then transferred to 60 µl drops of KSOM
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medium. The zygotes, determined by the presence of two pronuclei, were cultured to the blastocyst
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stage at 37°C in a 5% CO2 atmosphere. Well-developed late-cavitating blastocysts of similar
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morphology were sampled at 106–112 h post-hCG after culturing in KSOM medium [14].
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Pseudopregnant female mice were mated with vasectomized males 3.5 days prior to embryo transfer.
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Twelve IVF blastocysts were transferred to a single recipient, with six embryos placed in each uterine
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horn.
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High-throughput RNA sequencing (RNA-seq) and biological analysis
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Total RNAs were extracted from embryos at different stages with the TRIzol Reagent (Invitrogen,
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Carlsbad, CA, USA). Polyadenylated RNAs were isolated using the Oligotex mRNA Midi Kit (Qiagen,
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Valencia, CA, USA). The RNA-seq libraries were constructed using the SOLiD Whole Transcriptome
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Analysis Kit (Applied Biosystems, Carlsbad, CA, USA) following the standard protocol and
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sequenced on the SOLiD platform (Applied Biosystems) to generate high-quality single-end reads.
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The raw reads were aligned to genome sequences, trimming off a nucleotide from each of the 5′ and 3′
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ends and allowing up to two mismatches. Reads mapped to multiple locations were discarded and only
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uniquely mapped reads were used for the subsequent analysis. Gene expression levels were measured
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in reads per kilobase of exon model per million mapped reads (RPKM). A single pooling strategy for
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relatively large sample sizes was used, as described previously [15, 16].
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DAVID v6.7 (http://david.abcc.ncifcrf.gov) was used to annotate biological themes (gene
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ontology, GO). REVIGO analysis (http://revigo.irb.hr) was also performed to visualize the interactive
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relationship among enriched processes. The KEGG database (http://www.genome.jp/kegg) was used to
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determine the associated pathways. Data on MtGs were fed into STRING (http://string.embl.de) to
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build an interaction network. The phenotype annotations of MtGs were analyzed based on the Mouse
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Genome Informatics (MGI; http://www.informatics.jax.org/phenotypes.shtml) database.
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Apoptosis analysis
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Collected blastocysts were washed three times with 0.1% PVA/PBS and then transferred to PBS
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supplemented with 4% (v/v) paraformaldehyde and 0.5% Triton X-100 for simultaneous fixation and
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permeabilization at 37°C for 45 min. Apoptotic nuclei were detected using the In Situ Cell Death
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Detection Kit (Roche, Mannheim, Germany). The number of apoptotic nuclei was determined under a
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BX51epifluorescence microscope (Olympus, Tokyo, Japan).
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RNA isolation and quantitative real-time RT-PCR (qRT-PCR)
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Total RNA extraction from embryos was performed using TRIzol according to the manufacturer’s
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instructions. Reverse transcription (RT) was carried out using a commercially available first-strand
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cDNA synthesis kit (iScript cDNA Synthesis Kit; Bio-Rad Laboratories, USA). Real-time PCR was
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performed in the Bio-Rad CFX96 Real-Time PCR System using SsoFast EvaGreen Supermix
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(Bio-Rad Laboratories, Hercules, CA, USA). Used primers are listed in Supplementary Table S1.
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MtDNA copy number determination by qPCR
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The nuclear-encoded β-actin gene and the mitochondria-encoded ND5 gene were used to
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determine the mtDNA copy numbers with the primers listed in Supplementary Table S1. Standard
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curves were constructed using recombinant plasmids that were serially diluted 103–108 times. The
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mtDNA and nDNA copy numbers were calculated from the threshold cycle number (CT) and
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corrected using the standard curve. The overall number of mtDNA copies per cell was calculated using
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the following formula: mtDNA copies per cell = ND5 copy number / (β-actin copy number/2).
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Measurement of reduced glutathione (GSH) and oxidized glutathione (GSSG)
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The contents of intracellular reduced glutathione (GSH) and oxidized glutathione (GSSG) in each
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blastocyst were determined using commercially available kits (Beyotime, Jiangsu, China) according to
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the manufacturer’s instructions. Absorbance was measured at 412 nm using the Infinite M200 PRO
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NanoQuant microplate reader (Tecan, Männedorf, Switzerland). Approximately 30 E3.5 blastocysts
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and 20 E7.5 epiblasts were used for measurements.
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Methylated DNA immunoprecipitation-sequencing (MeDIP-seq)
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Global genomic DNA, including both nDNA and mtDNA, was isolated from embryonic samples
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using the DNeasy Kit (Qiagen) according to the manufacturer’s instructions. The quality of each DNA
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sample with respect to integrity, purity, and concentration was assessed using a DN-1000
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Spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). Genomic DNA was then
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fragmented using a Covarias sonication system (Covarias, Woburn, MA, USA). After sonication, the
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fragments were denatured to produce single-stranded DNA (ssDNA). Following denaturation, the
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ssDNA was incubated with antibodies recognizing 5-methylcytosine (5mC). Magnetic beads
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conjugated to anti-mouse-IgG were then used to bind the anti-5mC antibodies and unbound DNA was
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removed along with the supernatant. Finally, DNA was released by digesting the antibodies with
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proteinase K and collected. Sequencing was carried out in 50 bp reads on the Illumina Hiseq 2000
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(Illumina, San Diego, CA, USA) by the Beijing Genomics Institute (BGI, Shenzhen, Guangdong,
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China) following the standard protocol.
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MeDIP-qPCR
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Global DNA was isolated using the Solar MicroElute Genomic DNA Kit (Solar Technologies Inc.,
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Gaithersburg, MD, USA). Sonicated DNA (fragment length: 100–600 bp) was treated with the
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EpiQuik MeDIP Ultra Kit (Epigentek, Farmingdale, NY, USA) to enrich methylated DNA fragments.
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Briefly, samples were precipitated with anti-5-mC, while samples precipitated with non-immunized
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IgG served as a negative control. The enriched methylated DNA was quantified by qPCR using
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specific primers (Supplementary Table S1) and the enrichment efficiency of MeDIP-qPCR was
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measured as fold enrichment (FE) with the following formula: FE (%) = 2(IgG CT –Sample CT) × 100%, as
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presented in the product manual.
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Results
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General dynamic profiling of MtGs during early development
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We gathered information for over 1000 MtGs, as reported by Mootha’s study [3], from the
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transcriptomic data obtained from E3.5 blastocysts, E7.5 epiblasts, and E10.5 embryos
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(Supplementary Table S2). The hierarchical clustering heatmap showed that all MtGs can be sorted
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into three main groups based on expression dynamics, namely whether they were most abundant at
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E3.5, E7.5, or E10.5. Each group can be further divided into two clusters (Fig. 1A). Compared with
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E3.5 blastocysts, E7.5 epiblasts and E10.5 embryos were clustered more tightly, with similar MtG
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expression patterns. Functional analysis showed that each cluster was significantly associated with
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many aspects of mitochondrial functions or related processes, including OXPHOS, oxoacid and amino
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acid metabolism, and apoptosis (Supplementary Fig. 1A), implying that mitochondrial dynamics
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during early development are orchestrated via complicated expression patterns involving MtGs
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(Supplementary Fig. 1B).
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To further explore the involvement of mitochondrial functions and dynamics during early
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embryonic development, the expression patterns of MtGs at E3.5, E7.5, and E10.5 were compared
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consecutively, i.e., E7.5 versus E3.5 and E10.5 versus E7.5. These two transitions encompass a series
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of important developmental events, such as implantation, cellular differentiation, and organogenesis.
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In the first transition, i.e., from E3.5 blastocysts to E7.5 epiblasts, 920 MtGs displayed significant
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changes in expression (P < 0.05), accounting for approximately 80% of identified MtGs. During the
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transition from E7.5 epiblasts to E10.5 embryos, the expression of 843 MtGs changed significantly (P
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< 0.05), accounting for approximately 73% of identified MtGs. Both percentages were higher than the
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corresponding values of the global transcriptome, which were approximately 70% and 64%,
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respectively (Fig. 1B), implying that expression of MtGs is highly dynamic during early development.
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These observations also suggest that mitochondrial features may undergo a more dramatic transition
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from E3.5 blastocysts to E7.5 epiblasts, in accordance with the results of the hierarchical clustering.
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A Venn diagram analysis was performed to screen MtGs consistently up- or downregulated (FC >
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2) during the transition E3.5 to E10.5. According to the results of the analysis, 58 MtGs showed
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consistent upregulation while 31 MtGs were consistently downregulated (Fig. 1C). Considering that
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the expression of these MtGs consistently changed during early development, they may contribute
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significantly to the highly dynamic mitochondrial functions taking place during this stage.
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Detailed functional profiling of MtGs during early development
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To further understand the comprehensive mechanism underlying mitochondrial functions and
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dynamics during early development, high-resolution functional profiling was performed for the MtGs
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whose expression significantly changed (P < 0.05, FC > 2) during the transition from E3.5 to E7.5
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(Supplementary Table S3) as well as from 7.5 to E10.5 (Supplementary Table S4).
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GO classification of biological processes indicated that ‘Oxoacid metabolic process’, ‘Coenzyme
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metabolic process’, ‘Cellular amine metabolic process’, and ‘Fatty acid metabolic process’ were the
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four most significantly enriched terms in the transition from E3.5 blastocysts to E7.5 epiblasts,
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suggesting that metabolic changes are the most evident feature of mitochondrial modifications during
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this period. In addition, ‘Apoptotic mitochondrial changes’ and ‘Response to ROS’ may also be
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significantly involved in this transition. Similar processes were enriched in the transition from E7.5
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epiblasts to E10.5 embryos (Fig. 2A and B). Next, we performed REVIGO analysis to visualize the
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interactive relationship among the enriched processes. Results from both transitions suggest that
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‘Transmembrane transport’ may play a key role in regulating mitochondrial metabolism and
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mitochondria-mediated apoptosis (Fig. 2C and D).
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KEGG pathway analysis provided us with more detailed insights into mitochondrial
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modifications. For the transition from E3.5 blastocysts to E7.5 epiblasts, the altered mitochondrial
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energy metabolism included ‘TCA cycle’, ‘OXPHOS’, and ‘Fatty acid β-oxidation’, while the changed
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amino acid metabolism involved arginine, proline, valine, leucine, glutamate, and glycine. It should be
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noted that some pathways of neurodegenerative diseases, including ‘Alzheimer’s disease (AD)’,
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‘Parkinson’s disease (PD)’ and ‘Huntington’s disease (HD)’ were also enriched, mainly because of
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MtGs associated with ‘OXPHOS’ and ‘apoptosis’. Likewise, changes in energy metabolism and amino
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acid metabolism were also significant during the transition from E7.5 to E10.5 embryos (Table 1).
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Using dynamically changed MtGs (P < 0.05, FC > 2) as seed nodes, interaction networks were
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constructed. In addition to functional clusters similar to those identified by the GO and KEGG
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analyses, other processes or functions, such as ‘mitochondrial translation’ and ‘mitochondrial
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biogenesis’, were also significantly clustered. Another interesting observation was that some
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well-known genes responsible for the regulation of cell pluripotency and differentiation, such as
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members of the MAPK (Mapk8 and Mapk12), WNT (Wnt1 and Wnt3), and SMAD (Smad3 and Smad7)
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families, were clustered tightly with other MtGs, suggesting an essential role of mitochondrial
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functions in the regulation of pluripotency and differentiation in early embryos (Fig. 2E and F).
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Mitochondrial modifications required for successful implantation
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The above-mentioned functional profiling revealed that many mitochondrial modifications had
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undergone evident temporal changes by the implantation stage. The observed changes in the
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expression of some key genes of energy metabolism were in accordance with the ‘embryonic shift’
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from anaerobic to aerobic metabolism. Accordingly, MtGs associated with mitochondrial biogenesis
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showed changes that may accommodate the enhanced aerobic metabolism. It is noteworthy that the
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expression of MtGs underlying GSH biosynthesis and functions changed correspondingly, suggesting
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a physiological response to the increased ROS levels resulting from the enhanced mitochondrial
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functions (Fig. 3A).
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To gain further insight into the comprehensive mechanism underlying the increased
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mitochondrial biogenesis and GSH production in early embryonic development, we analyzed the
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dynamics of MtGs involved in these processes based on the gene list provided by Quick GO
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(https://www.ebi.ac.uk/QuickGO)
and
Wikipathways
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(http://www.wikipathways.org/index.php/WikiPathways). Results showed that the expression of most
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of the MtGs associated with these processes correspondingly changed from E3.5 to E7.5 (Fig. 3B).
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The changes of some selected MtGs were validated using qRT-PCR (Fig. 3C). Next, to understand the
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interactive relationship of these processes, we constructed a small network. This revealed a high level
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of association among these processes (Fig. 3D). Indeed, the involvement of mitochondrial biogenesis
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and GSH-based stress response in mitochondria-mediated apoptosis can also be deduced by the fact
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that many MtGs are shared among these terms.
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To assess the association between the resumption of mitochondrial biogenesis and mtDNA
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replication on the embryonic developmental potential, we compared the mtDNA copy numbers
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between in vivo conceived (IVO) and in vitro fertilized (IVF) embryos, which are characterized by
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higher and lower developmental rates, respectively. Our previous studies showed that IVF embryos
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have lower survival rate and weight, as well as greater variability in size and increased growth defects,
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compared to their IVO counterparts [6, 13, 17]. Quantitative analysis showed that mtDNA copy
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numbers in IVF embryos laid in a significantly lower range compared to those in IVO embryos (Fig.
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3E), suggesting that depressed mitochondrial resumption is strongly associated with impaired
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embryonic developmental potential.
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The presence of enhanced mitochondrial mass and metabolism during the implantation stage led
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us to speculate that postimplantation embryos face increased oxidative stress compared to
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preimplantation embryos. To this end, we determined the GSH/GSSG ratio, which is a well-accepted
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indicator for evaluating oxidative stress status [18], in E3.5 blastocysts and E7.5 epiblasts. We found
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the latter to display a significantly higher GSH/GSSG ratio, indicating increased oxidative stress soon
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after implantation (Fig. 3F).
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Subsequently, because of the significant changes in the expression patterns of apoptotic MtGs
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that had taken place by the implantation stage, we decided to compare the occurrence of apoptosis in
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E3.5 blastocysts and E7.5 epiblasts. TUNEL analysis showed that E7.5 epiblasts displayed a high rate
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of apoptosis compared to E3.5 blastocysts (Fig. 3G). Possible false-negative apoptotic nuclei in E3.5
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blastocysts can be excluded by the parallel observation of TUNEL-positive apoptotic nuclei in IVF
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blastocysts, which have been reported to have a relative higher apoptotic rate [6].
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The involvement of MtGs in embryonic survival and organogenesis
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To test the potential role of MtGs in embryonic survival and organogenesis, we performed an
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MGI analysis using dynamically changed MtGs (P < 0.05, FC >2; Supplementary Tables S5 and S6).
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Many MtGs were annotated with phenotypes associated with aberrant embryonic/fetal development,
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such as ‘Complete embryonic lethality’, ‘Embryonic growth arrest’, ‘Failure of somite differentiation’,
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and ‘Failure of embryo implantation’. In addition, many MtGs were associated with abnormal
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morphology or aberrant development of organs, especially of the neurosensory and cardiovascular
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systems, as well as with lethality during organogenesis. These observations suggested that orchestrated
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mitochondrial functions and dynamics are essential for embryonic survival and normal organogenesis
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both during and after implantation. In addition, we found that different mitochondrial modifications
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might functionally correlate with each other to regulate early organogenesis (Fig. 4).
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Dynamics of promoter DNA methylation of nDNA-encoded MtGs during early development
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The dramatic changes of mitochondrial functions and dynamics during early development,
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including the resumption of mitochondrial biogenesis and the shift from anaerobic to aerobic
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metabolism, coincide with de novo DNA methylation, which is one of the most important epigenetic
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events during early development. This led us to hypothesize that the de novo DNA methylation of
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MtGs may have an essential regulatory role in the mitochondrial modifications taking place during
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early development. To test this hypothesis, nDNA-encoded MtGs whose promoters were methylated at
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least once at three time-points (Supplementary Table S7) were hierarchically clustered based on their
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promoter DNA methylation levels, as described previously [19]. The resulting heatmap showed a
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generally progressive increase in promoter DNA methylation of MtGs during early development,
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especially of those belonging to clusters 1 and 2, which correspond to genes that are unmethylated in
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E3.5 blastocysts and gain promoter DNA methylation before E7.5 or E10.5, respectively. On the other
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hand, promoter DNA methylation increased slightly in cluster 3, which includes genes whose
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promoters appear methylated throughout early development (Fig. 5A).
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To test the correlation between promoter de novo methylation and the expression levels of MtGs
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during early development, we integrated the promoter DNA methylation profiles to the expression
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profiles of MtGs in clusters 1 and 2 (Fig. 5B; boxed by green and blue dotted lines, respectively). In
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cluster 1, 48 MtGs (54.5%) were downregulated during the transition from E7.5 to E10.5, with
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increased levels of promoter DNA methylation. In cluster 2, 85 MtGs (45.5%) showed decreased
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expression at E7.5 compared to E3.5, and the reduction in expression coincided with promoter de novo
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methylation taking place before E7.5. This result suggests that promoter de novo methylation may
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have a considerable regulatory effect on the expression of approximately half of MtGs, during early
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development.
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To further analyze the functional consequences of de novo methylation on mitochondrial
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modifications during early development, GO and KEGG analyses were performed for MtGs that were
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presumably regulated by increased promoter DNA methylation (indicated by green dots in Fig. 5A).
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The results showed that these MtGs were significantly associated with most mitochondrial functions
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taking place during both transitions. Amongst others, these included ‘Oxoacid metabolic process’,
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‘Cellular amino acid metabolic process’, ‘Electron transport chain’, ‘Mitochondrial transport’, and
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‘OXPHOS’ (Fig. 5C and D). It should be noted that although the number of enriched MtGs was very
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low (2–7), the levels of significance were very high, which implied that MtG promoter de novo
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methylation may profoundly affect mitochondrial functions and dynamics during early development.
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MtDNA methylation in postimplantation embryos
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Dnmt1 expression was found to be significantly higher in postimplantation than preimplantation
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embryos (Fig. 6A). This observation was confirmed by qRT-PCR analysis. As Dnmt1 can also
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translocate to the mitochondria for maintaining mtDNA methylation [20], we further investigated the
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expression dynamics of a transcript variant of Dnmt1 specifically targeted to mitochondria (mt-Dnmt1),
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which is not fully synchronized with the levels of total Dnmt1 (Fig. 6B). Based on the relatively stable
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expression of mt-Dnmt1 up to the implantation stage, we hypothesized that embryonic mtDNA may
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undergo methylation after implantation. This idea was supported by the enrichment of MeDIP reads on
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mtDNA in E7.5 epiblasts and E10.5 embryos (Fig. 6C, Supplementary Table S8). We validated this
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observation by performing MeDIP-qPCR with a highly sensitive and specific anti-5mC antibody. It
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should be mentioned that the primers used for detection were blasted against the mouse nuclear
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genome to prevent a possible contamination from nuclear sequences of mitochondrial origin.
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Focusing on the MeDIP-qPCR results from both hyper- (ND5, ND6) and hypomethylated (12S
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rRNA) regions, as well as a control region (D-loop), we observed that each of these regions was
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significantly methylated, with an increasing trend during the transition from E7.5 to E10.5 (Fig. 6D).
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Moreover, to confirm that mt-Dnmt1 can translocate to the mitochondria by the implantation stage, we
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tested the binding of mt-Dnmt1 to mtDNA by CHIP-qPCR using a non-specific anti-DNMT1 antibody
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and primers specific to mtDNA in E6.5 embryos, which represent a stage immediately after
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implantation. Results showed a significant enrichment of DNMT1 at two selected hypermethylated
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regions (ND5 and ND6) of mtDNA (Fig. 6E).
349 350
Discussion
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It is well documented that mitochondrial functions and dynamics are of prime importance to early
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development. Well-organized mitochondrial modifications are thought to be essential for embryonic
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survival and growth during implantation, as well as for subsequent differentiation and organogenesis.
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Focusing on MtGs, this study provided a comprehensive and detailed understanding of the
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mechanisms responsible for the orchestrated mitochondrial modifications taking place during early
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development.
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During the transition from E3.5 to E7.5, embryos undergo the differentiation of embryonic germ
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layers and implantation, two of the most important challenges that enable further embryonic survival
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and growth. On the other hand, in the period between E7.5 and E10.5, embryos initiate organogenesis
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following the completion of gastrulation [21]. During the transition from the blastocyst to the
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gastrulation stage, embryos undergo a shift in energy metabolism, in which glycolytic activity
362
gradually decreases but OXPHOS is rapidly enhanced. Coincident with this shift is the resumption of
363
mitochondrial biogenesis and mtDNA replication. Increased mitochondrial biogenesis and mtDNA
364
replication in somatic cells are thought to accommodate high energy demands during physiological
365
and pathological processes [22, 23]. In our study, we found that the expression of many key MtGs
366
involved in mitochondrial biogenesis and mtDNA replication significantly increases during
367
implantation. Among these, some are well-established MtGs considered responsible for the resumption
368
of mitochondrial biogenesis in early embryos, such as Polg, Polg2, and Tfam [24-26]. Other MtGs that
369
have been previously reported to play important roles in somatic cells may also be critical for this
370
resumption. For example, Ssbp1 encodes a subunit of a single-stranded DNA-binding complex that
371
can maintain the stability of mtDNA by removing mismatches during mtDNA replication [27] and
372
support mitochondrial protein synthesis and morphology in human osteosarcoma and embryonic
373
kidney cells [28, 29]. Stoml2, also known as Slp2, codes for a widely expressed mitochondrial inner
374
membrane protein and can induce mitochondrial biogenesis in human T lymphocytes [30]. Tk2 codes
375
for a deoxyribonucleoside kinase that localizes to the mitochondria and is required for the replication
376
and maintenance of mtDNA in cultured human somatic cells [31]. A recent study demonstrated that
377
Tk2 may be involved in the early development of zebrafish by modulating mtDNA metabolism [32];
378
however, a role for this gene in the resumption of mtDNA replication in mammalian embryos has not
379
yet been identified.
380
Mitochondria are dynamic organelles that are constantly undergoing fission and fusion to
381
maintain mitochondrial homeostasis and morphology [33-36]. An interesting observation of this study
382
was the increased level of Fis1, which is known to enable mitochondrial fission, as well as the
383
decreased levels of Mfn1/2 and Opa1, which facilitate mitochondrial fusion. Although the role of
384
mitochondrial fission and fusion during the period up to the implantation stage has not been
385
well-defined, mouse embryonic fibroblasts (MEFs), as well as ES and TS cells from mouse knockout
386
models displaying deficient fission and fusion, showed evident aberrations in mitochondrial mass and
387
morphology (elongated or fragmented mitochondria) [37-39]. Thus, we predict that the resumption of
388
mitochondrial growth by the implantation stage is not only facilitated by increased mitochondrial
389
biogenesis and mtDNA replication, but also by the appropriate balance between fission and fusion (Fig.
390
7A). In addition, deficient fission and fusion result in disrupted mitochondrial functions, distribution,
391
and apoptosis, with deficient embryos dying in midgestation [37-39]. These facts imply that fission
392
and fusion dynamics may also be involved in many aspects of mitochondrial modifications during this
393
critical period.
394
Enhanced mitochondrial functions not only provide more ATP but also produce more ROS.
395
Energy metabolism in mitochondria, including TCA, β-oxidation, and (especially) OXPHOS, is the
396
major source of ROS. Our results regarding the GSH/GSSG ratio suggested that embryos face
397
increased oxidative stress soon after implantation. Mitochondria are both a major source and a target
398
of ROS [40]. Mitochondrial glutathione (mGSH), which is synthesized in the cytosol and then
399
imported into the mitochondrial matrix, is thought to be the key survival antioxidant for maintaining
400
the appropriate mitochondrial redox environment [41]. Interestingly, the temporal pattern of GSH
401
biosynthesis is similar to the dynamics of the resumption of mitochondrial biogenesis by the
402
implantation stage [42]. Thus, increased GSH biosynthesis may be a physiological response to
403
enhanced mitochondrial functions and the consequent increase in ROS levels. Indeed, we observed an
404
evident activation of many key MtGs involved in GSH biosynthesis and metabolism. The expression
405
of Gclc and Gs (Glul), which code for the enzymes that catalyze the first (rate-limiting) and second
406
steps of glutathione biosynthesis, increased during implantation. We also found that Nrf1 and Nrf2
407
were upregulated; these well-known transcription factors can activate GSH-based antioxidative genes,
408
including Gclc, Gss, Glrxs, and Gpxs [43, 44]. Consistently, Keap1 and Cul3, which code for proteins
409
that inactivate Nrf2 by forming a KAP1/CUL3/NRF2 complex in the cytosol, were downregulated
410
during the transition from E3.5 blastocysts to E7.5 epiblasts. Previous studies in normal somatic cells
411
and cancer cells indicated that the inhibition of either Keap1 or Cul3 increases the nuclear
412
accumulation of Nrf2, leading to the activation of Nrf2-dependent antioxidative gene expression [45,
413
46]. Although the role of ROS in uncoupling NRF2 from the KAP1/CUL3 complex and thereby
414
upregulating the transcription of GSH-based antioxidative genes has been well documented in many
415
somatic cell types [47], the involvement of ROS in the Nrf2-induced activation of the GSH system has
416
never been demonstrated in early embryogenesis. Our data suggest that the enhancement of
417
mitochondrial functions in embryos by the implantation stage may increase the production of cellular
418
ROS, activating the expression of the GSH-based antioxidative system via the Nrf2-Keap1 signaling
419
pathway to protect mitochondria against oxidative stress (Fig. 7B). The transition from E3.5
420
blastocysts to E7.5 epiblasts was also characterized by a marked increase in the expression of many
421
Gpxs, which are the genes coding for proteins that catalyze the reduction of hydrogen peroxide and
422
lipid peroxides by GSH. Among these, Gpx3 and Gpx4 are well-known mitochondrial Gpx genes that
423
are essential for oxidative homeostasis in mitochondria [48, 49].
424
We also found many apoptotic genes undergoing significant changes during early development.
425
TUNEL analysis showed that E7.5 epiblasts displayed a high rate of apoptosis compared to E3.5
426
blastocysts, consistently to previously reported observations in hESCs undergoing differentiation [50].
427
Compared with MtGs associated with ‘Mitochondrial biogenesis and mtDNA replication’ and
428
‘GSH-based antioxidative response’, the gene expression dynamics of ‘Apoptotic mitochondrial
429
change’ showed a complicated pattern. Indeed, properly controlled mitochondrial apoptotic signaling
430
is not harmful to early embryos; in contrast, it is considered significant for the survival and
431
differentiation of early embryos [50, 51]. A PPI analysis showed that the term ‘Apoptotic
432
mitochondrial change’ was highly associated with ‘GSH-based antioxidative response’ and
433
‘Mitochondrial biogenesis’. Similarly, REVIGO analysis showed that ‘Apoptotic mitochondrial
434
change’ interacted significantly with ‘Oxoacid metabolism’. These observations imply that the
435
apoptotic and survival signals may be balanced by the GSH-based stress response (Fig. 7B).
436
Our data suggest that, in addition to successful implantation, mitochondrial functions or dynamics
437
may be also involved in early organogenesis. Using the MGI database, we found that many of the
438
MtGs whose expression was significantly altered (P < 0.05, FC >2) were associated with embryonic
439
death or aberrant development. At E7.5, when embryos are in an advanced stage of the gastrulation
440
process and have a formed neural plate, many of these MtGs were annotated with phenotypes such as
441
‘Decreased neuron number’, ‘Abnormal neural crest cell apoptosis’, and ‘Abnormal neural tube
442
morphology/development’. From E7.5 to E10.5, the neural plate folds to form the neural tube and the
443
brain, while structures and organs such as somites, the heart, and the limb buds start developing. MtGs
444
at this stage were annotated with phenotypes that included ‘Abnormal nervous system morphology’,
445
‘Abnormal eye development’, ‘Abnormal heart morphology’, and ‘Abnormal limb morphology’. It is
446
noteworthy that the MAPK and Wnt signaling pathways were tightly clustered with MtGs that are
447
responsible for mitochondrial functions. Previous studies in mouse and human ES cells indicated that
448
mitochondrial apoptotic signals might contribute to differentiation programs, probably via the MAPK
449
and Wnt signaling pathways [50, 51].
450
Our next step was to investigate whether the well-orchestrated mitochondrial functions and
451
dynamics taking place by the implantation stage are regulated by epigenetic modifications. Coinciding
452
with the dramatic mitochondrial changes during early development, embryos undergo de novo DNA
453
methylation. Aberrant de novo DNA methylation caused by deleting or mutating Dnmts in mice or ES
454
cells results in embryonic lethality and failed differentiation [52, 53]. Thus, we decided to investigate
455
the possible functional association of these two early developmental events. Our data showed that
456
most MtGs (clusters 1 and 2) underwent de novo methylation in their promoter regions during early
457
development. These observations were very similar to those reported by Borgel et al. [19] and Smith et
458
al. [54], who demonstrated that embryos undergo global promoter de novo methylation in the period
459
between the preimplantation and the postimplantation stages. In our study, the integrated analysis of
460
MtGs that underwent promoter de novo methylation revealed that approximately half of them
461
displayed reduced expression levels. Many of these MtGs are significantly associated with
462
mitochondrial functions and diseases. These results demonstrate that de novo DNA methylation, one of
463
the most important epigenetic events during mammalian embryogenesis, may have considerable
464
functional consequences for the mitochondrial modifications that are essential for embryonic survival
465
and growth.
466
Another finding was that the mtDNA of both E7.5 and E10.5 embryos showed significant
467
enrichment of MeDIP reads. This novel finding suggests that mtDNA methylation, which has been
468
reported in many somatic cell types [20, 55, 56], can be observed as early as immediately after
469
implantation. We also showed that this enrichment in early embryos was not limited to regions that
470
coded for enzymes essential for OXPHOS (ND5, ND6), but also in noncoding regions (12S rRNA) and
471
a control region (D-loop). In addition, in our study mtDNA methylation appeared to be independent of
472
CpG density, as it was detected in both high- and low-CpG regions. This result is consistent with the
473
findings of Bellizzi et al., who reported that both CpG and non-CpG regions of mtDNA can be
474
methylated in human blood and cultured cells [56]. To the best of our knowledge, this is the first study
475
to show that mtDNA becomes methylated in early embryos and that mt-DNMT1 can translocate into
476
the mitochondria matrix and bind to mtDNA for maintaining mtDNA methylation by the implantation
477
stage. Indeed, our unpublished data indicate that mtDNA undergoes a process similar to the de novo
478
DNA methylation of the nuclear genome, thereby demonstrating that highly dynamic DNA
479
methylation modifications are critical not only for the nuclear genome but also for the mitochondrial
480
genome.
481
Overall, our study provided high-resolution dynamic expression profiles of MtGs during early
482
embryogenesis. Our data indicate that orchestrated MtG expression is critical for the ‘embryonic shift’
483
in energy metabolism and the resumption of mitochondrial biogenesis, which is of prime importance
484
for successful embryonic implantation and survival. In addition, the mitochondria-mediated balance
485
between apoptosis and the stress response plays a significant role in the differentiation and
486
organogenesis of postimplantation embryos. Our data also suggest that promoter de novo methylation
487
of nDNA-encoded MtGs may have considerable functional consequences for mitochondrial
488
modifications. Finally, mtDNA methylation in somatic cells can be observed as early as immediately
489
after implantation. Our study can serve as a comprehensive reference for the further study of
490
mitochondrial modulations during early mammalian embryogenesis and provides a new insight into
491
the epigenetic mechanisms modulating mitochondrial functions and dynamics at this stage.
492
Acknowledgments
493
This work was supported by grants from the National Natural Science Foundation of China (No.
494
31672426 and 31472092) and the National High-Tech R&D Program (2013AA102506).
495 496
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497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540
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Figure legends
640
Figure 1. General dynamic profiling of mitochondria-related genes (MtGs) during early development.
641
(A) Hierarchical clustering analysis based on the dynamic expression levels of MtGs of embryos from
642
pre- to postimplantation. Normalized expression levels (RPKM) are represented by different colors:
643
red indicates high abundance and green indicates low abundance. The number of MtGs in each cluster
644
is presented on the right side. General trends in expression changes are indicated by the average
645
RPKM value of MtGs in each cluster. (B) Fold change (FC) distribution analysis of MtGs between
646
E3.5 blastocysts to E7.5 epiblasts as well as between E7.5 epiblasts and E10.5 embryos. Only MtGs
647
with statistically significant changes in expression were included (P < 0.05). (C) Venn diagrams of
648
upregulated (left panel, red) and downregulated (right panel, green) MtGs for two developmental
649
transitions. Tables show the major functions of MtGs that are consistently upregulated (left) or
650
downregulated (right) during early development.
651
Figure 2. General functional profiling of MtGs whose expression significantly changed (P < 0.05,
652
FC >2) during early development. (A-B) Classification of GO terms based on the functional
653
annotation of biological processes (BPs) enriched in the transition from E3.5 blastocysts to E7.5
654
epiblasts, as well as from E7.5 epiblasts to E10.5 embryos. The left ordinate represents the number of
655
enriched MtGs corresponding to each term and the right ordinate represents the enrichment score
656
(defined as −Log10 P-value). (C-D) Graph visualization of enriched BPs in A and B based on REVIGO
657
analysis. Bubble color indicates P-value. Functionally associated BPs are linked. (E-F) Interaction
658
networks of MtGs during early development created by a web-based search of the STRING database.
659
Boxed regions represent tightly interconnected functional clusters.
660
Figure 3. Mitochondrial modifications during implantation stage. (A) Model illustrating the
661
‘embryonic shift’ from anaerobic to aerobic metabolism, as well as the resumption of mitochondrial
662
biogenesis and the enhanced response to oxidative stress. Red text indicates upregulated MtGs, while
663
green text indicates downregulated MtGs. (B) Fold changes of representative MtGs involved in
664
essential mitochondrial modifications by the implantation stage. (C) Relative expression levels of
665
some representative MtGs in E3.5 blastocysts and E7.5 epiblasts determined by qRT-PCR. (D)
666
Interaction networks of MtGs responsible for essential mitochondrial modifications taking place
667
during the implantation stage. (E) Boxplot quantitative comparison of mtDNA copy numbers between
668
E10.5 embryos with higher and lower survival rates. (F) Ratios of reduced glutathione (GSH) to
669
oxidized glutathione (GSSG) in E3.5 blastocysts and E7.5 epiblasts; **P < 0.01. (G) Representative
670
images of apoptosis detected by TUNEL in E3.5 blastocysts and E7.5 epiblasts. Rightmost panels:
671
higher magnification of boxed regions in E7.5 epiblasts. The nuclei of blastomeres were labeled with
672
DAPI. Representative TUNEL-positive apoptotic nuclei are indicated with arrows. Scale bars, 100
673
μm.
674
Figure 4. Schematic diagram of the functional associations among MtGs that are annotated with
675
aberrant organogenesis during the postimplantation stage. Colored boxes indicate mitochondrial
676
modifications that may be essential for embryonic survival and normal organogenesis during the
677
implantation and postimplantation periods.
678
Figure 5. Dynamics of promoter DNA methylation of nDNA-encoded MtGs and functional
679
consequences during early development (A) Hierarchical clustering analysis based on dynamic
680
methylation levels of MtGs during the transition from pre- to postimplantation embryos. Normalized
681
methylation levels are represented by different colors: red indicates relatively hypermethylated
682
promoters and black indicates relatively hypomethylated promoters. The numbers of MtGs in each
683
cluster are displayed on the right side of the plot. Graphs next to the plot display promoter methylation
684
levels during early development. The red line (upper graph) indicates total normalized methylation
685
values while blue lines (three lower graphs) correspond to average normalized methylation levels in
686
each cluster. (B) Scatter plots of expression changes versus mean differences of methylation for the
687
MtGs of cluster 1 (upper plot, boxed by green dotted line) and cluster 2 (lower plot, boxed by blue
688
dotted line) whose promoters underwent de novo methylation before E7.5 and E10.5, respectively.
689
Green dots indicate MtGs that are downregulated during the process of promoter de novo methylation,
690
while red dots indicate upregulated MtGs (C-D) Functional profiling of MtGs corresponding to the
691
green dots of the shaded regions of the scatter plots in (B) and may be negatively regulated by
692
promoter de novo methylation taking place between E3.5 and E7.5 or between E7.5 and E10.5.
693
Figure 6. MtDNA methylation in postimplantation embryos. (A) Expression dynamics of Dnmt1
694
during early development as assessed by RNA-seq. (B) Relative expression levels of total Dnmt1 and
695
mt-Dnmt1 during early development as determined by qRT-PCR. (C) MtDNA methylation levels are
696
presented as enriched MeDIP-seq reads (y-axis) on mtDNA positions (x-axis) in E7.5 epiblasts (upper
697
plot) and E10.5 embryos (lower plot). (D) Relative methylation levels at selected regions of mtDNA as
698
detected by MeDIP-qPCR in E7.5 epiblasts (upper plot) and E10.5 embryos (lower plot). (E) Relative
699
enrichment of DNMT1 at selected regions (Nd5 and Nd6) of mtDNA as determined by CHIP-qPCR in
700
E6.5 embryos. Values indicated by different letters are significantly different (P < 0.05). *P < 0.05;
701
**P < 0.01.
702
Figure 7. Schematic diagrams illustrating essential mitochondrial modifications during early
703
development. (A) The resumption of mitochondrial biogenesis by the implantation stage appears to be
704
facilitated not only by increased mitochondrial biogenesis and mtDNA replication but also by the
705
skewed balance between fission and fusion. (B) Enhanced aerobic metabolism by the implantation
706
stage, especially OXPHOS, leads to increased ROS production, which appears be the inducer of GSH
707
biosynthesis. The apoptotic and survival signals in early embryos may be balanced by the GSH-based
708
stress response.
709
710
Table 1. Enriched KEGG pathways (Top 15) for MtGs significantly changed during early
711
development E7.5 epiblasts vs. E3.5 blastocysts
KEGG terms
E10.5 embryos vs. E7.5 epiblasts
Count
P-value
KEGG terms
Count
P-value
22
6.56E-16
Alzheimer's disease
24
2.45E-09
Fatty acid metabolism
17
1.60E-11
14
2.57E-09
Alzheimer's disease
31
8.82E-11
Huntington's disease
24
2.74E-09
Butanoate metabolism
14
1.63E-09
Parkinson's disease
18
2.92E-07
15
3.27E-09
Oxidative phosphorylation
17
1.12E-06
Huntington's disease
28
1.03E-08
Propanoate metabolism
8
2.03E-05
Propanoate metabolism
12
1.83E-08
Butanoate metabolism
8
8.60E-05
Pyruvate metabolism
13
7.36E-08
9
2.41E-04
PPAR signaling pathway
17
1.45E-07
ABC transporters
8
3.11E-04
Parkinson's disease
22
1.51E-07
Fatty acid metabolism
8
3.11E-04
Citrate cycle (TCA cycle)
11
3.37E-07
8
3.57E-04
14
5.22E-07
10
0.0010
15
7.23E-07
7
0.0019
Tryptophan metabolism
10
3.48E-05
9
0.0022
beta-Alanine metabolism
7
2.39E-04
6
0.0023
Arginine and proline metabolism
Valine, leucine and isoleucine degradation
Amyotrophic lateral sclerosis (ALS) Glycolysis / Gluconeogenesis
712
Arginine and proline metabolism
Amyotrophic lateral sclerosis (ALS)
Valine, leucine and isoleucine degradation Apoptosis Steroid hormone biosynthesis PPAR signaling pathway Glycine, serine and threonine metabolism
92
Cluster 5
203
Cluster 6
50 40 30 20 10
Cluster 5
60 45 30 15 0
Log 2 Fold change
Group 1 Cluster 6
Group 3
144
Cluster 4
Group 3
Cluster 4
10 38
6
107 116 223 248 90 74
2 -2
261 920 188
24
-6
-10 10
Expression levels (RPKM)
Cluster 3
Group 2
100 80 60 40 20
121
172
Cluster 2
Cluster 3
120 100 80 60 40
B
Cluster 2 100 80 60 40 20
Log 2 Fold change
Cluster 1
Group 1
Cluster 1 200 170 140 110 80 50
Group 2
E10.5
306
E7.5
Expression levels (RPKM)
E3.5
Expression levels (RPKM)
A
21
6
175 54 100 260 281 74 42
2 -2 -6
843 127
11
-10 -10 -5 0 5 10 15 Log2 average RPKM
C
Functions
Consistently upregulated MtGs (FC>2)
Apoptosis/ proliferation/ differentiation
Nfatc4, Prkca, Smad3, Pak7, Ndn, Ak1, Casp8, Cyp1b1, Stmn1, Dpysl2, Bcl2, Wnt1, Shh, Cav1, Nos3, Mtch1, Stard13
Lipid metabolism
Pla2g4a, Abcd2, Mlycd, Hmgcs2
E7.5 vs. E3.5 193 58
151 31
E10.5 vs. E7.5
94 Mpo, Glrx2, Idh1, Mgst1
transmembra ne transport
Scn1b, Slc8a2, Slc25a25, Cacna1b
Consistently down-regulated mito-genes (FC>2)
Apoptosis/ proliferation/ differentiation
Cyct, Dmc1, Lgals12, Mtus1, Spns1, Ndufs1, Spast
Genetic information
Dmc1, Ppargc1b
Mito-membrane organization
Mtx1, Dsp, Immt, Slc25a41, Efhd1, Timm9, Cacna1d, Myh9
Glucose/ lipid/ amino acis metabolism
Echdc2, Atp5g1, Cox7a2l, Dmgdh, Atg7, Ass1
E7.5 vs. E3.5
111 Anti-oxidation
Functions
E10.5 vs. E7.5
Figure 1
No. of enriched genes
35 30 25 20 15 10 5 0
60 40 20 0
C
D
E
F
Mitochondrial translation
β-oxidation & TCA
Enrichment score
No. of enriched genes
80
Enrichment score
No. of enriched genes
B 50
25
40
20
30
15
20
10
10
5
0
0
Enrichment score
A
OXPHOS & mitochondria translation & transmembrane transport
Electron transfer chain
Amino acid metabolism Transmembrane transport
OXPHOS
Response to ROS Apoptosis/ proliferation
TCA & β-oxidation & Amino acid metabolism
Mitochondrial biogenesis
Figure 2
Response to ROS & apoptosis & proliferation & differentiation Prostaglandin metabolism
E3.5
B
E7.5
Hk2, Pdha1, Pdha2
Glycolysis Increased ROS OXPHOS
Atp5a1, Atp5b, Atp5d, Atp5e, Atp5f1, Atp5g1, Atp5g2, Atp5h, Atp5j2, Atp5s
Log2 Fold change form E3.5 to E7.5
A
Response to oxidative stress
Gclc, Gs, Gpx3, Gpx7, Glrx5, Gstm1, Slc25a11, Cul3, Keap1
Log2 Fold change form E3.5 to E7.5
Mitochondrial biogenesis
Polg, Slc25a33, Polg2, Tfam, Ssbp1, Dhodh, Fis1, Mfn1, Mfn2
5
MtGs repressing mitochondrial biogenesis
8 7 6 5 4 3 2 1 0 -1 -2 -3
GSH-based antioxidative response
MtGs repressing GSH synthesis
E3.5
4
E7.5
3
Log2 Fold change form E3.5 to E7.5
Relative expression levels to E3.5
Mitochondrial biogenesis & mtDNA replication
Cpt1b, Cpt1c, Cpt2
β-oxidation
C
6 5 4 3 2 1 0 -1 -2 -3
2 1 0
8 7 6 5 4 3 2 1 0 -1 -2
Apoptotic mitochondrial change
GSH-based antioxidative response
D
E Apoptotic mitochondrial change
Mitochondrial biogenesis
mtDNA copy number
1500 1200 900 600 300 0
80
G
E7.5 epiblast
Boxed region a
DAPI
100 60 40 20 0 E3.5 (n = 30)
E7.5 (n = 20)
DAPI/ TUNEL
F
Ratio of GSH/ GSSG
E3.5 blastocysts
**
Figure 3
a
b
b
Hk2: abnormal
Lrp5: abnormal eye
neuronal precursor proliferation
development; abnormal limb morphology
Cybb:
Mthfd1: abnormal
cardiac hypertrophy
Mthfd1l:
abnormal neural tube morphology
heart morphology; abnormal neural tube closure
Glucose/ lipid/ amino acid metabolism
vascular endothelial cell morphology
Dnaja3:
enlarged heart; cardiac interstitial fibrosis
Nos3: abnormal heart
morphology; abnormal limb morphology; abnormal neuron morphology; abnormal vascular branching morphogenesis
Cav1: abnormal astrocyte morphology; cardiomyopathy
Drd2: abnormal neuronal
Mitochondrial biogenesis & mtDNA replication
morphology; abnormal sensory capabilities
Shh : abnormal eye Polg: dilated
Abcd2 : abnormal nervous
heart left ventricle
system physiology; abnormal nervous system physiology
development; abnormal heart morphology; abnormal limb morphology; abnormal nervous system morphology
Hspa5 : abnormal
Slc8a2 :
abnormal neuron physiology
bone morphology
Apoptotic changes
abnormal sensory capabilities
abnormal neuron physiology
neuron differentiation/ proliferation
Atp7a: abnormal limb
Transmembrane transport
Cacna1b :
Scn2a1:
migration; abnormal neuron physiology
Nos2: abnormal heart
Abcd1: abnormal lens morphology; abnormal nervous system physiology
Ptrf: abnormal
Pink1: abnormal
neuron physiology; abnormal sensory capabilities
Ucp2: decreased
Vdr : abnormal heart ventricle morphology; abnormal limb bone morphology
Rnf7 : abnormal neuronal
neuron apoptosis
Casp2: abnormal
migration
neuron apoptosis
Response to stress
Bbc3 : abnormal heart left Glrx2 : abnormal
ventricle pressure; abnormal neuron physiology
eye physiology
Sod1 : neurodegeneration
Fxn : neurodegeneration Gstm1 : increased neuron apoptosis
Apaf1 : abnormal neural tube
morphology; abnormal neuronal migration/differentation; increased neuron apoptosis
Figure 4
Log2 Fold change (RNA-seq)
500
Cluster 1
0
Cluster 2 18 15 12 9 6 3 0
10 8 6 4 2
D
0
4
4.5
5
-3
48
Cluster 2
6
102
3 0
4
4.5
5
5.5
6
-3
85
-6
Log2 Fold change (MeDIP-seq)
Cluster 1 10
8
8
6
6
4
4 2
2
0
0
-Log 10 P value
4.0 3.0 2.0 1.0 0.0
0
Log2 Fold change (MeDIP-seq)
Log2 Fold change (RNA-seq)
3.5 2.8 2.1 1.4 0.7 0.0
40
3
-6
Cluster 2
3.0 2.4 1.8 1.2 0.6 0.0
-Log 10 P value
C
No. of enriched genes
Cluster 3
Cluster 1
6
1000
Cluster 3
69
212
Cluster 2
B
Total 1500
No. of enriched genes
Cluster 1
Ave. normalized Ave. normalized Ave. normalized methylation levels methylation levels methylation levels
103
Total normalized methylation levels
A
KEGG pathway (Cluster 2)
Count
P-value
KEGG pathway (Cluster 1)
Count
Pvalue
Aminoacyl-tRNA biosynthesis
5
0.0002
Glyoxylate and dicarboxylate metabolism
3
0.001
Alzheimer's disease
7
0.002
Alzheimer's disease
5
0.002
Arginine & proline metabolism
4
0.008
Huntington's disease
5
0.002
Huntington's disease
6
0.012
Parkinson's disease
4
0.008
Alanine, aspartate ,glutamate metabolism
3
0.022
Amyotrophic lateral sclerosis
3
0.014
Phenylalanine, tyrosine and tryptophan biosynthesis
2
0.038
Apoptosis
3
0.032
Figure 5
0.15 0.10 0.05 0.00
b 6
c
4 2
a
0
0.10 0.08 0.06 0.04 0.02 0.00
E10.5
1.6 1.2
ND5
a a
0.8 0.4 0.0
3.0
**
2.0 1.0 0.0 ND5
ND6 D-loop
Figure 6
IgG
5mC
**
15.0 **
10.0 5.0
**
**
**
**
0.0 **
60.0
E10.5
40.0 ** 20.0
**
**
IgG DNMT1
*
4.0
E7.5 20.0
0.0 12S
a
E3.5 E7.5 E10.5
D
E7.5
0.10 0.08 0.06 0.04 0.02 0.00
E6.5
2.0
E3.5 E7.5 E10.5
E7.5 E10.5
E
mt-Dnmt1
Methylation level detected by MeDIP-qPCR
Methylation level detected by MeDIP-seq
8
Relative expression levels
0.20
E3.5
C
Total Dnmt1
Relative expression levels
0.25
Fold enrichment
B RPKM of Dnmt1
A
**
**
ND6
A D
Nucleus MtGs for fusion and fission
Nrfs Polg, Polg2, Tfam, Ssbp1, Tk2, Stoml2, Fis1
Fis1, Mfn1, Mfn2, Opa1
Fis1
Opa1 Mfn1/2
E3.5
Fission
E7.5
Fusion
Fusion Fission Mitochondrial biogenesis & mtDNA replication
Casp3
B
Apoptosis
Damage
Cyto C
β-oxidation ROS TCA
Mitochondrion Slc25a11
Cyto C Bax, Bcl2l1, Bid, Bbc3 (Puma)
Damage
GSH
P53 OXPHOS
ROS
Nucleus ROS
GSH Nrf2 Kep1 Cul3
ROS
O-
O2-
Nrf2 Kep1 Cul3
Nrf2 Gs
Reduced glutathione (GSH) Gpx
Gclc, Gs, Gpxs, Gstm1, Glrx2
Gclc Glutamlycysteine
Clycine
Glutamate Cysteine
Gstm1 Oxidized glutathione (GSSG) ROS Prot-SH
Prot-S-SG Glrx2
Gclc
Upregulated genes
Mfn1
Downregulated genes Biochemical reaction Macromolecular damage Transmembrane transport Enhenced aerobic metabolism mtDNA
Figure 7
A
Ten most abundant MtGs in each cluster, enriched GO processes and KEGG pathways 10 most abundant MtGs
GO
Pathway
mt-Nd1, Hspa8, Hsp90ab1, Atp5l, mt-Cytb, mtNd2, mt-Co1, mt-Rnr2, mt-Rnr1, Cox5b
Oxoacid metabolism, Transmembrane transport, Translation, Electron transport chain, Coenzyme metaboliam
Oxidative phosphorylation, Huntington's disease, Alzheimer's disease, Parkinson's disease, Aminoacyl-tRNA biosynthesis
Cluster 2
Slc25a5, mt-Nd4, mt-Nd5, Ckb, Cox6a1, Ppp1cc, Cox8a, Uqcrc1, Calm1, Cs
Oxoacid metabolism; Fatty acid metabolism; Cellular lipid metabolism;Coenzyme metaboliam; Translation
Fatty acid metabolism, Alzheimer's disease, Propanoate metabolism, Valine, leucine and isoleucine degradation, Parkinson's disease
Cluster 3
Atp5b; Atp5g3; Atp5a1; Hspd1; Prelid1; Slc2a3; Vdac1; Atp5f1; Atp5e; Phb2
Oxoacid metabolism; Cellular amino acid metabolism, Transmembrane transport,Oxidative phosphorylation, Nitrogen compound biosynthesis
Parkinson's disease, Huntington's disease, Oxidative phosphorylation, Alzheimer's disease, Arginine, proline metabolism
Cluster 4
Rpl10a, Ywhae, Hspe1, Rpl23, Atp5h, Atp5g2, Ddx5, Cd24a, Uqcrh
Oxoacid metabolism; Apoptotic mitochondrial changes, Cellular amine metabolism; Mitochondrial transport; Cellular amino acid metabolism
Huntington's disease; Alzheimer's disease; Parkinson's disease; Arginine and proline metabolism; Oxidative phosphorylation
Cluster 5
Slc25a3, Ap2m1, Slc25a4, Atp5o Ndufb8, Atp5j, Ndufs3 Ndufb6, Gpx1, Mtx2
Electron transport chain; Response to reactive oxygen species; Transmembrane transport; Regulation of programmed cell death; Energy derivation by oxidation of organic compounds
Huntington's disease; Parkinson's disease; Alzheimer's disease, Oxidative phosphorylation; Insulin signaling pathway
Cluster 6
Stmn1, Cox7c, Sod1, Chchd2, Atp5j2, Idh2 Ndufa4, Ndufs2, Mdh1 Mtch1
Electron transport chain, Oxoacid metabolis, Fatty acid metabolism, Coenzyme metabolism, Cellular lipid metabolic process
Oxidative phosphorylation; Alzheimer's disease; Huntington's disease; Parkinson's disease; Valine, leucine and isoleucine degradation
B
Expression levels (RPKM)
Cluster 1
200 150
100 50 0
Supplementary Fig. 1. Dynamic and functional profiling of MtGs during early development. (A) Ten most
abundant MtGs in each cluster of Figure 1A, as well as enriched functional processes based on Gene ontology (GO) and KEGG analyses. (B) 3D-view of gene expression patterns of MtGs in each cluster of Figure 1A.
Supplementary Fig. 1