Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 721 records · Page 40Linked to original sources

bioRxiv2023

VHL Mutation Drives Human Clear Cell Renal Cell Carcinoma Progression Through PI3K/AKT-Dependent Cholesteryl Ester Accumulation

BackgroundCholesteryl ester (CE) accumulation in intracellular lipid droplets (LDs) is an essential signature of clear cell renal cell carcinoma (ccRCC), but its molecular mechanism and pathological significance remain elusive. MethodsEnabled by the label-free Raman spectromicroscopy, which integrated stimulated Raman scattering microscopy with confocal Raman spectroscopy on the same platform, we quantitatively analyzed LD distribution and composition at the single cell level in intact ccRCC cell and tissue specimens in situ without any processing or exogenous labeling. Since we found that commonly used ccRCC cell lines actually did not show the CE-rich signature, primary cancer cells were isolated from human tissues to retain the lipid signature of ccRCC with CE level as high as the original tissue, which offers a preferable cell model for the study of cholesterol metabolism in ccRCC. Moreover, we established a patient-derived xenograft (PDX) mouse model that retained the CE-rich phenotype of human ccRCC. FindingsSurprisingly, our results revealed that CE accumulation was induced by tumor suppressor VHL mutation, the most common mutation of ccRCC. Moreover, VHL mutation was found to promote CE accumulation by upregulating HIF and subsequent PI3K/AKT/mTOR/SREBPs pathway. Inspiringly, inhibition of cholesterol esterification remarkably suppressed ccRCC aggressiveness in vitro and in vivo with negligible toxicity, through the reduced membrane cholesterol-mediated downregulations of integrin and MAPK signaling pathways. InterpretationCollectively, our study improves current understanding of the role of CE accumulation in ccRCC and opens up new opportunities for treatment. FundingThis work was supported by National Natural Science Foundation of China (No. U23B2046 and No. 62027824), National Key R&D Program of China (No. 2023YFC2415500), Fundamental Research Funds for the Central Universities (No. YWF-22-L-547), PKU-Baidu Fund (No. 2020BD033), Peking University First Hospital Scientific and Technological Achievement Transformation Incubation Guidance Fund (No.2022CX02), and Beijing Municipal Health Commission (No. 2020-2Z-40713).

cancer biology↗

bioRxiv2023

Minimal Positional Substring Cover: A Haplotype Threading Alternative to Li & Stephens Model

The Li & Stephens (LS) hidden Markov model (HMM) models the process of reconstructing a haplotype as a mosaic copy of haplotypes in a reference panel (haplotype threading). For small panels the probabilistic parameterization of LS enables modeling the uncertainties of such mosaics, and has been the foundational model for haplotype phasing and imputation. However, LS becomes inefficient when sample size is large (tens of thousands to millions), because of its linear time complexity (O(MN), where M is the number of haplotypes and N is the number of sites in the panel). Recently the PBWT, an efficient data structure capturing the local haplotype matching among haplotypes, was proposed to offer fast methods for giving some optimal solution (Viterbi) to the LS HMM. But the solution space of the LS for large panels is still elusive. Previously we introduced the Minimal Positional Substring Cover (MPSC) problem as an alternative formulation of LS whose objective is to cover a query haplotype by a minimum number of segments from haplotypes in a reference panel. The MPSC formulation allows the generation of a haplotype threading in time constant to sample size (O(N)). This allows haplotype threading on very large biobank scale panels on which the LS model is infeasible. Here we present new results on the solution space of the MPSC by first identifying a property that any MPSC will have a set of required regions, and then proposing a MPSC graph. In addition, we derived a number of optimal algorithms for MPSC, including solution enumerations, the Length Maximal MPSC, and h-MPSC solutions. In doing so, our algorithms reveal the solution space of LS for large panels. Even though we only solved an extreme case of LS where the emission probability is 0, our algorithms can be made more robust by PBWT smoothing. We show that our method is informative in terms of revealing the characteristics of biobank-scale data sets and can improve genotype imputation.

bioinformatics↗

bioRxiv2023

LoxCode in vivo clonal barcoding resolves mammalian epiblast contribution to fetal organs

Much remains to be learned about the clonal fate of mammalian epiblast cells in vivo. Here we develop a high diversity, high throughput, Cre recombinase-driven DNA LoxCode barcoding technology for in vivo clonal lineage tracing. E5.5 pre-gastrulation embryos were barcoded in utero and epiblast clones later assessed for their contribution to a wide range of tissues and cell types in the E12.5 organogenesis-stage embryo. While a few epiblast clones contributed broadly to most tissues and cell types of the three germ layers, many clones were lineage biased towards either blood, ectoderm lineages, mesenchymal tissues or limbs. In addition to lineage bias, most epiblast clones were differentially fated for tissue types or descendants in tissues compartments across the body axes. Using a stochastic agent-based model of embryogenesis and LoxCode barcoding, we inferred and experimentally validated predicted cell fate biases as well as clonal compositions across tissues that are consistent with events of lineage segregation and shared trajectory of lineage differentiation. Our study has demonstrated the power of LoxCode barcoding in investigating multi-modal clonal fate at high throughput, thus enabling an in-depth interrogation of the clonal contribution of E5.5 epiblast cells to fetal tissues, organs and body parts.

developmental biology↗

bioRxiv2023

Crystal structure of a mammalian CMTM6 and its interaction model with PD-L1

CKLF-like MARVEL transmembrane domain-containing protein 6 (CMTM6) is a master regulator of PD-L1. By binding PD-L1 at the plasma membrane and recycling endosomes, CMTM6 prevents the lysosomal degradation of PD-L1 and maintains its cell surface expression, thus stabilizing the inhibitory PD-1/PD-L1 axis. However, the mechanism of CMTM6/PD-L1 interaction is unknown. Here we report the first experimentally determined structure of CMTM6 from bovine. Combined with a low-resolution cryo-EM map, computational docking analysis and a protein binding assay an interaction model between CMTM6 and PD-L1 was proposed, providing a structural framework for the CMTM6 regulation on PD-L1.

biophysics↗

bioRxiv2022

Neurotensin receptor allosterism revealed in complex with a biased allosteric modulator

The NTSR1 neurotensin receptor (NTSR1) is a G protein coupled receptor (GPCR) found in the brain and peripheral tissues with neurotensin (NTS) being its endogenous peptide ligand. In the brain, NTS modulates dopamine neuronal activity, induces opioid-independent analgesia, and regulates food intake. Recent studies indicate that biasing NTSR1 toward {beta}-Arrestin signaling can attenuate the actions of psychostimulants and other drugs of abuse. Here we provide the cryoEM structures of NTSR1 ternary complexes with heterotrimeric Gq and Go with and without the brain penetrant small molecule SBI-553. In functional studies, we discovered that SBI-553 displays complex allosteric actions exemplified by negative allosteric modulation for G proteins that are G subunit selective and positive allosteric modulation and agonism for {beta}-Arrestin translocation at NTSR1. Detailed structural analysis of the allosteric binding site illuminated the structural determinants for biased allosteric modulation of SBI-553 on NTSR1. These insights promise to both accelerate the structure-guided design of more effective NTSR1 therapeutics and provide insights into the complexities of GPCR allosteric modulation.

biophysics↗

bioRxiv2022

Integrating spatial transcriptomics data across different conditions, technologies, and developmental stages

With the rapid generation of spatial transcriptomics (ST) data, integrative analysis of multiple ST datasets from different conditions, technologies, and developmental stages is becoming increasingly important. However, identifying shared and specific spatial domains across ST datasets of multiple slices remains challenging. To this end, we develop a graph attention neural network STAligner for integrating and aligning ST datasets, enabling spatially-aware data integration, simultaneous spatial domain identification, and downstream comparative analysis. We apply STAligner to the integrative analysis of ST datasets of the human cortex slices from different samples, the mouse olfactory bulb slices generated by two profiling technologies, the mouse hippocampus tissue slices under normal and Alzheimers disease conditions, and the spatiotemporal atlases of mouse organogenesis. STAligner efficiently captures the shared tissue structures across different slices, the disease-related substructures, and the dynamical changes during mouse embryonic development. Additionally, the shared spatial domain and nearest neighbor pairs identified by STAligner can be further considered as corresponding pairs to guide the three-dimensional reconstruction of consecutive slices, achieving more accurate local structure-guided registration results than the existing method.

bioinformatics↗

bioRxiv2022

A refined characterization of large-scale genomic differences in the first complete human genome

The first telomere-to-telomere (T2T) human genome assembly (T2T-CHM13) release was a milestone in human genomics. The T2T-CHM13 genome assembly extends our understanding of telomeres, centromeres, segmental duplication, and other complex regions. The current human genome reference (GRCh38) has been widely used in various human genomic studies. However, the large-scale genomic differences between these two important genome assemblies are not characterized in detail yet. Here, we identify 590 discrepant regions ([~]226 Mbp) in total. In addition to the previously reported non-syntenic regions, we identify 67 additional large-scale discrepant regions and precisely categorize them into four structural types with a newly developed website tool (SynPlotter). The discrepant regions ([~]20.4 Mbp) excluding telomeric and centromeric regions are highly structurally polymorphic in humans, where copy number variation are likely associated with various human disease and disease susceptibility, such as immune and neurodevelopmental disorders. The analyses of a newly identified discrepant region--the KLRC gene cluster--shows that the depletion of KLRC2 by a single deletion event is associated with natural killer cell differentiation in [~]20% of humans. Meanwhile, the rapid amino acid replacements within KLRC3 is consistent with the action of natural selection during primate evolution. Our study furthers our understanding of the large-scale structural variation differences between these two crucial human reference genomes and future interpretation of studies of human genetic variation.

genomics↗

bioRxiv2022

PD-L1 regulates inflammatory macrophage development from human pluripotent stem cells by maintaining interferon-gamma signal

PD-L1 (programmed death-ligand 1) serves as a pivotal immune checkpoint in both the innate and adaptive immune systems. PD-L1 is expressed in macrophages in response to interferon-gamma (IFN{gamma}). We examined whether PD-L1 might regulate macrophage development. We established PD-L1-/- human pluripotent stem cells, differentiated them into macrophages, and observed a 60% reduction of CD11B+CD45+ macrophages in PD-L1-/-, orthogonally verified with PD-L1 inhibitor BMS-1166 reduced macrophages to the same fold. Single-cell RNA sequencing further confirmed the 60% reduction of macrophages as well as the down-regulation of macrophage-defining transcription factors SPI1, KLF6, and MAFB. Further, PD-L1-/- macrophages reduced the level of inflammatory signals such as NF{kappa}B, TNF, and chemokines CXCL and CCL families. Whilst anti-inflammatory TGF-{beta} was upregulated. Finally, we identified that PD-L1-/- macrophages significantly down-regulated interferon-stimulated genes (ISGs) despite IFN{gamma} in differentiation media. Mechanistically, PD-L1-/- macrophages reduced IFNGR1 expression explaining that cells could not respond to IFN{gamma}. These data suggest that PD-L1 regulates inflammatory macrophage development by maintaining the IFN{gamma} signal.

immunology↗

bioRxiv2022

The compact CasPi (Cas12l) bracelet "provides" a unique structural platform for DNA manipulation

CRISPR-Cas modules serve as the adaptive nucleic-acid immune systems for prokaryotes, and provide versatile tools for nucleic-acid manipulation in various organisms. Here, we discovered a new miniature type V system, CRISPR-Cas{pi} (Cas12l) ([~]860 aa), from the environmental metagenome. Complexed with a large guide-RNA ([~]170 nt) comprising the tracrRNA and crRNA, Cas{pi} (Cas12l) recognizes a unique 5 C-rich PAM for DNA cleavage under a broad range of biochemical conditions, and generates gene editing in mammalian cells. Cryo-EM study reveals a bracelet architecture of Cas{pi} effector encircling the DNA target at 3.4-[A] resolution, substantially different from the canonical two-lobe architectures of Cas12 and Cas9 nucleases. And the large guide-RNA serves as a two-arm scaffold for effector assembly. Our study expands the knowledge of DNA targeting mechanisms by CRISPR effectors, and offers an efficient but compact platform for DNA manipulations.

biophysics↗

bioRxiv2022

Performance characteristics allow for confinement of a CRISPR toxin-antidote gene drive designed for population suppression in a reaction-diffusion model

Gene drives alleles that can bias their own inheritance are a promising way to engineer populations for control of disease vectors, invasive species, and agricultural pests. Recent advancements in the field have yielded successful examples of powerful suppression type drives and confined modification type drives, but developing confined suppression drives has proven more difficult. This is because the necessary power for strong suppression is often incompatible with the characteristics needed for drive confinement. However, one type of CRISPR toxin-antidote drive may be strong enough and confined, the TADE (Toxin-Antidote Dominant Embryo) suppression drive. By disrupting a haplolethal target gene and a haplosufficient female fertility gene, this drive quickly eliminates wild-type alleles and eventually induces population suppression. It has been shown to perform effectively in panmictic populations. However, confinement in spatial scenarios may be substantially different. Here, we use a reaction-diffusion model to assess the performance of TADE suppression drive in continuous space. We measure the drive wave advance speed while varying several performance parameters and find that moderate fitness costs or embryo cutting (from maternally deposited nuclease) can eliminate the drives ability to form a wave of advance. We assess the release size required for the drive to propagate, and finally, we investigate migration corridor scenarios. Depending on the corridor size and dispersal, it is often possible for the drive to suppress one population and then persist in the corridor without invading the second population. This prevents re-invasion by wild-type, which may be a particularly desirable outcome in some scenarios. Thus, even imperfect variants of TADE suppression drive may be excellent candidates for confined population suppression.

genetics↗

bioRxiv2022

NaWRKY3 is a master transcriptional regulator of defense network against Alternaria alternata in Nicotiana attenuata

WRKY transcription factors are involved in plant defense responses against pathogens. However, no WRKYs have been reported yet in resistance of Nicotiana species to Alternaria alternata, a necrotrophic fungal pathogen causing brown spot disease. Here, we found that silencing NaWRKY3 lead to wild tobacco Nicotiana attenuata highly susceptible to A. alternata. Combination of transcriptome, electrophoretic mobility shift, ChIP-qPCR and dual-LUC analyses, we uncovered that NaWRKY3 bound to many defense genes promoter and activated their expression. Target genes included: 1) lipoxygenases 3, ACC synthase 1 and ACC oxidase 1, three key enzyme genes for JA and ethylene biosynthesis which were critical for A. alternata resistance; 2) feruloyl-CoA 6-hydroxylase 1 (NaF6H1), the key enzyme gene for phytoalexins against A. alternata, scopoletin and scopolin; and 3) three A. alternata resistance genes, long non-coding RNA (LncRNA L2), NADPH oxidase (NaRboh D) and berberine bridge-like (NaBBL28). Silencing LncRNA L2 reduced A. alternata-induced levels of JA and NaF6H1 expression. NaRboh D-silenced plants were strongly impaired in ROS production and stomata closure responses. NaBBL28 was the first A. alternata resistance BBLs identified and was involved in HGL-DTGs hydroxylation. Finally, NaWRKY3 could bind to its own promoter but acted as a transcriptional repressor. Thus we demonstrated that NaWRKY3 is a fine-tuned master regulator of defense network against A. alternata in N. attenuata by regulating different signaling pathways and defense metabolites. For the first time, such an important WRKY was identified in Nicotiana species, providing new insight into defense mechanism of Nicotiana plants to A. alternata.

molecular biology↗

bioRxiv2022

Transcription factor TFAP2C affects porcine early embryo development via regulating epigenetic modification

Transcription factors (TFs) have the potential function in regulating gene expression. Transcription factor TFAP2C plays important roles in the regulation of post-implantation embryonic development in mice, the reprogramming process, trophectoderm formation and carcinogenesis, but its role in porcine early embryo development remains unclear. This study was conducted to investigate the role of TFAP2C in porcine early embryo development using siRNA cytoplasmic injection. The RNAseq and immunofluorescence staining were performed to detect gene expression, and ChIP and dual luciferase reporter assays were used to elucidate the mechanism. The results showed that the deficiency of TFAP2C could lead to embryonic development disorder. The percentage of the blastocyst in the TFAP2C knockdown (TFAP2C-KD) group (7.76{+/-}1.86%) was significantly decreased compared to the control group (22.92{+/-}1.97%) (P**<0.01). The RNAseq results showed that 1208 genes were downregulated and 792 genes were upregulated after siRNA injection. The expression of epigenetic modification enzymes KDM5B, SETD2 (P**<0.01) etc. were significantly elevated in TFAP2C-KD group. Meanwhile, the modification levels of H3K4me3, H3K4me2 and H3K9me3 (P*<0.05) were significantly decreased, and the modification levels of H3K36me3 (P**<0.01) and DNA methylation (P**<0.01) were significantly increased in TFAP2C-KD group. DNMT1 was mostly expressed in cytoplasm in the control group, while it was mainly expressed in nuclei in the TFAP2C-KD group. In addition, TFAP2C could bind to the promoter region of SETD2, and the mutation of the TFAP2C binding site resulted in increased activity of SETD2 promoter (P**<0.01). The knockdown of TFAP2C affects histone modification and DNA methylation by regulating the expression of SETD2, KDM5B etc. and other genes, thereby inhibiting embryonic development. TFAP2C binds to the promoter region of SETD2 and acts as a hindrance protein. This study fills in the deficiency of TFAP2C in porcine early embryo development and provides theoretical support for animal husbandry production and biomedicine. Author SummaryThe correct activation of embryonic genes is required during early embryonic development, and the activation of these genes is subject to strict epigenetic regulation, such as DNA methylation, histone acetylation and methylation, with abnormalities in either leading to birth defects and developmental defects in individuals. TFs have specific binding motifs that regulate gene expression by binding to them. TFAP2C has been studied in post-implantation embryonic development and trophectoderm generation, however, the effect on early embryo development is unknown. Our findings suggest that TFAP2C deficiency disrupts gene expression patterns and leads to abnormal epigenetic modifications, resulting in abnormal embryo development. Furthermore, we found for the first time that TFAP2C can bind to the promoter region of SETD2, thereby affecting early embryo development in pigs. This indicates the critical role of TFAP2C in early embryo development in pigs on one hand, and also provides theoretical support for livestock production and biomedicine.

developmental biology↗

bioRxiv2022

Dynamic Interaction Learning and MultimodalRepresentation for Drug Response Prediction

Mining multimodal pharmaceutical data is crucial for in-silico drug candidate screening and discovery. A daunting challenge of integrating multimodal data is to enable dynamic feature modeling generalizable for real-world applications. Unlike conventional approaches using a simple concatenation with fixed parameters, in this paper, we develop a dynamic interaction learning network to adaptively integrate drug and different reactants on multimodal tasks towards robust drug response prediction. The primary objective of dynamic learning falls into two key aspects: at micro-level, we aim to dynamically search specific relational patterns on the whole reactant range for each drug-reactant pair; at macro-level, drug features can be used to adaptively correlate with different reactants. Extensive experiments demonstrate the validity of our approach in both drug protein interaction (DPI) and cancer drug response (CDR) tasks. Our approach achieves superior performance on both DPI (AUC = 0.967) and CDR (AUC = 0.932) tasks, outperforming competitive baselines from four real-world, drug-outcome datasets. In addition, the performance on the challenging blind subsets is remarkably improved, where AUC value increases from 0.843 to 0.937 on blind protein set of DPI task, and Pearsons correlation value increases from 0.516 to 0.566 on blind drug set of CDR task. A series of case studies highlight the potential generalization and interpretability of dynamic learning in the in-silico drug response assessment.

bioinformatics↗

bioRxiv2022

OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization

AlphaFold2 revolutionized structural biology with the ability to predict protein structures with exceptionally high accuracy. Its implementation, however, lacks the code and data required to train new models. These are necessary to (i) tackle new tasks, like protein-ligand complex structure prediction, (ii) investigate the process by which the model learns, which remains poorly understood, and (iii) assess the models generalization capacity to unseen regions of fold space. Here we report OpenFold, a fast, memory-efficient, and trainable implementation of AlphaFold2. We train OpenFold from scratch, fully matching the accuracy of AlphaFold2. Having established parity, we assess OpenFolds capacity to generalize across fold space by retraining it using carefully designed datasets. We find that OpenFold is remarkably robust at generalizing despite extreme reductions in training set size and diversity, including near-complete elisions of classes of secondary structure elements. By analyzing intermediate structures produced by OpenFold during training, we also gain surprising insights into the manner in which the model learns to fold proteins, discovering that spatial dimensions are learned sequentially. Taken together, our studies demonstrate the power and utility of OpenFold, which we believe will prove to be a crucial new resource for the protein modeling community.

bioinformatics↗

bioRxiv2022

A novel method revealing animal evolutionary relationships based on milk Mid-infrared

Mid-infrared spectra (MIRS) can effectively reflect the chemical bonds in milk, which has been widely used in dairy herd improvement. However, the relationship between MIRS and animal evolution remains largely unclear. This study firstly found great differences in MIRS and the components of milk by analyzing MIRS information of 12 different mammal species. A five-level discriminant model of evolutionary level based on MIRS was established with a test set kappa coefficient >0.97. In addition, a regression model of genetic distance was also established to estimate the genetic distance of different animal species with a correlation coefficient of R >0.94. These results showed that this method could be used for accurate mammalian evolutionary relationship assessment. We further clarified the potential relationship between MIRS and genes, such as PPP3CA and SCD that could change MIRS by regulating specific milk components. In conclusion, we expand the application of MIRS in animal species identification and evolution research and provide new perspectives for the research on the formation mechanism of different animal milk special components.

evolutionary biology↗

bioRxiv2022

Robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing (MGA-Seq)

Genomic abnormalities, including structural variation (SV), copy number variation (CNV), single-nucleotide polymorphism (SNP), homogenously staining regions (HSR) and extrachromosomal DNA (ecDNA), are strongly associated with cancer, rare diseases and infertility. A robust technology to simultaneously detect these genomic abnormalities is highly desired for clinical diagnosis and basic research. In this study, we developed a simple and cost-effective method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect SNPs, CNVs, SVs, ecDNA and HSRs in a single tube. This method has been successfully applied in both cancer cell lines and clinical tumour samples and revealed that focal amplification in tumour tissue is substantially heterogeneous. Notably, we delineated the architecture of focal amplification and the ecDNA network by MGA-Seq, which facilitated the exploration of the regulation of gene expression in ecDNA. This method could be extensively applied for diagnosis and may greatly facilitate the investigation of the genomic mechanism for genetic diseases.

genomics↗

bioRxiv2022

Comparative Mucomic Analysis of Three Functionally Distinct Cornu aspersum Secretions

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail, Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials. C. asperum secretes three mucus -- one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties to understand structure-function relationships through an integrative "mucomics" approach. We identify new macromolecular components of these hydrogels, including a novel protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences between C. aspersum mucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

biochemistry↗

bioRxiv2022

Dynamic changes in the transcriptome of oocytes during adolescent-onset PCOS in mice

(1) Background: This study aimed to explore temporal changes in the transcriptome of oocytes in an adolescent-onset polycystic ovarian syndrome (PCOS) mouse model. (2) Methods: An adolescent-onset PCOS mouse model was established using DHEA. Genes with a similar expression trend over time were identified using trend analysis. KEGG pathway enrichment analysis and gene regulatory network diagrams were examined for signaling pathways to identify potential hub genes related to the pathogenesis of PCOS. (3) Results: Four main trends of gene expression were extracted, of which six combinations of Venn diagrams were generated. Differentially expressed genes were mainly enriched in oxidative phosphorylation, cell cycle, P53 signaling pathway. Cell cycle-related genes (Skp1, Ccnb1, Orc1 and 5, Wee2, Mapk3, Cdc20) were abnormally down-regulated in the DHEA group. Ptges3 was the top1 DEGs at the initial stage of PCOS modeling. (4) Conclusion: This study provides a novel insight into the altered transcriptome of oocytes from PCOS mice. mtDNA-related genes and Cell cycle-related genes play the most important role in the development of PCOS. Ptges3 was the one of the top DEGs which was up-regulated in DHEA group at the initial stage of modeling, which suggested it may play an important role in the early stage of PCOS.

genetics↗