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Molecular Medicine Reports logoLink to Molecular Medicine Reports
. 2016 Sep 22;14(5):4223–4231. doi: 10.3892/mmr.2016.5761

Long non-coding RNAs regulate effects of β-crystallin B2 on mouse ovary development

Qian Gao 1,*, Hanxiao Ren 1,*, Mingkun Chen 1, Ziguang Niu 1, Haibo Tao 1, Yin Jia 1, Jianrong Zhang 1, Wenjie Li 1,
PMCID: PMC5101957  PMID: 27666820

Abstract

β-crystallin B2 (CRYBB2) knockout mice exhibit morphological and functional abnormalities in the ovary. Long non-coding RNAs (lncRNAs) regulate gene transcription and translation, and epigenetic modification of genomic DNA. The present study investigated the role of lncRNAs in mediating the effects of CRYBB2 in the regulation of ovary development in mice. In the current study, ovary tissues from wild-type (WT) and CRYBB2 knockout mice were subjected to lncRNA and mRNA microarray profiling. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to group the differentially expressed lncRNAs into regulated gene pathways and functions. The correlation matrix method was used to establish a network of lncRNA and mRNA co-expression. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to verify expression of a number of these differentially expressed lncRNAs and mRNAs. There were 157 differentially expressed lncRNAs and 1,085 differentially expressed mRNAs between ovary tissues from WT and CRYBB2 knockout mice. The GO and KEGG analyses indicated that these differentially expressed lncRNAs and mRNAs were important in Ca2+ signaling and ligand and receptor interactions. The correlation matrix method established an lncRNA and mRNA co-expression network, consisting of 53 lncRNAs and 45 mRNAs with 98 nodes and 75 connections. RT-qPCR confirmed downregulation of lncRNA A-30-P01019163 expression, which further downregulated its downstream gene purinergic receptor P2X, ligand-gated ion channel, 7 (P2rx7) expression in ovary tissues from CRYBB2 knockout mice. In conclusion, CRYBB2 regulates expression of different lncRNAs to influence ovary development. lncRNA A-30-P01019163 may affect ovarian cell cycle and proliferation by regulating P2rx7 expression in the ovary.

Keywords: β-crystallin B2, long non-coding RNAs, ovary development, signal transduction

Introduction

β-crystallin B2 (CRYBB2) expression was initially reported in the eye lens where it functions to maintain lens transparency and refractive index. CRYBB2 deficiency was demonstrated to result in the generation of age-associated cataracts (1). However, a number of previous studies demonstrated that CRYBB2 is also expressed in the retina, brain, testis, and ovary (25). Our previous study observed that CRYBB2 was expressed in human and mouse ovaries, particularly in ovarian granulosa cells (6). CRYBB2 knockout mice exhibited morphological and functional abnormalities in the ovary, including reduced ovarian index (ratio of ovary weight to total body weight) with increased follicle atresia, reduced mature follicles and dysregulated estrous cycle (7). Our data from a previous study also indicated a high level of estrogen in the diestrus and metestrus, but a low level of progesterone in the metestrus compared with wild-type (WT) mice (6). At the genetic level, expression of cell cycle and apoptosis-associated proteins, including B-cell lymphoma 2, cyclin-dependent kinase 4, and cyclin D2, were markedly lower in the CRYBB2 knockout mice compared with WT mice (6). These data suggest that CRYBB2 may be important in ovary development, however, the underlying molecular mechanism by which CRYBB2 regulates ovarian development remains to be elucidated.

To identify and assess the role of CRYBB2 in ovary development, differentially expressed long non-coding RNAs (lncRNAs) were profiled in CRYBB2 knockout mice. lncRNAs are a class of non-coding RNAs with nucleotides >200 bp and transcribed by RNA polymerase II. Functionally, lncRNAs may regulate gene transcription, protein translation, and epigenetic modification of genomic DNA. Altered expression and regulation of lncRNAs has been associated with human diseases and aging (812). For example, previous studies have suggested that overexpression of lncRNA HOX transcript antisense RNA associated with the recurrence of hepatocellular carcinoma, poor prognosis in colorectal cancer, and malignant behaviors of gastrointestinal stromal tumors (1315). lncRNAs modulate cell functions by regulating expression of targeted downstream genes (16), which may in turn affect embryo development (17), inactivate the X chromosome, and regulate genomic imprinting (18). Thus, the current study assessed whether these lncRNAs mediate the functions of CRYBB2 in ovary development and investigated the underlying mechanisms. Microarray profiling between ovarian tissues from CRYBB2 knockout and WT mice was conducted and bioinformatic analysis of differentially expressed lncRNAs and mRNAs was performed. A number of these differentially expressed lncRNAs and mRNAs were verified using quantitative reverse transcription-polymerase chain reaction (RT-qPCR).

Materials and methods

Animals

Male and female C57BL/6 mice were obtained from the Experimental Animal Center of the Second Military Medical University (Shanghai, China). CRYBB2 knockout mice were generated by the Ingenious Targeting Laboratory (Ronkonkoma, NY, USA), as described previously (19). All mice were maintained on a 12 h light/dark cycle with a temperature of 21±1°C and humidity of 50~70% in a pathogen-free facility with access to food and water ad libitum. Bedding material and a plastic house or tube was placed in the cage for environmental enrichment. Daily examinations were performed on all animals throughout the experimental period. Humane euthanasia of mice was performed under isoflurane anesthesia using intracardiac injection of pentobarbitone (150 mg/kg). The present study was conducted in accordance with institutional guidelines and approved by the Animal Care and Use Committee of Changhai Hospital (Shanghai, China).

A total of three 8-9-week-old (weight, 18.0±2.0 g) female CRYBB2 knockout mice and three age-matched WT female mice were obtained. Ovary tissues were collected from mice following a 10-day experimental period.

RNA isolation, cDNA synthesis and labeling, and hybridization

Ovarian tissues were homogenized on ice and total cellular RNA was isolated using TRIzol reagent (Invitrogen; Thermo Fisher Scientific, Inc., Waltham, MA, USA) according to the manufacturer's protocol and then quantified using NanoDrop ND-1000 (Thermo Fisher Scientific, Inc., Wilmington, DE, USA) and agarose gel electrophoresis. RNA samples were further purified using an RNeasy Mini kit (Qiagen, Inc., Valencia, CA, USA) and reverse transcribed into cDNA with fluorescent labeling for microarray hybridization using using the AffinityScript QPCR cDNA Synthesis kit (Agilent Technologies, Inc., Santa Clara, CA, USA). These labeled cDNA probes were then hybridized to Agilent mouse expression profiling (8×60K) microarray using the Gene Expression Hybridization kit (Agilent Technologies, Inc.) according to the manufacturer's protocol. The arrays were scanned into a file and analyzed using Feature Extraction software, version v10.7.3.1 (Agilent Technologies, Inc.). The arrays were scanned at 5 µm/pixel resolution using an Axon GenePix 4000B scanner (Molecular Devices, LLC, Sunnyvale, CA, USA) piloted by GenePix Pro 6.0 software (Molecular Devices, LLC) and then imported into NimbleScan software (version 2.5; Roche NimbleGen, Inc., Madison, WI, USA) for grid alignment and expression data analysis. Expression data were normalized using quantile normalization and the Robust Multichip Average algorithm included in the NimbleScan software. The probe level files and mRNA level files were generated following normalization. All mRNA level files were imported into Agilent GeneSpringGX software (version 11.0; Agilent Technologies, Inc.) for further analysis. Differentially expressed lncRNAs and mRNAs were identified via fold change filtering.

Functional analysis of microarray data

Gene Ontology (GO; www.geneontology.org) was performed to group differentially expressed lncRNAs and their targeted genes into biological processes, cellular components, and molecular features of the biological functions. Kyoto Encyclopedia of Genes and Genomes (KEGG; www.genome.jp/kegg) analysis was performed to identify roles of the target genes and group them into gene pathways. The correlation matrix method was used to establish a diagram of lncRNA and mRNA co-expression regulatory networks. Prior to functional analyses, the predicted potential lncRNA targets were integrated with the differentially expressed mRNAs using a cut-off value of ≥2.0 fold change or P<0.05.

RT-qPCR

Total RNA was isolated from granulosa cells from the ovaries of WT and CRYBB2 knockout mice using TRIzol reagent and reverse transcribed into cDNA using the PrimeScript RT Reagent Kit (Takara Biotechnology, Co., Ltd., Dalian, China) according to the manufacturer's protocols. These cDNA samples were then subjected to qPCR analysis using a Applied Biosystems 7300 Real-Time PCR system (Applied Biosystems; Thermo Fisher Scientific, Inc.) with the SYBR Green PCR Master Mix kit (Takara Biotechnology, Co., Ltd.). qPCR amplification was conducted at 95°C for 2 min, followed by 40 cycles of 95°C for 15 sec, and 60°C for 30 sec. The relative expression of each target gene compared to β-actin was calculated using the 2−ΔΔCq method (20). Specific primers used were as follows: Forward, 5′-AGCCATGTACGTAGCCATCC-3′ and reverse, 5′-CTCTCAGCTGTGGTGGTGAA-3′ for β-actin; forward, 5′-CGAGTTGGTGCCAGTGTGGA-3′ and reverse, 5′-CCTGCTGTTGGTGGCCTCTT-3′ for P2rx7; and forward, 5′-TCCACTCAGGAAGAGCTGGT-3′ and reverse, 5′-TAGCACCCTCGGGATATCTG-3′ for lncRNAA-30-P01019163.

Statistical analysis

All data were presented as the mean ± standard deviation. The data were Log2-transformed and median centered by genes using Cluster software, version 3.0 (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm). Statistical analyses were performed using SPSS 17.0 (SPSS, Inc., Chicago, IL, USA). The data were statistically analyzed using an unpaired Student's t-test or by one-way analysis of variance followed by Tukey's test. P<0.05 was considered to indicate a statistically significant difference.

Results

Microarray profiling of differentially expressed lncRNAs and mRNA in ovary tissues from wild type and CRYBB2 knockout mice

Microarray data on differential lncRNA and mRNA expression levels were analyzed using Cluster software, version 3.0 with the cut-off values set as ≥2-fold difference or P<0.05. The data indicated 157 differentially expressed lncRNAs (42 downregulated vs. 115 upregulated) and 1,085 differentially expressed mRNAs (570 downregulated vs. 515 upregulated; Fig. 1). The genes were selected according to a software forecast associated with the processes of ovarian development, and the lncRNAs associated with these genes were selected (Tables I and II).

Figure 1.

Figure 1.

Cluster analysis of differentially expressed lncRNAs and mRNAs in ovary tissues from WT and β-crystallin B2 knockout mice. The horizontal axis represents the sample group and the vertical axis represents the differentially expressed mRNAs or lncRNAs. Upregulated genes are red and downregulated genes are green. Included are 157 lncRNAs (42 downregulated vs. 115 upregulated) and 1,085 mRNAs (570 downregulated vs. 515 upregulated) KO, knockout; WT, wild-type; lncRNA, long non-coding RNA.

Table I.

Differentially expressed long non-coding RNAs in ovary tissues from β-crystallin B2 knockout mice.

Probe name P-value FC (abs) Regulation
A_30_P01032506 0.001900622 2.244835 Down
A_30_P01029732 0.026376737 2.3413253 Down
A_30_P01020038 0.020382054 2.3550973 Down
A_30_P01019163 0.008867065 2.3823233 Down
A_30_P01017808 0.003141625 2.3902857 Down
A_30_P01028465 0.026580842 2.3909771 Down
A_30_P01024278 0.010205811 2.4727218 Down
A_30_P01031572 0.036648612 2.5956807 Down
A_30_P01027590 0.034441914 2.6343288 Down
A_30_P01022135 0.04770927 3.120179 Down
A_30_P01031631 0.001265911 3.135137 Down
A_30_P01032372 0.009654216 3.4001627 Down
A_30_P01032133 0.012271924 3.434039 Down
A_30_P01024342 2.97×10−4 3.7296832 Down
A_30_P01024108 0.004697592 3.8198798 Down
A_30_P01022445 2.66×10−5 3.8623033 Down
A_30_P01022656 2.08×10−4 4.069888 Down
A_30_P01023636 0.02164327 4.4273615 Down
A_30_P01022538 9.77×10−4 5.492365 Down
A_30_P01033546 0.004913332 5.9940124 Down
A_30_P01019023 0.024659809 3.7894382 Up
A_30_P01024108 0.004697592 3.8198798 Up
A_30_P01017880 0.034943227 3.8256395 Up
A_30_P01022445 2.66×10−5 3.8623033 Up
A_30_P01026472 0.022304738 3.8728366 Up
A_30_P01030900 0.023211088 3.9997435 Up
A_30_P01022656 2.08×10−4 4.069888 Up
A_30_P01018745 1.84×10−5 4.266393 Up
A_30_P01033353 0.03583063 4.398616 Up
A_30_P01021636 0.01934708 4.4207296 Up
A_30_P01023636 0.02164327 4.4273615 Up
A_30_P01022538 9.77×10−4 5.492365 Up
A_30_P01019825 0.006051722 5.5902176 Up
A_30_P01033546 0.004913332 5.9940124 Up
A_30_P01024788 1.11×10−5 7.118162 Up
A_30_P01024270 6.38×10−5 8.226261 Up
A_30_P01027087 0.003292078 8.981714 Up
A_30_P01031162 0.011685452 9.579193 Up
A_30_P01021698 1.31×10−5 10.52238 Up
A_30_P01020936 4.52×10−4 22.788074 Up

FC, fold change.

Table II.

Differentially expressed mRNAs in ovary tissues from β-crystallin B2 knockout mice.

Gene P-value FC (abs) Regulation
Prkar2b 0.040216 2.1857524 Down
Lrp11 0.006975 2.9040618 Down
P2rx7 4.11×10−4 4.6213336 Down
Calml3 0.011701 5.126569 Down
Dclre1c 3.39×10−4 5.1453366 Down
Lpcat2 0.002695 5.828531 Down
Stk32a 0.001242 5.833555 Down
Cyp19a1 0.034041 6.1799 Down
Megf10 0.045621 6.1827664 Down
Plcxd1 1.04×10−4 6.82413 Down
Gm5103 0.005622 8.389297 Down
Fermt1 0.001363 8.656997 Down
Mlxip 3.10×10−4 8.746344 Down
Slc6a2 0.046581 8.750824 Down
Gm7969 0.012795 9.970471 Down
Ces2a 0.028129 10.472376 Down
Dclre1c 1.23×10−4 10.645219 Down
Ostn 9.07×10−6 11.019576 Down
Jph4 0.001674 12.722166 Down
Onecut2 0.048542 13.894124 Down
Ces2a 0.028128909 10.472376 Up
Dclre1c 1.23×10−4 10.645219 Up
Jph4 0.001673621 12.722166 Up
Onecut2 0.04854157 13.894124 Up
Itln1 5.97×10−5 14.339393 Up
Arsk 7.13×10−5 16.06716 Up
Sfrp4 0.023781205 17.065975 Up
Plekhg4 0.047409292 17.067673 Up
Nuf2 6.05×10−5 17.872303 Up
Adh7 0.0064019 18.950857 Up
Itln1 4.63×10−5 19.05549 Up
Ptgfr 0.032550577 20.059986 Up
Pou6f1 1.71×10−4 23.766891 Up
Saa2 0.023944996 25.063555 Up
Wnt10b 0.02046059 27.648937 Up
Ifi202b 0.001051159 28.72067 Up
Dcpp1 0.014649089 40.37458 Up
Cd5l 4.12×10−4 42.74245 Up
Dcpp2 0.012848383 45.13117 Up

FC, fold change.

Bioinformatic analysis of differentially expressed lncRNAs and mRNA in ovary tissues from WT and CRYBB2 knockout mice

GO analysis was performed for functional annotation of differentially expressed lncRNAs and mRNAs and it was observed that they were predominantly involved in cell cycle regulation, cell proliferation, metabolism, and signal transduction (Table III). One particular gene, P2rx7, localized in the cytoplasm, functions to regulate cell cycle progression and proliferation, and the signal transduction process.

Table III.

Gene ontology analysis of differentially expressed genes.

Term Number of genes (%) P-value
Biological process
  Cell cycle and proliferation   3 (4) 0.479979
  Stress response   4 (6) 0.205102
  Transport   5 (7) 0.563981
  Developmental processes   6 (9) 0.459856
  RNA metabolism   7 (10) 0.315857
  Other metabolic processes 12 (17) 0.007676
  Cell organization and biogenesis   6 (9) 0.193590
  Cell-cell signaling   1 (1) 0.502761
  Signal transduction   11 (16) 0.120754
  Protein metabolism   6 (9) 0.502818
  Death   1 (1) 0.827556
  Other biological processes   8 (11) 0.990425
Cellular component
  Cytosol   1 (2) 0.505969
  Mitochondrion   1 (2) 0.862146
  Endoplasmic reticulum/golgi   3 (5) 0.460760
  Other cytoplasmic organelle   1 (2) 0.604395
  Nucleus 10 (18) 0.306385
  Plasma membrane   6 (1) 0.438812
  Other membranes 14 (26) 0.661329
  Translational apparatus   1 (2) 0.330956
  Non-structural extracellular   2 (4) 0.830334
  Other cellular component 15 (28) 0.354726
Molecular function
  Enzyme regulator activity   3 (5) 0.141417
  Transcription regulatory activity   4 (7) 0.174629
  Transporter activity   2 (4) 0.623057
  Signal transduction activity 11 (20) 0.082302
  Nucleic acid binding activity   7 (13) 0.252320
  Kinase activity   2 (4) 0.503159
  Other molecular function 26 (47) 0.535279

Subsequently, KEGG analysis was conducted to group differentially expressed lncRNAs and mRNA into gene pathways. The data from the present study indicated that the genes predominantly formed signaling pathways associated with the regulation of Ca2+ signaling, ligand and receptor interactions, and other cell signaling pathways (Table IV). For example, P2rx7 was identified to be predominantly involved in Ca2 + signaling.

Table IV.

KEGG pathways analysis of differentially expressed genes.

Term Count P-value Genes Up Down
Glutathione metabolism 1 0.106032 Gsta2 0 1
Metabolism of xenobiotics by cytochrome P450 1 0.143567 Gsta2 0 1
Drug metabolism-cytochrome P450 1 0.147434 Gsta2 0 1
Ribosome 1 0.172182 Rps3a 0 1
PPAR signaling pathway 1 0.143567 Adipoq 0 1
Calcium signaling pathway 3 0.00614 P2rx7, Ptger1, Ptafr 3 0
Cytokine-cytokine receptor interaction 1 0.45143 Cxcl1 0 1
Chemokine signaling pathway 1 0.353888 Cxcl1 0 1
Neuroactive ligand-receptor interaction 4 0.001745 P2rx7, Ptger1, Ptafr, Vipr1 4 0
Cell cycle 1 0.226819 Hdac1 0 1
Apoptosis 1 0.179664 Prkar2b 1 0
Notch signaling pathway 1 0.099971 Hdac1 0 1
Insulin signaling pathway 1 0.268146 Prkar2b 1 0
Adipocytokine signaling pathway 1 0.139685 Adipoq 0 1
Type II diabetes mellitus 1 0.099971 Adipoq 0 1
Huntington's disease 1 0.334126 Hdac1 0 1
Pathways in cancer 1 0.530933 Hdac1 0 1
Chronic myeloid leukemia 1 0.155119 Hdac1 0 1

Building the lncRNA-mRNA regulatory network

The lncRNA target predictions were superimposed into the lncRNA-mRNA correlation network. As presented in Fig. 2, the network has a total of 98 nodes, 75 connections, 53 lncRNAs and 45 mRNAs. Expression of glutathione S-transferase α 2 (Gsta2) and DEAD (Asp-Glu-Ala-Asp) box polypeptide 43 (Ddx43) was regulated by a total of five lncRNAs, while expression of coiled-coil domain containing 68 (Ccdc68), olfactory receptor 464 (Olfr464) and low density lipoprotein receptor-related protein 11 (Lrp11) were regulated by four lncRNAs. In addition, expression levels of protein kinase, cAMP dependent regulatory, type II β (Prkar2b), leucine-rich repeat-containing G protein-coupled receptor 6 (Lgr6) and adiponectin, C1Q and collagen domain containing (Adipoq) were regulated by a total of three lncRNAs.

Figure 2.

Figure 2.

lncRNA-mRNA regulatory network. Circles represent genes and triangles represent lncRNAs; lines represent the association between the two types of regulation (solid line represents a cis-regulation, the dashed line represents the trans-regulation). lncRNA, long non-coding RNA.

Validation of differentially expressed lncRNAs and mRNAs in ovary tissues of WT and CRYBB2 knockout mice

RT-qPCR analysis of different lncRNAs and mRNAs was performed and it was demonstrated that expression levels of lncRNA A-30-P01019163 and P2rx7 were significantly different between10 cases of ovary tissues from WT and CRYBB2 knockout mice (P<0.05; Fig. 3), whereas other lncRNAs and mRNAs did not indicate any difference between WT and CRYBB2 knockout mouse ovary tissues (data not shown).

Figure 3.

Figure 3.

Validation of differentially expressed lncRNAs and mRNAs in ovary tissues from WT and CRYBB2 knockout mice. (A) RT-qPCR indicated lncRNA A-30-P01019163 was downregulated in ovary tissues from CRYBB2 KO mice; (B) RT-qPCR indicated P2rx7 was downregulated in ovary tissues from the CRYBB2 KO mice. *P<0.05. RT-qPCR, reverse transcription-quantitative polymerase chain reaction; KO, knock out; WT, wild-type.

Discussion

CRYBB2 knockout mice exhibit abnormal morphological and functional mouse ovaries. The current study investigated the underlying molecular mechanisms by which CRYBB2 affects expression of lncRNAs to alter mouse ovary structure and function. Certain aberrant lncRNA expression in the regulation of other genes was assessed. A total of 157 differentially expressed lncRNAs and 1,085 mRNAs were observed. The GO database analysis indicated that these altered gene expressions and were predominantly distributed in the biological process of metabolism, immune system, and signal transduction. The KEGG database pathway analysis suggested that the predominant signaling pathways were associated with Ca2+ signaling and ligand-receptor interaction.

Subsequent to establishing a correlation matrix lncRNA and mRNA co-expression network map, a total of 98 nodes, 75 connections, 53 lncRNAs, and 45 mRNAs were identified. Gsta2 and Ddx43 were regulated by five lncRNAs, Ccdc68, Olfr464 and Lrp11 by four lncRNAs, Prkar2b, Lgr6, and Adipoq by three lncRNAs. Gsta2 participates in cytochrome P450 metabolism and cytochrome P450 is important in the conversion of androgens to estrogens. P2rx7, Olfr464, Lrp11, Prkar2b, Lgr6, and Adipoq are involved in cellular signal transduction and P2rx7, Prkar2b, and Hdac1 are involved in regulation of the cell cycle and cell proliferation, while Prkar2b, Hdac1, and Dock7 are important in cell development. lncRNA A-30-P01019163 and P2rx7 were differentially expressed in ovarian tissues of CRYBB2 knockout mice.

Crybb2 not only functions to maintain lens transparency and refractive index, but also affects ovary development in mice. At the gene level, Crybb2 may mediate Ca2+ signal transduction (21,22). The current study demonstrated that Crybb2 also regulates expression of lncRNAs in ovarian tissues, which may be a novel area of research on Crybb2-regulation of gene expression. Previous studies using large scale cDNA library sequencing and next generation sequencing demonstrated abundant lncRNAs in mammals, however, not all lncRNAs are functional and only a relatively small proportion have been demonstrated to be biologically relevant (11,23). For example, as of mid-2014, 197 lncRNAs have been functionally annotated in lncRNA databases (24). However, other lncRNAs may be translated into proteins (25). In addition, lncRNAs, unlike miRNAs, can down- or upregulate gene expression by targeting transcriptional activators or repressors (10), in addition to post-transcriptional regulation of protein expression.

In the current study differentially expressed lncRNAs in ovary tissues of CRYBB2 knockout mice were profiled and a total of 157 differentially expressed lncRNAs were observed. Furthermore, differentially expressed mRNAs were profiled and a total of 1,085 differentially expressed mRNAs in ovary tissues of CRYBB2 knockout mice were observed. GO and KEGG pathway analyses were performed to determine associations between these lncRNAs and mRNAs, and a number of these were subsequently verified using RT-qPCR. It was observed that lncRNA A-30-P01019163 and P2rx7 were significantly differentially expressed between10 cases of ovary tissues from WT and CRYBB2 knockout mice. Thus, CRYBB2 knockout could downregulate expression of lncRNA A-30-P01019163 and, subsequently, suppress expression of the downstream gene P2rx7 and affect ovarian cell signal transduction, cell cycle, and ultimately ovarian development.

The current study is a proof-of-principle study and there are certain limitations. For example, it was not confirmed how lncRNA A-30-P01019163 regulates P2rx7 expression and the mechanistic investigation into how lncRNA A-30-P01019163-regulated P2rx7 expression mediates the effects of CRYBB2 on ovary development could be expanded on.

In conclusion, CRYBB2 regulates expression of different lncRNAs to influence ovary development. lncRNA A-30-P01019163 may affect ovarian cell cycle and proliferation by regulating P2rx7 expression in the ovary.

Acknowledgements

The authors would like to thank Shanghai Sensichip Infotech Co., Ltd. (Shanghai, China) for assistance with bioinformatic analysis and Medjaden Bioscience Ltd. for assisting in the preparation of the manuscript. The present study was supported in part by grants from the National Natural Science Foundation of China (grant nos. 81170834 and 81300748).

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