Expression profiles of long non‑coding RNAs during fetal lung development
- Authors:
- Published online on: October 5, 2020 https://doi.org/10.3892/etm.2020.9273
- Article Number: 144
Abstract
Introduction
Long non-coding RNAs (lncRNAs) are characterized by their length (>200 nucleotides), intron/exon structure, the presence of a 3' untranslated region and termination region, and a limited coding potential supported by the absence of open reading frames (1). Biochemically, lncRNAs are thought to mediate local gene expression as cis-regulatory elements, affect transcription of multiple genes as trans-regulatory elements and act as a scaffold for chromatin structure maintenance (2,3). In terms of function, lncRNAs have been reported to participate in numerous biological processes, including X chromosome inactivation, genomic imprinting, cell cycle regulation and the regulation of stem cell pluripotency (4,5). Additionally, the molecular functions of lncRNAs have been highlighted to have roles in various diseases, particularly those relevant to endocrinology, reproduction, metabolism, immunology, neurobiology, muscle biology and cancer (6-9).
Several studies have investigated the association between neonatal lung diseases and lncRNAs. Cheng et al (10) reported 9 lncRNAs that were potentially associated with bronchopulmonary dysplasia (BPD) and these data may provide novel insight into the biological roles of lncRNAs in the pathogenesis of BPD. Numerous lncRNAs are significantly differentially expressed in various lung diseases. For instance, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been reported to have an important role in lung cancer progression (11-13). Although the loss of MALAT1 does not affect lung development (14), a previous study indicated that the upregulation of MALAT1 may protect preterm infants with BPD by inhibiting apoptosis (15). Deletions of chromosomes encompassing other lncRNAs may cause lethal lung developmental disorders (16). Szafranski et al (17) demonstrated that deletion of a small non-coding methylated region at 16q24.1, included in lncRNA genes, caused the lethal lung developmental disorder alveolar capillary dysplasia with misalignment of pulmonary veins with parent-of-origin effects in a human model. These data indicated that lncRNAs may regulate fetal lung development.
As the survival rate increases among preterm infants, respiratory distress syndrome (RDS) and BPD are becoming more and more common (18). One widely accepted cause of BPD is insufficient fetal lung development during pregnancy (19). Additionally, a lack of a pulmonary surfactant synthesized by type II alveolar epithelial cells is acknowledged as a major cause of RDS (20). Consequently, there may be a close association between neonatal respiratory diseases and lung development.
Fetal lung development is a complex and continuous process. The development of lung structure includes the embryonic, fetal and postnatal stages (21). Fetal embryonic lung development may be divided into the pseudo-glandular period (7-16 weeks of gestation), canalicular period (16-25 weeks of gestation) and terminal saccular period (25 weeks to full term gestation) (22). Different stages of lung development have different characteristics (23). During the terminal saccular period, with the appearance of alveolar septum, capillaries, elastic fibers and collagen fibers, terminal vesicles become alveolar (21). Alveolar maturation begins at 30 weeks of gestation. Lung potential gas volume and surface area increase from 25 weeks of gestation to full term (24). Increased alveoli, lung volume and surface area provide the anatomical potential for gas exchange and, therefore, provide the basis for fetal survival following birth (25-27). In the present study, three periods of fetal lung development, divided by gestational week, were investigated through the examination of morphological and lncRNA expression changes in three groups of fetal lung tissue samples. An Affymetrix Human GeneChip was employed to assess the differential expression of lncRNAs between three phases of fetal lung development. Bioinformatics methods were also used to analyze the potential functions and pathways associated with the protein-coding genes associated with the differentially expressed lncRNA. These data may provide a theoretical basis for the prevention and treatment of neonatal lung developmental diseases, including RDS and BPD.
Materials and methods
Patients and samples
The present study protocol was approved by the Ethics Committee of Nanjing Maternal and Child Health Care Hospital, Nanjing, China [approval no. (2014) 74]. All of the patients included provided written informed consent to participate in the current study. Abortion was most commonly induced due to personal or social factors, rather than due to congenital problems.
The inclusion criteria were as follows: i) Gestational age of the fetus at the time-point of abortion was 7-28 weeks; ii) fetal abortion was performed due to personal or social factors; iii) pregnant females were aged 20-35 years; and iv) pregnant females provided written informed consent.
The exclusion criteria were as follows: i) Pregnant females with a history of hypertension or diabetes, or kidney, heart, connective tissue or autoimmune diseases; ii) pregnant females with a known history of exposure to radioactivity, toxic substances or drugs; iii) maternal use of glucocorticoids (e.g., dexamethasone, prednisone or beclomethasone) prior to abortion; iv) pregnant females with signs of infection, including positive amniotic fluid culture, increased C-reactive protein or procalcitonin; and v) previously detected chromosomal abnormalities or congenital malformations of the fetus.
Abortion procedure
Procedures took place between August 2014 and February 2015 at Nanjing Maternity and Child Health Care Hospital. Physicians explained the medical method and possible adverse reactions of abortion to the pregnant females who then provided voluntary written informed consent. Females at 8-13 weeks of gestation took mifepristone (200 mg orally), then misoprostol (400 µg sublingually) followed by mifepristone (200 mg orally) after 24-48 h. If the abortion was not complete, repeated misoprostol was taken sublingually every 3 h and up to 4 doses were administered until complete abortion. For females at 14-28 weeks of gestation, amniocentesis was performed prior to the intra-amniotic injection of 0.5% rivanol solution (100 mg) to induce contractions and initiate labor. The pregnant females took mifepristone (25 mg orally), which was used to soften the cervix (28-30). Fetal right-lung tissue samples were collected within 2 h of labor. Fetal lungs were isolated and were divided into three groups according to the fetal gestational age. These groups were termed S1 (embryonic week, 7-16), S2 (embryonic week, 16-25) and S3 (embryonic week, 25-28). A total of 10 samples were collected at S1 (mean age, 27.2±1.56 years; mean fetal gestational age, 13.57±0.73 weeks) 14 samples at S2 (mean age, 25.5±0.84 years; mean fetal gestational age, 20.73±0.72) and 12 samples at S3 (mean age, 25.92±1.13 years; mean fetal gestational age, 26.75±0.23 weeks). The median overall gestational age was 21.35 weeks with a range of 15.58-26.18 weeks.
The right lungs were washed with PBS and cut into several parts (2x4x6 mm), all of which were kept for histological examination. A 5 mg sample of each of the lungs was cut into small pieces in homogenization buffer (Trevigen, Inc.). The lungs were homogenized with a Sonifier (Branson Ultrasonics Corporation) with an amplitude of 14 microns for 10 sec. The cell supernatant was obtained by centrifugation at 12,000 x g for 15 min at 4˚C. Total RNA from the right lungs was isolated from the supernatant using TRIzol® reagent (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's protocol. RNA quality and quantity were measured on a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Inc.). A total of 1 µg of total RNA was taken from each sample and subjected to 1.5% agarose gel electrophoresis (120 V) for 15 min to determine the integrity of 28 and 18s ribosomal RNA under a gel imager (Bio-Rad Laboratories, Inc.) and to ensure that there were no residual RNA enzymes.
Histology
Lung tissues were fixed with 4% buffered paraformaldehyde at 4˚C overnight, dehydrated [50% ethanol for 2 h, 70% ethanol for 2 h, 85% ethanol for 2 h, 95% ethanol for 2 h, anhydrous ethanol for 1.5 h and anhydrous ethanol (fresh configuration) II for 1.5 h] and embedded in paraffin. Sections with a thickness of 3-4 µm were prepared for H&E staining and immunohistochemistry. Sections were dewaxed with xylene and rehydrated in a graded series of ethanol/water solutions. The sections were then stained with hematoxylin for 5 min, differentiated with 1% ethanol hydrochloride for 3 sec and transferred to eosin solution for 2 min. All procedures were performed at room temperature. The sections were then dehydrated and mounted. A total of three sections were randomly selected from each sample and a total of 108 H&E-stained sections were taken for image analysis, which was performed under a light microscope (BX51; Olympus Corporation) at magnifications of x200 and x400 to observe changes in fetal lung development between groups S1, S2 and S3.
Affymetrix Human GeneChip analysis
The GeneChip® Human Transcriptome Array 2.0 (Affymetrix Inc.) serves as an advanced and comprehensive gene expression profiling tool for whole-transcript coverage available on any microarray platform (31). Probes are distributed across the full length of a gene, including specific probes covering splice junctions, providing a more complete and accurate picture of overall gene expression with additional capacity for transcript isoform analysis. In brief, following the extraction of total RNA, 10 µg of RNA was used to synthesize double-stranded complementary (c)DNA using an Ambion WT expression kit (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's protocol. The cDNA was then fragmented and labelled with the Affymetrix GeneChip WT terminal labelling kit (Affymetrix Inc.), according to the manufacturer's protocol. The fragmented cDNA was hybridized using the GeneChip hybridization, wash and stain kit (Affymetrix Inc.), according to the manufacturer's protocol. Hybridization was performed at 65˚C with rotation for 16 h in an Affymetrix GeneChip Hybridization Oven 645 (Affymetrix Inc.). The GeneChip arrays were washed and stained on an Affymetrix Fluidics Station 450 (Affymetrix Inc.), followed by scanning on a GeneChip Scanner 3000 (Affymetrix Inc.). The microarray analysis was performed by Genminix Informatics Co., Ltd.
Reverse transcription-quantitative PCR (RT-qPCR)
A total of 0.1 g of lung tissue was homogenized in a homogenizer (Kinematica AG). Total RNA was isolated from fetal lungs using TRIzol® reagent. cDNA was synthesized with the Transcriptor First Strand cDNA Synthesis kit (Roche Diagnostics Co., Ltd.), according to the manufacturer's protocol. An aliquot of 1 µg total RNA was added to each reaction mixture. RT-qPCR was performed on an ABI 7500 thermal cycler (Applied Biosystems; Thermo Fisher Scientific, Inc.) with SYBR Green (Roche Diagnostics Co., Ltd.). The thermocycling conditions were as follows: 95˚C for 5 min, followed by 40 cycles of 95˚C for 20 sec and 55˚C for 20 sec. At the end of each run, a melting curve analysis was performed at 72˚C to monitor primer dimers and formation of non-specific products. Relative quantification of gene expression in multiple samples was achieved by normalization to the expression of an endogenous control gene, GAPDH. The relative expression levels were calculated by the 2-∆∆Cq method (32). Primer sequences are listed in Table I.
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses
The GO project offers a controlled vocabulary to label gene and gene product attributes in any organism (geneontology.org; date of access, May 2015). Categories covered by GO analysis include biological process, cellular component and molecular function. GO analysis provides an interpretation of the relevance of genes differentially expressed between the groups by suggesting possible functions of the genes and functions associated with the genes. Fisher's exact test and the χ2 test were performed to calculate the P-value and false discovery rate of each GO term function. The input used in the bioinformatics analysis was the crossover genes of differentially expressed lncRNA-associated genes and differential mRNA genes co-expressed with lncRNA that were screened in the lncRNA expression profiling results. The criterion for screening differentially expressed genes for statistical significance was P<0.05, thus screening out the significant functions exerted by the differentially expressed genes.
KEGG (kegg.jp/kegg/pathway.html) pathway analysis is a functional analysis tool, mapping a set of genes that may be associated with a certain lncRNA to potential pathways they are accumulated in. Fisher's exact test and χ2 test were used to identify differentially expressed genes. P<0.05 was used to screen and obtain significantly associated pathways. The probability of enrichment of a differentially expressed gene set in a term entry was represented by an enrichment score (EC), with a higher EC indicating a higher significance of the entry. The EC was calculated as the negative base 10 log of the P-value.
Statistical analysis
All quantitative data are expressed as the mean ± standard error of the mean. All experiments were repeated ≥3 times with similar results. Data were analyzed using a SPSS statistical package (version no. 17.0; SPSS, Inc.) and the results of the RT-qPCR were evaluated by one-way ANOVA with the Student-Newman-Keuls post-hoc test. P<0.05 was considered to indicate a statistically significant difference.
Results
Histology
In the S1 group, the bronchial tree extended to numerous bronchioles, which were composed of epithelial cells. In a single layer of cubic cells, cells were tall, columnar and arranged in rings. In the S2 group, terminal bronchioles branched out into greater numbers of respiratory bronchioles and cubic epithelial cells appeared short and columnar compared with S1. A dilated alveolar lumen, increased alveolar septa, thinner interstitium and hyperplasia of capillaries were observed in the fetal lungs in the S2 and S3 groups. Alveolar sacs formed in the S3 group and pulmonary alveoli took shape. In S3, a greater number of alveolar septa appeared compared with the S1 and S2 groups, and the interstitium was thinner compared with the S1 and S2 groups. In S3, epithelial cells had a cubic or flat shape (Fig. 1).
lncRNA microarray profiles
Affymetrix Human GeneChip was utilized to determine the expression spectrum of lncRNAs during fetal lung development. As a result, 687 lncRNAs were indicated to be differentially expressed among the three groups (S1, S2 and S3) of fetal lung tissue samples. According to these data, there were 34 upregulated lncRNAs and 12 downregulated lncRNAs that were significantly differentially expressed among all combinations of S1 vs. S2 vs. S3 (fold-change ≥1.5). Among the 687 differentially expressed lncRNAs, 39 downregulated and 202 upregulated lncRNAs were identified in the S2 vs. S1 comparison (fold-change >2). Furthermore, 24 lncRNAs were downregulated and 78 upregulated in the S3 vs. S2 comparison (fold-change >2) and 77 downregulated and 535 upregulated lncRNAs were identified in the S3 vs. S1 comparison (fold-change >2; Tables II and III). Hierarchical clustering was performed in order to display distinguishable lncRNA expression profiles among the groups. Taken together, these data were consistent with the notion that different lncRNAs may be involved in the different phases of lung development (Fig. 2).
 | Table IIDownregulated differentially expressed lncRNAs between the three stages of fetal lung development. |
| Table IIIUpregulated differentially expressed lncRNAs between the 3 stages of fetal lung development. |
As certain lncRNAs exhibited more significant fold-changes among the three groups, 4 lncRNAs were selected based on these data, including two downregulated lncRNAs (n336823 and ENST00000445168; Table IV) and two upregulated lncRNAs (n3408848 and n387037; Table V).
| Table IVSpecific fold-changes of ≥1.5 consistently upregulated lncRNAs identified following screening. |
| Table VSpecific fold-changes of ≥1.5 consistently downregulated lncRNAs identified following screening. |
RT-qPCR
The expression levels of the selected lncRNAs were confirmed by RT-qPCR. Among these differentially expressed lncRNAs, n340848 and n387037 were indicated to be continuously increased in expression with progression through the three phases of lung development, while the expression levels of ENST00000445168 and n336823 were reduced with progression. These results were consistent with the GeneChip data obtained. The relative trends in expression of these lncRNAs are presented in Fig. 3.
GO analysis and KEGG pathway analysis
Upregulated transcripts were indicated to be associated with the GO terms cell adhesion, hydrogen peroxide decomposition and protein kinase C of a G protein-coupled receptor signaling pathway (Fig. 4A). The top three biological process terms associated with the downregulated transcripts were G protein-coupled receptor signaling pathway coupled to the cyclic guanosine monophosphate nucleotide second messenger, brain development and cerebral cortex development (Fig. 4A).
Additionally, KEGG enrichment analysis was performed to investigate the possible roles of the lncRNA-associated protein-coding genes. The most significant pathways enriched in the set of upregulated protein-coding genes included cell adhesion molecules, as well as adherens junction and glyceride metabolism (Fig. 5A). Biosynthesis of an amino acid, basal cell carcinoma and glycolysis/gluconeogenesis were the most important pathways enriched in the set of down-regulated genes (Fig. 5B).
Discussion
In the present study, 687 lncRNAs were identified to be differentially expressed among three groups (embryonic periods S1, S2 and S3) of human fetal lung tissue samples. The results revealed 34 upregulated lncRNAs and 12 downregulated lncRNAs, which were significantly differentially expressed among all combinations of S1 vs. S2 vs. S3 (fold-change ≥1.5; P<0.05). Among these differentially expressed lncRNAs, n340848, n387037, n336823 and ENST00000445168 were then validated by RT-qPCR. These results were consistent with the GeneChip results. GO enrichment analysis revealed that the majority of the GO terms associated with these genes belonged to the biological process category. The fact that one lncRNA is able to target numerous genes suggests that lncRNAs may be involved in a series of biological processes.
Among the four lncRNAs selected, lncRNA n340848 is located on chromosome 6, overlapping with a gene called neural precursor cell expressed developmentally down-regulated 9 (NEDD9). The highest levels of NEDD9 mRNA and protein have been detected in lungs and kidneys (33). NEDD9 has been reported to act as a scaffold protein and is part of the Crk-associated substrate family, which regulates protein complex control of cell invasion and differentiation (34). n387037 is a 1,342-bp lncRNA with a genomic overlap with the platelet and endothelial cell adhesion molecule 1 (PECAM1) gene (5). PECAM1 expression has been reported in almost all tissues and is expressed at the highest levels in the placenta, lungs and fat tissues (35). It has been indicated as a novel therapeutic target in neonatal respiratory distress syndrome and ventilator-induced lung injury (36). LncRNA n336823 is 26,063 bp long and overlaps with patched 1, which encodes a member of the patched family of proteins and a component of the hedgehog (HH) signaling pathway (37). HH signaling is crucial for embryonic development and tumorigenesis (38). Numerous studies have indicated that activation of the HH signaling pathway is associated with the progression of multiple solid tumors, including lung cancer (1,39).
lncRNA ENST0000445168 (also known as 02038-202), encoded on chromosome 3, is an intergenic lncRNA, whose transcription occurs entirely within the genomic interval between two adjacent protein-coding genes (40,41). These results indicated that the four lncRNAs mentioned above may take part in the etiology and pathogenesis of disorders of neonatal lung development; however, further research is required for confirmation.
Numerous studies have indicated that various lncRNAs are involved in different biological events (38,42,43). lncRNA NR_033925, also known as forkhead box (FOX)F1-AS1 or FOXF1-adjacent non-coding developmental regulatory RNA, is encoded upstream of FOXF1(44). It is highly expressed in human lungs and has an important effect on the development of the heart and gastrointestinal tract (45). lncRNA n409380, associated with the FOXP2 gene, promotes embryonic development and the proliferation of lung epithelial cells (46). lncRNA n335087 and lncRNA n339275 overlap with gene TGF-β receptor 2 and are involved in lung development-associated tracheal morphogenesis and leukocytic protein phosphorylation (17).
Certain studies have addressed the specific expression patterns or function of lncRNAs in lung development. Herriges et al (47) screened 363 lncRNAs in the lung and foregut endoderm and indicated that they were spatially associated with transcription factors across the genome. It has been reported that lncRNAs in the lungs are located near genes of transcription factors, including NK2 homeobox 1 (NKX2.1), GATA binding protein 6, FOXA2 and FOXF1, which are essential in foregut and lung development (48,49). One of these lncRNAs, NKX2.1-associated non-coding intergenic RNA (NANCI), performs an important function in lung development by acting upstream of the critical transcription factor NKX2.1 and downstream of Wnt/β-catenin signaling to regulate lung endoderm gene expression and morphogenesis (16). Furthermore, a previous study identified a feedback loop within the NANCI-NKX2.1 gene duplex to explain how this subset acts as a rheostat to buffer the expression of neighboring transcription factor genes, to maintain tissue-specific cellular identity during development and postnatal homeostasis (47).
In conclusion, the results of the present study indicated that the lncRNA expression profile varies among different phases of fetal lung development. These results provided certain indications of the roles of lncRNAs in human fetal lung development. In the future, functional verification, target gene prediction and validation of the identified lncRNAs will be performed in vitro and in vivo to provide novel insight into the pathogenesis of neonatal pulmonary diseases.
Acknowledgements
Not applicable.
Funding
The present study was supported by the National Natural Science Foundation of China (grant no. 781270725).
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
JS, ZB, YY, XGZ and XYZ designed the experiments. JS, ZB, WZ, CM, YS and QK performed the experiments, collected data, generated the figures and interpreted the results. JS, ZB, XGZ and XYZ wrote the manuscript. All authors read and approved the final manuscript.
Ethics approval and consent to participate
All procedures were approved by the Ethics Committee of Nanjing Maternal and Child Health Hospital, Nanjing, China [approval no. (2014) 74] and all patients provided written informed consent.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
References
|
Schmitz SU, Grote P and Herrmann BG: Mechanisms of long noncoding RNA function in development and disease. Cell Mol Life Sci. 73:2491–2509. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Ulitsky I and Bartel DP: lincRNAs: Genomics, evolution, and mechanisms. Cell. 154:26–46. 2013.PubMed/NCBI View Article : Google Scholar | |
|
Rinn JL and Chang HY: Genome regulation by long noncoding RNAs. Annu Rev Biochem. 81:145–166. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Wang KC and Chang HY: Molecular mechanisms of long noncoding RNAs. Mol Cell. 43:904–914. 2011.PubMed/NCBI View Article : Google Scholar | |
|
Mercer TR, Dinger ME and Mattick JS: Long non-coding RNAs: Insights into functions. Nat Rev Genet. 10:155–159. 2009.PubMed/NCBI View Article : Google Scholar | |
|
Wang C, Wang L, Ding Y, Lu X, Zhang G, Yang J, Zheng H, Wang H, Jiang Y and Xu L: LncRNA structural characteristics in epigenetic regulation. Int J Mol Sci. 18(2659)2017.PubMed/NCBI View Article : Google Scholar | |
|
Wangyang Z, Daolin J, Yi X, Zhenglong L, Lining H, Yunfu C and Xingming J: NcRNAs and Cholangiocarcinoma. J Cancer. 9:100–107. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Jiang W, Liu Y, Liu R, Zhang K and Zhang Y: The lncRNA DEANR1 facilitates human endoderm differentiation by activating FOXA2 expression. Cell Rep. 11:137–148. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Wang P, Lu S and Mao H, Bai Y, Ma T, Cheng Z, Zhang H, Jin Q, Zhao J and Mao H: Identification of biomarkers for the detection of early stage lung adenocarcinoma by microarray profiling of long noncoding RNAs. Lung Cancer. 88:147–153. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Cheng HR, He SR, Wu BQ, Li DC, Hu TY, Chen L and Deng ZH: Deep Illumina sequencing reveals differential expression of long non-coding RNAs in hyperoxia induced bronchopulmonary dysplasia in a rat model. Am J Transl Res. 9:5696–5707. 2017.PubMed/NCBI | |
|
Schmidt LH, Spieker T, Koschmieder S, Schäffers S, Humberg J, Jungen D, Bulk E, Hascher A, Wittmer D, Marra A, et al: The long noncoding MALAT-1 RNA indicates a poor prognosis in non-small cell lung cancer and induces migration and tumor growth. J Thorac Oncol. 6:1984–1992. 2011.PubMed/NCBI View Article : Google Scholar | |
|
Xu C, Yang M, Tian J, Wang X and Li Z: MALAT-1: A long non-coding RNA and its important 3' end functional motif in colorectal cancer metastasis. Int J Oncol. 39:169–175. 2011.PubMed/NCBI View Article : Google Scholar | |
|
Lai MC, Yang Z, Zhou L, Zhu QQ, Xie HY, Zhang F, Wu LM, Chen LM and Zheng SS: Long non-coding RNA MALAT-1 overexpression predicts tumor recurrence of hepatocellular carcinoma after liver transplantation. Med Oncol. 29:1810–1816. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Zhang B, Arun G, Mao YS, Lazar Z, Hung G, Bhattacharjee G, Xiao X, Booth CJ, Wu J, Zhang C and Spector DL: The lncRNA Malat1 is dispensable for mouse development but its transcription plays a cis-regulatory role in the adult. Cell Rep. 2:111–123. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Cai C, Qiu J, Qiu G, Chen Y, Song Z, Li J and Gong X: Long non-coding RNA MALAT1 protects preterm infants with bronchopulmonary dysplasia by inhibiting cell apoptosis. BMC Pulm Med. 17(199)2017.PubMed/NCBI View Article : Google Scholar | |
|
Herriges MJ, Swarr DT, Morley MP, Rathi KS, Peng T, Stewart KM and Morrisey EE: Long noncoding RNAs are spatially correlated with transcription factors and regulate lung development. Genes Dev. 28:1363–1379. 2014.PubMed/NCBI View Article : Google Scholar | |
|
Szafranski P, Dharmadhikari AV, Brosens E, Gurha P, Kolodziejska KE, Zhishuo O, Dittwald P, Majewski T, Mohan KN, Chen B, et al: Small noncoding differentially methylated copy-number variants, including lncRNA genes, cause a lethal lung developmental disorder. Genome Res. 23:23–33. 2013.PubMed/NCBI View Article : Google Scholar | |
|
Moss TJ: Respiratory consequences of preterm birth. Clin Exp Pharmacol Physiol. 33:280–284. 2006.PubMed/NCBI View Article : Google Scholar | |
|
Pierro M, Ciarmoli E and Thébaud B: Bronchopulmonary dysplasia and chronic lung disease: Stem cell therapy. Clin Perinatol. 42:889–910. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Kumar A and Bhatnagar V: Respiratory distress in neonates. Indian J Pediatr. 72:425–428. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Schittny JC: Development of the lung. Cell Tissue Res. 367:427–444. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Burri PH: Fetal and postnatal development of the lung. Annu Rev Physiol. 46:617–628. 1984.PubMed/NCBI View Article : Google Scholar | |
|
Copland I and Post M: Lung development and fetal lung growth. Paediatr Respir Rev. 5 (Suppl A):S259–S264. 2004.PubMed/NCBI View Article : Google Scholar | |
|
Roth-Kleiner M and Post M: Similarities and dissimilarities of branching and septation during lung development. Pediatr Pulmonol. 40:113–134. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Burri PH: Structural aspects of postnatal lung development-alveolar formation and growth. Biol Neonate. 89:313–322. 2006.PubMed/NCBI View Article : Google Scholar | |
|
Zoetis T and Hurtt ME: Species comparison of lung development. Birth Defects Res B Dev Reprod Toxicol. 68:121–124. 2003.PubMed/NCBI View Article : Google Scholar | |
|
Hislop AA: Airway and blood vessel interaction during lung development. J Anat. 201:325–334. 2002.PubMed/NCBI View Article : Google Scholar | |
|
WHO 2018: Medical management of abortion: Available online: https://www.who.int/reproductivehealth/publications/medicalmanagement-abortion/en/. | |
|
Chen QJ, Hou SP, Meads C, Huang YM, Hong QQ, Zhu HP and Cheng LN: EBM-CONNECT Collaboration: Mifepristone in combination with prostaglandins for termination of 10-16 weeks' gestation: A systematic review. Eur J Obstet Gynecol Reprod Biol. 159:247–254. 2011.PubMed/NCBI View Article : Google Scholar | |
|
ACOG Practice Bulletin No. 135: Second-trimester abortion. Obstet Gynecol 121: 1394-1406, 2013. | |
|
Young RA: Biomedical discovery with DNA arrays. Cell. 102:9–15. 2000.PubMed/NCBI View Article : Google Scholar | |
|
Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001.PubMed/NCBI View Article : Google Scholar | |
|
Duff MO, Olson S, Wei X, Garrett SC, Osman A, Bolisetty M, Plocik A, Celniker SE and Graveley BR: Genome-wide identification of zero nucleotide recursive splicing in Drosophila. Nature. 521:376–379. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Chang JX, Gao F, Zhao GQ and Zhang GJ: Expression and clinical significance of NEDD9 in lung tissues. Med Oncol. 29:2654–2660. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Gumina RJ, Kirschbaum NE, Rao PN, van Tuinen P and Newman PJ: The human PECAM1 gene maps to 17q23. Genomics. 34:229–232. 1996.PubMed/NCBI View Article : Google Scholar | |
|
Villar J, Zhang H and Slutsky AS: Lung repair and regeneration in ARDS: Role of PECAM1 and Wnt Signaling. Chest. 155:587–594. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Jia Y, Wang Y and Xie J: The Hedgehog pathway: Role in cell differentiation, polarity and proliferation. Arch Toxicol. 89:179–191. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Kopp F and Mendell JT: Functional classification and experimental dissection of long noncoding RNAs. Cell. 172:393–407. 2018.PubMed/NCBI View Article : Google Scholar | |
|
McMillan R and Matsui W: Molecular pathways: The hedgehog signaling pathway in cancer. Clin Cancer Res. 18:4883–4888. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Bu D, Yu K, Sun S, Xie C, Skogerbø G, Miao R, Xiao H, Liao Q, Luo H, Zhao G, et al: NONCODE v3.0: Integrative annotation of long noncoding RNAs. Nucleic Acids Res. 40 (Database Issue):D210–D215. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Khalil AM, Guttman M, Huarte M, Garber M, Raj A, Rivea Morales D, Thomas K, Presser A, Bernstein BE, van Oudenaarden A, et al: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proc Natl Acad Sci USA. 106:11667–11672. 2009.PubMed/NCBI View Article : Google Scholar | |
|
McDonel P and Guttman M: Approaches for understanding the mechanisms of long noncoding RNA regulation of gene expression. Cold Spring Harb Perspect Biol. 11(a032151)2019.PubMed/NCBI View Article : Google Scholar | |
|
Wu H, Yang L and Chen LL: The diversity of long noncoding RNAs and their generation. Trends Genet. 33:540–552. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Schnatwinkel C and Niswander L: Nubp1 is required for lung branching morphogenesis and distal progenitor cell survival in mice. PLoS One. 7(e44871)2012.PubMed/NCBI View Article : Google Scholar | |
|
Sauvageau M, Goff LA, Lodato S, Bonev B, Groff AF, Gerhardinger C, Sanchez-Gomez DB, Hacisuleyman E, Li E, Spence M, et al: Multiple knockout mouse models reveal lincRNAs are required for life and brain development. Elife. 2(e01749)2013.PubMed/NCBI View Article : Google Scholar | |
|
Mahlapuu M, Enerbäck S and Carlsson P: Haploinsufficiency of the forkhead gene Foxf1, a target for sonic hedgehog signaling, causes lung and foregut malformations. Development. 128:2397–2406. 2001.PubMed/NCBI | |
|
Herriges MJ, Tischfield DJ, Cui Z, Morley MP, Han Y, Babu A, Li S, Lu M, Cendan I, Garcia BA, et al: The NANCI-Nkx2.1 gene duplex buffers Nkx2.1 expression to maintain lung development and homeostasis. Genes Dev. 31:889–903. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Goss AM, Tian Y, Tsukiyama T, Cohen ED, Zhou D, Lu MM, Yamaguchi TP and Morrisey EE: Wnt2/2b and beta-catenin signaling are necessary and sufficient to specify lung progenitors in the foregut. Dev Cell. 17:290–298. 2009.PubMed/NCBI View Article : Google Scholar | |
|
Yang H, Lu MM, Zhang L, Whitsett JA and Morrisey EE: GATA6 regulates differentiation of distal lung epithelium. Development. 129:2233–2246. 2002.PubMed/NCBI |
