Literature DB >> 26181329

Comparative Transcriptome Analysis of Cell-Free Fetal RNA from Amniotic Fluid and RNA from Amniocytes in Uncomplicated Pregnancies.

J H Kang1, H J Park2, Y W Jung2, S H Shim3, S R Sung3, J E Park3, D H Cha2, E H Ahn4.   

Abstract

OBJECTIVES: We aimed to compare tissue-specific expression profiles and biological pathways of RNA from amniocytes and amniotic fluid supernatant (AFS) from second-trimester pregnancies by using transcriptome analysis. Additionally, we wanted to explore whether cell-free RNA from AFS exhibits a unique gene expression signature that more adequately reflects the fetal developmental process than amniocyte RNA.
METHODS: Amniotic fluid samples were prospectively collected in the second trimester of pregnancy from euploid fetuses. Total RNA was extracted from amniocytes and AFS and hybridized to Affymetrix GeneChip Human Arrays. Significantly differentially expressed transcripts between amniocytes and AFS were obtained by using Welch's t-test. Unsupervised hierarchical clustering was used to visualize overall expression characteristics and differences in transcripts between AFS and amniocytes. The biological functions of selected genes were analyzed using various online Gene Ontology databases.
RESULTS: A total of 3,072 and 15,633 transcripts were detected in the second-trimester AFS and amniocytes, respectively. Hierarchical clustering revealed differential transcript expression between AFS and amniocytes. We found 353 genes that were specifically enriched in the AFS only, and tissue expression analysis showed enrichment of brain-specific genes in the AFS. Biological pathway analysis revealed that AFS-specific transcripts were mainly involved in embryonic development, cardiovascular development, and cellular morphology pathways.
CONCLUSION: This study demonstrated differential tissue-specific gene expression profiles and biological pathways between AFS and amniocytes. The results suggested that AFS is the preferred RNA source to investigate potential biomarkers of fetal neurodevelopment.

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Year:  2015        PMID: 26181329      PMCID: PMC4504687          DOI: 10.1371/journal.pone.0132955

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Background

Amniotic fluid is a dynamic solution that performs multiple functions for the developing fetus at different ages. During the second trimester, the amniotic fluid composition is similar to that of fetal plasma with rapid bi-directional diffusion via non-keratinized fetal skin between the fetus and the amniotic fluid [1]. Amniotic fluid is composed of cells, termed “amniocytes” and acellular fluid. Amniotic fluid supernatant (AFS) is the fraction of amniotic fluid after centrifugation. Amniocytes are derived from all three germ layers of the embryo, ranging from unspecified progenitors to mature differentiated cells. AFS contains suspended fetal transcripts including cell-free RNA and RNA released from amniocytes. The kinetics and origin of cell-free fetal RNA in the AFS have not been fully unraveled yet. Amniotic fluid mRNA can be associated with membrane-derived vesicles, which greatly enhance the mRNA stability and are released from healthy cells in exosomes or virtosomes. Additionally, cell-free RNA can be a product of either apoptosis or necrosis [2,3]. RNA of AFS consists of cell-free fetal RNA from fetal circulation and RNA particles from amniocytes. Cell-free mRNA can act as a messenger between cells and modify the biology of the recipient cells through changes in various cellular responses such as an immune response [3]. It is assumed that cell-free fetal RNA particles in amniotic fluid include cell-free RNA in fetal circulation, and that they play an important role in fetal development in health and disease. Since the detection of cell-free fetal nucleic acids in maternal serum [4], the use of transcriptomes for prenatal diagnosis has rapidly developed. Cell-free fetal DNA represents a subfraction of 6–10% of total cell-free DNA in first- and second-trimester pregnancies and rises up to 10–20% in third-trimester pregnancies [5,6]. Cell-free fetal DNA is 100‒200-fold more abundant in amniotic fluid than in maternal plasma [7]. Amniotic fluid is an excellent source of material for research, as large quantities of supernatant can be obtained and there is no maternal nucleic acid contamination. In addition, amniotic fluid cell-free nucleic acids are more likely to originate from the fetus itself, in contrast to circulating cell-free fetal nucleic acids, which are predominantly of trophoblast origin [8]. Genomic analysis of cell-free fetal RNA from amniotic fluid can offer important real-time information on fetal physiology, development, and potential disease status in ongoing pregnancies. Therefore, it is important for studying human development and for antenatal diagnosis, and can provide clues for new biomarkers and therapeutic targets. In recent transcriptome studies of cell-free fetal RNA in AFS [9-12], diverse tissue-specific transcripts have been investigated, and it was found that neurodevelopment-related genes are especially abundant in mid-trimester AFS. All of these studies have used AFS samples, and no study has compared the differences in gene expression between AFS and amniocytes until date, except one previous [13] and the current study. In this study, we investigated the tissue-specific expression patterns and their biological relevance in second-trimester amniotic fluid cell-free fetal RNA by comparing the transcriptomes of amniocytes and AFS. Specifically, we aimed to provide more information on the specific biological value of AFS cell-free RNA, which excludes the effect of amniocyte cellular RNA. We hypothesized that AFS is a more diverse source of fetal RNA and a more accurate biological marker for providing real-time information on fetal developmental physiology than RNA from amniocytes.

Materials and Methods

2.1 Subjects

The ten pregnant women enrolled in this study were recruited from the department of Obstetrics and Gynecology, CHA Gangnam Medical Center, CHA Medical University (Seoul, Korea). This study was approved by the Ethical Review Board for Human Genome Studies at CHA Gangnam Medical Center, College of Medicine CHA University. We obtained written informed consent from all pregnant women to participate in the study. Karyotype results confirmed that the amniotic fluid samples were from 8 normal females and 2 normal males. The gestational age at amniocentesis ranged from 16 4/7 to 20 2/7 weeks. There were no pregnancy complications, and all babies had a normal postnatal outcome. Clinical information on the participants is presented in Table 1.
Table 1

Clinical information of the participants in this study.

No.KaryotypeAge (yrs)GA (wks+days)Indication of amniocentesis
CHA-0146,XY3817+3advanced maternal age
CHA-0246,XX3820+2screening positive
CHA-0346,XX2717+0screening positive
CHA-0446,XY3117+2screening positive
CHA-0746,XX3516+4screening positive
CHA-3346,XX3216+5single umbilical artery
CHA-4446,XX3617+3screening positive
CHA-5246,XX4018+6advanced maternal age
CHA-8046,XX3117+6screening positive
CHA-8546,XX3417+2maternal anxiety (prev. Turner synd. pregnancy)

2.2 RNA extraction

Ten second-trimester amniotic fluid samples were centrifuged at 350 × g for 10 min at room temperature to separate amniocytes, and the amniocytes were cultured for one passage. The supernatants and amniocytes were stored at -70°C until use. Total RNA was extracted from the amniocytes by using the QIAamp RNeasy Mini Kit (Qiagen, Hilden, Germany). Total RNA was extracted from 10–20 ml of AFS by using the QIAamp Circulating Nucleic Acid Kit with carrier RNA (Qiagen) with an on-column DNase digestion step to remove genomic DNA according to the manufacturer’s instructions. The RNA was purified with the RNeasy MinElute Cleanup Kit (Qiagen). The RNA quality was analyzed using the Agilent 2100 Bioanalyzer and the RNA concentration in each sample was measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). The RNA samples with an A260:A280 ratio greater than 1.8 were stored at -70°C for further analysis.

2.3 Microarray

Gene expression was analyzed with the GeneChip PrimeView Human Gene Expression Array (Affymetrix, Santa Clara, CA, USA), which contains over 530,000 probes covering more than 36,000 transcripts and variants, which represent more than 20,000 genes mapped through RefSeq or via UniGene annotation. Biotinylated aRNA was prepared according to the standard Affymetrix protocol (Expression Analysis Technical Manual, 2001) from 100 ng total RNA using the GeneChip 3’ IVT Express Kit (Affymetrix). Following fragmentation, 12 μg of aRNA was hybridized to the GeneChip array for 16 h at 45°C. The GeneChips were washed and stained in the Affymetrix Fluidics Station 450, and scanned using the Affymetrix GeneChip Scanner 3000 7G. The data were analyzed with Robust Multi-array Analysis (RMA) using Affymetrix default analysis settings and global scaling as normalization method. The trimmed mean target intensity of each array was arbitrarily set to 100. The normalized and log-transformed intensity values were analyzed using GeneSpring 12.5 (Agilent Technologies, CA, USA).

2.4 Data analysis

The data were imported into the GeneSpring GX 7.3 software (Agilent Technologies) for filtering and basic statistical analysis. Signals were considered “detected” when their value was larger than the median value of control probe signal. Hierarchical clustering analyses were used to visualize overall expression characteristics of all samples. We compared gene expression in paired AFS and amniocyte samples. We identified genes that were differentially expressed in AFS, amniocytes, and both samples by using ANOVA followed by Benjamini-Hochberg multiple testing corrections. Genes were considered significantly differentially expressed in both AFS and amniocytes if they had a fold-change of at least 2 and a Benjamini-Hochberg adjusted P-value < 0.05. Biological function pathway analysis was done using the web-based Ingenuity Pathway Analysis (IPA) software system, which identifies the pathways associated with a list of uploaded genes. In this analysis, we uploaded the three lists of differentially expressed genes as described above. A threshold of P < 0.05 was set to identify active functions. A P-value was calculated by Fisher's exact test to determine the significance of the association of the dataset and the specific pathway. Additionally, the online Database for Annotation, Visualization and Integrated Discovery (DAVID) toolkit 6.7, an ontology-based webtool (http://david.abcc.ncifcrf.gov/), was utilized to statistically evaluate groups of genes identified in previous publications and other public resources for tissue-specific analysis. Similar to IPA, we uploaded the gene lists using the official gene symbols to identify enriched gene ontologies, which were selected by primary filtering.

Results

We obtained 10 amniotic fluid samples from women in the second-trimester pregnancy. The median gestational age at amniocentesis was 17 weeks (range 16‒20 weeks). The mean maternal age was 34 years. The amniotic fluid samples were from 2 male and 8 female fetuses. The indication for amniocentesis was advanced maternal age or a positive serum screening test result (Table 1). The genome-wide expression profiles of amniocyte and AFS RNA were compared using PrimeView Human Gene Expression Arrays. Unsupervised hierarchical clustering showed that the AFS RNA profile was distinctly different from that of amniocytes (Fig 1). We found that 3,072 genes were expressed in AFS and 15,633 genes were expressed in amniocytes (S1 File). Of these, 353 genes were expressed uniquely in AFS, while 12,914 genes were expressed in amniocytes alone and 2,719 genes were expressed in both AFS and amniocytes (Fig 2A). Among the 2,719 genes expressed in both, 402 genes were up-regulated and 1,015 genes were down-regulated in AFS compared to amniocytes (Fig 2B). To identify whether the three different groups of detected genes showed tissue-specific expression, we performed DAVID analysis. Among the 353 genes uniquely expressed in the AFS, we identified 150 tissue-specific genes associated with the brain, spleen, blood, heart, saliva, and testis (Table 2) with most genes being expressed in the brain (119 genes) and spleen (11 genes). The amniocytes were mainly enriched for transcripts from the placenta, lung, epithelium, uterus, skin, and liver (Table 3). Among the 2,719 genes detected in both AFS and amniocytes, the transcripts mainly originated from the brain, placenta, lung, and uterus (Table 4). Detailed gene lists are supplied as supplementary files (S2 File, S3 File and S4 File).
Fig 1

Unsupervised hierarchical clustering analysis for genes differentially expressed between amniocytes and amniotic fluid expression profiles.

Fig 2

A. Venn diagram of the numbers of genes detected in the AFS and amniocytes by comparative transcriptome analysis.

B. Venn diagram showing the numbers of up- and down-regulated genes that overlapped between the AFS and amniocytes.

Table 2

Tissue-specific genes uniquely expressed in the AFS.

Organ p-valueBH valueNo. of genes
Expressed exclusively in testis0.0080.6845
Heart0.0180.8334
Saliva0.0210.7523
Blood0.0460.9006
Brain0.0470.843119
Spleen0.0530.82711
Primary B-Cells0.0950.9372
Table 3

Tissue-specific genes uniquely expressed in the amniocytes.

Organ p-valueBH valueNo. of genes
Umbilical cord blood3.22E-291.19E-2621 
Skin2.96E-285.50E-26189 
Cajal-Retzius cell1.40E-271.73E-2510 
Epithelium2.37E-262.20E-24265 
Fetal brain cortex8.60E-246.38E-22
Placenta2.23E-201.38E-18380 
Muscle1.27E-186.74E-1759 
Lung2.06E-161.03E-14272 
B-cell lymphoma1.99E-148.19E-13
Cervix carcinoma2.15E-147.99E-1314 
Uterus2.29E-147.71E-13222 
Platelet9.42E-142.91E-1218 
Cervix1.72E-114.92E-1031 
Urinary bladder3.74E-099.92E-0810 
Liver4.47E-091.11E-07109 
Eye2.73E-086.32E-0762 
Pancreas8.64E-081.88E-0645 
Kidney1.22E-072.52E-0692 
Lymph1.66E-073.23E-0633 
Ovarian carcinoma2.03E-073.76E-06
Promyelocytic leukemia2.22E-073.92E-06
Ovary2.37E-074.00E-0663 
Bone marrow2.44E-073.94E-0637 
Keratinocyte6.58E-071.02E-05
Hepatoma6.35E-069.43E-05
Colon adenocarcinoma9.02E-061.29E-04
Adrenal gland1.05E-051.44E-0411 
T-cell3.27E-054.34E-04
Prostate2.15E-040.002742935 
Coronary artery2.40E-040.002965
Dendritic cell4.62E-040.0055176
Fibroblast6.51E-040.0075272
Table 4

Tissue-specific genes expressed in both AFS and amniocytes.

Organ p-value BH valueNo. of genes
Skin3.82E-221.10E-1938 
Muscle1.05E-181.51E-16
Epithelium2.14E-152.02E-1331 
Uterus3.98E-152.87E-1341 
Placenta1.19E-146.82E-13172 
Lung2.22E-141.06E-1242 
Cervix7.15E-102.28E-08
Pancreas6.58E-091.89E-0712 
Cervix carcinoma9.53E-092.49E-07
Ovary1.93E-084.62E-0715 
Eye6.45E-081.32E-0613 
Platelet8.79E-081.68E-06
Liver4.55E-077.25E-0629 
Brain9.08E-071.37E-05388 
Kidney3.08E-064.42E-0518 
Lymph9.36E-061.28E-04
Ovarian carcinoma1.04E-051.36E-04
Colon5.21E-056.23E-0438 
B-cell8.02E-040.008487

A. Venn diagram of the numbers of genes detected in the AFS and amniocytes by comparative transcriptome analysis.

B. Venn diagram showing the numbers of up- and down-regulated genes that overlapped between the AFS and amniocytes. Pathway enrichment analysis by IPA to examine the roles of differentially expressed genes (DEGs) in the AFS samples revealed 61 functional categories. Table 5 presents the genes that are more than 10-fold up-regulated and with P-value < 0.01 including the categories that are related to general organ systems and functionality. Embryonic development, cardiovascular development, and cell morphology pathways were enriched biological functions in genes uniquely expressed in the AFS. The genes uniquely expressed in amniocytes were mainly enriched in infectious disease, cell death and survival, and protein synthesis pathways (Table 6). Functional analyses of DEGs in both AFS and amniocytes showed that particular genes were significantly differentially regulated in AFS compared to amniocytes (Table 7). SPON2, known to be involved in the clearance of influenza viruses, is up-regulated more than 30-fold in AFS compared to amniocytes. Other up-regulated genes included LRFN1, NFIC, ATG9B, TBC1D16, and GPRIN1. Genes that were down-regulated in AFS comprised RPL34, PSMA6, and UBC, which are involved in protein synthesis and degradation.
Table 5

Top biological functions identified in unique genes of AFS by Ingenuity Pathway Analysis (IPA).

Category p value rangeNo. of genesAssociated function
Behavior9.90E-055Mechanical allodynia behavior
Connective Tissue Disorders, Skeletal and Muscular1.40E-032Synostosis of cranium
Embryonic Development, Organismal Development2.23E-04 ~ 1.40E-0330Development of body trunk, neuroectoderm, rhombomere 1
Cardiovascular System Development and Function3.48E-04 ~ 9.12E-0332Activation and contraction of heart, cardiogenesis, morphogenesis, growth of blood vessel
Cell Morphology, Cellular Compromise, Inflammatory4.28E-04 ~ 2.39E-0214Swelling of cisternae, breakage of cellular membrane, disorganization of cells etc.
Organismal Injury and Abnormalities6.57E-04 ~ 8.69E-0320Strength of skeletal muscle, fibrosis of tissue, damage of lung
Gene Expression8.48E-04 ~ 4.29E-036Binding of octamer element and synthetic promoter
Skeletal and Muscular System Development and Function8.48E-04 ~ 1.20E-025Strength of skeletal muscle, deposition of cartilage matrix, force generation of muscle and myotube
Embryonic Development, Nervous System1.20E-03 ~ 6.00E-037Formation of mesencephalon and cerebellar cortex
Cell Death and Survival1.21E-03 ~ 2.39E-0233Activation-induced cell death, loss of neurons, etc.
Table 6

Top biological functions identified in unique genes of amniocytes by Ingenuity pathway analysis (IPA).

Category p value rangeNo. of genesAssociated function
Infectious Disease8.46E-17 ~ 6.82E-08416Viral Infection, infection of cells, replication of Influenza A virus
RNA Post-Transcriptional Skeletal and Muscular1.65E-16105Processing of RNA
Post-Translational Modification3.38E-14 ~ 2.25E-09135Ubiquitination, folding of protein, conformational modification of protein
Cell Death and Survival4.87E-14 ~6.79E-08783Apoptosis, necrosis, cell viability of tumor cell lines
Protein Synthesis5.34E-13 ~ 5.24E-08274Translation of protein, initiation of translation of protein, metabolism of protein, expression of protein
Cellular Growth and Proliferation1.52E-10782Proliferation of cells
Cancer6.58E-12 ~ 4.62E-09424Mammary tumor, colon cancer, breast or ovarian cancer
Dermatological Diseases1.11E-0950Chronic psoriasis
Neurological Disease1.29E-09 ~ 7.47E-09217Disorder of basal ganglia, Movement Disorders
DNA Replication, Recombination, and Repair, Energy Production, Nucleic Acid Metabolism, Small Molecule Biochemistry1.27E-08 ~ 4.19E-08129Catabolism of nucleoside triphosphate, repair of DNA
Table 7

Particular genes significantly differentially regulated in AFS compared to amniocytes.

Up-regulated genes
Bio-functionGene nameDescriptionFC
Cell Death and SurvivalCTBP1C-terminal binding protein 12.4
NFICnuclear factor I/C (CCAAT-binding transcription factor)4
SMURF1SMAD specific E3 ubiquitin protein ligase 12.8
LRFN1leucine rich repeat and fibronectin type III domain containing 16.3
MED29mediator complex subunit 292.5
Cellular Function and MaintenanceATG9BATG9 autophagy related 9 homolog B3.6
HERC1hect (homologous to the E6-AP (UBE3A) carboxyl terminus) domain2.1
SYNPO2synaptopodin 22.4
TBC1D16TBC1 domain family, member 163.2
TBC1D17TBC1 domain family, member 172.3
GPRIN1G protein regulated inducer of neurite outgrowth 13.6
Antimicrobial ResponseHLA-Amajor histocompatibility complex, class I, A2.9
SPON2spondin 2, extracellular matrix protein33.3
Cardiovascular SystemMBmyoglobin2.3
THRAthyroid hormone receptor, alpha (erythroblastic leukemia viral (v-erb-a) oncogene homolog, avian)2.7
Down-regulated genes
Bio-function Gene name Description FC
Cell Death and SurvivalAP1G1adaptor-related protein complex 1, gamma 1 subunit6.5
MAFGv-maf musculoaponeurotic fibrosarcoma oncogene homolog G22.6
TEAD2TEA domain family member 214.1
CancerIRX5iroquois homeobox 52.2
PRICKLE1prickle homolog 1 (Drosophila)18.7
RANBP3RAN binding protein 314.3
RPL34ribosomal protein L3497.4
BAZ1Bbromodomain adjacent to zinc finger domain, 1B25.9
CHD4chromodomain helicase DNA binding protein 48.2
PSMA6proteasome (prosome, macropain) subunit, alpha type, 6189.8
UBAC1UBA domain containing 15
Protein SynthesisAPEHN-acylaminoacyl-peptide hydrolase16.8
BANPBTG3 associated nuclear protein3
D2HGDHD-2-hydroxyglutarate dehydrogenase3.3
PMPCApeptidase (mitochondrial processing) alph20.9
PPP2R3Aprotein phosphatase 2, regulatory subunit B'', alpha15.1
SGSM3small G protein signaling modulator 313.3
UBCubiquitin C67.89
USP19ubiquitin specific peptidase 192.8
Cellular MovementGDI1GDP dissociation inhibitor 121.5
SNX27sorting nexin family member 278.7

FC: Fold change, indicates up-regulation in AFS RNA relative to amniocytes, respectively. This table lists genes that showed FC > 2.0.

FC: Fold change, indicates up-regulation in AFS RNA relative to amniocytes, respectively. This table lists genes that showed FC > 2.0.

Discussion

In this study, we investigated tissue-specific expression patterns enriched in second- trimester amniotic fluid cell-free fetal RNA and compared them with those in second-trimester amniocytes by using transcriptome analysis. To our knowledge, this is the first published study comparing global gene expression of amniocytes and AFS. Our results demonstrated different RNA expression patterns in tissue-specific genes and biological pathways between both sample types. Although the possible effects of the in vivo half-life of fetal transcripts in AFS should be considered, the AFS contains less genetic information than the amniocytes. We detected 353 genes that were unique to the supernatant. These included genes specific to the brain, spleen, blood, testis, heart, and saliva. The brain-specific transcripts were highly represented, with 119 genes. The 12,914 genes that were uniquely expressed in the amniocytes were specific to more diverse organs and mainly originated from the umbilical cord blood, skin, placenta, lung, epithelium, uterus, and liver. Additionally, in cellular RNA of amniocytes, tissue-specific genes of putatively non-fetal origin (umbilical cord, placenta, and uterus) were abundant. Genes that were common between AFS and amniocytes were specific to the brain, skin, uterus, placenta, and lung. Particularly brain-specific genes were enriched in the AFS alone and in the genes common in both amniocytes and AFS. It must be that brain development is main fetal developmental process during second trimester pregnancy. Our results were consistent with previous findings that brain-specific genes are important in second-trimester fetal development [9-12]. It is assumed that they play an important role in fetal brain development and can provide new biomarkers for monitoring of brain development. Genes specific to testis, spleen, heart, saliva, and primary B-cells are present only in AFS. Future studies should include a more in-depth evaluation of the roles of these genes in fetal development. Functional analysis of the DEGs showed that the highly expressed genes in second trimester AFS and amniocytes were involved in different pathways; while the AFS was enriched for genes involved in embryonic and cardiovascular development, and cell morphology, the pathways regulating infectious disease, cell death and survival, and protein synthesis were represented only in the amniocytes. Among the genes expressed in both AFS and amniocytes, those involved in cell death and survival and antimicrobial response were up-regulated, while genes of cancer and protein synthesis pathway were down-regulated. As the AFS was enriched for genes implicated in cardiovascular and embryonic development, and cell morphology, AFS might be the preferred sample to study these processes in developing fetus. In cultured amniocytes, the cellular RNA is likely affected by the culture environment. There are up-regulated genes related to cell-dogma, as transcription, translation, and replication, and response to growth stimulation, as apoptosis, necrosis, and cell proliferation. Notably, the embryonic development pathway was represented only in the AFS, corroborating that AFS RNA—without any effect of amniocyte RNA—is the preferred source to search for potential biomarkers of fetal development. Several studies have shown that AFS transcriptome analysis can provide information on the development of a number of different organs in living human fetuses. Previous AFS transcriptome studies on fetuses with twin-to-twin transfusion syndrome [14], Down syndrome [9], trisomy 18 [10, 11], and Turner syndrome [15], revealed that several genes and biological pathways were associated with the fetal developmental pathophysiology. AFS transcripts could play an important role in systemic cell-to-cell signaling and modulation of the fetal physiology. In this study, we provided a list of genes that are highly expressed in amniocytes and AFS in mid-trimester. The transcriptome analysis of the AFS suggested that fetal brain-specific RNA appears to be a major source of amniotic fluid RNA, without the effect of the amniocytes. Therefore, AFS RNA might be useful to uncover the mechanism of development of the central nervous system (CNS) in fetuses and to find biomarkers for and the pathogenic mechanism of CNS disorders. Future studies could compare the transcriptomes of fetuses with CNS anomalies, unknown intrauterine growth restriction, unknown intrauterine fetal death, and unknown cerebral palsy, with those of normal fetuses based on AFS samples that are devoid of uncultured amniocyte effects. We expect that this study will provide a foundation for future studies on differential gene expression of amniotic fluid in abnormal fetal development and on the influences of amniotic fluid and amniocytes on normal fetal development in mid-trimester pregnancies. This study had several limitations. Firstly, the sample size (10 samples) was small. Secondly, there were differences in fetal gender (female sex dominance), gestational age, and maternal BMI in the samples, and fetal gene expression patterns in AFS vary according to these factors [14, 16, 17]. Thirdly, the stability of RNA from AFS and amniocytes differs; cell-free RNA is relatively unstable compared to cellular RNA, suggesting that nucleic acid degradation might have affected the results. Finally, culture of amniocytes could change the RNA expression in the cells. Therefore, this study provided preliminary data, and future studies with larger sample sizes, uncultured amniocytes, and controlled confounding factors will be needed to analyze the AFS transcriptome in more detail and to reveal markers for fetal developmental physiology. In conclusion, we found distinct differences in gene expression, tissue-specific genes, and biological pathway in AFS and amniocytes. The transcriptome of AFS alone was enriched for fetal brain-specific transcripts in comparison to the amniocyte transcriptome. We showed that AFS is indeed a valuable source of RNA and a might be a source of important biological markers providing real-time information on fetal development physiology. Future transcriptome studies of cell-free RNA in amniotic fluid from live pregnancies with developmental disorders can permit advanced understanding of the early etiology of disease and may suggest innovative approaches to treatment.

Lists of genes differentially expressed in AFS, amniocytes, and both samples.

(XLSX) Click here for additional data file.

Detailed lists of tissue-specific genes expressed in AFS.

(XLSX) Click here for additional data file.

Detailed lists of tissue-specific genes expressed in amniocytes.

(XLSX) Click here for additional data file.

Detailed lists of tissue-specific genes expressed in both AFS and amniocytes.

(XLSX) Click here for additional data file.
  17 in total

1.  Large amounts of cell-free fetal DNA are present in amniotic fluid.

Authors:  D W Bianchi; E S LeShane; J M Cowan
Journal:  Clin Chem       Date:  2001-10       Impact factor: 8.327

2.  Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus.

Authors:  Y M Dennis Lo; K C Allen Chan; Hao Sun; Eric Z Chen; Peiyong Jiang; Fiona M F Lun; Yama W Zheng; Tak Y Leung; Tze K Lau; Charles R Cantor; Rossa W K Chiu
Journal:  Sci Transl Med       Date:  2010-12-08       Impact factor: 17.956

Review 3.  Cell-free fetal nucleic acids in amniotic fluid.

Authors:  L Hui; D W Bianchi
Journal:  Hum Reprod Update       Date:  2010-10-05       Impact factor: 15.610

Review 4.  Amniotic fluid: not just fetal urine anymore.

Authors:  Mark A Underwood; William M Gilbert; Michael P Sherman
Journal:  J Perinatol       Date:  2005-05       Impact factor: 2.521

5.  Presence of filterable and nonfilterable cell-free mRNA in amniotic fluid.

Authors:  Paige B Larrabee; Kirby L Johnson; Inga Peter; Diana W Bianchi
Journal:  Clin Chem       Date:  2005-06       Impact factor: 8.327

6.  Functional genomic analysis of amniotic fluid cell-free mRNA suggests that oxidative stress is significant in Down syndrome fetuses.

Authors:  Donna K Slonim; Keiko Koide; Kirby L Johnson; Umadevi Tantravahi; Janet M Cowan; Zina Jarrah; Diana W Bianchi
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-27       Impact factor: 11.205

7.  Microfluidics digital PCR reveals a higher than expected fraction of fetal DNA in maternal plasma.

Authors:  Fiona M F Lun; Rossa W K Chiu; K C Allen Chan; Tak Yeung Leung; Tze Kin Lau; Y M Dennis Lo
Journal:  Clin Chem       Date:  2008-08-14       Impact factor: 8.327

Review 8.  The amniotic fluid transcriptome as a guide to understanding fetal disease.

Authors:  Lillian M Zwemer; Diana W Bianchi
Journal:  Cold Spring Harb Perspect Med       Date:  2015-02-13       Impact factor: 6.915

9.  Transcriptomic analysis of cell-free fetal RNA suggests a specific molecular phenotype in trisomy 18.

Authors:  Keiko Koide; Donna K Slonim; Kirby L Johnson; Umadevi Tantravahi; Janet M Cowan; Diana W Bianchi
Journal:  Hum Genet       Date:  2010-12-09       Impact factor: 4.132

Review 10.  The virtosome-a novel cytosolic informative entity and intercellular messenger.

Authors:  Peter B Gahan; Maurice Stroun
Journal:  Cell Biochem Funct       Date:  2010-10       Impact factor: 3.685

View more
  8 in total

1.  Transcriptomic Analysis of Cell-free Fetal RNA in the Amniotic Fluid of Vervet Monkeys (Chlorocebus sabaeus).

Authors:  Anna J Jasinska; Dalar Rostamian; Ashley T Davis; Kylie Kavanagh
Journal:  Comp Med       Date:  2020-01-22       Impact factor: 0.982

2.  A comparison of sample collection methods for quantifying cell-free fetal neurodevelopment transcripts in amniotic fluid.

Authors:  Lisa Hui; Stephen Tong; Tu'Uhevaha J Kaitu'u-Lino; Natalie J Hannan
Journal:  BMC Res Notes       Date:  2016-07-07

3.  Amniotic fluid cell-free transcriptome: a glimpse into fetal development and placental cellular dynamics during normal pregnancy.

Authors:  Adi L Tarca; Roberto Romero; Roger Pique-Regi; Percy Pacora; Bogdan Done; Marian Kacerovsky; Gaurav Bhatti; Sunil Jaiman; Sonia S Hassan; Chaur-Dong Hsu; Nardhy Gomez-Lopez
Journal:  BMC Med Genomics       Date:  2020-02-12       Impact factor: 3.063

4.  Absence of GP130 cytokine receptor signaling causes extended Stüve-Wiedemann syndrome.

Authors:  Yin-Huai Chen; Giedre Grigelioniene; Phillip T Newton; Jacob Gullander; Maria Elfving; Anna Hammarsjö; Dominyka Batkovskyte; Hessa S Alsaif; Wesam I Y Kurdi; Firdous Abdulwahab; Veerabahu Shanmugasundaram; Luke Devey; Séverine Bacrot; Jana Brodszki; Celine Huber; Ben Hamel; David Gisselsson; Nikos Papadogiannakis; Katarina Jedrycha; Barbara Gürtl-Lackner; Andrei S Chagin; Gen Nishimura; Dominik Aschenbrenner; Fowzan S Alkuraya; Arian Laurence; Valérie Cormier-Daire; Holm H Uhlig
Journal:  J Exp Med       Date:  2020-03-02       Impact factor: 14.307

5.  Immunological observations and transcriptomic analysis of trimester-specific full-term placentas from three Zika virus-infected women.

Authors:  Fok-Moon Lum; Vipin Narang; Susan Hue; Jie Chen; Naomi McGovern; Ravisankar Rajarethinam; Jeslin Jl Tan; Siti Naqiah Amrun; Yi-Hao Chan; Cheryl Yp Lee; Tze-Kwang Chua; Wearn-Xin Yee; Nicholas Kw Yeo; Thiam-Chye Tan; Xuan Liu; Sam Haldenby; Yee-Sin Leo; Florent Ginhoux; Jerry Ky Chan; Julian Hiscox; Chia-Yin Chong; Lisa Fp Ng
Journal:  Clin Transl Immunology       Date:  2019-11-05

Review 6.  Quantifying Fetal Reprogramming for Biomarker Development in the Era of High-Throughput Sequencing.

Authors:  Fu-Sheng Chou; Krystel Newton; Pei-Shan Wang
Journal:  Genes (Basel)       Date:  2021-02-25       Impact factor: 4.096

7.  Identification of a novel gene signature in second-trimester amniotic fluid for the prediction of preterm birth.

Authors:  Min-A Kim; Eun-Ju Lee; Wookyeom Yang; Ha-Yeon Shin; Young-Han Kim; Jae-Hoon Kim
Journal:  Sci Rep       Date:  2022-03-31       Impact factor: 4.379

8.  Systems biology evaluation of cell-free amniotic fluid transcriptome of term and preterm infants to detect fetal maturity.

Authors:  Beena D Kamath-Rayne; Yina Du; Maria Hughes; Erin A Wagner; Louis J Muglia; Emily A DeFranco; Jeffrey A Whitsett; Nathan Salomonis; Yan Xu
Journal:  BMC Med Genomics       Date:  2015-10-22       Impact factor: 3.063

  8 in total

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