DOI: 10.5061/dryad.b8gtht7qb
title: Data from: Role of serotonin in human placental cytotrophoblast differentiation and gene expression

description: Serotonin (5-hydroxytryptamine; 5-HT) is transported into the human
 placenta through the serotonin transporter (SERT/SLC6A4) on the surface of
 the syncytiotrophoblast, where it ultimately makes its way to the
 circulation within the conceptus. During this transit a significant amount
 of 5-HT becomes concentrated in the cytotrophoblast nucleus. We used
 immunochemistry, inhibitors of SERT and transglutaminase 2 (TGM2; the
 enzyme that mediates the covalent linkage of 5-HT to protein glutamine
 residues—a process known as serotonylation), and RNA sequencing to
 elucidate the mechanism and consequences of this nuclear localization.
 Exogenous 5-HT recapitulated the uptake of 5-HT into the trophoblasts and
 its preferential concentration in cytotrophoblast nuclei we observed in
 the intact placenta. Inhibiting SERT with escitalopram or TGM2 with
 cystamine blocked cytotrophoblast differentiation in vitro; namely,
 flattening, aggregation and forming syncytia. Cystamine eliminated the
 staining of the nuclei in placental explants by exogenous 5-HT, suggesting
 that serotonylation mediated this phenomenon. This was confirmed by
 western blots and immunoprecipitation which identified histone 3 (H3), and
 specifically the 5th glutamine residue in H3, as a site of serotonylation.
 Blocking serotonylation led to marked changes in RNA expression. Of the
 38,524 mRNAs identified in these trophoblasts, cystamine changed the
 expression of 1,986 and escitalopram significantly altered 374. Both
 treatments altered the expression of 155 mRNAs either positively or
 negatively. In general, the genes that were downregulated were involved
 with cell proliferation, morphogenesis, motility, and growth—while genes
 that were upregulated controlled cell survival and protection pathways.
 These findings suggests that maternal 5-HT promotes placental,
 embryonic/fetal, and organismal development through histone serotonylation
 and consequent alterations in gene expression. They raise the possibility
 that alterations in 5-HT flux in the placenta affect placental and fetal
 growth, as well as organismal somatic and neurologic developmental
 trajectories.
description: <strong>Specimens</strong> Term
 placentas were collected anonymously from patients undergoing elective
 repeat Cesarian sections who delivered healthy babies. All the women who
 provided term placental samples signed an informed consent (Yale IRB
 protocol 1208010742). <strong>Trophoblast
 Purification</strong> Cytotrophoblast were
 prepared from fresh human term placentas by trypsin digestion and Percoll
 gradient fractionation, with the addition of an anti-CD9 and CD45 magnetic
 bead purification step, as previously described (1,2). During the initial
 steps of the digestions and up to the magnetic purification step, 10%
 fetal bovine serum (FBS, Gemini Bio-Products, Broderick, CA, 100-106)
 diluted in DMEM/F12 (Gibco, ThermoFisher Scientific, Waltham, MA,
 11330-032) with 4 mM L-glutamine, 1% penicillin/streptomycin was utilized.
 After the magnetic purification step, no FBS was added to the culture
 media, unless specifically noted. Cytotrophoblasts were then diluted to
 1x10<sup>6</sup> cells per ml in DMEM/F12 with 4 mM
 L-glutamine, 1% penicillin/streptomycin and either: 1) pelleted
 immediately by centrifugation for a zero-time point; 2) cultured in two-
 or four-chamber Nunc™ Lab-Tek™ II Chamber Slide™ System slides
 (ThermoFisher Scientific) or six-wells plates
 (CELLSTAR<sup>®</sup> #657160 6-well cell culture plates) for
 24-96 hours in humidified 5% CO<sub>2</sub>-95% air at 37˚C;
 or 3) and used for additional studies as described below.
 <strong>RNA sequencing</strong>
 RNA Seq Quality Control: Total RNA quality was determined by
 estimating the A260/A280 and A260/A230 ratios by Nanodrop (Nanodrop,
 ND-1000, ThermoFisher Scientific). RNA integrity was determined by running
 an Agilent Bioanalyzer 2100 gel, which measures the ratio of the ribosomal
 peaks. RNA Seq Library Prep: Using the Kapa RNA
 HyperPrep Kit with RiboErase (KR1351, Roche Diagnostics, Indianapolis,
 IN), rRNA was depleted starting from a normalized input of total RNA by
 hybridization of rRNA to complementary DNA oligonucleotides, followed by
 treatment with RNase H and DNase to remove rRNA duplexed toDNA. Samples
 were then fragmented using heat and magnesium. 1<sup>st</sup>
 strand synthesis was performed using random priming.
 2<sup>nd</sup> strand synthesis incorporated dUTPs into the
 2<sup>nd</sup> strand cDNA. Adapters were then ligated, and
 the library was amplified. Strands marked with dUTPs were not amplified
 allowing for strand-specific sequencing. Indexed libraries that meet
 appropriate cut-offs for both quantity and quality were quantified by
 qRT-PCR using a commercially available kit (KAPA Library Quant Kit, Roche
 Diagnostics, 07960298001) and insert size distribution determined with an
 Agilent Bioanalyzer (Agilent TapeStation 4200). Samples with a yield of
 ≥0.5 ng/µl were used for sequencing. Flow Cell
 Preparation and Sequencing: Sample concentrations were normalized to 2.0
 nM and loaded onto an Illumina NovaSeq (San Diego, CA) flow cell at a
 concentration that yields 35 million passing filter clusters per sample.
 Samples were sequenced using 100bp paired-end sequencing on an Illumina
 NovaSeq according to Illumina protocols. The 10bpunique dual index was
 read during additional sequencing reads that automatically follow the
 completion of read 1. Data generated during sequencing runs were
 simultaneously transferred to the Yale Center for Genomic Analysis (New
 Haven, CT) high-performance computing cluster. A positive control
 (prepared bacteriophage Phi X library) provided by Illumina was spiked
 into every lane at a concentration of 0.3% to monitor sequencing quality
 in real time. Data Analysis and Storage: Signal
 intensities were converted to individual base calls during a run using the
 system's Real Time Analysis (RTA) software. Base calls were
 transferred from the machine's dedicated personal computer to the
 Yale High Performance Computing cluster via a 1 Gigabit network mount for
 downstream analysis. Primary analysis—sample de-multiplexing and alignment
 to the human genome—was performed using Illumina's CASAVA 1.8.2
 software suite. The data were returned to the user if the sample error
 rate was less than 2% and the distribution of reads per sample in a lane
 was within reasonable tolerance. Data was retained on the cluster for at
 least 6 months, after which it was transferred to a tape backup
 system. Following RNA sequencing, low quality reads
 were trimmed, and adaptor contamination were removed using Trim Galore
 (v0.5.0; Babraham Bioinformatics, Cambridge, UK). Trimmed reads were
 mapped to the human reference genome (mm10) using HISAT2 (v2.1.0) (3).
 Gene expression levels were quantified using StringTie (v1.3.3b) (4) with
 gene models (v27) from the GENCODE project (5). Differentially expressed
 genes were identified using DESeq2 (v 1.22.1) (6). Transcripts per million
 (TPM) were calculated as previously described (7), while adjusted p values
 were calculated with DESeq2 using the Benjamini and Hochberg method
 (8). <strong>References</strong>
 1.         Kliman HJ, Nestler JE, Sermasi E, Sanger JM, Strauss
 JF, 3rd. Purification, characterization, and in vitro differentiation of
 cytotrophoblasts from human term placentae. Endocrinology.
 1986;118(4):1567-1582. 2.         Tang Z, Tadesse S,
 Norwitz E, Mor G, Abrahams VM, Guller S. Isolation of hofbauer cells from
 human term placentas with high yield and purity. Am J Reprod Immunol.
 2011;66(4):336-348. 3.         Kim D, Paggi JM, Park C,
 Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with
 HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37(8):907-915.
 4.         Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell
 JT, Salzberg SL. StringTie enables improved reconstruction of a
 transcriptome from RNA-seq reads. Nat Biotechnol.
 2015;33(3):290-295. 5.         Frankish A, Diekhans M,
 Ferreira AM, Johnson R, Jungreis I, Loveland J, Mudge JM, Sisu C, Wright
 J, Armstrong J, Barnes I, Berry A, Bignell A, Carbonell Sala S, Chrast J,
 Cunningham F, Di Domenico T, Donaldson S, Fiddes IT, Garcia Giron C,
 Gonzalez JM, Grego T, Hardy M, Hourlier T, Hunt T, Izuogu OG, Lagarde J,
 Martin FJ, Martinez L, Mohanan S, Muir P, Navarro FCP, Parker A, Pei B,
 Pozo F, Ruffier M, Schmitt BM, Stapleton E, Suner MM, Sycheva I,
 Uszczynska-Ratajczak B, Xu J, Yates A, Zerbino D, Zhang Y, Aken B,
 Choudhary JS, Gerstein M, Guigo R, Hubbard TJP, Kellis M, Paten B, Reymond
 A, Tress ML, Flicek P. GENCODE reference annotation for the human and
 mouse genomes. Nucleic Acids Res. 2019;47(D1):D766-D773.
 6.         Love MI, Huber W, Anders S. Moderated estimation of
 fold change and dispersion for RNA-seq data with DESeq2. Genome Biol.
 2014;15(12):550. 7.         Zhao Y, Li MC, Konate MM,
 Chen L, Das B, Karlovich C, Williams PM, Evrard YA, Doroshow JH, McShane
 LM. TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification
 Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived
 Models Repository. J Transl Med. 2021;19(1):269.
 8.         Hochberg Y, Benjamini Y. More powerful procedures for
 multiple significance testing. Stat Med. 1990;9(7):811-818.
description: # Data from: Role of serotonin in human placental cytotrophoblast
 differentiation and gene expression Dataset DOI:
 [10.5061/dryad.b8gtht7qb](10.5061/dryad.b8gtht7qb) ## Description of the
 data and file structure This README_Kliman_29Jul2025_Endocrinolgy_DATA.txt
 file was generated on 6Apr2025, and updated on 29Jul25, by Harvey J.
 Kliman, MD, PhD  **GENERAL INFORMATION** 1\. Title of Dataset:
 Endocrinology-S-25-00232 files 2\. Author Information * Harvey J. Kliman,
 MD, PhD * Yale University School of Medicine *
 [harvey.kliman@yale.edu](mailto:harvey.kliman@yale.edu)   * Nolwenn S.
 Morris, PhD * Yale University School of Medicine *
 [nolwennsue.morris@yale.edu](mailto:nolwennsue.morris@yale.edu)   3\. Date
 of data collection: 2024 4\. Geographic location of data collection: New
 Haven, CT, USA 5\. This work was supported by the Fulbright-Monahan
 Foundation (NSM), the University of Paris (NSM), and the Reproductive and
 Placental Research Unit, Yale University School of Medicine (HJK). 6\. All
 the patients who provided term placental samples signed an informed
 consent (Yale IRB protocol 12696 through the Reproductive Sciences Biobank
 at Yale University). 7\. Please refer to the following citations for
 methodological details: 1.   Kliman HJ, Nestler JE, Sermasi E, Sanger JM,
 Strauss JF, 3rd. Purification, characterization, and in vitro
 differentiation of cytotrophoblasts from human term placentae.
 Endocrinology. 1986;118(4):1567-1582. 2.   Tang Z, Tadesse S, Norwitz E,
 Mor G, Abrahams VM, Guller S. Isolation of hofbauer cells from human term
 placentas with high yield and purity. Am J Reprod Immunol.
 2011;66(4):336-348. 3.   Kim D, Paggi JM, Park C, Bennett C, Salzberg SL.
 Graph-based genome alignment and genotyping with HISAT2 and
 HISAT-genotype. Nat Biotechnol. 2019;37(8):907-915. 4.   Pertea M, Pertea
 GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables
 improved reconstruction of a transcriptome from RNA-seq reads. Nat
 Biotechnol. 2015;33(3):290-295. 5.   Frankish A, Diekhans M, Ferreira AM,
 Johnson R, Jungreis I, Loveland J, Mudge JM, Sisu C, Wright J, Armstrong
 J, Barnes I, Berry A, Bignell A, Carbonell Sala S, Chrast J, Cunningham F,
 Di Domenico T, Donaldson S, Fiddes IT, Garcia Giron C, Gonzalez JM, Grego
 T, Hardy M, Hourlier T, Hunt T, Izuogu OG, Lagarde J, Martin FJ, Martinez
 L, Mohanan S, Muir P, Navarro FCP, Parker A, Pei B, Pozo F, Ruffier M,
 Schmitt BM, Stapleton E, Suner MM, Sycheva I, Uszczynska-Ratajczak B, Xu
 J, Yates A, Zerbino D, Zhang Y, Aken B, Choudhary JS, Gerstein M, Guigo R,
 Hubbard TJP, Kellis M, Paten B, Reymond A, Tress ML, Flicek P. GENCODE
 reference annotation for the human and mouse genomes. Nucleic Acids Res.
 2019;47(D1):D766-D773. 6.   Love MI, Huber W, Anders S. Moderated
 estimation of fold change and dispersion for RNA-seq data with DESeq2.
 Genome Biol. 2014;15(12):550. 7.   Zhao Y, Li MC, Konate MM, Chen L, Das
 B, Karlovich C, Williams PM, Evrard YA, Doroshow JH, McShane LM. TPM,
 FPKM, or Normalized Counts? A Comparative Study of Quantification Measures
 for the Analysis of RNA-seq Data from the NCI Patient-Derived Models
 Repository. J Transl Med. 2021;19(1):269. 8.   Hochberg Y, Benjamini Y.
 More powerful procedures for multiple significance testing. Stat Med.
 1990;9(7):811-818. ### Files and variables #### DATA & FILE OVERVIEW
 Number of files: 90 Types of files: * DESeq2_fulltable (all data with
 R-based DESeq2 statistical methods to normalize and analyze the RNA-seq
 data) * padj0.05_FC1_DEG (Differentially expressed genes with a Log2Fold
 change &gt;1 or &lt;-1 and a p adjusted value of &lt;0.05) *
 padj0.05_FC2_DEG (Differentially expressed genes with a Log2Fold change
 &gt;2 or &lt;-2 and a p adjusted value of &lt;0.05) **Number of
 genes/rows:** * DESeq2_fulltable files: always 58,288 *
 padj0.05_FC1_DEG(n): condition specific; n = number of genes that satisfy
 these parameters for each condition pair * padj0.05_FC2_DEG(n): condition
 specific; n = number of genes that satisfy these parameters for each
 condition pair **Abbreviations** * 5-HT (serotonin, 5-hydroxytryptamine,
 CAS 153-98-0) * Cys (cystamine, CAS 56-17-7) * Lex (escitalopram oxalate,
 Lexapro, CAS 219861-08-2)   **Variable Lists  (Table Column Headers):** *
 genes: Lists the genes analyzed. * GeneVer: Version of the gene annotation
 used. * GeneID: Unique identifier for each gene. * GeneType: Type or
 category of gene (e.g., protein-coding, non-coding. * GeneName:
 Standardized name of the gene. * mean_XXX: Mean of gene expression in XXX
 condition. * mean_YYY: Mean of gene expression in YYY condition. *
 log2FoldChange: Log2 fold change of expression between the XXX condition
 and YYY condition. * lfcSE: Standard error of the log2 fold change. *
 stat: Statistical value used to determine significance (e.g., test
 statistic). * pvalue: P-value indicating the significance of differential
 expression. * padj: Adjusted p-value for multiple testing correction. *
 S_12D24_1st condition in file name (12D24 is the experiment designation
 and hence specific placenta being examined). * S_21E24_1st condition in
 file name (21E24 is the experiment designation and hence specific placenta
 being examined). * S_27C24_1st condition in file name (27C24 is the
 experiment designation and hence specific placenta being examined). *
 S_12D24_2nd condition in file name (12D24 is the experiment designation
 and hence specific placenta being examined). * S_21E24_2nd condition in
 file name (21E24 is the experiment designation and hence specific placenta
 being examined). * S_27C24_2ndcondition in file name (27C24 is the
 experiment designation and hence specific placenta being examined).  
 **Conditions (stated in file name):** * 5HT_vs_Ctrl: 5-HT v Control *
 5HT_vs_cys_2b_5HT: 5-HT v (Cystamine + 5-HT) * 5HT_vs_cys: 5-HT v
 Cystamine * 5HT_vs_lex_2b_5HT: 5-HT v (escitalopram + 5-HT) * 5HT_vs_lex:
 5-HT v escitalopram * Ctrl_vs_5HT: Control v 5-HT * Ctrl_vs_cys_2b_5HT:
 Control v (Cystamine + 5-HT) * Ctrl_vs_cys: Control v Cystamine *
 Ctrl_vs_lex: 5-HT v escitalopram * cys_2b_5HT_vs_5HT: (Cystamine + 5-HT) v
 5-HT * cys_2b_5HT_vs_Ctrl: (Cystamine + 5-HT) v Control *
 cys_2b_5HT_vs_cys: (Cystamine + 5-HT) v Cystamine *
 cys_2b_5HT_vs_lex_2b_5HT: (Cystamine + 5-HT) v (escitalopram + 5-HT) *
 cys_2b_5HT_vs_lex: (Cystamine + 5-HT) v escitalopram * cys_vs_5HT:
 Cystamine v 5-HT * cys_vs_Ctrl: Cystamine v Control * cys_vs_cys_2b_5HT:
 Cystamine v (Cystamine + 5-HT) * cys_vs_lex_2b_5HT: Cystamine v
 (escitalopram + 5-HT) * cys_vs_lex: Cystamine v escitalopram *
 lex_2b_5HT_vs_5HT: (escitalopram + 5-HT) v 5-HT * lex_2b_5HT_vs_Ctrl:
 (escitalopram + 5-HT) v Control * lex_2b_5HT_vs_cys_2b_5HT: (escitalopram
 + 5-HT) v (Cystamine + 5-HT) * lex_2b_5HT_vs_cys: (escitalopram + 5-HT) v
 Cystamine * lex_2b_5HT_vs_lex: (escitalopram + 5-HT) v escitalopram *
 lex_vs_5HT: escitalopram v 5-HT * lex_vs_Ctrl: escitalopram v Control *
 lex_vs_cys_2b_5HT: escitalopram v (Cystamine + 5-HT) * lex_vs_cys:
 escitalopram v Cystamine * lex_vs_lex_2b_5HT: escitalopram v (escitalopram
 + 5-HT) ### Full list of the 90 filenames:
 5HT_vs_Ctrl_DESeq2_fulltable.xlsx 5HT_vs_Ctrl_padj0.05_FC1_DEG9.xlsx
 5HT_vs_Ctrl_padj0.05_FC2_DEG9.xlsx 5HT_vs_cys_2b_5HT_DESeq2_fulltable.xlsx
 5HT_vs_cys_2b_5HT_padj0.05_FC1_DEG2897.xlsx
 5HT_vs_cys_2b_5HT_padj0.05_FC2_DEG2732.xlsx
 5HT_vs_cys_DESeq2_fulltable.xlsx 5HT_vs_cys_padj0.05_FC1_DEG2949.xlsx
 5HT_vs_cys_padj0.05_FC2_DEG2787.xlsx
 5HT_vs_lex_2b_5HT_DESeq2_fulltable.xlsx
 5HT_vs_lex_2b_5HT_padj0.05_FC1_DEG240.xlsx
 5HT_vs_lex_2b_5HT_padj0.05_FC2_DEG225.xlsx
 5HT_vs_lex_DESeq2_fulltable.xlsx 5HT_vs_lex_padj0.05_FC1_DEG735.xlsx
 5HT_vs_lex_padj0.05_FC2_DEG682.xlsx Ctrl_vs_5HT_DESeq2_fulltable.xlsx
 Ctrl_vs_5HT_padj0.05_FC1_DEG9.xlsx Ctrl_vs_5HT_padj0.05_FC2_DEG9.xlsx
 Ctrl_vs_cys_2b_5HT_DESeq2_fulltable.xlsx
 Ctrl_vs_cys_2b_5HT_padj0.05_FC1_DEG2277.xlsx
 Ctrl_vs_cys_2b_5HT_padj0.05_FC2_DEG2150.xlsx
 Ctrl_vs_cys_DESeq2_fulltable.xlsx Ctrl_vs_cys_padj0.05_FC1_DEG2293.xlsx
 Ctrl_vs_cys_padj0.05_FC2_DEG2165.xlsx
 Ctrl_vs_lex_2b_5HT_DESeq2_fulltable.xlsx
 Ctrl_vs_lex_2b_5HT_padj0.05_FC1_DEG132.xlsx
 Ctrl_vs_lex_2b_5HT_padj0.05_FC2_DEG123.xlsx
 Ctrl_vs_lex_DESeq2_fulltable.xlsx Ctrl_vs_lex_padj0.05_FC1_DEG413.xlsx
 Ctrl_vs_lex_padj0.05_FC2_DEG396.xlsx
 cys_2b_5HT_vs_5HT_DESeq2_fulltable.xlsx
 cys_2b_5HT_vs_5HT_padj0.05_FC1_DEG2897.xlsx
 cys_2b_5HT_vs_5HT_padj0.05_FC2_DEG2732.xlsx
 cys_2b_5HT_vs_Ctrl_DESeq2_fulltable.xlsx
 cys_2b_5HT_vs_Ctrl_padj0.05_FC1_DEG2277.xlsx
 cys_2b_5HT_vs_Ctrl_padj0.05_FC2_DEG2150.xlsx
 cys_2b_5HT_vs_cys_DESeq2_fulltable.xlsx
 cys_2b_5HT_vs_cys_padj0.05_FC1_DEG5.xlsx
 cys_2b_5HT_vs_cys_padj0.05_FC2_DEG5.xlsx
 cys_2b_5HT_vs_lex_2b_5HT_DESeq2_fulltable.xlsx
 cys_2b_5HT_vs_lex_2b_5HT_padj0.05_FC1_DEG1887.xlsx
 cys_2b_5HT_vs_lex_2b_5HT_padj0.05_FC2_DEG1802.xlsx
 cys_2b_5HT_vs_lex_DESeq2_fulltable.xlsx
 cys_2b_5HT_vs_lex_padj0.05_FC1_DEG1942.xlsx
 cys_2b_5HT_vs_lex_padj0.05_FC2_DEG1839.xlsx
 cys_vs_5HT_DESeq2_fulltable.xlsx cys_vs_5HT_padj0.05_FC1_DEG2949.xlsx
 cys_vs_5HT_padj0.05_FC2_DEG2787.xlsx cys_vs_Ctrl_DESeq2_fulltable.xlsx
 cys_vs_Ctrl_padj0.05_FC1_DEG2293.xlsx
 cys_vs_Ctrl_padj0.05_FC2_DEG2165.xlsx
 cys_vs_cys_2b_5HT_DESeq2_fulltable.xlsx
 cys_vs_cys_2b_5HT_padj0.05_FC1_DEG5.xlsx
 cys_vs_cys_2b_5HT_padj0.05_FC2_DEG5.xlsx
 cys_vs_lex_2b_5HT_DESeq2_fulltable.xlsx
 cys_vs_lex_2b_5HT_padj0.05_FC1_DEG1892.xlsx
 cys_vs_lex_2b_5HT_padj0.05_FC2_DEG1810.xlsx
 cys_vs_lex_DESeq2_fulltable.xlsx cys_vs_lex_padj0.05_FC1_DEG1805.xlsx
 cys_vs_lex_padj0.05_FC2_DEG1715.xlsx
 lex_2b_5HT_vs_5HT_DESeq2_fulltable.xlsx
 lex_2b_5HT_vs_5HT_padj0.05_FC1_DEG240.xlsx
 lex_2b_5HT_vs_5HT_padj0.05_FC2_DEG225.xlsx
 lex_2b_5HT_vs_Ctrl_DESeq2_fulltable.xlsx
 lex_2b_5HT_vs_Ctrl_padj0.05_FC1_DEG132.xlsx
 lex_2b_5HT_vs_Ctrl_padj0.05_FC2_DEG123.xlsx
 lex_2b_5HT_vs_cys_2b_5HT_DESeq2_fulltable.xlsx
 lex_2b_5HT_vs_cys_2b_5HT_padj0.05_FC1_DEG1887.xlsx
 lex_2b_5HT_vs_cys_2b_5HT_padj0.05_FC2_DEG1802.xlsx
 lex_2b_5HT_vs_cys_DESeq2_fulltable.xlsx
 lex_2b_5HT_vs_cys_padj0.05_FC1_DEG1892.xlsx
 lex_2b_5HT_vs_cys_padj0.05_FC2_DEG1810.xlsx
 lex_2b_5HT_vs_lex_DESeq2_fulltable.xlsx
 lex_2b_5HT_vs_lex_padj0.05_FC1_DEG18.xlsx
 lex_2b_5HT_vs_lex_padj0.05_FC2_DEG18.xlsx lex_vs_5HT_DESeq2_fulltable.xlsx
 lex_vs_5HT_padj0.05_FC1_DEG735.xlsx lex_vs_5HT_padj0.05_FC2_DEG682.xlsx
 lex_vs_Ctrl_DESeq2_fulltable.xlsx lex_vs_Ctrl_padj0.05_FC1_DEG413.xlsx
 lex_vs_Ctrl_padj0.05_FC2_DEG396.xlsx
 lex_vs_cys_2b_5HT_DESeq2_fulltable.xlsx
 lex_vs_cys_2b_5HT_padj0.05_FC1_DEG1942.xlsx
 lex_vs_cys_2b_5HT_padj0.05_FC2_DEG1839.xlsx
 lex_vs_cys_DESeq2_fulltable.xlsx lex_vs_cys_padj0.05_FC1_DEG1805.xlsx
 lex_vs_cys_padj0.05_FC2_DEG1715.xlsx
 lex_vs_lex_2b_5HT_DESeq2_fulltable.xlsx
 lex_vs_lex_2b_5HT_padj0.05_FC1_DEG18.xlsx
 lex_vs_lex_2b_5HT_padj0.05_FC2_DEG18.xlsx The RNA sequencing was performed
 by the staff members of the Yale Center for Genomic Analysis, whose center
 is supported by the National Institute of General Medical Sciences of the
 National Institutes of Health under Award Number 1S10OD030363-01A1. ##
 Code/software Microsoft Excel or other software that can read Excel files.
 ## Access information N/A. ## Human subjects data Term placentas were
 collected anonymously from patients undergoing elective repeat Cesarian
 sections who delivered healthy babies. All the women who provided term
 placental samples signed an informed consent (Yale IRB protocol
 1208010742). All data has been de-identified.