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Single cell RNA-sequencing reveals placenta cellular heterogeneity in adverse pregnancy

ABSTRACT: The placenta is a highly heterogeneous organ and is closely related to adverse pregnancy. The previous bulk sequencing of whole tissue could not show the characteristics of individual cells and the interactions between cells. Here, we select the placental tissues of the gestational diabetes group(GDM), preeclampsia group(PE), advanced age group(GL) and normal control group for single-cell sequencing in order to explain the mechanism of related diseases in more depth.nated spatial and temporal regulation of gene expression in the murine hindlimb determines the identity of mesenchymal progenitors and the development of diversity of musculoskeletal tissues they form. Hindlimb development has historically been studied with lineage tracing of individual genes selected a priori, or at the bulk tissue level, which does not allow for the determination of single cell transcriptional programs yielding mature cell types and tissues. To identify the cellular trajectories of lineage specification during limb bud development, we used single cell mRNA sequencing (scRNA-seq) to profile the developing murine hindlimb.

ORGANISM(S): Homo sapiens

PROVIDER: GSE173193 | GEO | 2021/05/04

REPOSITORIES: GEO

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Project description:Genomic expression profiles of blood and placenta reveal significant immune-related pathways and categories in Chinese women with Gestational Diabetes Gestational diabetes mellitus (GDM) is a complex metabolic disease which occurs in pregnancy with high prevalence, and its pathogenesis remains elusive. Thus far, there has been no comprehensive gene expression profiling in Chinese women with GDM. In this study, we attempt to define the genes and/or pathways that are involved in GDM with Chinese ethnicity, by the Illumina microarray technique. We found 5,197 and 243 genes with significantly altered expression due to GDM in blood and placenta tissues, respectively. Previously known genes (such as TNF, IL1B, LEP, IFNG, and HLA-G) with altered gene expression in GDM were also validated here. In addition, we identified undescribed genes VAV3, PTPN6, CD48 and IL15, in which expression was related to GDM by microarray and Q-RT-PCR assays. To identify GDM-associated pathways, we used analyses with integrated functional annotation (i.e. KEGG) and extracted two significant pathways, which were Natural killer cell mediated cytotoxicity (hsa04650; FDR = 7.10E-09) in blood and Cytokine-cytokine receptor interaction (hsa04060; FDR = 1.07E-03) in placenta tissues. Immune system process (GO: 0002376) was identified by GO analysis with FDR P-value = 7.01E-60 in blood and FDR P-value = 3.57E-08 in placenta tissues, indicating the importance of immunological and inflammatory categories in GDM. Furthermore, despite differences in the quantity of gene expression, we observed a similar functional distribution between expression of blood and placenta tissues in GDM under the categories of immunity. These newly identified key genes and pathways may provide valuable information for the pathogenesis of GDM and advance disease diagnosis, prevention, medication design, and clinical treatment of the disease. One individual GDM blood tissue sample and one pooled GDM blood tissue sample were compared to one pooled healthy blood tissue sample. One pooled GDM placenta tissue sample was compared to one pooled healthy placenta tissue sample.

Project description:Long non-coding RNAs (lncRNAs) comprise a diverse class of transcripts that can regulate molecular and cellular processes in brain development and diseasee. LncRNAs exhibit cell type- and tissue-specific expression, but little is known about the expression and function of lncRNAs in the developing human brain. Here, we deeply profiled lncRNAs from polyadenylated and total RNA obtained from human neocortex at different stages of development and integrated this resource to analyze the transcriptomes of single cells. While lncRNAs were generally detected at low levels in whole tissues, single cell transcriptomics revealed that many lncRNAs are abundantly expressed in individual cells and are cell type-specific. Furthermore, we used CRISRPi to show that LOC646329, a lncRNA enriched in radial glia but detected at low abundance in tissues, regulates cell proliferation. The discrete and abundant expression of lncRNAs among individual cells has important implications for both their biological function and utility for distinguishing neural cell types. 16 Bulk Tissue Samples from GW13-23; 226 Single Cells from GW19.5-23.5 ------------------ bulk_tpm.polya.txt: bulk RNA-seq expression; using polyA full reference scell_ncounts.genes.thresh.txt: single cell RNA-seq expression; using polyA stringent reference; includes 50 GW16, GW21, GW21p3 cells previously analyzed (Pollen et. al. 2014) polya_RNA_stringent_ref.gtf: bulk RNA-seq polyA stringent transcriptome reference polya_RNA_full_ref.gtf: bulk RNA-seq polyA full transcriptome reference total_RNA_stringent_ref.gtf: bulk RNA-seq total stringent transcriptome reference total_RNA_full_ref.gtf: bulk RNA-seq total full transcriptome reference GW13_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW13_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW14.5_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW16_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW21_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_1_total_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_polya_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_polya_plus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_total_minus.bw: strand-specific bulk RNA-seq alignment signal GW23_2_total_plus.bw: strand-specific bulk RNA-seq alignment signal

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Single cell RNA-sequencing reveals placenta cellular heterogeneity in adverse pregnancy

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