Single-Cell Sequencing and Analysis

Barcode specifically labeled the transcripts of each signal cell by using a Chromium Next GEM Single Cell 3' Kit v3.1 (10X Genomics Inc, San Francisco, USA). Libraries were constructed and sequenced on an Illumina NovaSeq 6000 platform (S10OD032203) at a sequencing depth of ~800 million reads in Tufts University Core Facility (TUCF). The sequencing results were demultiplexed and cell barcodes were extracted. Subsequently, Single-Cell Analysis in Python (SCANPY) 26 (link) was utilized for data clustering analysis and visualization. SCSA 29 , an automatic tool and distinct marker genes from published papers was used for cluster annotation. The ligand-receptor interaction data were generated by Squidpy 58 (link) (based on CellPhoneDB 59 (link) and Omnipath 60 (link) database) via screening and paring the ligands and receptors, which expressed in more than 10% of cells in each cluster. The lncRNA-RNA reaction tool, intaRNA 52 (link),71 (link), was used to predict the direct bind site of lncR-APDC and Tff2. The newest intaRNA package was downloaded from GitHub to perform the analysis, which was able to analyze more than 2000 nt full length of lncRNAs and can be optimized on multiple settings.

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Zhu Z.X., Liu Y., Wang J., Xie Y., Li R.Y., Ma Q., Tu Q., Melhem N.A., Couldwell S., El-Araby R.E., Tai A., Van Dyke T.E., Karimbux N., Jeong Y.N, & Chen J.J. (2023). A novel lncRNA-mediated epigenetic regulatory mechanism in periodontitis. International Journal of Biological Sciences, 19(16), 5187-5203.

Publication 2023

Chromium Next GEM Single Cell 3' Kit v3.1 NovaSeq 6000

Cells Chromium Genes marker Ligands Lncrnas Python Signal cell Single cell analysis Tff2

Corresponding Organization : Tufts University

Other organizations : Sichuan University, Novant Health Forsyth Medical Center

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Variable analysis

independent variables

Chromium Next GEM Single Cell 3' Kit v3.1 (10X Genomics Inc, San Francisco, USA)

dependent variables

Sequencing depth of ~800 million reads
Clustering analysis and visualization with SCANPY
Cluster annotation with SCSA and distinct marker genes from published papers
Ligand-receptor interaction data generated by Squidpy (based on CellPhoneDB and Omnipath database)
LncRNA-RNA interaction prediction with intaRNA

control variables

Sequencing was performed at Tufts University Core Facility (TUCF)

Annotations

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