Sp 3dpf scRNA-Seq
Arnone, Maria Immacolata et al. (2021), Sp 3dpf scRNA-Seq, Dryad, Dataset, https://doi.org/10.5061/dryad.n5tb2rbvz
Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of transcription factors shared by this population of neurons in sea urchin and vertebrate pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we reconstruct the Pdx-1-driven gene regulatory network in these cells. We hypothesize that a similar network was active in an ancestral deuterostome cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.
Single cell RNA sequencing was performed using the 10x Genomics single cell capturing system. Specimens from four independent biological replicates, ranging from 6000-20.000 cells, were loaded on the 10X Genomics Chromium Controller. Single cell cDNA libraries were prepared using the Chromium Single Cell 3’ Reagent Kit (Chemistries v2 and v3). Libraries were sequenced by GeneCore (EMBL, Heidelberg, Germany) for 75 bp paired-end reads (Illumina NextSeq 500), resulting in a mean of 88M reads. Cell Ranger Software Suite 3.0.2 (10x Genomics) was used for the alignment of the single-cell RNA-seq output reads and generation of feature, barcode and matrices. The genomic index was made in Cell Ranger using the S. purpuratus genome version 3.1. Cell Ranger output matrices for four biological and two technical replicates were used for further analysis in Seurat v3.0.2 R package.