Unsupervised Trajectory Analysis of Single-Cell RNA-Seq and Imaging Data Reveals Alternative Tuft Cell Origins in the Gut

Abstract

Summary Modern single-cell technologies allow multiplexed sampling of cellular states within a tissue. However, computational tools that can infer developmental cell-state transitions reproducibly from such single-cell data are lacking. Here, we introduce p-Creode, an unsupervised algorithm that produces multi-branching graphs from single-cell data, compares graphs with differing topologies, and infers a statistically robust hierarchy of cell-state transitions that define developmental trajectories. We have applied p-Creode to mass cytometry, multiplex immunofluorescence, and single-cell RNA-seq data. As a test case, we validate cell state-transition trajectories predicted by p-Creode for intestinal tuft cells, a rare, chemosensory cell type. We clarify that tuft cells are specified outside of the Atoh1-dependent secretory lineage in the small intestine. However, p-Creode also predicts, and we confirm, that tuft cells arise from an alternative, Atoh1-driven developmental program in the colon. These studies introduce p-Creode as a reliable method for analyzing large datasets that depict branching transition trajectories. p-Creode is publicly available for download here: https://github.com/KenLauLab/pCreode.

Neurog3-Independent Methylation Is the Earliest Detectable Mark Distinguishing Pancreatic Progenitor Identity

“…p-Creode allows for pseudo-temporal ordering that depicts progression relationships (Herring et al, 2018). This analysis revealed that progenitors progressively lose Neurog3 expression while gaining β- or α-cell features in two separate trajectories (Figure 1G).…”

“…Overall, 3,368 cells were sequenced with, on average, 5,886 unique transcripts per cell (as measured by number of UMIs) identified from, on average, 56,343 reads per cell. Sequencing data were mapped, quantified, and normalized following the protocol of our previous report (Herring et al, 2018). …”

“…For p-Creode analysis (Herring et al, 2018), a Neurog3-dependent gene set (Gu et al, 2004) was used in place of the routine Neighborhood Variance Ratio select gene procedure. p-Creode parameters were selected according to documented sources (https://github.com/KenLauLab/pCreode), and the representative trajectory from N=100 runs were used.…”

An Inter-Species Translation Model Implicates Integrin Signaling in Infliximab-Resistant Colonic Crohn’s Disease

“…Single-cell encapsulation of gut epithelial tissue was performed using the inDrop platform (1CellBio) with an in vitro transcription library preparation protocol, as previously described (46,47). inDrop utilizes CEL-Seq in preparation for sequencing and is summarized as follows: (1) reverse transcription (RT), (2) ExoI nuclease digestion, (3) SPRI purification (SPRIP), (4) second strand synthesis, (5) SPRIP, (6) T7 in vitro transcription linear amplification, (7) SPRIP, Approximately 3,000 cells for each sample entered the microfluidic chip.…”

Tree‐ensemble analysis assesses presence of multifurcations in single cell data

“…TSCAN first clusters the data, then like Monocle infers a tree from the data (Ji & Ji, ). p‐Creode fits multiple trees to the data, uses the data to smooth them, then identifies the tree which is most central within these (Herring et al , ). These algorithms can all (with the exception of SCUBA, which requires time annotations) return branch points regardless of the actual evidence in the data, and any decision on the presence or absence of a branch point must be made by the user.…”