Tabaka, M. | Search bioRxiv

bioRxiv2017

Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming.

Understanding the molecular programs that guide cellular differentiation during development is a major goal of modern biology. Here, we introduce an approach, WADDINGTON-OT, based on the mathematics of optimal transport, for inferring developmental landscapes, probabilistic cellular fates and dynamic trajectories from large-scale single-cell RNA-seq (scRNA-seq) data collected along a time course. We demonstrate the power of WADDINGTON-OT by applying the approach to study 65,781 scRNA-seq profiles collected at 10 time points over 16 days during reprogramming of fibroblasts to iPSCs. We construct a high-resolution map of reprogramming that rediscovers known features; uncovers new alternative cell fates including neuraland placental-like cells; predicts the origin and fate of any cell class; highlights senescent-like cells that may support reprogramming through paracrine signaling; and implicates regulatory models in particular trajectories. Of these findings, we highlight Obox6, which we experimentally show enhances reprogramming efficiency. Our approach provides a general framework for investigating cellular differentiation.

bioinformatics↗

bioRxiv2016

Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) and RNA-seq profiles from activated CD4+ T cells of up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, in patterns consistent with the 3D organization of chromosomes measured by in situ Hi-C in T cells. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak through disrupting binding sites for transcription factors important for T cell differentiation and activation. These ATAC quantitative trait nucleotides (ATAC-QTNs) have the largest effects on co-accessible peaks, are associated with gene expression from the same aliquot of cells, are rarely affecting core binding motifs, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis- regulatory elements, in isolation or in concert, to influence gene expression in primary immune cells that play a key role in many human diseases.

genomics↗