Biology subjects

Jerber, J.

Publications and source records attributed to Jerber, J..

3 recordsLinked to original sources

bioRxiv2024

An in vivo and in vitro spatiotemporal atlas of human midbrain development

The dopaminergic system has key roles in human physiology and is implicated in a broad range of neurological and neuropsychiatric conditions that are increasingly investigated using induced pluripotent stem cell-derived midbrain models. To determine the similarity of such models to human systems, we undertook single cell and spatial profiling of first and second trimester fetal midbrain and compared it to in vitro midbrain models. Our initial histological analysis of second trimester fetal midbrain revealed structural complexity already similar to that of adult tissue, although this similarity did not fully extend to transcriptional activity. Moreover, we show that in vitro models recapitulate the transcriptional activity of late first trimester fetal midbrain, while 3D models replicate the spatial organization and cellular microenvironments of first and second trimester fetal midbrain. Understanding the extent of human tissue recapitulation in midbrain laboratory models is essential to justify their use as biological proxies.

neuroscience↗

bioRxiv2022

Effects of somatic mutations on cellular differentiation in iPSC models of neurodevelopment

The use of induced pluripotent stem cells (iPSC) as models for development and human disease has enabled the study of otherwise inaccessible tissues. A remaining challenge in developing reliable models is our limited understanding of the factors driving irregular in vitro differentiation of iPSCs, particularly the impact of acquired somatic mutations. We leveraged data from a pooled dopaminergic neuron differentiation experiment of 238 iPSC lines profiled with single-cell and whole-exome sequencing to study how somatic mutations affect differentiation outcomes. Differentiation was tracked at three time points corresponding to neural progenitors, early neurons and mature neurons. We found that deleterious somatic mutations in key developmental genes, notably the BCOR gene, are strongly associated with failure in dopaminergic neuron differentiation, with lines carrying such mutations also showing larger proliferation rate in culture. We further identified broad differences in cell type composition between failed and successfully differentiating lines, as well as significant changes in gene expression contributing to the inhibition of neurogenesis, a functional process also targeted by deleterious mutations in failed lines. Our work highlights the need to routinely measure the burden of deleterious mutations in iPSC lines and calls for caution in interpreting differentiation-related phenotypes in disease-modelling experiments.

genomics↗

bioRxiv2020

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

Common genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

genetics↗