# System dynamics and gene network architecture of early T-cell development

> **NIH NIH R01** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2022 · $537,755

## Abstract

PROJECT SUMMARY
 Timing of developmental progression is well-studied in early embryos, but cell lineages are generated
stochastically from stem-cell precursors in later stages of life, and relatively little is known about the gene
networks that control the probabilities that individual cells will initiate development or their rates of
developmental progression. Mouse T cell development from multipotent blood precursors is an advantageous
model for revealing mechanisms of these kinds of systems. The stages within the T-cell pathway are well
defined in gene expression patterns, and cells starting from specific stages along the pathway can be tracked
efficiently through development in vitro. Different cohorts of T cell progenitors from earlier or later embryonic
and postnatal life have cell-intrinsic differences in the speeds with which they can differentiate. We hypothesize
that the earliest cells in this pathway begin with a positively stabilized “Phase 1” gene regulatory network state
that intrinsically opposes differentiation, until cumulative responses to signaling can induce a flip to a new
network state. The differences in intrinsic differentiation speeds between different T-cell cohorts, and the
extents of proliferation they undergo before differentiation is complete, are correlated with the persistence of
the phase 1 regulatory state. However, until now it has been difficult to dissect these networks critically
because cells in the earliest stages of T-cell development are rare and may have varied kinds of heterogeneity.
 This proposal is driven by new technological advances that open an exciting opportunity to dissect this
mechanism functionally in single cells for the first time, and by a new systems biology collaboration that offers
superior analyses of single-cell transcriptional responses to regulatory perturbation, both at the gene and at the
cell levels. The new computational methods are optimized for revealing how gene network alterations shift
subsets of cells between normal or abnormal developmental states. The experimental tools include recently
developed mice with fluorescent reporters that report lineage commitment status of individual cells; imaging
conditions that allow tracking living, individual clones through the whole commitment process; and an effective
Cas9 transgenic mouse system that allows us to delete genes efficiently in primary T-cell precursors, so that
impacts of perturbations on both gene expression and developmental kinetics can be defined. We can both
define molecular sub-states in the starting population and monitor the impacts of specific regulatory factor
perturbations using single-cell RNA-seq (10Genomics) and a new highly multiplex single-molecule fluorescent
in situ hybridization technology for high sensitivity quantitation of low-abundance transcripts. Predictions of key
network regulators will be directly tested here by perturbations and time-lapse imaging of clones differentiating
from single cells....

## Key facts

- **NIH application ID:** 10380658
- **Project number:** 5R01HD100039-04
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** ELLEN V. ROTHENBERG
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $537,755
- **Award type:** 5
- **Project period:** 2019-07-15 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10380658

## Citation

> US National Institutes of Health, RePORTER application 10380658, System dynamics and gene network architecture of early T-cell development (5R01HD100039-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10380658. Licensed CC0.

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