# Beyond Pseudotime: Enhanced Single-cell Genomics Tools for Understanding the Temporal Dynamics of Development and Disease

> **NIH NIH R35** · UNIVERSITY OF ARIZONA · 2020 · $364,590

## Abstract

ABSTRACT
From a single fertilized egg, the human genome must regulate an incredible succession of cellular divisions and
fate decisions to give rise to the adult human body and its ~30 trillion cells [1]. The genome must also orchestrate
highly diverse functions in these terminal cell types and in many instances allow for dynamic responses to a
variety of stimuli - from white blood cells responding to stimulation [2] to hepatocytes responding to hormonal
cues [3]. Furthermore, developmental processes are asynchronous and continue for many cell types into
adulthood. Fundamental to our understanding of the causal links in all of these processes is the concept of time.
While time course studies have a long history in genomics [4], single-cell genomic technologies are providing
unprecedented views into the temporal dynamics of cellular differentiation and response at a genomic scale [5].
This will have widespread implications for our strategies of stem cell therapy, windows of intervention in disease
progression, and our basic understanding of developmental biology. However, these inferences are to-date
limited and rely on a concept called ‘pseudotime’ [5], which is difficult to validate and can be warped relative to
real time. To truly understand how the genome coordinates development, differentiation, and disease we need
new tools that allow us to better measure several key features of developmental trajectories: the ordering
of regulatory cascades, the duration of the key genomic events in developmental processes, and the
specific DNA sequences that can regulate temporal expression patterns. In order to address these
concerns, we will develop a new suite of tools that leverage single-cell readouts to better understand the
genomic regulation of time. In particular, we will focus on highly multiplexed assays to better understand the
necessary and sufficient ordering of regulatory cascades in differentiation pathways, assays to convert
pseudotime to real time, and genome scalable assays to identify and validate the exact regulatory
sequences that define temporal patterns of gene expression.

## Key facts

- **NIH application ID:** 10026833
- **Project number:** 1R35GM137896-01
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Darren A Cusanovich
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $364,590
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10026833

## Citation

> US National Institutes of Health, RePORTER application 10026833, Beyond Pseudotime: Enhanced Single-cell Genomics Tools for Understanding the Temporal Dynamics of Development and Disease (1R35GM137896-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10026833. Licensed CC0.

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