# Ultra-Low and Single-Cell Transcriptome Analysis in Patient-Derived Rare CLL Precursor Cells

> **NIH NIH R50** · OHIO STATE UNIVERSITY · 2020 · $148,966

## Abstract

Project Summary/Abstract
The Project PI is the Technical Director of the OSUCCC Genomics Shared Resources (GSR) and a Research
Assistant Professor in the Division of Hematology at the OSU College of Medicine. She set up and directed the
Illumina sequencing operation for close to 9 years now. As the GSR serves both the clinical/translational
research community and the basic science communities at OSU, the Project PI has gained extensive insights
related to the impact of quality (e.g., species, integrity, presence of contaminants, preservation process,
nucleic acids extraction protocols) and quantity (concentration and total amount) of input material on
sequencing library characteristics, sequencing data quality and read distributions in the genome. This wealth of
knowledge helps to open up another front of research interest (in addition to DNA methylation and cancer
epigenetics) for the PI resulting in the list of technology-related publications highlighted in the Biosketch
document as well as the technology manuscripts under preparation as described in Research Strategy #3 and
Research Strategy #5. For the R50 Application, the Mentor PIs (Dr. Muthusamy and Dr. Byrd) both share the
same vision that properly controlled and well-designed low cell number- and single-cell RNA-seq in rare
precursor populations in CLL and AML will allow us to evaluate the leukemic stem cell potential in CLL and
AML, examine mechanism of drug sensitivity and biology in these rare cell populations. If successful, this
research direction will open up avenues for novel therapies, relapse prevention and ultimately cellular level
personalized medicine. As little is known about these precursor populations, careful characterization of their
bulk transcriptomic profile is a reasonable first step to take to form the foundation of subsequent transcriptomic
profiles from individual single-cells. Briefly, the overall research design is as follows: 1) standardize and
optimize volume of cell sorting buffers for 10-, 50- and 100 cells; 2) use two types of external control RNA
spike-in to correct for diverse total RNA in rare precursor cells; 3) guided by data from #2 to adjust for cell
numbers to allow data normalization for between group comparisons with cell types with diverse RNA amount;
4) move forward with single-cell RNA-seq analysis guided by the most robust approaches available at that time
(e.g., Fluidigm C1 or 10X Genomics and their single-cell RNA-seq kit)

## Key facts

- **NIH application ID:** 10012782
- **Project number:** 5R50CA211524-05
- **Recipient organization:** OHIO STATE UNIVERSITY
- **Principal Investigator:** Pearlly Yan
- **Activity code:** R50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $148,966
- **Award type:** 5
- **Project period:** 2016-09-20 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10012782

## Citation

> US National Institutes of Health, RePORTER application 10012782, Ultra-Low and Single-Cell Transcriptome Analysis in Patient-Derived Rare CLL Precursor Cells (5R50CA211524-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10012782. Licensed CC0.

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