# Functional Genomics Core

> **NIH NIH P30** · UNIVERSITY OF PENNSYLVANIA · 2024 · $113,743

## Abstract

SUMMARY
The Functional Genomics Core (FGC) provides state-of-the-art experiment planning, sample preparation,
quality assessment, library construction, DNA sequencing, and data analysis services to DRC members using
state-of-the-art Illumina Sequencers including the high-throughput but flexible NovaSEQ 6000 system. We
have experience with ChIP-seq, nucleosome mapping, whole exome and whole genome resequencing in
mouse, human, zebrafish, and other species. We offer RNAseq, microRNAseq, GroSeq, CLIP-seq,
nucleosome mapping, ATAC-Seq, ChIPseq, whole genome and targeted DNA methylome analysis,
hydroxymethyl DIP, single cell ATACseq, single cell RNAseq and multiomics approaches. A goal of the FGC is
to quickly adapt and occasionally develop new protocols for sequencing-based functional genomics analysis
relevant to DRC members. We also offer a self-service sequencing services for advanced users at a minimal
fee. Importantly, in response to DRC member requests, we provide extensive bioinformatics services, tailored
to individual projects, to DRC members. The Core remains in high demand, with 46 current users. The FGC
has provided data and analysis for over 70 research publications of DRC members during the past funding
period and supported multiple grant applications.
PHS 398/2590 (Rev. 09/20) Page FUNCTIONAL GENOMICS CORE: Director - K. Kaestner

## Key facts

- **NIH application ID:** 10845587
- **Project number:** 5P30DK019525-48
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** KLAUS H KAESTNER
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $113,743
- **Award type:** 5
- **Project period:** 1997-03-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10845587

## Citation

> US National Institutes of Health, RePORTER application 10845587, Functional Genomics Core (5P30DK019525-48). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10845587. Licensed CC0.

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