# The molecular mechanisms and functional significance of gene positioning

> **NIH NIH R35** · NORTHWESTERN UNIVERSITY · 2023 · $550,463

## Abstract

Project Summary
Understanding the molecular control of transcriptional responses of cells to environmental signals is
essential to understand how environment, aging and lifestyle impact physiology. My lab has discovered
that the position of genes is actively controlled by cells and that this impacts transcription in several
ways. Although we study this phenomenon in the simple budding yeast, it is conserved to more complex
animals, including humans. We recently showed that a majority of transcription factors control the
interaction of genes with the Nuclear Pore Complex (NPC), impacting the spatial arrangement of genes
and the interaction of chromosomes. Furthermore, we have shown that this interaction with the NPC can
either promote stronger transcription and alter chromatin structure to poise genes for future expression.
Thus, transcription factor-mediated targeting to the NPC likely has broad effects on both the spatial
organization of the genome and gene expression. The goals of this work are to determine the molecular
mechanisms by which transcription factors and NPCs spatially arrange the yeast genome and to
understand how these interactions impact gene expression and chromatin structure.

## Key facts

- **NIH application ID:** 10669133
- **Project number:** 5R35GM136419-04
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Jason Hays Brickner
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $550,463
- **Award type:** 5
- **Project period:** 2020-08-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10669133

## Citation

> US National Institutes of Health, RePORTER application 10669133, The molecular mechanisms and functional significance of gene positioning (5R35GM136419-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10669133. Licensed CC0.

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