Date of Award
2026
Document Type
Thesis
Degree Name
Doctor of Philosophy (PhD)
Thesis Advisor
Junyue Cao
Abstract
Over the past two decades, transcriptomic technologies have transformed our understanding of cellular diversity and tissue organization. Early bulk and microarray-based studies provided the first molecular signatures of aging and disease but averaged signals across millions of heterogeneous cells, masking the spatial and cellular origins of transcriptional change. The advent of single-cell RNA sequencing (scRNA-seq) resolved this heterogeneity, uncovering distinct cellular states and aging-associated transcriptional programs; however, tissue dissociation inherently erases spatial context—an essential determinant of cell identity and function. To overcome this limitation, spatial transcriptomics technologies were developed to map gene expression directly within intact tissues. While imaging-based methods such as MERFISH, seqFISH, and STARmap achieve molecular precision, they remain costly and low-throughput, whereas sequencing-based approaches such as Slide-seq, DBiT-seq, and Stereo-seq improve scalability but require complex fabrication and imaging steps. Building upon the conceptual framework of molecular connectomics—which uses DNA as a molecular “glue” to encode spatial proximity—I developed IRISeq (Indexed Receiver–Sender sequencing), an optics-free, sequencing-based platform for high-throughput spatial transcriptomics. IRISeq reconstructs tissue architecture by reading out barcode–barcode interactions that record local molecular adjacency, enabling scalable spatial mapping without imaging. The method achieves tunable resolution (5–50 μm) and is readily extendable to centimeter-scale tissue coverage, making it suitable for multi-organ analysis. Using IRISeq, I generated a comprehensive spatial atlas of aging across more than seventy coronal sections from adult and aged mouse brains, encompassing wild-type and lymphocyte-deficient models (Rag1 and Prkdc). The dataset includes over 460,000 spatially barcoded transcriptomes integrated with 783,000 single-cell RNA-seq profiles. This analysis revealed region- and cell-type-specific aging signatures, including lymphocyte-dependent activation of interferon and inflammatory pathways, and the preservation of ependymal cell populations and microglial homeostasis upon lymphocyte depletion. These findings highlight a key role for adaptive immunity in modulating neuroinflammatory and aging-associated programs during aging. Overall, IRISeq provides a robust, cost-effective, and scalable framework for spatially resolved transcriptomic profiling. By bridging molecular identity with physical context, it advances the goal of reconstructing tissue architecture entirely through sequencing—offering a new paradigm for multi-organ spatial genomics and a molecular blueprint for understanding how cellular interactions shape aging and disease.
License and Reuse Information
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Abdulraouf, Abdulraouf, "Imaging Reconstruction Utilizing Indexed Sequencing for Studying Mammalian Tissue Aging" (2026). Student Theses and Dissertations. 852.
https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/852
Comments
A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy