Spectral Analysis of Graph Collapse in Hematopoietic Gene Networks

Seungik Cho

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Keywords: gene regulatory networks, spectral graph theory, GATA1 knockout, hematopoiesis, Laplacian eigenvalues, single cell analysis, lineage stability

Abstract:

Gene regulatory networks (GRNs) orchestrate cell
fate decisions, yet conventional transcriptomic analyses often
overlook subtle but critical structural disruptions in bioinformatics.
We present a spectral framework that reveals local GRN
collapse after GATA1 knockout, a key transcription factor in
erythroid and eosinophil differentiation. Using Laplacian-based
spectral descriptors, we detect a marked collapse in a granulocyte
subpopulation, despite minimal global transcriptomic change.
This collapse is characterized by low-frequency eigenvalue accumulation,
reduced connectivity, and high localized instability.
Our findings suggest that GATA1 maintains hidden regulatory
attractors in hematopoietic GRNs, and their loss causes lineagespecific
structural failure. This is the first application of graph
spectral theory to capture cell-type–specific GRN fragility in
single-cell perturbation data, offering a theoretical framework
for evaluating transcription factor function and cell identity
resilience.

Track: 6. Theoretical Biomedical Informatics

Registration Id: 9FNBQ5SCZN6

Submission Number: 125