# Sequence Determinants of G-Quadruplex Thermostability: Aligning Evidence from High-Precision Biophysics and High-Throughput Genomics

## TL;DR

This paper reviews how DNA sequences affect the stability of G-quadruplex structures, combining biophysical and genomic data to better understand their role in biology.

## Contribution

The paper integrates biophysical and genomic evidence to establish a unified framework for predicting G-quadruplex stability from sequence.

## Key findings

- G-quadruplex stability is influenced by the length and integrity of the G-tract core.
- Loop length inversely correlates with stability, though composition and context matter.
- Flanking sequences modulate stability and can influence G-quadruplex topology.

## Abstract

G-quadruplexes (G4s) are non-canonical nucleic acid structures that function as key regulatory elements in crucial cellular processes. Their biological functions are intrinsically linked to thermostability, which is governed by specific sequence features. This review systematically synthesizes evidence from high-precision biophysical studies and high-throughput genomic assays to delineate the sequence determinants of G4 thermostability. Analyses align the trends derived from both methodological paradigms and establish that stability emerges from a complex interplay among three structural elements: the G-tract core, whose length and integrity generally govern stability despite notable exceptions such as the anomalous stability of short G-tracts with 1-nt loops and the stabilization induced by large, structured bulges; the loops, which exhibit a consistent inverse relationship between length and stability across methods, though with context-dependent compositional effects and methodological disparities; and the flanking sequences, whose composition modulates stability and can bias topological outcomes. By integrating findings across scales, this work provides a unified conceptual framework connecting biophysical measurements with genomic observations—a critical step toward computationally predicting G4 stability, topology, and function directly from sequence, thereby advancing the understanding of their roles in health and disease.