Variation and selection at predicted G-quadruplexes across the human pangenome

Jun 23, 2026· SK Mohanty, MG Marin, L Smeds, F Chiaromonte, CD Huber, KD Makova, Human Pangenome Reference Consortium · 0 min read
Abstract
G-quadruplexes (G4s), non-canonical DNA structures whose sequence motifs occupy approximately 1% of the human genome, are important for myriad cellular functions, including regulating transcription and replication. Yet they also contribute to genomic instability by increasing mutations and structural variation. Despite their significance, G4 motifs have not been studied in detail across multiple human genomes. Here, we conducted a comprehensive analysis of presence/absence and sequence variation, measured selection strength, and evaluated gene expression regulation potential for predicted G4s (pG4s) across population groups in the second release of the Human Pangenome Reference Consortium dataset, comprising high-quality, near-telomere-to-telomere diploid genomes from 231 individuals worldwide, along with three reference assemblies. Across the human pangenome, we identified over 353 million pG4s, including 1.15 million pG4s absent from reference assemblies but shared across other haplotypes. Our analysis revealed that pG4 sharing patterns recapitulate human population structure: African individuals displayed lower levels of pG4 sharing than non-Africans, whereas East Asian individuals exhibited higher levels of sharing. By analyzing the site frequency spectrum across various genomic annotations, we computed and compared selection coefficients (Sd) at pG4 vs. non-pG4 sites. As expected, the strongest purifying selection (Sd ≥ 10) was detected at protein-coding exons, where pG4 sites had similar or lower selection coefficients compared with those for pG4 sites. Strikingly, this pattern reversed at regulatory regions: although purifying selection was weaker overall at promoters, introns, enhancers, and replication origins (1 ≤ Sd < 10), pG4 sites at these regions experienced stronger selection than non-pG4 sites—suggesting that pG4s play functional roles outside coding sequences. Additionally, by integrating pG4 data with long-read transcriptome data profiles from this large cohort, we found that pG4s located at promoters and at (or near) exon-intron junctions may influence variation in gene expression levels and transcript isoforms, respectively, across the human pangenome individuals. Leveraging extensive population-scale data, our research illuminates the fundamental importance and functional relevance of G4s across human genomes.
Type
Publication
bioRxiv
publication
Saswat Kumar Mohanty
Authors
Ph.D. Student
Saswat is interested in understanding the evolution of non-B-DNA structures in primates. Currently, he is working mainly on a specific type of non-B-DNA structure called the G-quadruplex or G4, for example, developing bioinformatic tools to analyze genome-wide distribution of these structures.
Linnéa Smeds
Authors
Postdoctoral Scholar
Linnéa’s research in the Makova lab involves investigating selection in non-canonical DNA from primates, especially G4 quadruplexes, using bioinformatics methods. Linnéa worked for 8 years as a bioinformatician in Dr. Hans Ellegren’s lab, developing approaches to study speciation, mutation rate and sex chromosome evolution in birds, before taking on a Ph. D. in evolutionary genetics. Her thesis “Conservation genomics in inbred Scandinavian wolves using bioinformatic methods” involved work on Y chromosome evolution, admixture, genetic load and structural variation.
Francesca Chiaromonte
Authors
Francesca is a statistician developing methods for the analysis of large, high-dimensional and complex data, and applying such methods in contemporary “Omics” sciences and other scientific fields – including Meteorology and Economics.
Kateryna Makova, Ph.D.
Authors
Professor
Kateryna is interested in genomics, evolution, and human genetics. Her lab studies mutations using both computational and experimental approaches. Additional topics of interest include sex chromosome evolution and genomics of childhood obesity.