Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.10.23.756838

Influenza A virus H5Nx genotypes assigned by genetic similarity are incongruent with global phylogenies

Abstract

Influenza A virus H5N1 and other H5 subtypes (H5Nx) have broad host ranges and pose a pandemic risk. Since early 2022, H5 clade 2.3.4.4b has predominated globally, causing unprecedented mortality in wild birds, poultry, and mammals, with spillovers to humans. Accurate viral classification is essential for tracking H5Nx variant emergence and spread, but reassortment among genome segments with distinct evolutionary histories complicates genotyping. H5Nx genotype assignment tools, GenoFlu in North America and Genin2 in Europe, assign segments to clusters by genetic similarity to reference sequences and define genotypes as constellations of segment clusters. However, genetic similarity does not necessarily imply recent shared ancestry because mutations may occur multiple times across the tree and branches may exhibit variable evolutionary rates. Furthermore, similarity is defined relative to references that may inadequately represent diversity. We evaluated the congruence of genetic similarity-based H5Nx clusters and genotypes with phylogenies of global sequences across eight segments. Publicly available H5Nx nucleotide sequences from 41,366 samples were assigned genotypes using GenoFlu and Genin2, and maximum likelihood phylogenies were inferred for each segment. Phylogenetic clusters were identified using TreeCluster for a range of patristic distance thresholds and CD-HIT clusters were identified for a range of genetic similarity thresholds. Clustering methods were evaluated based on phylogenetic purity, monophyly, and diversity. Reassortment within predominant GenoFlu and Genin2 genotypes was evaluated based on their phylogenetic cluster spans. Expectedly, GenoFlu was largely unable to assign genomes from outside of North America, South America, and Antarctica from 2022 to 2025, whereas Genin2 assignments struggled outside of Europe, Africa, and Western Asia. Only 14.2% of GenoFlu clusters were monophyletic, while Genin2 clusters were more variable across segments (overall 49.3% monophyletic). Despite CD-HIT yielding genetic distance clusters of similar size to TreeCluster, they were less monophyletic (44%) and encompassed greater phylogenetic diversity. We identified several genotypes, such as GenoFlu B3.13, D1.1, and D1.3, with internal segments that had diversified into contiguous clusters. Similarly, the wide phylogenetic span of GenoFlu genotypes B3.5 and A3, and Genin2 genotypes EA-2020-C, EA-2021-AB, and EA-2022-CH suggest they may erroneously combine multiple reassortants. Genetic similarity-based H5Nx genotyping tools are rapid, stable, and sufficient for broad categorization, but may group viruses with distinct evolutionary histories and fail to assign divergent viruses, risking biased surveillance, modeling, and risk assessment.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

McLaughlin, A., Tran, H., Tait, D., Nguyen, H.-H., Rudar, J., Giacinti, J. A., Signore, A. V., Lung, O. A., Berhane, Y., Poljak, Z., Maguire, F.. 2026-10-26. Influenza A virus H5Nx genotypes assigned by genetic similarity are incongruent with global phylogenies. https://doi.org/10.64898/2026.10.23.756838

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Carrier-Limited Release Risk in Electrospun Nanofibers for Regenerative Endodontics: Constraint Discovery from 25 Formulations

Regenerative endodontics needs an intracanal carrier that keeps disinfecting across a dressing interval that clinicians schedule at one to four weeks, without harming the stem cells that rebuild the pulp. We ask what one completed 25-formulation electrospinning campaign of poly(vinylpyrrolidone) (PVP) fibers carrying metronidazole, ciprofloxacin, minocycline and Ca(OH)2 can decide, and use machine learning for constraint discovery and decision support rather than as a new predictor. After an audit against the source thesis, logistic regression predicts fine-fiber formation at 96% leave-one-out accuracy, but a one-threshold rule does as well, the gain over the 80% majority baseline is not significant (exact McNemar p = 0.125), and accuracy falls to 84% when mixture loading is encoded per component. Diameter models interpolate within formulation families (ridge MAE 193 nm, 95% CI 96 to 317 nm) and fail across them (R^2 < 0). Because the campaign never measured release, we assemble a same-drug, cross-carrier evidence table: 17 bounded metronidazole and ciprofloxacin observations from seven studies, with two-sided censoring. Water-soluble carriers (PVP, PVA) completed release within 80 h (PVP within 8 h); no water-insoluble monolithic carrier reached 90% within its observation window, releasing 1.5 to 50%; both within-study comparisons separate at matched loading; and blend, core-shell and thick-mat architectures released over 3 to 28 days. The PVP mats therefore carry a carrier-limited release risk, not a proven ceiling, and one dissolution experiment can confirm or overturn it. A censoring-aware screen keeps three necessarily and one possibly nondominated formulation, and fixed-budget replays show that uncertainty sampling finds failed formulations sooner, except the one it is confidently wrong about.

bioinformatics↗

CellMethMarker provides an integrated database of human cell- and tissue-type-specific DNA methylation markers

Cell- and tissue-type-specific DNA methylation markers provide epigenetic signatures of cellular identity and are widely used to infer cellular origin from bulk and single-cell methylomes. Existing resources mainly emphasize disease-associated biomarkers, methylome atlases, genomic annotations or RNA-based cell markers, leaving an unmet need for an integrated region-level resource dedicated to such markers. Here we present CellMethMarker (http://gu-zhanglab.hfcas.ac.cn/CellMethMarker), a curated database integrating 347,514 de novo markers derived from uniformly processed whole-genome and reduced-representation bisulfite sequencing datasets, 2,203,507 literature-derived marker records and harmonized metadata for 2,810 samples. CellMethMarker enables cell- and tissue-centered marker retrieval, coordinate-based search, genome-browser visualization, interactive methylation analysis and data download. In an independent single-cell methylome atlas, these markers recover the expected cell-type-associated methylation patterns, and a platform-matched reference built from them lowers the mean deconvolution error from 0.365 to 0.144. CellMethMarker therefore links region-level DNA methylation variation to cellular identity and supports methylome-based cell-type annotation and deconvolution.

bioinformatics↗

IG-28 enables identification and quantification of high-confidence isoforms from large bulk and single-cell full-length cDNA datasets

The technology to sequence full-length transcriptomes from bulk and single-cell samples has rapidly advanced. As a result, full-length cDNA datasets now reach billions of reads in size which is beyond the capability of most established isoform identification tools. Here, we introduce IG-28 which addresses this challenge with its capability to process and analyze large fl-cDNA datasets fast and using minimal computational resources. In contrast to its predecessor Mandalorion, IG-28 is not limited to bulk fl-cDNA but is capable of parsing, processing, and analyzing single-cell fl-cDNA datasets. It does so in a lightweight, flexible manner, integrating seamlessly with established scRNA-seq analysis workflows. We benchmarked IG-28 against a variety of established and new isoform identification tools using several bulk and a complex single-cell fl-cDNA dataset and found that IG-28 consistently outperformed the other tools by identifying high-confidence public isoforms.

bioinformatics↗