Pattar, V. | bioRxiv Science

bioRxiv2026

Disruption of a CCR5-like immunoglobulin gene is linked to plague susceptibility in black-footed ferrets

Black-footed ferrets (Mustela nigripes) are among the worlds most endangered mammals and remain highly vulnerable to sylvatic plague caused by Yersinia pestis, yet the genetic basis of this susceptibility has remained unknown. Current conservation strategies rely on vaccination of captive-bred animals and large-scale flea control with insecticides, approaches that are costly, labor-intensive, and difficult to implement across the species natural range. Several closely related mustelid species, including the domestic ferret, are substantially more resistant to plague, providing an opportunity to identify naturally evolved immune mechanisms through comparative immunogenomics. Here we identify a conserved class of immunoglobulin lambda variable genes encoding unusually long antigen-binding loops with CCR5-mimicking sequence features that are widespread among Caniformia species. Because CCR5 has been implicated in host interactions with Yersinia species, we hypothesized that antibodies encoded by these germline genes contribute to plague resistance through receptor-like molecular mimicry. Consistent with this hypothesis, we show that these genes are under strong purifying selection in mustelids, are actively expressed in antibody repertoires, and monoclonal antibodies encoded by them reduced intracellular Y. pestis survival in macrophages. In contrast, all analyzed black-footed ferrets carried a frameshifting deletion resulting in loss of gene expression. These findings identify a naturally disrupted germline antibody gene as a candidate determinant of plague susceptibility in black-footed ferrets, demonstrating that variation in germline immunoglobulin genes can influence susceptibility to a lethal infectious disease. Ultimately, these findings lay the groundwork for genetically informed conservation management and the development of new antibody-based anti-plague strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/734856v2_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@19d8ac1org.highwire.dtl.DTLVardef@a37aorg.highwire.dtl.DTLVardef@1ecd1e0org.highwire.dtl.DTLVardef@c6fd67_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Sequence similarity estimation by random subsequence sketching

Sequence similarity estimation is essential for many bioinformatics tasks, including functional annotation, phylogenetic analysis, and overlap graph construction. Alignment-free methods aim to solve large-scale sequence similarity estimation by mapping sequences to more easily comparable features that can approximate edit distances efficiently. Substrings or k-mers, as the dominant choice of features, face an unavoidable compromise between sensitivity and specificity when selecting the proper k-value. Recently, subsequence-based features have shown improved performance, but they are computationally demanding, and determining the ideal subsequence length remains an intricate art. In this work, we introduce SubseqSketch, a novel alignment-free scheme that maps a sequence to an integer vector, where the entries correspond to dynamic, rather than fixed, lengths of random subsequences. The cosine similarity between these vectors exhibits a strong correlation with the edit similarity between the original sequences. Through experiments on benchmark datasets, we demonstrate that Sub-seqSketch is both efficient and effective across various alignment-free tasks, including nearest neighbor search and phylogenetic clustering. A C++ implementation of SubseqSketch is openly available at https://github.com/Shao-Group/SubseqSketch.

bioinformatics↗