Yamakawa, T. | bioRxiv Science

bioRxiv2026

Rice brown spot resistance gene bsr1 also confers resistance to bacterial blight by suppressing sucrose efflux

Brown spot (BS), caused by the fungal pathogen Bipolaris oryzae, is a major disease threatening global rice production. However, the genetic basis of host BS resistance remains unclear. Here, we identified brown spot resistance 1 (bsr1), a quantitative trait locus conferring BS resistance, by map-based cloning. We show that bsr1 encodes a sucrose transporter and that a near-isogenic line carrying bsr1 (bsr1-NIL) in the susceptible Koshihikari genetic background exhibited resistance to BS by suppressing sucrose efflux into the apoplast after pathogen attack. Furthermore, bsr1-NIL also showed strain-specific resistance to bacterial blight caused by Xanthomonas oryzae pv. oryzae through the same mechanism. These findings demonstrate that bsr1 confers dual resistance to fungal and bacterial diseases by regulating sucrose efflux. Our study identifies a previously unrecognized mechanism underlying resistance to both BS and bacterial blight and highlights bsr1 as a promising target for breeding disease-resistance rice cultivars. Rice (Oryza sativa L.) is a staple food for more than half of the worlds population1. Brown spot (BS), caused by the fungus Bipolaris oryzae, is one of the most prevalent fungal diseases of rice, and its incidence has increased under global warming2. BS infects coleoptiles, leaves, leaf sheaths, panicle branches, glumes, and spikelets, and severe infection can substantially reduce grain yield.

plant biology↗

bioRxiv2026

Hidden Structural Bias in Proteomics: Sonication-induced Selective Fragmentation of Intrinsically Disordered Regions

Sonication is a fundamental technique in proteome sample preparation, primarily used for protein solubilization and shearing of genomic DNA. Although the mechanical shearing of DNA is well-characterized, its unintended impact on protein structural integrity remains a significant "blind spot" in high-throughput analytical workflows. In this study, we systematically investigated sonication-induced protein fragmentation by combining gel-based fractionation (PEPPI-MS) with sequence-level compositional analysis and bioinformatic mapping. Our results demonstrate that sonication does not significantly alter overall proteome identification or the recovery of membrane proteins; however, it induces extensive and non-random protein fragmentation. Sonication caused an approximately three-fold increase in the abundance of >45 kDa protein-derived fragments migrating into the <40 kDa fraction, and 1,620 high-molecular-weight (MW) proteins were uniquely detected in the lower-MW fraction upon sonication, an eight-fold increase over non-sonicated controls. Peptide-level amino acid composition analysis revealed subtle but directional shifts in the sonication-derived fragments. This residue-level signature is reinforced by two orthogonal structural analyses (MobiDB peptide-level mapping and protein-level profiling using metapredict V3 software), which show that sonication-susceptible proteins harbor more than twice the disordered content of length-matched controls (median 40% vs. 18%). This study identifies a previously unrecognized "structural bias" whereby intrinsically disordered region (IDR)-rich proteins are selectively compromised during sample preparation. Because these fragments are indistinguishable from enzymatic digestion products in conventional bottom-up proteomics, the underlying structural damage is effectively masked in global quantitative datasets, potentially distorting biological interpretations related to protein size, isoforms, and stability, particularly for IDR-rich classes, such as transcription factors and signaling molecules. We propose that optimizing and standardizing sonication parameters is essential for ensuring the accuracy and reproducibility of quantitative proteomic analyses.

cell biology↗