bioRxivGeneticsPreprint
T2T Pangenome Reveals a 3.3kb Structural Variation Driving the De Novo Evolution of a Subspecies-Specific NLR Gene in Rice
Abstract
BackgroundThe genomic region spanning 1.1-1.3 Mb on rice chromosome 6 is a recognized structural variation (SV) hotspot linked to Rice Black-Streaked Dwarf Virus (RBSDV) resistance. However, the precise molecular mechanism has remained elusive due to the inherent "reference bias" of the japonica-based genome, which lacks the critical causative sequences. MethodsLeveraging a neuro-symbolic-driven analysis of gap-free Telomere-to-Telomere (T2T) pangenome datasets and the LGEMP engine, we conducted a high-resolution comparative study between indica (9311) and japonica (Nippon bare). This approach allowed us to treat genomic variations as 3D structural building blocks rather than linear strings. ResultsWe identified a 3.3 kb large-scale insertion uniquely present at the 1.21 Mb locus in 9311. This SV, likely mediated by transposable elements, exhibits extreme sequence divergence (24% identity). We demonstrate that this insertion acts as a topological modifier, driving a dramatic functional shift: while the japonica allele encodes a basic DUF590 transporter, the indica allele has undergone de novo evolution into a complete CC-NBS-LRR (NLR) immune receptor. Transcriptomic profiling confirmed the generation of six novel isoforms (T01-T06) enabled by the SVs structural re-organization. Validation across 16 representative T2T assemblies confirms this 3.3 kb SV as an indica-specific "evolutionary patch," effectively filling the "missing heritability" gap in rice viral immunity. ConclusionOur findings uncover a novel mechanism of gene birth through structural re-organization at high-diversity hotspots. By integrating T2T pangenomics with AI-driven inference, this study provides a definitive molecular marker for the precision breeding of virus-resistant crops and redefines our understanding of subspecies-specific adaptation..
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- approach: experimental assay
- Citations
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