In silico characterization and expression profiling of loci associated with sugar, alkaloid, and starch accumulation in Nicotiana tabacum

Translating QTL and GWAS signals into functionally validated gene targets remains a critical bottleneck in crop improvement, particularly in complex polyploid genomes such as Nicotiana tabacum (∼4.3 Gb, 2n = 48). To address this, we systematically characterised 15 candidate genes nominated for tobacco leaf chemistry traits, including nicotine, nornicotine, total sugar, reducing sugar, fructose, and sugar–alkali ratio. The candidate proteins, spanning 210–881 amino acids across seven subcellular compartments, exhibited functionally interpretable domain architectures, including bHLH-MYC, SnRK2 kinase, UDP-glycosyltransferase GT1, ALMT, and RING finger domains, in 10 of 15 proteins, establishing mechanistic hypotheses aligned with associated traits. Structural integrity was further supported by AlphaFold3 modelling, confirming high-confidence folds with binding pockets co-localised within conserved functional domains. At the regulatory level, promoter analysis revealed a universal TGACG-motif and ABRE elements across all candidates, while the auxin-responsive AuxRR-core was exclusive to the alkaloid-associated gene Nt16g00236 , suggesting trait-specific transcriptional control. Haplotype analysis reinforced this specificity, identifying significant allelic associations in eight candidate genes, including five genes on chromosome 8 and three genes on chromosome 16. Directional antagonism was observed at the chromosome 8 loci, where nicotine- and nornicotine-elevating haplotypes coincided with reduced sugar–alkali ratio, indicative of pleiotropic carbon–nitrogen partitioning. Complementing these findings, tissue-specific and stress-responsive expression profiling revealed shoot- and root-preferential patterns consistent with trait biology, temporally distinct drought-induction waves, and a cold-induced root-to-shoot expression switch in Nt22g03479 , all corroborated by qRT-PCR validation. Collectively, these findings establish a multi-evidence functional framework for candidate gene prioritisation, advancing marker-assisted breeding and targeted experimental validation in tobacco improvement.