A reproducible compartment-aware k-mer set-algebra and MAW workflow for plant genomes maps contrasting nuclear-organelle sharing landscapes in Arabidopsis and rice

Plant cells contain three genetically distinct DNA compartments—nuclear, chloroplast, and mitochondrial—and biologically meaningful sequence sharing among them is expected because organellar DNA can move into the nucleus and, in some cases, between organelles. This complicates alignment-free k -mer analysis, the interpretation of compartment-specific sequence vocabularies, and the evaluation of missing-sequence signals such as minimal absent words (MAWs). A reproducible workflow that treats these compartments explicitly is therefore useful both for plant genome analysis and for read-backed quality control. A fully scripted workflow was applied to a telomere-to-telomere-scale Arabidopsis thaliana nuclear reference (Col-CEN v1.2) and a chromosome-level Oryza sativa ssp. japonica reference (GCF_034140825.1), together with chloroplast, mitochondrial, and raw-read datasets. Distinct canonical k-mer types were counted for k = 11–31 and decomposed into mutually exclusive set-algebra categories. The same framework was then used for read-backed validation and for MAW/nullomer testing under Markov models with false-discovery-rate (FDR) control. The two plant species showed markedly different sharing landscapes. In Arabidopsis, chloroplast k-mers became largely compartment-specific by k = 31 (85.6% of the chloroplast set), whereas mitochondrial k-mers remained dominated by nuclear overlap (93.4% of the mitochondrial set at k = 31). In rice, chloroplast k-mers remained strongly shared with the nuclear genome across the entire range (88.6% of the chloroplast set at k = 31), whereas mitochondrial–nuclear sharing remained high but lower than that in Arabidopsis (77.5% at k = 31). Raw-read validation showed that assembly-derived k-mers were almost completely supported by reads in both species (> 99.7% at k = 31 and KMC3 -ci = 1), whereas the read-only fraction collapsed sharply as the minimum-occurrence threshold (-ci) increased from 1 to 10. Because one raw-read dataset was analyzed per species, these contrasts are best interpreted as species-specific workflow case studies rather than as a direct sequencing-platform benchmark. MAW lists derived from chloroplast, mitochondrial, nuclear, and raw-read datasets contained many candidates, but all FDR-adjusted runs returned zero significant nullomers, consistent with the corresponding sequence-based null models rather than with biologically exceptional absence. This workflow provides a reproducible framework for quantifying compartment-specific and shared plant sequence vocabularies, validating those vocabularies against raw reads, and testing absent-word candidates under explicit null models. The two-species application shows that chloroplast and mitochondrial compartments need not behave similarly and that raw-read-only vocabularies are highly sensitive to low-support k -mers. Together, these analyses provide a robust starting framework for plant compartment-aware k -mer interpretation, while locus-level explanations for shared or absent words remain a downstream task for follow-up analyses.