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

backgroundPlant 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.

resultsA 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.

conclusionsThis 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.