Mitonuclear interactions have been proposed as evolutionary drivers of sexual reproduction, sexual selection, adaptation, and speciation. We investigated the role of pre-mating isolation in maintaining functional mitonuclear interactions in a wild population with divergent sets of proposed co-adapted mitonuclear genotypes. Two lineages have been identified in the eastern yellow robin Eopsaltria australis - putatively climate-adapted to ‘inland’ and ‘coastal’ climates. The lineages differ by ~7% of mitochondrial DNA positions, whereas nuclear genome differences are concentrated into a sex-linked region enriched with mitochondrial genes. This pattern can be explained by female-linked selection accompanied by male-mediated gene flow across the narrow hybrid zone in which the two lineages coexist. It remains unknown whether lineage divergence is driven by intrinsic incompatibilities (particularly in females, under Haldane’s rule), extrinsic incompatibilities, or both. We tested whether non-random mating with respect to partners’ mitolineages or Z-linked variation could facilitate lineage divergence. We used field data, Z-linked and mitolineage genetic markers from two locations where the lineages hybridize, to test whether females choose to mate with (1) males of their own mitolineage and/or bearing similar Z-linked variation, as might be expected if hybrids experience intrinsic incompatibilities, or (2) putatively locally-adapted males, as expected under environmental selection. Comparisons of field observations and simulations present no evidence of non-random mating: the observed reduced female gene flow likely operates via post-mating isolation. Future studies testing for female-biased mortality at different life stages and female habitat selection should clarify the mechanisms of selection.

Identifying sex-linked markers in genomic datasets is important, because their analyses can reveal sex-specific biology, and their presence in supposedly neutral autosomal datasets can result in incorrect estimates of genetic diversity, population structure and parentage. But detecting sex-linked loci can be challenging, and available scripts neglect some categories of sex-linked variation. Here, we present new R functions to (1) identify and separate sex-linked loci in ZW and XY sex determination systems and (2) infer the genetic sex of individuals based on these loci. Two additional functions are presented, to (3) remove loci with artefactually high heterozygosity, and (4) produce input files for parentage analysis. We test these functions on genomic data for two sexually-monomorphic bird species, including one with a neo-sex chromosome system, by comparing biological inferences made before and after removing sex-linked loci using our function. We found that standard filters, such as low read depth and call rate, failed to remove up to 28.7% of sex-linked loci. This led to (i) overestimation of population FIS by ≤ 9%, and the number of private alleles by ≤ 8%; (ii) wrongly inferring significant sex-differences in heterozygosity, (iii) obscuring genetic population structure, and (iv) inferring ~11% fewer correct parentages. We discuss how failure to remove sex-linked markers can lead to incorrect biological inferences (e.g., sex-biased dispersal and cryptic population structure) and misleading management recommendations. For reduced-representation datasets with at least 15 known-sex individuals of each sex, our functions offer convenient, easy-to-use resources to avoid this, and to sex the remaining individuals.