Sperm subpopulations differing in mitochondrial abundance show divergent nuclear allele frequencies.

Abstract

Mammalian ejaculates contain heterogeneous sperm subpopulations that differ in subcellular architecture and developmental history, despite appearing morphologically uniform. The extent to which this cellular heterogeneity reflects underlying nuclear genomic structure within a sire remains largely unexplored. Mitochondrial architecture in sperm is established during spermatogenesis, with final assembly and organization occurring during spermiogenesis under nuclear genomic control, positioning variation in mitochondrial abundance and organization as a potential phenomic indicator of within-sire allelic segregation. Here, we tested whether sperm subpopulations defined by differing mitochondrial abundance exhibit systematic differences in nuclear allele representation. Boar sperm were resolved into low and high mitochondrial subpopulations using fluorescence-activated cell sorting based on MitoTracker™ Green fluorescence while excluding debris, doublets, and non-viable cells. Epifluorescence microscopy confirmed that high MitoTracker™ Green fluorescence sperm possessed longer mitochondrial sheaths, validating a structural distinction between subpopulations. Whole-genome sequencing of paired mitochondrial subpopulations from three boars was performed, and allelic ratio distortion was evaluated relative to heterozygous baseline populations. Analyses across heterozygous loci genome-wide identified candidate allele frequency shifts between mitochondrial-defined subpopulations, suggesting non-random segregation of alleles within ejaculates. Using a minimum sequencing depth of 30 reads in both sorted fractions, 182 candidate SNPs were identified with evidence of allele-frequency differences between mitochondrial fluorescence-defined subpopulations. These findings suggest that sperm mitochondrial abundance can potentially serve as an indirect, high-throughput marker of nuclear genomic heterogeneity within sires. This proof-of-concept framework establishes a foundation for future studies integrating sperm phenotyping, genome-wide allele-frequency analysis and functional validation to better characterize gamete-level heterogeneity.