Positional identification of a candidate gene for MALE STERILITY 2 ( MS2 ) by linkage mapping and transcriptomic data in Cryptomeria japonica D. Don
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Background
Japanese cedar ( Cryptomeria japonica D. Don) is a major plantation species in Japan, but its abundant pollen production is a primary cause of seasonal allergic rhinitis (pollinosis). To mitigate this public health issue, the use of male-sterile cultivars has been promoted. Five types of recessive male-sterile mutations ( ms1 – ms5 ) have been identified, and the causal genes and mutations for MS1 and MS4 have been elucidated. However, the gene responsible for MS2-type male sterility remains unknown.
Results
We aimed to identify the candidate gene responsible for MS2-type male sterility using a map-based cloning strategy. High-resolution linkage mapping localized the MS2 locus to a 1.56 cM interval on linkage group 5, corresponding to an 8.64 Mb region of the reference genome. Ninety-one genes in this region were subjected to functional annotation, gene expression analysis, and mutation screening. Among these, a single gene, SUGI_0493010 , encoding a GDSL-type esterase/lipase protein (GELP), fulfilled all three criteria: it showed homology to pollen development genes in Arabidopsis thaliana , was specifically expressed in male strobili, and carried a deleterious amino acid substitution (S40F) within the predicted catalytic domain in ms2 mutant. The same mutation was also detected in a heterozygous individual ( Ms2/ms2 ) from a separate breeding population, whose genotype was confirmed through progeny testing. Structural annotation revealed that the affected serine residue lies within the conserved GDSL motif, suggesting a functional disruption of enzymatic activity.
Conclusions
Our results strongly suggest that SUGI_0493010 ( GELP ) is the causal gene for MS2-type male sterility in C. japonica . This finding enhances our understanding of male sterility mechanisms in conifers and provides a valuable genetic resource for breeding pollen-free trees. The study also demonstrates the effectiveness of combining genetic mapping with transcriptomic and mutational data in forest tree genomics.
