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Spatial inheritance patterns across maize ears are associated with alleles that reduce pollen fitness.

The Plant journal : for cell and molecular biology · 1 Mar 2026 · 10.1111/tpj.70760

Abstract

Often, more pollen grains land on recipient flowers than there are ovules to fertilize. Consequently, the haploid male gametophyte engages in post-pollination competition, one way that pollen genotype can influence inheritance. The maize (Zea mays subsp. mays L.) inflorescence (ear), with its elongated stigma and style structures (silks), has a conspicuous spatial heterogeneity, with longer silks at the base of the ear than at the apex. To evaluate the hypothesis that alleles with reduced pollen fitness influence the spatial distribution of progeny genotypes along the ear, we developed an updated phenotyping platform that maps fluorescently marked mutant (Ds-GFP) kernel phenotypes on the ear via an implementation of the Faster R-CNN machine vision model (EarVision.v2) and a statistical pipeline that evaluates the relationship between kernel position and transmission ratio (EarScape). Our dataset (1384 ears) represents 58 Ds-GFP insertion alleles. None of the 48 alleles with Mendelian inheritance showed any significant spatial trend. In contrast, 50% of alleles with a pollen-specific transmission defect (5/10) exhibited significant spatial effects. An insertional mutant of the gene encoding a putative actin-binding protein, base-to-apex gradient1* (bag1*), is associated with decreased mutant transmission at the ear base relative to the apex. Surprisingly, a mutant allele of another pollen-expressed gene (Zm00001eb236740) generates the opposite trend, decreased mutant transmission toward the ear apex; and two mutant alleles of the sperm cell attachment factor gamete expressed2 (gex2) can produce ears with transmission highest at both base and apex. We conclude that pollen fitness mutants cause unexpectedly diverse spatial patterns of progeny genotypes.

Plant phenotyping relevance

トウモロコシ穂上のカーネル表現型を画像認識でマッピングする更新版フェノタイピング基盤と統計解析パイプラインが中心的に開発・適用されているため。

abstractwe developed an updated phenotyping platform that maps fluorescently marked mutant (Ds-GFP) kernel phenotypes on the ear via an implementation of the Faster R-CNN machine vision model (EarVision.v2) and a statistical pipeline that evaluates the relationship between kernel position and transmission ratio (EarScape).

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