High expression in maize pollen correlates with genetic contributions to pollen fitness as well as with coordinated transcription from neighboring transposable elements

Abstract

In flowering plants, gene expression in the haploid male gametophyte (pollen) is essential for sperm delivery and double fertilization. Pollen also undergoes dynamic epigenetic regulation of expression from transposable elements (TEs), but how this process interacts with gene expression is not clearly understood. To explore relationships among these processes, we quantified transcript levels in four male reproductive stages of maize (tassel primordia, microspores, mature pollen, and sperm cells) via RNA-seq. We found that, in contrast with vegetative cell-limited TE expression in Arabidopsis pollen, TE transcripts in maize accumulate as early as the microspore stage and are also present in sperm cells. Intriguingly, coordinate expression was observed between highly expressed protein-coding genes and their neighboring TEs, specifically in mature pollen and sperm cells. To investigate a potential relationship between elevated gene transcript level and pollen function, we measured the fitness cost (male-specific transmission defect) of GFP-tagged coding sequence insertion mutations in over 50 genes identified as highly expressed in the pollen vegetative cell, sperm cell, or seedling (as a sporophytic control). Insertions in seedling genes or sperm cell genes (with one exception) exhibited no difference from the expected 1:1 transmission ratio. In contrast, insertions in over 20% of vegetative cell genes were associated with significant reductions in fitness, showing a positive correlation of transcript level with non-Mendelian segregation when mutant. Insertions in maize gamete expressed2 (Zm gex2), the sole sperm cell gene with measured contributions to fitness, also triggered seed defects when crossed as a male, indicating a conserved role in double fertilization, given the similar phenotype previously demonstrated for the Arabidopsis ortholog GEX2.

A cost-effective maize ear phenotyping platform enables rapid categorization and quantification of kernels

“…These data can be used in a variety of ways, such as measuring patterns of kernel distribution, quantifying empty space on the ear, and recording other phenotypes such as abnormal or aborted kernels. For our experimental objectives, the system made it feasible to generate a nearly two-fold larger set of fluorescent kernel transmission data compared to our initial study (Warman et al 2020). Manual quantification of the original dataset took approximately 50 hours.…”

“…With these methods, we were able to detect weak but significant transmission defects (~45% transmission of a markerlinked mutation) for a number of mutant alleles, using both anthocyanin and GFP kernel markers. Manually counted ear scanner image validation is described in detail in a previous study (Warman et al, 2020).…”

“…To increase throughput, we investigated computer vision methods to identify kernel locations and phenotypes from two-dimensional ear projections. We were most interested to establish a pipeline to automate the counting of Ds-GFP vs. wild-type (non-fluorescent) kernels, due to the broadly applicable use of this marker to quantify transmission rates for several thousand available mutations (Li et al, 2013;Warman et al, 2020). First, a traditional computer vision approach was assessed for its feasibility for quantification of images with GFP kernel markers.…”

“…Crosses from the 2019 field season included plants with previously tested mutant alleles to determine whether transmission rates identified in 2018 remained consistent in the following year. Crosses also contained plants with additional alleles that were not included in the published analysis (Warman et al, 2020), either because of insufficient crosses in 2018 (5 alleles) or lack of PCR confirmation of Ds insertion location (7 alleles). In total, approximately 1000 ears from plants containing 60 mutant alleles were quantified using individual computer vision models for 2018 and 2019 field seasons.…”

“…The transmission of mutant genes can be easily tracked in maize kernels by taking advantage of a wide variety of visible endosperm markers (Neuffer et al, 1997;Li et al, 2013), which can be genetically linked to a mutant of interest (e.g. (Arthur et al, 2003;Phillips and Evans, 2011;Bai et al, 2016;Huang et al, 2017;Warman et al, 2020)). On the ear, kernels occur as an ordered array of progeny, which allows the transmission of mutant alleles to be tracked not only by total transmission for each individual cross, but within individual ears.…”