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bioRxiv · 10.1101/2024.01.26.577421

Self-incompatibility based functional genomics for rapid phenotypic characterization of seed metabolism genes

Azeez, A.·Bates, P. D.
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Abstract

Reverse-genetic characterization of plant gene function through technologies such as CRISPR/Cas, RNAi, or gene overexpression requires the ability to efficiently transform the plant species of interest. However, efficient transformation systems are not available for most plant species. Physaria fendleri is an oilseed plant valued for its unusual hydroxylated fatty acids (HFA, e.g. lesquerolic acid) that accumulates up to 60% of seed oil and is a non-toxic alternative to castor (Ricinus communis) seeds as a source for HFA for the chemical industry. Domestication and improvement of P. fendleri seed oil requires characterization of genes involved in developing seed metabolism. Tissue culture-based transformation of P. fendleri is laborious, low-efficiency, and time-consuming (T1 [~]18 months). Additionally, P. fendleri is self-incompatible requiring laborious hand pollination for propagation and seed collection from transgenic lines. We developed a rapid virus-induced gene silencing (VIGS) method to characterize genes within developing seeds. Identification of the self-incompatibility mechanisms in P. fendleri allowed the use of self-compatibility as a novel visual selectable marker by co-targeting the gene of interest (GOI) with the self-incompatibility gene S-locus receptor kinase (SRK). Seeds develop without cross-pollination from silenced SRK and each of those seeds contain the GOI silenced, allowing rapid phenotypic characterization of the seeds in the first generation. Through this methodology we confirmed the in vivo function of two key genes (FAH12, FAE1) involved in lesquerolic acid production. Thus, this self-compatibility based functional genomics approach is a rapid methodology for in vivo reverse-genetic gene characterization in self-incompatible plants.

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Azeez, A., Bates, P. D.. 2024-01-30. Self-incompatibility based functional genomics for rapid phenotypic characterization of seed metabolism genes. https://doi.org/10.1101/2024.01.26.577421

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