Extreme weather trends have increased the number of severe flooding events that affect agriculture, including rice production both in the US and internationally. Heavy rainfall can cause young rice plants to be temporarily completely submerged, a stress that can cause plant death or reduce grain yield. Recently, a new submergence tolerance QTL, qSub8.1 was identified from a population derived from Ciherang-Sub1 and IR10F365 that may have a complimentary effect with the known submergence tolerance regulator SUB1A during vegetative stage development. One of our goals is to investigate qSub8.1 mode of action in enhancing submergence tolerance in conjunction with SUB1A. Toward this goal, three rice varieties, Ciherang-Sub1, Ciherang, and IR64-Sub1, were sequenced with 150 bp pair-end whole genome shotgun sequencing (Illumina HiSeq4000). The genome profile showed that qSub8 region is mainly from Ciherang with a few introgressed segments from IR64-Sub1. These findings have been be used to further characterize qSub8.1 along with transcriptomic data which has recently been generated. To evaluate interactions between qSub8.1 and SUB1A we performed RNA-sequencing transcriptome analyses on the shoot basal region of four genotypes that differ in the presence and absence of both loci/QTL. The data indicate qSub8.1 reinforces the quiescence strategy conferred by SUB1A during submergence. The CRISPR/Cas9 system was used to knock out the SUB1A allele in Ciherang-Sub1 and ten SUB1A knockout lines have been generated through Agrobacterium-mediated transformation. Phenotyping of T1-seedlings after being completely submerged for 16 days showed that some of the SUB1A-knockout transformants showed significantly higher shoot elongation and more chlorophyll reduction than Ciherang-Sub1. Homologous mutants of the knock out T1 lines will be selected and T2-harvested seeds will be used for further physiological and molecular study.

Funded by NIFA 2017-67013-26194.

Keywords: Submergence, rice, SUB1, qSub8.1, genome assembly, CRISPR/Cas9, transcriptomics