New Insights in Flowering Pathway Through Mqtl, Transcriptome Profiling and Crispr Approaches in Rice

Background and aim: rice is a major model crop for plant genetic studies. heading date (hd) is a critical plant trait that effectively contributes to the final yield and environmental adaptation. meta quantitative trait loci (mqtl) analysis discovers the most stable qtls and effectively narrows down the confidence interval for identification of candidate genes (cg). therefore, a comprehensive mqtl analysis was conducted to identify the most reliable genomic regions related to hd in rice. the most promising cgs were evaluate by creating novel mutants using crispr approach and analyzing classical mutants. the genes mechanisms were further evaluated using comparative whole transcriptome analysis on contrasting genotypes and conditions.methods: the mqtl analysis was conducted on 243 qtls for hd in 122 rice populations reported in the last two decades. consequently, the two most promising genes related to hd were selected for further analysis. the heading date 1 (hd1) was subjected to a comparative whole transcriptome analysis using wild-type plants and the hd1-1 isogenic mutant background under both long day and short day conditions. moreover, a site-directed mutagenesis of heading date repressor 1 (hdr1) in the hd1-1 mutant was performed using crispr/cas9 to further study the function and interaction of these genes during rice flowering time.results: the mqtl analysis confined 243 hd qtls into 23 mqtls with a narrowed ci. novel cgs were detected in different mqtls interval. the results of transcriptome analysis on hd1 mutants on different day length conditions indicated several genes involved in the circadian rhythm and response to abiotic stresses. we also detected some tf families such as mads-box, bzip and dof regulated by hd1 during flowering time. the crispr approach successfully created several double mutants (hd1-1/hdr1) and their effects on flowering time were evaluated under control conditions.conclusion: the results of this study provided useful information on the most promising genomic loci controlling yield and yield-related traits in rice that can be used in breeding programs. moreover, the whole transcriptome analysis and created novel mutants enhanced our knowledge on the gene regulatory networks related to flowering time.