Elucidating the genetic components of root system architecture for improved water productivity in rice

Abstract

Rice (Oryza sativa L.) is a major staple crop, providing 50–80% of daily calorific intake for over half of the global population and is among the major cereals that is vulnerable to water deficit conditions. Enhancing drought resilience in rice requires a comprehensive understanding of root system architecture (RSA), which plays a pivotal role in water and nutrient uptake. Improvement of RSA is a promising strategy to improve water productivity in rice. The present study was aimed at elucidating the donors, component traits and genetic components of root system architecture for realizing improved water productivity in rice. The experiments were conducted at the Department of Plant Physiology, College of Agriculture, Vellanikkara. The genotype screening experiments were conducted at three levels in Completely Randomized Design (CRD) with two treatments (control and stress) and three replications. The first two were conducted in hydroponics and the third in root structure facility. In the first screening, fifty rice genotypes were used. The rice seedlings were exposed to two treatments, Yoshida solution (unstressed media) and Yoshida solution containing PEG6000 10% (osmotic stress), for 21 days. Subsequently, images were recorded and used for analysis of depth of rooting, total root length, total root surface area, total root volume and mean root diameter. In addition, various biochemical observations such as chlorophyll a, chlorophyll b, total chlorophyll and total carotenoid contents, lipid peroxidation and biomass of both root and shoot were recorded. The second level of screening was conducted from the shortlisted set of 12 good performing and 12 poor performing genotypes based on the results of root parameters obtained from the first level screening. Finally, for molecular analysis, one representative tolerant and susceptible genotype under water deficit condition was selected. The observations on depth of rooting showed that under control conditions, the values ranged from 6.3 cm in Jeerakasala to 21.8 cm in Sahbhagi Dhan. Under stress conditions, the depth varied from 10.8 cm in Gandhakasala to 21.5 cm in Shakti. In case of total root length, under control conditions, the root length was highest in Okkan Puncha (83.0 cm), while it was only 17.5 cm in Gandhakasala. Under stress conditions, the length was superior in Mullann Channa (161.8 cm), while 42.2 cm in Jeerakasala. When total root surface area was analysed, it was 17.8 cm² in Keeripallan and 3.5 cm² in Kumkumasali. Under stress, it varied from 34.6 cm² in Veliyan to 2.2 cm² in Mundakutty, the lowest. Under control conditions, the total root volume ranged from 0.47 cm³ in Keeripallan to 0.05 cm³ in Kumkumasali, while under stress conditions, it varied from 0.87 cm³ in Veliyan to 0.1 cm³ in Jeerakasala. Under stress condition, the mean root diameter increased in genotypes compared to control condition. Under control condition, it ranged from 0.8 mm in Mallikuruva to 0.5 mm in Thowan. Under stress conditions, it ranged from 0.9 mm in Kumkumasali to 0.5 mm in Kattamodan. Based on the above screening result, a subset of 24 genotypes was characterized as 12 tolerant and 12 susceptible, used for the second level hydroponics screening and results were reaffirmed. The experiment at third level was conducted in units named root structures with dimensions 16 feet x 6 feet x 3.5 feet (length x width x height). When the plant reached the active tillering stage, cycles of drought and recovery were given as one treatment, and the other was irrigated every two days. At booting stage, the plant was uprooted, and imaging was done for whole plant. Observations on Canopy Temperature Depression, Membrane Stability Index, depth of rooting, total root volume, total root length and biomass were recorded. The poor performing set exhibited a significantly lower response over superior genotypes. Based on the results obtained from the above three experiments, two representative contrasting genotypes with respect to drought tolerance namely Shakti (tolerant) and Champavu (susceptible) were selected. The genotypes were used for allele mining experiments. Based on in silico expression analysis, MULTIPASS 3 (MPS3) was identified as a promising candidate. Subsequently, the promoter of the root-specific stress-inducible gene MPS3 was targeted from both the genotypes for allele mining. Using gene specific primers, ~2000 bp promoter region was amplified by PCR from the contrasting genotypes and cloned in pCAMBIA1303 vector. The purified recombinant plasmids were sent for sequencing, that was carried forward for allele mining by sequence comparison. Allele mining of promoter sequences using Clustal Omega and PlantPAN tools uncovered variations in regulatory regions, offering insights into potential differences in gene expression patterns that may impact key physiological traits and stress responses. The present investigation thus offered a set of elite donors for RSA and water productivity in rice. Additionally, the genes identified from the present study can be used as targets for genetic improvement of high yielding rice cultivars.