Two forward genetic screens for vein density mutants in sorghum converge on a cytochrome P450 gene in the brassinosteroid pathway.

The specification of vascular patterning in plants has interested plant biologists for many years. In the last decade a new context has emerged for this interest. Specifically, recent proposals to engineer C(4) traits into C(3) plants such as rice require an understanding of how the distinctive venation pattern in the leaves of C(4) plants is determined. High vein density with Kranz anatomy, whereby photosynthetic cells are arranged in encircling layers around vascular bundles, is one of the major traits that differentiate C(4) species from C(3) species. To identify genetic factors that specify C(4) leaf anatomy, we generated ethyl methanesulfonate- and γ-ray-mutagenized populations of the C(4) species sorghum (Sorghum bicolor), and screened for lines with reduced vein density. Two mutations were identified that conferred low vein density. Both mutations segregated in backcrossed F(2) populations as homozygous recessive alleles. Bulk segregant analysis using next-generation sequencing revealed that, in both cases, the mutant phenotype was associated with mutations in the CYP90D2 gene, which encodes an enzyme in the brassinosteroid biosynthesis pathway. Lack of complementation in allelism tests confirmed this result. These data indicate that the brassinosteroid pathway promotes high vein density in the sorghum leaf, and suggest that differences between C(4) and C(3) leaf anatomy may arise in part through differential activity of this pathway in the two leaf types.

Evaluating the Performance of Rice Genotypes for Improving Yield and Adaptability Under Direct Seeded Aerobic Cultivation Conditions.

With the changing climatic conditions and reducing labor-water availability, the potential contribution of aerobic rice varieties and cultivation system to develop a sustainable rice based agri-food system has never been more important than today. Keeping in mind the goal of identifying high-yielding aerobic rice varieties for wider adaptation, a set of aerobic rice breeding lines were developed and evaluated for grain yield, plant height, and days to 50% flowering in 23 experiments conducted across different location in Philippines, India, Bangladesh, Nepal, and Lao-PDR between 2014 and 2017 in both wet and dry seasons. The heritability for grain yield ranged from 0.52 to 0.90. The season-wise two-stage analysis indicated significant genotype x location interaction for yield under aerobic conditions in both wet and dry seasons. The genotype × season × location interaction for yield was non-significant in both seasons indicating that across seasons the genotypes at each location did not show variability in the grain yield performance. Mean grain yield of the studied genotypes across different locations/seasons ranged from 2,085 to 6,433 Kg ha-1. The best-fit model for yield stability with low AIC value (542.6) was AMMI(1) model. The identified stable genotypes; IR 92521-143-2-2-1, IR 97048-10-1-1-3, IR 91326-7-13-1-1, IR 91326-20-2-1-4, and IR 91328-43-6-2-1 may serve as novel breeding material for varietal development under aerobic system of rice cultivation. High yield and stable performance of promising breeding lines may be due to presence of the earlier identified QTLs including grain yield under drought, grain yield under aerobic conditions, nutrient uptake, anaerobic germination, adaptability under direct seeded conditions, and tolerance to biotic stress resistance such as qDTY 2.1 , qDTY 3.1 , qDTY 12.1 , qNR 5.1 , AG 9.1 , qEVV 9.1 , qRHD 1.1 , qRHD 5.1, qRHD 8.1 qEMM 1.1 , qGY 6.1 , BPH3, BPH17, GM4, xa4, Xa21, Pita, and Pita2. The frequency of xa4 gene was highest followed by qAG 9.1, GM4, qDTY 3.1 , qDTY 2.1 , qGY 6.1, and qDTY 12.1.

Root Traits Enhancing Rice Grain Yield under Alternate Wetting and Drying Condition.

Reducing water requirements and lowering environmental footprints require attention to minimize risks to food security. The present study was conducted with the aim to identify appropriate root traits enhancing rice grain yield under alternate wetting and drying conditions (AWD) and identify stable, high-yielding genotypes better suited to the AWD across variable ecosystems. Advanced breeding lines, popular rice varieties and drought-tolerant lines were evaluated in a series of 23 experiments conducted in the Philippines, India, Bangladesh, Nepal and Cambodia in 2015 and 2016. A large variation in grain yield under AWD conditions enabled the selection of high-yielding and stable genotypes across locations, seasons and years. Water savings of 5.7-23.4% were achieved without significant yield penalty across different ecosystems. The mean grain yield of genotypes across locations ranged from 3.5 to 5.6 t/ha and the mean environment grain yields ranged from 3.7 (Cambodia) to 6.6 (India) t/ha. The best-fitting Finlay-Wilkinson regression model identified eight stable genotypes with mean grain yield of more than 5.0 t/ha across locations. Multidimensional preference analysis represented the strong association of root traits (nodal root number, root dry weight at 22 and 30 days after transplanting) with grain yield. The genotype IR14L253 outperformed in terms of root traits and high mean grain yield across seasons and six locations. The 1.0 t/ha yield advantage of IR14L253 over the popular cultivar IR64 under AWD shall encourage farmers to cultivate IR14L253 and also adopt AWD. The results suggest an important role of root architectural traits in term of more number of nodal roots and root dry weight at 10-20 cm depth on 22-30 days after transplanting (DAT) in providing yield stability and preventing yield reduction under AWD compared to continuous flooded conditions. Genotypes possessing increased number of nodal roots provided higher yield over IR64 as well as no yield reduction under AWD compared to flooded irrigation. The identification of appropriate root architecture traits at specific depth and specific growth stage shall help breeding programs develop better rice varieties for AWD conditions.