Combining Protein Content and Grain Yield by Genetic Dissection in Bread Wheat under Low-Input Management

Responses of wheat kernel weight to diverse allelic combinations under projected climate change conditions

Introduction

In wheat, kernel weight (KW) is a key determinant of grain yield (GY). However, it is often overlooked when improving wheat productivity under climate warming. Moreover, little is known about the complex effects of genetic and climatic factors on KW. Here, we explored the responses of wheat KW to diverse allelic combinations under projected climate warming conditions.

Methods

To focus on KW, we selected a subset of 81 out of 209 wheat varieties with similar GY, biomass, and kernel number (KN) and focused on their thousand-kernel weight (TKW). We genotyped them at eight kompetitive allele-specific polymerase chain reaction markers closely associated with TKW. Subsequently, we calibrated and evaluated the process-based model known as Agricultural Production Systems Simulator (APSIM-Wheat) based on a unique dataset including phenotyping, genotyping, climate, soil physicochemistry, and on-farm management information. We then used the calibrated APSIM-Wheat model to estimate TKW under eight allelic combinations (81 wheat varieties), seven sowing dates, and the shared socioeconomic pathways (SSPs) designated SSP2-4.5 and SSP5-8.5, driven by climate projections from five General Circulation Models (GCMs) BCC-CSM2-MR, CanESM5, EC-Earth3-Veg, MIROC-ES2L, and UKESM1-0-LL.

Results

The APSIM-Wheat model reliably simulated wheat TKW with a root mean square error (RMSE) of < 3.076 g TK-1 and R2 of > 0.575 (P < 0.001). The analysis of variance based on the simulation output showed that allelic combination, climate scenario, and sowing date extremely significantly affected TKW (P < 0.001). The impact of the interaction allelic combination × climate scenario on TKW was also significant (P < 0.05). Meanwhile, the variety parameters and their relative importance in the APSIM-Wheat model accorded with the expression of the allelic combinations. Under the projected climate scenarios, the favorable allelic combinations (TaCKX-D1b + Hap-7A-1 + Hap-T + Hap-6A-G + Hap-6B-1 + H1g + A1b for SSP2-4.5 and SSP5-8.5) mitigated the negative effects of climate change on TKW.

Discussion

The present study demonstrated that optimizing favorable allelic combinations can help achieve high wheat TKW. The findings of this study clarify the responses of wheat KW to diverse allelic combinations under projected climate change conditions. Additionally, the present study provides theoretical and practical reference for marker-assisted selection of high TKW in wheat breeding.

Wheat traits and the associated loci conferring radiation use efficiency

Wheat (Triticum aestivum L.) radiation use efficiency (RUE) must be raised through crop breeding to further increase the yield potential, as the harvest index is now close to its theoretical limit. Field experiments including 209 wheat cultivars which have been widely cultivated in China since the 1940s were conducted in two growing seasons (2018-2019 and 2019-2020) to evaluate the variations of phenological, physiological, plant architectural, and yield-related traits and their contributions to RUE and to identify limiting factors for wheat yield potential. The average annual genetic gain in grain yield was 0.60% (or 45.32 kg ha^-1  year^-1 ; R²  = 0.44, P < 0.01), mainly attributed to the gain in RUE (r = 0.85, P < 0.01). The net photosynthetic rates were positively and closely correlated with grain RUE and grain yield, suggesting source as a limiting factor to future yield gains. Thirty-four cultivars were identified, exhibiting not only high RUE, but also traits contributing to high RUE and 11 other critical traits - of known genetic basis - as potential parents for breeding to improve yield and RUE. Our findings reveal wheat traits and the associated loci conferring RUE, which are valuable for facilitating marker-assisted breeding to improve wheat RUE and yield potential.

Genetic Potential and Inheritance Patterns of Physiological, Agronomic and Quality Traits in Bread Wheat under Normal and Water Deficit Conditions

Water scarcity is a major environmental stress that adversatively impacts wheat growth, production, and quality. Furthermore, drought is predicted to be more frequent and severe as a result of climate change, particularly in arid regions. Hence, breeding for drought-tolerant and high-yielding wheat genotypes has become more decisive to sustain its production and ensure global food security with continuing population growth. The present study aimed at evaluating different parental bread wheat genotypes (exotic and local) and their hybrids under normal and drought stress conditions. Gene action controlling physiological, agronomic, and quality traits through half-diallel analysis was applied. The results showed that water-deficit stress substantially decreased chlorophyll content, photosynthetic efficiency (FV/Fm), relative water content, grain yield, and yield attributes. On the other hand, proline content, antioxidant enzyme activities (CAT, POD, and SOD), grain protein content, wet gluten content, and dry gluten content were significantly increased compared to well-watered conditions. The 36 evaluated genotypes were classified based on drought tolerance indices into 5 groups varying from highly drought-tolerant (group A) to highly drought-sensitive genotypes (group E). The parental genotypes P₃ and P₈ were identified as good combiners to increase chlorophyll b, total chlorophyll content, relative water content, grain yield, and yield components under water deficit conditions. Additionally, the cross combinations P₂ × P₄, P₃ × P₅, P₃ × P₈, and P₆ × P₇ were the most promising combinations to increase yield traits and multiple physiological parameters under water deficit conditions. Furthermore, P₁, P₂, and P₅ were recognized as promising parents to improve grain protein content and wet and dry gluten contents under drought stress. In addition, the crosses P₁ × P₄, P₂ × P₃, P₂ × P₅, P₂ × P₆, P₄ × P₇, P₅ × P₇, P₅ × P₈, P₆ × P₈, and P₇ × P₈ were the best combinations to improve grain protein content under water-stressed and non-stressed conditions. Certain physiological traits displayed highly positive associations with grain yield and its contributing traits under drought stress such as chlorophyll a, chlorophyll b, total chlorophyll content, photosynthetic efficiency (Fv/Fm), proline content, and relative water content, which suggest their importance for indirect selection under water deficit conditions. Otherwise, grain protein content was negatively correlated with grain yield, indicating that selection for higher grain yield could reduce grain protein content under drought stress conditions.