Leaf width gene LW5/D1 affects plant architecture and yield in rice by regulating nitrogen utilization efficiency

Zhu, Yuejin; T, Li; Xu, Jing; Wang, Jiajia; Wang, Li; Zou, Weiwei; Zhu, Li; Chen, Guang; Hu, Jiang; Gao, Zhenyu; Ren, Deyong; Shen, Lan; Zhang, Qiang; Guo, Longbiao; Hu, Songping; Qian, Qian; Zhang, Guangheng

doi:10.1016/j.plaphy.2020.10.035

Cited by 21 publications

(16 citation statements)

References 31 publications

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“…The phenotypic traits reported to be associated with NUE in cereal crops so far include root number, length, density, and branching (Morita et al, 1988 ; Yang et al, 2012 ; Steffens and Rasmussen, 2016 ), dense and erect panicle (Sun et al, 2014 ), plant height (Gaju et al, 2011 ), and leaf width (Zhu et al, 2020 ). The collocation of QTLs for N-uptake and root architecture traits have suggested that breeding for better and efficient root systems is a way to improve NUE (Coque et al, 2008 ; Sandhu et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

et al. 2021

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Nitrogen is one of the most important macronutrients for crop growth and metabolism. To identify marker-trait associations for complex nitrogen use efficiency (NUE)-related agronomic traits, field experiments were conducted on nested synthetic wheat introgression libraries at three nitrogen input levels across two seasons. The introgression libraries were genotyped using the 35K Axiom® Wheat Breeder's Array and genetic diversity and population structure were examined. Significant phenotypic variation was observed across genotypes, treatments, and their interactions across seasons for all the 22 traits measured. Significant positive correlations were observed among grain yield and yield-attributing traits and root traits. Across seasons, a total of 233 marker-trait associations (MTAs) associated with fifteen traits of interest at different levels of nitrogen (N0, N60, and N120) were detected using 9,474 genome-wide single nucleotide polymorphism (SNP) markers. Of these, 45 MTAs for 10 traits in the N0 treatment, 100 MTAs for 11 traits in the N60 treatment, and 88 MTAs for 11 traits in the N120 treatment were detected. We identified putative candidate genes underlying the significant MTAs which were associated directly or indirectly with various biological processes, cellular component organization, and molecular functions involving improved plant growth and grain yield. In addition, the top 10 lines based on N response and grain yield across seasons and treatments were identified. The identification and introgression of superior alleles/donors improving the NUE while maintaining grain yield may open new avenues in designing next generation nitrogen-efficient high-yielding wheat varieties.

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Section: Introductionmentioning

confidence: 99%

Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

et al. 2021

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“…It is speculated that this locus may contain target genes involved in the regulation of leaf cell division or vascular bundles development, thereby mainly affecting the occurrence and development of FLW. For example, in rice, lw5 mainly affects the increase in the number of primary vascular bundles in the leaves, which leads to the increase in the width of the leaves (Zhu et al., 2020). Overexpression of OsSRK1 (an Atypical S‐Receptor‐Like Kinase) may affect the number of cells per leaf and the formation of vascular bundles, resulting in increased leaf width (Zhou et al., 2020).…”

Section: Discussionmentioning

confidence: 99%

Mapping and validation of major and stable QTL for flag leaf size from tetraploid wheat

et al. 2022

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The flag leaf is an important photosynthetic organ of wheat (Triticum aestivum L.). Appropriate flag leaf size can effectively increase grain yield. In this study, a tetraploid wheat population of recombinant inbred lines (RILs) and a genetic map constructed based on a wheat 55K single‐nucleotide polymorphism (SNP) array were used to identify quantitative trait loci (QTL) for flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and the flag leaf length/width ratio (FLR). A novel and major interval flanked by markers AX‐111633224 and AX‐109317229 was identified. This interval includes QTL for FLL (QFll.sau‐AM‐4B.2), for FLW (QFlw.sau‐AM‐4B.4), for FLA (QFla.sau‐AM‐4B), and for FLR (QFlr.sau‐AM‐4B). Based on the genotypes of the closely linked KASP (Kompetitive allele‐specific polymerase chain reaction [PCR]) marker (KASP‐AX‐108756198), QFlw.sau‐AM‐4B.4 and QFla.sau‐AM‐4B were successfully verified in two F3 populations with different genetic backgrounds. Genetic associations between flag leaf‐related traits and other agronomic traits were detected and analyzed. Four genes in this interval were likely involved in the growth and development of the flag leaf size. In conclusion, this study provides clues for excavating genes related to flag leaf size and breeding variety with ideal plant structure.

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“…Map-based cloning followed by CRISPR-Cas9, gene-editing confirmed the involvement of Leaf Width 5 (LW5) in N uptake and utilization ( Zhu et al, 2020 ). The lw5 mutant showed higher rate of photosynthesis, higher chlorophyll content and higher N uptake rate, however the reduced grain nutrient remobilization results in small grains.…”

Section: Introductionmentioning

confidence: 94%

Genome Editing Targets for Improving Nutrient Use Efficiency and Nutrient Stress Adaptation

et al. 2022

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In recent years, the development of RNA-guided genome editing (CRISPR-Cas9 technology) has revolutionized plant genome editing. Under nutrient deficiency conditions, different transcription factors and regulatory gene networks work together to maintain nutrient homeostasis. Improvement in the use efficiency of nitrogen (N), phosphorus (P) and potassium (K) is essential to ensure sustainable yield with enhanced quality and tolerance to stresses. This review outlines potential targets suitable for genome editing for understanding and improving nutrient use (NtUE) efficiency and nutrient stress tolerance. The different genome editing strategies for employing crucial negative and positive regulators are also described. Negative regulators of nutrient signalling are the potential targets for genome editing, that may improve nutrient uptake and stress signalling under resource-poor conditions. The promoter engineering by CRISPR/dead (d) Cas9 (dCas9) cytosine and adenine base editing and prime editing is a successful strategy to generate precise changes. CRISPR/dCas9 system also offers the added advantage of exploiting transcriptional activators/repressors for overexpression of genes of interest in a targeted manner. CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) are variants of CRISPR in which a dCas9 dependent transcription activation or interference is achieved. dCas9-SunTag system can be employed to engineer targeted gene activation and DNA methylation in plants. The development of nutrient use efficient plants through CRISPR-Cas technology will enhance the pace of genetic improvement for nutrient stress tolerance of crops and improve the sustainability of agriculture.

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Leaf width gene LW5/D1 affects plant architecture and yield in rice by regulating nitrogen utilization efficiency

Cited by 21 publications

References 31 publications

Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

Genetic Dissection Uncovers Genome-Wide Marker-Trait Associations for Plant Growth, Yield, and Yield-Related Traits Under Varying Nitrogen Levels in Nested Synthetic Wheat Introgression Libraries

Mapping and validation of major and stable QTL for flag leaf size from tetraploid wheat

Genome Editing Targets for Improving Nutrient Use Efficiency and Nutrient Stress Adaptation

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