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The OsNRT2.3a and OsNRT2.3b isoforms play important roles in the uptake and transport of nitrate during rice growth. However, it is unclear which cis-acting element controls the transcription of OsNRT2.3 into these specific isoforms. In this study, we used a yeast one-hybrid assay to obtain the TATA-box binding protein OsTBP2.1, which binds to the TATA-box of OsNRT2.3, and verified its important role through transient expression and RNA-seq. We found that the TATA-box of OsNRT2.3 mutants and binding protein OsTBP2.1 together increased the transcription ratio of OsNRT2.3b to OsNRT2.3a. The overexpression of OsTBP2.1 promoted nitrogen uptake and increased rice yield compared with the wild-type; however, the OsTBP2.1 T-DNA mutant lines exhibited the opposite trend. Detailed analyses demonstrated that the TATA-box was the key cis-regulatory element for OsNRT2.3 to be transcribed into OsNRT2.3a and OsNRT2.3b. Additionally, this key cis-regulatory element, together with the binding protein OsTBP2.1, promoted the development of rice and increased grain yield.

Nitrogen (N) is an essential nutrient element for plants; however, high N accumulation often leads to a decrease in photosynthetic nitrogen use efficiency (PNUE). In rice (Oryza sativa L.), well-developed aerenchyma is formed to promote oxygen transport from the shoot to the root tips as an adaptation to submerged and oxygen-deficient environment. Total N concentrations were increased in the rice root by changes in O2 levels in the rhizosphere. However, few reports have focused on how aerenchyma formation-related genes participate in photosynthesis and affect nitrogen allocation in rice. In this study, we found that OsLSD1.1, located in the chloroplast, cell membrane, and nucleus, may be involved in the photosystem II reaction and affect chloroplast development. OsLSD1.1 knockout was found to significantly reduce the quantum efficiency of the PSII reaction center (ΦPSII). Furthermore, we observed that the nitrogen accumulation decreased in the grain of OsLSD1.1 mutants. RNA-Seq transcriptome analysis revealed that OsPEPC3, OsPsbR1, OsNRG2, OsNRT1.5A, OsNRT1.7, and OsAMT3;2 were downregulated in m12 compared with N-WT (wild-type Nipponbare), which may be a reason that photosynthesis and nitrogen transport were inhibited. Taken together, our findings demonstrated that OsLSD1.1 may be key in plant growth, photosynthesis, and nitrogen allocation in rice. Our results may provide theoretical support for the discovery of key genes for nitrogen physiological use efficiency.

Drought stress is a major environmental stress, which adversely affects the biological and molecular processes of plants, thereby impairing their growth and development. In the present study, we found that the expression level of OsTBP2.2 which encodes for a nucleus-localized protein member belonging to transcription factor IID (TFIID) family, was significantly induced by polyethylene glycol (PEG) treatment. Therefore, knockdown mutants of OsTBP2.2 gene were generated to investigate the role of OsTBP2.2 in rice response to drought stress. Under the condition of drought stress, the photosynthetic rate, transpiration rate, water use efficiency, and stomatal conductance were significantly reduced in ostbp2.2 lines compared with wild type, Dongjin (WT-DJ). Furthermore, the RNA-seq results showed that several main pathways involved in &ldquo, MAPK (mitogen-activated protein kinase) signaling pathway&rdquo, &ldquo, phenylpropanoid biosynthesis&rdquo, defense response&rdquo, and &ldquo, ADP (adenosine diphosphate) binding&rdquo, were altered significantly in ostbp2.2. We also found that OsPIP2, 6, OsPAO and OsRCCR1 genes were down-regulated in ostbp2.2 compared with WT-DJ, which may be one of the reasons that inhibit photosynthesis. Our findings suggest that OsTBP2.2 may play a key role in rice growth and the regulation of photosynthesis under drought stress and it may possess high potential usefulness in molecular breeding of drought-tolerant rice.

Drought stress is a major environmental stress, which adversely affects the biological and molecular processes of plants, thereby impairing their growth and development. In the present study, we found that the expression level of OsTBP2.2 which encodes for a nucleus-localized protein member belonging to transcription factor IID (TFIID) family, was significantly induced by polyethylene glycol (PEG) treatment. Therefore, knockdown mutants of OsTBP2.2 gene were generated to investigate the role of OsTBP2.2 in rice response to drought stress. Under the condition of drought stress, the photosynthetic rate, transpiration rate, water use efficiency, and stomatal conductance were significantly reduced in ostbp2.2 lines compared with wild type, Dongjin (WT-DJ). Furthermore, the RNA-seq results showed that several main pathways involved in “MAPK (mitogen-activated protein kinase) signaling pathway”, “phenylpropanoid biosynthesis”, “defense response” and “ADP (adenosine diphosphate) binding” were altered significantly in ostbp2.2. We also found that OsPIP2;6, OsPAO and OsRCCR1 genes were down-regulated in ostbp2.2 compared with WT-DJ, which may be one of the reasons that inhibit photosynthesis. Our findings suggest that OsTBP2.2 may play a key role in rice growth and the regulation of photosynthesis under drought stress and it may possess high potential usefulness in molecular breeding of drought-tolerant rice.

Key message A comprehensive linkage atlas for seed yield in rapeseed. Abstract Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

A comprehensive linkage atlas for seed yield in rapeseed. Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

A high-density SNP-based genetic linkage map was constructed and integrated with a previous map in the Tapidor x Ningyou7 (TNDH) Brassica napus population, giving a new map with a total of 2041 molecular markers and an average marker density which increased from 0.39 to 0.97 (0.82 SNP bin) per cM. Root and shoot traits were screened under low and ‘normal’ phosphate (Pi) supply using a ‘pouch and wick’ system, and had been screened previously in an agar based system. The P-efficient parent Ningyou7 had a shorter primary root length (PRL), greater lateral root density (LRD) and a greater shoot biomass than the P-inefficient parent Tapidor under both treatments and growth systems. Quantitative trait loci (QTL) analysis identified a total of 131 QTL, and QTL meta-analysis found four integrated QTL across the growth systems. Integration reduced the confidence interval by ~41%. QTL for root and shoot biomass were co-located on chromosome A3 and for lateral root emergence were co-located on chromosomes A4/C4 and C8/C9. There was a major QTL for LRD on chromosome C9 explaining ~18% of the phenotypic variation. QTL underlying an increased LRD may be a useful breeding target for P uptake efficiency in Brassica.