Not enough attention has been paid to the comparison in yield performance and N responsiveness between hybrid rice and inbred rice using the large number of new cultivars released after 2000 under machine transplanting. Field experiments were conducted in 2017 and 2018; 48 widely planted rice cultivars included four groups, namely indica hybrids (IHs), japonica inbreds (JIs), indica-japonica hybrids (IJHs), and indica inbreds (IIs) that were transplanted by machine with three nitrogen fertilizer levels (0, 150, 300 kg ha−1). The average yield of the hybrids (IHs, IJHs) was higher than that of JIs or IIs with a higher crop-growing rate (CGR) during the total growth duration, regardless of the N application level; moreover, longer total growth duration was responsible for the higher yield in IJHs than in IHs. The IHs had a large gap yield which mainly came from the genetic improvement in the CGR during the grain-filling stage. The yield gap was relatively small in JIs, and longer growth duration combined with optimal daily mean temperature during the grain-filling stage was the critical factor for high yield. The JIs or IJHs had higher yield under the N300 level, while the response of IHs to nitrogen varied with different cultivars. Cultivars with higher CGR during the grain-filling stage had higher yield under the N300 level. In conclusion, this study suggests that high CGR during the grain-filling stage may be a vital trait for the development of rice with high yield and high N responsiveness at machine transplanting.
Plant long non-coding RNA (lncRNA) is a type of newly emerging epigenetic regulator playing a critical role in plant growth, development, and biotic stress responses.
Abstract Substantial genetic variation is found in weedy rice ( Oryza sativa f. spontanea Roshev.) populations from different rice‐planting regions with the change of farming styles. To determine the association of such genetic variation with rice farming changes is critical for understanding the adaptive evolution of weedy rice. We studied weedy‐rice specific novel single nucleotide polymorphisms (SNPs) by genome‐wide comparison between DNA sequences of weedy and cultivated rice, in addition to polymerase chain reaction fingerprinting at 22 selected novel SNP loci in weedy rice populations. A great number of novel SNPs were identified across the weedy rice genome. High frequencies of the novel SNPs were determined at the 22 selected loci, although with considerable variation among weedy rice populations in different rice‐planting regions. The highest frequency (∼57%) of novel SNPs was identified in weedy rice populations from Jiangsu that experienced the most dramatic changes in rice farming styles, including the shift from transplanting to direct seeding, and from indica to japonica varieties. The lowest frequency (∼29%) was detected in weedy rice populations from Northeast China, where rice farming has undergone relatively less change. The association between frequencies of novel SNPs in weedy rice populations and the extent of changes in rice farming styles suggests the critical role of adaptive mutation and accumulation of the mutation influenced by human activities in the rapid evolution of weedy rice.
A population of F8 recombinant inbred lines (RILs), derived from a cross between IR26 (Oryza sativa L. spp. indica) and Jiucaiqing (japonica), were used to identify the quantitative trait loci (QTLs) for Cd2+ content in brown rice under 5 mg/kg Cd2+ stress. Two QTLs, qCCBR-11a and qCCBR-11b, associated with the Cd2+ content in brown rice, were detected on chromosome 11. qCCBR-11a was located at the position between markers RM6288 and RM6544, accounting for 11.17% of the phenotypic variance with an additive effect value of 0.089. qCCBR-11b at the interval between markers RM167 and RM5704 explained 7.66% of the phenotypic variance with an additive effect value of 0.075. In addition, the correlation coefficients between Cd2+ content of brown rice and plant height, spikelets per panicle, filled grains per panicle, seed setting rate, and 1 000-grain weight were not significant. This suggested that the Cd2+ content in brown rice under Cd2+ stress was an independent genetic trait.
Rice foot rot disease caused by the pathogen Dickeya zeae (formerly known as Erwinia chrysanthemi pv. zeae), is a newly emerging damaging bacterial disease in China and the southeast of Asia, resulting in the loss of yield and grain quality. However, the genetic resistance mechanisms mediated by miRNAs to D. zeae are unclear in rice. In the present study, 652 miRNAs including osa-miR396f predicted to be involved in multiple defense responses to D. zeae were identified with RNA sequencing. A total of 79 differentially expressed miRNAs were detected under the criterion of normalized reads ≥10, including 51 known and 28 novel miRNAs. Degradome sequencing identified 799 targets predicted to be cleaved by 168 identified miRNAs. Among them, 29 differentially expressed miRNA and target pairs including miRNA396f-OsGRFs were identified by co-expression analysis. Overexpression of the osa-miR396f precursor in a susceptible rice variety showed enhanced resistance to D. zeae, coupled with significant accumulation of transcripts of osa-miR396f and reduction of its target the Growth-Regulating Factors (OsGRFs). Taken together, these findings suggest that miRNA and targets including miR396f-OsGRFs have a role in resisting the infections by bacteria D. zeae.
Additional file 1 : Fig. S1. Sequence alignment of the Gγ proteins in rice, Arabidopsis and maize. The red line indicates the predicted nuclear localization signal sequence. The red box indicates the CaaX isoprenylation motif at the C-terminal end. The green line indicates the GGL domain. Fig. S2. Subcellular localization of RGG1ΔNLS-GFP. Scale bar, 20 μm. Fig. S3. Internode lengths of NIP and the RGG1 OE lines. Scale bar, 5 cm. Fig. S4. Comparison of plant and grain phenotypes between WYJ30 and the OE lines. Fig. S5. Targeted mutagenesis of RGG1 in the WYJ30 background and protein sequence alignment of WYJ30 and the mutants. Fig. S6. Gene Ontology (GO) DEG enrichment of the biological process, molecular function and cellular component categories. Fig. S7. Relative expression levels of genes concerning cytokinin biosynthesis. Fig. S8. NaCl treatment of NIP and the transgenic lines. Table S1. Comparison of major agronomic traits between NIP and the transgenic lines. Table S2. Comparison of major agronomic traits between WYJ30 and the transgenic lines. Table S3. Primers used in this study.
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