Genetic architecture to cause dynamic change in tiller and panicle numbers revealed by genome-wide association study and transcriptome profile in rice

Genome-Wide Association Analysis of Effective Tillers in Rice under Different Nitrogen Gradients

Nitrogen is a crucial element that impacts rice yields, and effective tillering is a significant agronomic characteristic that can influence rice yields. The way that reduced nitrogen affects effective tillering is a complex quantitative trait that is controlled by multiple genes, and its genetic basis requires further exploration. In this study, 469 germplasm varieties were used for a genome-wide association analysis aiming to detect quantitative trait loci (QTL) associated with effective tillering at low (60 kg/hm2) and high (180 kg/hm2) nitrogen levels. QTLs detected over multiple years or under different treatments were scrutinized in this study, and candidate genes were identified through haplotype analysis and spatio-temporal expression patterns. A total of seven genes (NAL1, OsCKX9, Os01g0690800, Os02g0550300, Os02g0550700, Os04g0615700, and Os04g06163000) were pinpointed in these QTL regions, and were considered the most likely candidate genes. These results provide favorable information for the use of auxiliary marker selection in controlling effective tillering in rice for improved yields.

Rice receptor kinase FLR7 regulates rhizosphere oxygen levels and enriches the dominant Anaeromyxobacter that improves submergence tolerance in rice

Oxygen is one of the determinants of root microbiome formation. However, whether plants regulate rhizosphere oxygen levels to affect microbiota composition and the underlying molecular mechanisms remain elusive. The receptor-like kinase (RLK) family member FERONIA modulates the growth-defense tradeoff in Arabidopsis. Here, we established that rice FERONIA-like RLK 7 (FLR7) controls rhizosphere oxygen levels by methylene blue staining, oxygen flux, and potential measurements. The formation of oxygen-transporting aerenchyma in roots is negatively regulated by FLR7. We further characterized the root microbiota of 11 FLR mutants including flr7 and wild-type Nipponbare (Nip) grown in the field by 16S ribosomal RNA gene profiling and demonstrated that the 11 FLRs are involved in regulating rice root microbiome formation. The most abundant anaerobic-dependent genus Anaeromyxobacter in the Nip root microbiota was less abundant in the root microbiota of all these mutants, and this contributed the most to the community differences between most mutants and Nip. Metagenomic sequencing revealed that flr7 increases aerobic respiration and decreases anaerobic respiration in the root microbiome. Finally, we showed that a representative Anaeromyxobacter strain improved submergence tolerance in rice via FLR7. Collectively, our findings indicate that FLR7 mediates changes in rhizosphere oxygen levels and enriches the beneficial dominant genus Anaeromyxobacter and may provide insights for developing plant flood prevention strategies via the use of environment-specific functional soil microorganisms.

BSA-Seq for the Identification of Major Genes for EPN in Rice

Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative trait locus (QTL) for EPN in rice is limited, and there is also limited research on the gene for EPN in rice. Therefore, the excavation and analysis of major genes related to EPN in rice is of great significance for molecular breeding and yield improvement. This study used japonica rice varieties Dongfu 114 and Longyang 11 to construct an F5 population consisting of 309 individual plants. Two extreme phenotypic pools were constructed by identifying the EPN of the population, and QTL-seq analysis was performed to obtain three main effective QTL intervals for EPN. This analysis also helped to screen out 34 candidate genes. Then, EPN time expression pattern analysis was performed on these 34 genes to screen out six candidate genes with higher expression levels. Using a 3K database to perform haplotype analysis on these six genes, we selected haplotypes with significant differences in EPN. Finally, five candidate genes related to EPN were obtained.

Genome-Wide Association Study Reveals the Genetic Basis of Total Flavonoid Content in Brown Rice

Flavonoids have anti-inflammatory, antioxidative, and anticarcinogenic effects. Breeding rice varieties rich in flavonoids can prevent chronic diseases such as cancer and cardio-cerebrovascular diseases. However, most of the genes reported are known to regulate flavonoid content in leaves or seedlings. To further elucidate the genetic basis of flavonoid content in rice grains and identify germplasm rich in flavonoids in grains, a set of rice core collections containing 633 accessions from 32 countries was used to determine total flavonoid content (TFC) in brown rice. We identified ten excellent germplasms with TFC exceeding 300 mg/100 g. Using a compressed mixed linear model, a total of 53 quantitative trait loci (QTLs) were detected through a genome-wide association study (GWAS). By combining linkage disequilibrium (LD) analysis, location of significant single nucleotide polymorphisms (SNPs), gene expression, and haplotype analysis, eight candidate genes were identified from two important QTLs (qTFC1-6 and qTFC9-7), among which LOC_Os01g59440 and LOC_Os09g24260 are the most likely candidate genes. We also analyzed the geographic distribution and breeding utilization of favorable haplotypes of the two genes. Our findings provide insights into the genetic basis of TFC in brown rice and could facilitate the breeding of flavonoid-rich varieties, which may be a prevention and adjuvant treatment for cancer and cardio-cerebrovascular diseases.

Natural variation in Tiller Number 1 affects its interaction with TIF1 to regulate tillering in rice

Tiller number per plant-a cardinal component of ideal plant architecture-affects grain yield potential. Thus, alleles positively affecting tillering must be mined to promote genetic improvement. Here, we report a Tiller Number 1 (TN1) protein harbouring a bromo-adjacent homology domain and RNA recognition motifs, identified through genome-wide association study of tiller numbers. Natural variation in TN1 affects its interaction with TIF1 (TN1 interaction factor 1) to affect DWARF14 expression and negatively regulate tiller number in rice. Further analysis of variations in TN1 among indica genotypes according to geographical distribution revealed that low-tillering varieties with TN1-hap^L are concentrated in Southeast Asia and East Asia, whereas high-tillering varieties with TN1-hap^H are concentrated in South Asia. Taken together, these results indicate that TN1 is a tillering regulatory factor whose alleles present apparent preferential utilization across geographical regions. Our findings advance the molecular understanding of tiller development.

Deciphering the Genetic Code of Autoimmune Kidney Diseases

Autoimmune kidney diseases occur due to the loss of tolerance to self-antigens, resulting in inflammation and pathological damage to the kidneys. This review focuses on the known genetic associations of the major autoimmune kidney diseases that result in the development of glomerulonephritis: lupus nephritis (LN), anti-neutrophil cytoplasmic associated vasculitis (AAV), anti-glomerular basement disease (also known as Goodpasture's disease), IgA nephropathy (IgAN), and membranous nephritis (MN). Genetic associations with an increased risk of disease are not only associated with polymorphisms in the human leukocyte antigen (HLA) II region, which governs underlying processes in the development of autoimmunity, but are also associated with genes regulating inflammation, such as NFkB, IRF4, and FC γ receptors (FCGR). Critical genome-wide association studies are discussed both to reveal similarities in gene polymorphisms between autoimmune kidney diseases and to explicate differential risks in different ethnicities. Lastly, we review the role of neutrophil extracellular traps, critical inducers of inflammation in LN, AAV, and anti-GBM disease, where inefficient clearance due to polymorphisms in DNase I and genes that regulate neutrophil extracellular trap production are associated with autoimmune kidney diseases.

Co-Overexpression of Two Key Source Genes, OsBMY4 and OsISA3, Improves Multiple Key Traits of Rice Seeds

Optimized source-sink interactions are determinants of both rice yield and quality. However, most source genes have not been well studied in rice, a major grain crop. In this study, OsBMY4 and OsISA3, the key β-amylase and debranching enzymes that control transient starch degradation in rice leaves, were co-overexpressed in rice in order to accelerate starch degradation efficiency and increase the sugar supply for sink organs. Systematic analyses of the transgenic rice indicated that co-overexpression of OsBMY4 and OsISA3 not only promoted rice yield and quality, but also improved seed germination and stress tolerance. Moreover, since the OsBMY4 gene has not been characterized, we generated osbmy4 mutants using CRIPSR/Cas9 gene editing, which helped to reveal the roles of β-amylase in rice yield and quality. This study demonstrated that specific modulation of the expression of some key source genes improves the source-sink balance and leads to improvements in multiple key traits of rice seeds.

Panicle Ratio Network: streamlining rice panicle measurement by deep learning with ultra-high-definition aerial images in the field

The heading date and effective tiller percentage are important traits in rice, and they directly affect plant architecture and yield. Both traits are related to the ratio of the panicle number to the maximum tiller number, referred to as the panicle ratio (PR). In this study, an automatic PR estimation model (PRNet) based on a deep convolutional neural network was developed. Ultra-high-definition unmanned aerial vehicle (UAV) images were collected from cultivated rice varieties planted in 2384 experimental plots in 2019 and 2020 and in a large field in 2021. The determination coefficient between estimated PR and ground-measured PR reached 0.935, and the root mean square error values for the estimations of the heading date and effective tiller percentage were 0.687 d and 4.84%, respectively. Based on the analysis of the results, various factors affecting PR estimation and strategies for improving PR estimation accuracy were investigated. The satisfactory results obtained in this study demonstrate the feasibility of using UAVs and deep learning techniques to replace ground-based manual methods to accurately extract phenotypic information of crop micro targets (such as grains per panicle, panicle flowering, etc.) for rice and potentially for other cereal crops in future research.

Genome-Wide Association Study of the Genetic Basis of Effective Tiller Number in Rice

BACKGROUND

Effective tiller number (ETN) has a pivotal role in determination of rice (Oryza sativa L.) grain yield. ETN is a complex quantitative trait regulated by both genetic and environmental factors. Despite multiple tillering-related genes have been cloned previously, few of them have been utilized in practical breeding programs.

RESULTS

In this study, we conducted a genome-wide association study (GWAS) for ETN using a panel of 490 rice accessions derived from the 3 K rice genomes project. Thirty eight ETN-associated QTLs were identified, interestingly, four of which colocalized with the OsAAP1, DWL2, NAL1, and OsWRKY74 gene previously reported to be involved in rice tillering regulation. Haplotype (Hap) analysis revealed that Hap5 of OsAAP1, Hap3 and 6 of DWL2, Hap2 of NAL1, and Hap3 and 4 of OsWRKY74 are favorable alleles for ETN. Pyramiding favorable alleles of all these four genes had more enhancement in ETN than accessions harboring the favorable allele of only one gene. Moreover, we identified 25 novel candidate genes which might also affect ETN, and the positive association between expression levels of the OsPILS6b gene and ETN was validated by RT-qPCR. Furthermore, transcriptome analysis on data released on public database revealed that most ETN-associated genes showed a relatively high expression from 21 days after transplanting (DAT) to 49 DAT and decreased since then. This unique expression pattern of ETN-associated genes may contribute to the transition from vegetative to reproductive growth of tillers.

CONCLUSIONS

Our results revealed that GWAS is a feasible way to mine ETN-associated genes. The candidate genes and favorable alleles identified in this study have the potential application value in rice molecular breeding for high ETN and grain yield.