Genome-Wide Association Study Identified Novel Candidate Loci/Genes Affecting Lodging Resistance in Rice

Genetic Dissection of Major Rice QTLs for Strong Culms and Fine Mapping of qWS5 for Breeding Application in Transplanted System

BACKGROUND

Rice is one of the major staples that feeds about one half of the global populations, and it is important to identify the genetic loci for the traits related to yield improvement. Lodging will cause severe yield loss when it happens, and stem diameter has been characterized as an important trait for lodging resistance. However, most QTLs for stem diameter have not been finely dissected due to their sensitivity to environmental fluctuation.

RESULT

In this study, we performed QTL analysis for stem diameter using populations derived from Nipponbare (NIP) and strong culm variety YYP1, and confirmed the single and combined effect of three major QTLs by recombinant inbred lines (RILs). Based on the QTL location, we found that qWS5 is a novel QTL not well characterized before. To finely dissect the novel locus, several recombinant heterogeneous inbred families (HIFs) were selected from the RILs for linkage analysis and their derived nearly isogenic lines (NILs) were subjected to detailed trait investigation throughout different years. The HIF-NILs strategy confined the QTL to about 380 kb region supported by repeated genotype and phenotype data, and it lays the foundation for QTL cloning in the future. In addition, introgression of the QTL to an elite japonica variety SD785 was performed by successive backcrossing, and it confirmed the value of qWS5 in increasing stem diameter and other agronomic traits during rice breeding.

CONCLUSIONS

We prove that qWS5 is a novel QTL with relatively stable effect for stem diameter and the QTL can be finely mapped to small region by the HIF-NILs strategy. The result will facilitate the improvement of rice lodging resistance by molecular marker assisted selection breeding.

Strong culm: a crucial trait for developing next-generation climate-resilient rice lines

Lodging, a phenomenon characterized by the bending or breaking of rice plants, poses substantial constraints on productivity, particularly during the harvesting phase in regions susceptible to strong winds. The rice strong culm trait is influenced by the intricate interplay of genetic, physiological, epigenetic, and environmental factors. Stem architecture, encompassing morphological and anatomical attributes, alongside the composition of both structural and non-structural carbohydrates, emerges as a critical determinant of lodging resistance. The adaptive response of the rice culm to various biotic and abiotic environmental factors further modulates the propensity for lodging. Advancements in next-generation sequencing technologies have expedited the genetic dissection of lodging resistance, enabling the identification of pertinent genes, quantitative trait loci, and novel alleles. Concurrently, contemporary breeding strategies, ranging from biparental approaches to more sophisticated methods such as multi-parent-based breeding, gene pyramiding, genomic selection, genome-wide association studies, and haplotype-based breeding, offer perspectives on the genetic underpinnings of culm strength. This review comprehensively delves into physiological attributes, culm histology, epigenetic determinants, and gene expression profiles associated with lodging resistance, with a specialized focus on leveraging next-generation sequencing for candidate gene discovery.

Genome-wide association studies for a comprehensive understanding of the genetic architecture of culm strength and yield traits in rice

Lodging resistance in rice is a complex trait determined by culm morphological and culm physical strength traits, and these traits are a major determinant of yield. We made a detailed analysis of various component traits with the aim of deriving optimized parameters for measuring culm strength. Genotyping by sequencing (GBS)-based genome-wide association study (GWAS) was employed among 181 genotypes for dissecting the genetic control of culm strength traits. The VanRaden kinship algorithm using 6,822 filtered single-nucleotide polymorphisms (SNPs) revealed the presence of two sub-groups within the association panel with kinship values concentrated at<0.5 level, indicating greater diversity among the genotypes. A wide range of phenotypic variation and high heritability for culm strength and yield traits were observed over two seasons, as reflected in best linear unbiased prediction (BLUP) estimates. The multi-locus model for GWAS resulted in the identification of 15 highly significant associations (p< 0.0001) for culm strength traits. Two novel major effect marker-trait associations (MTAs) for section modulus and bending stress were identified on chromosomes 2 and 12 with a phenotypic variance of 21.87% and 10.14%, respectively. Other MTAs were also noted in the vicinity of previously reported putative candidate genes for lodging resistance, providing an opportunity for further research on the biochemical basis of culm strength. The quantitative trait locus (QTL) hotspot identified on chromosome 12 with the synergistic association for culm strength trait (section modulus, bending stress, and internode breaking weight) and grain number can be considered a novel genomic region that can serve a dual purpose of enhancing culm strength and grain yield. Elite donors in the indica background with beneficial alleles of the identified major QTLs could be a valuable resource with greater significance in practical plant breeding programs focusing on improving lodging resistance in rice.

Genetic analyses and prediction for lodging‑related traits in a diverse Iranian hexaploid wheat collection

Lodging is one of the most important limiting environmental factors for achieving the maximum yield and quality of grains in cereals, including wheat. However, little is known about the genetic foundation underlying lodging resistance (LR) in wheat. In this study, 208 landraces and 90 cultivars were phenotyped in two cropping seasons (2018-2019 and 2019-2020) for 19 LR-related traits. A genome-wide association study (GWAS) and genomics prediction were carried out to dissect the genomic regions of LR. The number of significant marker pairs (MPs) was highest for genome B in both landraces (427,017) and cultivars (37,359). The strongest linkage disequilibrium (LD) between marker pairs was found on chromosome 4A (0.318). For stem lodging-related traits, 465, 497, and 478 marker-trait associations (MTAs) and 45 candidate genes were identified in year 1, year 2, and pooled. Gene ontology exhibited genomic region on Chr. 2B, 6B, and 7B control lodging. Most of these genes have key roles in defense response, calcium ion transmembrane transport, carbohydrate metabolic process, nitrogen compound metabolic process, and some genes harbor unknown functions that, all together may respond to lodging as a complex network. The module associated with starch and sucrose biosynthesis was highlighted. Regarding genomic prediction, the GBLUP model performed better than BRR and RRBLUP. This suggests that GBLUP would be a good tool for wheat genome selection. As a result of these findings, it has been possible to identify pivotal QTLs and genes that could be used to improve stem lodging resistance in Triticum aestivum L.

Identification and estimation of lodging in bread wheat genotypes using machine learning predictive algorithms

BACKGROUND

Lodging or stem bending decreases wheat yield quality and quantity. Thus, the traits reflected in early lodging wheat are helpful for early monitoring to some extent. In order to identify the superior genotypes and compare multiple linear regression (MLR) with support vector regression (SVR), artificial neural network (ANN), and random forest regression (RF) for predicting lodging in Iranian wheat accessions, a total of 228 wheat accessions were cultivated under field conditions in an alpha-lattice experiment, randomized incomplete block design, with two replications in two cropping seasons (2018-2019 and 2019-2020). To measure traits, a total of 20 plants were isolated from each plot and were measured using image processing.

RESULTS

The lodging score index (LS) had the highest positive correlation with plant height (r = 0.78**), Number of nodes (r = 0.71**), and internode length 1 (r = 0.70**). Genotypes were classified into four groups based on heat map output. The most lodging-resistant genotypes showed a lodging index of zero or close to zero. The findings revealed that the RF algorithm provided a more accurate estimate (R2 = 0.887 and RMSE = 0.091 for training data and R2 = 0.768 and RMSE = 0.124 for testing data) of wheat lodging than the ANN and SVR algorithms, and its robustness was as good as ANN but better than SVR.

CONCLUSION

Overall, it seems that the RF model can provide a helpful predictive and exploratory tool to estimate wheat lodging in the field. This work can contribute to the adoption of managerial approaches for precise and non-destructive monitoring of lodging.

Identification of a Rice Leaf Width Gene Narrow Leaf 22 (NAL22) through Genome-Wide Association Study and Gene Editing Technology

Rice leaf width (RLW) is a crucial determinant of photosynthetic area. Despite the discovery of several genes controlling RLW, the underlying genetic architecture remains unclear. In order to better understand RLW, this study conducted a genome-wide association study (GWAS) on 351 accessions from the rice diversity population II (RDP-II). The results revealed 12 loci associated with leaf width (LALW). In LALW4, we identified one gene, Narrow Leaf 22 (NAL22), whose polymorphisms and expression levels were associated with RLW variation. Knocking out this gene in Zhonghua11, using CRISPR/Cas9 gene editing technology, resulted in a short and narrow leaf phenotype. However, seed width remained unchanged. Additionally, we discovered that the vein width and expression levels of genes associated with cell division were suppressed in nal22 mutants. Gibberellin (GA) was also found to negatively regulate NAL22 expression and impact RLW. In summary, we dissected the genetic architecture of RLW and identified a gene, NAL22, which provides new loci for further RLW studies and a target gene for leaf shape design in modern rice breeding.

Lodging resistance of rice plants studied from the perspective of culm mechanical properties, carbon framework, free volume, and chemical composition

In this study, four varieties of rice were cultivated on the same farmland under same conditions and for same duration. However, their lodging resistance was found to be obviously different from each other. Herein, three key factors that highly influenced the lodging resistance were identified. First, in terms of morphological trait, in contrast to the generally believed theory that the overall thickness of the fresh culm wall governs the strength, the thickness of the depressed region of the dried basal culm wall largely determined the mechanical properties by acting as the weak link. This depressed region represents the vulnerable part with high syneresis rate. Second, the culm and its carbon framework exhibited sufficient strength and rigidity for both support and stability of the rice stem. The constraint of high lodging resistance of rice plants is attributed to the culm flexibility. Furthermore, the results of the positron annihilation lifetime spectroscopy corroborate that the most amorphous part and the highest-fraction free volume in the culm carbon framework were found for samples that exhibited high lodging resistance. This result confirmed the significant influence of the culm flexibility on lodging resistance. Third, a higher level of nitrogen element content in the basal culm can benefit its growth and development, which may contribute to an increase in lodging resistance of rice plants.

Unveiling the genetic architecture for lodging resistance in rice (Oryza sativa. L) by genome-wide association analyses

Lodging is one of the major abiotic stresses, affecting the total crop yield and quality. The improved lodging resistance and its component traits potentially reduce the yield losses. The section modulus (SM), bending moment at breaking (M), pushing resistance (PR), and coefficient of lodging resistance (cLr) are the key elements to estimate the lodging resistance. Understanding the genetic architecture of lodging resistance-related traits will help to improve the culm strength and overall yield potential. In this study, a natural population of 795 globally diverse genotypes was further divided into two (indica and japonica) subpopulations and was used to evaluate the lodging resistance and culm strength-related traits. Significant diversity was observed among the studied traits. We carried out the genome-wide association evaluation of four lodging resistance traits with 3.3 million deep resolution single-nucleotide polymorphic (SNP) markers. The general linear model (GLM) and compressed mixed linear model (MLM) were used for the whole population and two subpopulation genome-wide association studies (GWAS), and a 1000-time permutation test was performed to remove the false positives. A total of 375 nonredundant QTLs were observed for four culm strength traits on 12 chromosomes of the rice genome. Then, 33 pleiotropic loci governing more than one trait were mined. A total of 4031 annotated genes were detected within the candidate genomic region of 33 pleiotropic loci. The functional annotations and metabolic pathway enrichment analysis showed cellular localization and transmembrane transport as the top gene ontological terms. The in silico and in vitro expression analyses were conducted to validate the three candidate genes in a pleiotropic QTL on chromosome 7. It validated OsFBA2 as a candidate gene to contribute to lodging resistance in rice. The haplotype analysis for the candidate gene revealed a significant functional variation in the promoter region. Validation and introgression of alleles that are beneficial to induce culm strength may be used in rice breeding for lodging resistance.

Detection of QTLs for Plant Height Architecture Traits in Rice (Oryza sativa L.) by Association Mapping and the RSTEP-LRT Method

Plant height (PH) and its component traits are critical determinants of lodging resistance and strongly influence yield in rice. The genetic architecture of PH and its component traits were mined in two mapping populations. In the natural population composed of 504 accessions, a total of forty simple sequence repeat (SSR) markers associated with PH and its component traits were detected across two environments via association mapping. Allele RM305-210 bp on chromosome 5 for PH had the largest phenotypic effect value (PEV) (−51.42 cm) with a reducing effect. Allele RM3533-220 bp on chromosome 9 for panicle length and allele RM264-120 bp on chromosome 8 for the length of upper first elongated internode (1IN) showed the highest positive PEV. Among the elongated internodes with negative effects being desirable, the allele RM348-130 bp showed the largest PEV (−7.48 cm) for the length of upper second elongated internode. In the chromosome segment substitution line population consisting of 53 lines, a total of nine QTLs were detected across two environments, with the phenotypic variance explained (PVE) ranging 10.07–28.42%. Among the detected QTLs, q1IN-7 explained the largest PVE (28.42%) for the 1IN, with an additive of 5.31 cm. The favorable allele RM257-125 bp on chromosome 9 for the 1IN increasing was detected in both populations. The favorable alleles provided here could be used to shape PH architecture against lodging.