Identification of QTNs, QTN-by-environment interactions, and their candidate genes for grain size traits in main crop and ratoon rice

New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study

BACKGROUND

Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield.

RESULTS

Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.

CONCLUSIONS

Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.

Appropriately Reduced Nitrogen and Increased Phosphorus in Ratooning Rice Increased the Yield and Reduced the Greenhouse Gas Emissions in Southeast China

Reducing greenhouse gas emissions while improving productivity is the core of sustainable agriculture development. In recent years, rice ratooning has developed rapidly in China and other Asian countries, becoming an effective measure to increase rice production and reduce greenhouse gas emissions in these regions. However, the lower yield of ratooning rice caused by the application of a single nitrogen fertilizer in the ratooning season has become one of the main reasons limiting the further development of rice ratooning. The combined application of nitrogen and phosphorus plays a crucial role in increasing crop yield and reducing greenhouse gas emissions. The effects of combined nitrogen and phosphorus application on ratooning rice remain unclear. Therefore, this paper aimed to investigate the effect of combined nitrogen and phosphorus application on ratooning rice. Two hybrid rice varieties, 'Luyou 1831' and 'Yongyou 1540', were used as experimental materials. A control treatment of nitrogen-only fertilization (187.50 kg·ha-1 N) was set, and six treatments were established by reducing nitrogen fertilizer by 10% (N1) and 20% (N2), and applying three levels of phosphorus fertilizer: N1P1 (168.75 kg·ha-1 N; 13.50 kg·ha-1 P), N1P2 (168.75 kg·ha-1 N; 27.00 kg·ha-1 P), N1P3 (168.75 kg·ha-1 N; 40.50 kg·ha-1 P), N2P1 (150.00 kg·ha-1 N; 13.50 kg·ha-1 P), N2P2 (150.00 kg·ha-1 N; 27.00 kg·ha-1 P), and N2P3 (150.00 kg·ha-1 N; 40.50 kg·ha-1 P). The effects of reduced nitrogen and increased phosphorus treatments in ratooning rice on the yield, the greenhouse gas emissions, and the community structure of rhizosphere soil microbes were examined. The results showed that the yield of ratooning rice in different treatments followed the sequence N1P2 > N1P1 > N1P3 > N2P3 > N2P2 > N2P1 > N. Specifically, under the N1P2 treatment, the average two-year yields of 'Luyou 1831' and 'Yongyou 1540' reached 8520.55 kg·ha-1 and 9184.90 kg·ha-1, respectively, representing increases of 74.30% and 25.79% compared to the N treatment. Different nitrogen and phosphorus application combinations also reduced methane emissions during the ratooning season. Appropriately combined nitrogen and phosphorus application reduced the relative contribution of stochastic processes in microbial community assembly, broadened the niche breadth of microbial communities, enhanced the abundance of functional genes related to methane-oxidizing bacteria and soil ammonia-oxidizing bacteria in the rhizosphere, and decreased the abundance of functional genes related to methanogenic and denitrifying bacteria, thereby reducing greenhouse gas emissions in the ratooning season. The carbon footprint of ratooning rice for 'Luyou 1831' and 'Yongyou 1540' decreased by 25.82% and 38.99%, respectively, under the N1P2 treatment compared to the N treatment. This study offered a new fertilization pattern for the green sustainable development of rice ratooning.

Utilization of the Winkler scale of plants using big data temperature presented by the Korea Meteorological Administration

Introduction

Rice is an important food source that can provide a stable supply of calories for most people around the world. However, owing to the recent rapid temperature rise, we are facing social issues related to the increase in the Winkler scale. In this study, a strategy for screening potential candidate genes related to the yield according to the Winkler scale is presented, and the possibility of using a candidate gene identified through sequence haplotype and homology analysis as a breeding source is suggested.

Methods

QTL for the Winkler scale was identified using a population of 120 double haploids derived from a cross between Cheongchoneg, Indica, and Nagdong, Japonica.

Results and discussion

A total of 79 candidate genes were detected in the identified QTL region, and OsHAq8 was finally screened. Through haplotype analysis, OsHAq8 was derived from the Indica group and orthologous to Graminae's activator of Hsp90 ATPase, suggesting that it is a candidate gene involved in yield according to temperature during the growing period. The expression level of OsHAq8 increased as the Winkler scale increased. The findings of this study can serve as a crucial indicator for predicting harvest time and grain quality while achieving a stable yield through marker selection and adaptation to climate change. Climate change occurs more frequently. In these situations, it is very important to predict harvest time and apply relevant candidate genes to breeding. The candidate genes presented in this study can be effectively applied to rice breeding in preparation for climate change.

Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum

MAIN CONCLUSION

Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.

Genome-wide association study of cooking-caused grain expansion in rice (Oryza sativa L.)

Cooking-caused rice grain expansion (CCRGE) is a critical trait for evaluating the cooking quality of rice. Previous quantitative trait locus (QTL) mapping studies on CCRGE have been limited to bi-parental populations, which restrict the exploration of natural variation and mapping resolution. To comprehensively and precisely dissect the genetic basis of CCRGE, we performed a genome-wide association study (GWAS) on three related indices: grain breadth expansion index (GBEI), grain length expansion index (GLEI), and grain length-breadth ratio expansion index (GREI), using 345 rice accessions grown in two years (environments) and 193,582 SNP markers. By analyzing each environment separately using seven different methods (3VmrMLM, mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO), we identified a total of 32, 19 and 27 reliable quantitative trait nucleotides (QTNs) associated with GBEI, GLEI and GREI, respectively. Furthermore, by jointly analyzing the two environments using 3VmrMLM, we discovered 19, 22 and 25 QTNs, as well as 9, 5 and 7 QTN-by-environment interaction (QEIs) associated with GBEI, GLEI and GREI, respectively. Notably, 12, 9 and 15 QTNs for GBEI, GLEI and GREI were found within the intervals of previously reported QTLs. In the vicinity of these QTNs or QEIs, based on analyses of mutation type, gene ontology classification, haplotype, and expression pattern, we identified five candidate genes that are related to starch synthesis and endosperm development. The five candidate genes, namely, LOC_Os04g53310 (OsSSIIIb, near QTN qGREI-4.5s), LOC_Os05g02070 (OsMT2b, near QTN qGLEI-5.1s), LOC_Os06g04200 (wx, near QEI qGBEI-6.1i and QTNs qGREI-6.1s and qGLEI-6.1t), LOC_Os06g12450 (OsSSIIa, near QTN qGLEI-6.2t), and LOC_Os08g09230 (OsSSIIIa, near QTN qGBEI-8.1t), are predicted to be involved in the process of rice grain starch synthesis and to influence grain expansion after cooking. Our findings provide valuable insights and will facilitate genetic research and improvement of CCRGE.

Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses

INTRODUCTION

Quantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement.

METHODS

In this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses.

RESULTS

Among the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield.

DISCUSSION

All these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.