Genome-wide association studies of yield-related traits in high-latitude japonica rice

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.

Genetic potential of grain-related traits in rice landraces: phenomics and multi-locus association analyses

BACKGROUND

Grain length, width, weight, and the number of grains per panicle are crucial determinants contributing to yield in cereal crops. Understanding the genetic basis of grain-related traits has been the main research object in crop science.

METHODS AND RESULTS

Kerala has a collection of different rice landraces. Characterization of these valuable genetic resources for 39 distinct agro-morphological traits was carried out in two seasons from 2017 to 2019 directly in farmers field. Most characteristics were polymorphic except ligule shape, leaf angle, and panicle axis. The results of principal component analysis implied that leaf length, plant height, culm length, flag leaf length, and grain-related traits were the principal discriminatory characteristics of rice landraces. For identifying the genetic basis of key grain traits of rice, three multi locus GWAS models were performed based on 1,47,994 SNPs in 73 rice accessions. As a result, 48 quantitative trait nucleotides (QTNs) were identified to be associated with these traits. After characterization of their function and expression, 15 significant candidate genes involved in regulating grain width, number of grains per panicle, and yield were identified.

CONCLUSIONS

The detected QTNs and candidate genes in this study could be further used for marker-assisted high-quality breeding of rice.

Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.)

Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population's hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing.

Combined genome-wide association study and epistasis analysis reveal multifaceted genetic architectures of plant height in Asian cultivated rice

Plant height (PH) in rice (Oryza sativa) is an important trait for its adaptation and agricultural performance. Discovery of the semi-dwarf1 (SD1) mutation initiated the Green Revolution, boosting rice yield and fitness, but the underlying genetic regulation of PH in rice remains largely unknown. Here, we performed genome-wide association study (GWAS) and identified 12 non-repetitive QTL/genes regulating PH variation in 619 Asian cultivated rice accessions. One of these was an SD1 structural variant, not normally detected in standard GWAS analyses. Given the strong effect of SD1 on PH, we also divided 619 accessions into subgroups harbouring distinct SD1 haplotypes, and found a further 85 QTL/genes for PH, revealing genetic heterogeneity that may be missed by analysing a broad, diverse population. Moreover, we uncovered two epistatic interaction networks of PH-associated QTL/genes in the japonica (Geng)-dominant SD1^NIP subgroup. In one of them, the hub QTL/gene qphSN1.4/GAMYB interacted with qphSN3.1/OsINO80, qphSN3.4/HD16/EL1, qphSN6.2/LOC_Os06g11130, and qphSN10.2/MADS56. Sequence variations in GAMYB and MADS56 were associated with their expression levels and PH variations, and MADS56 was shown to physically interact with MADS57 to coregulate expression of gibberellin (GA) metabolic genes OsGA2ox3 and Elongated Uppermost Internode1 (EUI1). Our study uncovered the multifaceted genetic architectures of rice PH, and provided novel and abundant genetic resources for breeding semi-dwarf rice and new candidates for further mechanistic studies on regulation of PH in rice.