Isolation and initial characterization of GW5, a major QTL associated with rice grain width and weight

Analysis of the role of the rice metallothionein gene OsMT2b in grain size regulation

Seed size is one of the three main characteristics determining rice yield. Clarification of the mechanisms regulating seed size in rice has implications for improving rice yield. Although several genes have been reported to regulate seed size, most of the reports are fragmentary. The role of metallothioneins (MTs) in regulating seed size remains unknown. Here, we found that OsMT2b was expressed in both spikelets and developing seeds. OsMT2b-overexpression lines had large and heavy seeds, and RNAi (RNA interference) lines had small and light seeds. Scanning electron microscopy (SEM) observations revealed that OsMT2b regulated spikelet hull size by affecting cell expansion in the outer epidermis. Histological analysis indicated that OsMT2b affected the number of cells in the cross-section of spikelet hulls, which affected seed size. The fresh weight of seeds was consistently higher in OsMT2b-overexpression lines than in seeds of the wild-type (WT) and RNAi lines from 6 DAP (days after pollination) until maturity, indicating that OsMT2b affected seed filling. Reverse transcription-quantitative PCR (RT-qPCR) analyses revealed that OsMT2b regulates the expression of reactive oxygen species scavenging-related genes involved in seed size regulation. In conclusion, our results indicated that OsMT2b positively regulates seed size, which provides a novel approach for regulating seed size with genetic engineering technology.

GW3, encoding a member of the P450 subfamily, controls grain width by regulating the GA4 content in spikelets of rice (Oryza sativa L.)

KEY MESSAGE

A stable QTL, GW3, controlling grain width was identified in two populations. Its causal gene LOC_Os03g04680 was verified by gene-based haplotype analysis, expression analysis, gene knockout and complementation transgenic tests. Grain width (GW) is one of the key traits affecting grain size and determines grain yield and appearance quality in rice. Mining gene loci and elite alleles controlling GW is necessary. The GW phenotypes of the two populations were investigated in three environments, which showed abundant phenotypic variation. GW3, encoding a P450 subfamily protein, was identified and validated as a causal gene by gene-based haplotype analysis, expression analysis, gene knockout and complementation transgenic tests. The accessions with large GW values had high gene expression levels. In addition, the GW of the accessions with the GG allele was significantly greater than that of the accessions with the AA allele. The Hap 1 and Hap 3 were identified as elite haplotypes, which can increase GW. The expression levels of OsKO1, OsGA3ox1, OsGA20ox1 and OsGA20ox2 in the young panicle of A7444 were significantly greater than those in the young panicle of the mutants, indicating that GW3 may be involved in the gibberellins (GA) biosynthesis pathway to regulate GW. GA4 content detection and electron scanning analysis revealed that GA4 regulates GW by affecting glume cell size. These results provide new insights for studying the genetic mechanism of rice GW and provide a material basis for breeding high-yield rice varieties.

Profiling and Improvement of Grain Quality Traits for Consumer Preferable Basmati Rice in the United States

Basmati rice is a premium aromatic rice that consumers choose primarily because of its distinct aroma and excellent grain quality. The grain quality of Basmati rice (GQBR) reflects the perspectives of producers, processors, sellers, and consumers related to the production, processing, marketing, and consumption of Basmati rice. Consumers, an invaluable part of the production demand and value chain of the Basmati rice industry, have the freedom to choose from different types of aromatic rice. Consumers expect their preferred Basmati rice to possess all superior rice grain qualities, including the physical, biochemical, and physiological properties. Gene functional analysis explained that a 10-base pair deletion in the promoter region of the OsSPL16 gene causes the slender grains in Basmati rice, whereas an 8-base-pair deletion in exon 7 of the OsBadh2 gene (located in the fgr region on rice chromosome 8) results in the distinct aroma. Furthermore, a combination of the genetic characteristics of the gw8 and gs3 genes has led to the creation of a long-grain Basmati-type rice cultivar. It has also been demonstrated that agricultural, genetic, and environmental conditions significantly influence GQBR. Hence, research on improving GQBR requires a multidimensional approach and sophisticated elements due to the complexity of its nature and preference diversity. This review covers the basic definitions of grain quality traits, consumer preference criteria, influencing factors, and strategies for producing superior-quality Basmati rice in the United States. This knowledge will be useful in improving the grain quality of Basmati and Basmati-type rice, as well as developing appropriate breeding programs that will meet the preferences of different countries and cultures.

Improving Rice Grain Quality Through Ecotype Breeding for Enhancing Food and Nutritional Security in Asia-Pacific Region

Rice grain is widely consumed as a staple food, providing essential nutrition for households, particularly marginalized families. It plays a crucial role in ensuring food security, promoting human nutrition, supporting good health, and contributing to global food and nutritional security. Addressing the diverse quality demands of emerging diverse and climate-risked population dietary needs requires the development of a single variety of rice grain that can meet the various dietary and nutritional requirements. However, there is a lack of concrete definition for rice grain quality, making it challenging to cater to the different demands. The lack of sufficient genetic study and development in improving rice grain quality has resulted in widespread malnutrition, hidden hunger, and micronutrient deficiencies affecting a significant portion of the global population. Therefore, it is crucial to identify genetically evolved varieties with marked qualities that can help address these issues. Various factors account for the declining quality of rice grain and requires further study to improve their quality for healthier diets. We characterized rice grain quality using Lancastrians descriptor and a multitude of intrinsic and extrinsic quality traits. Next, we examined various components of rice grain quality favored in the Asia-Pacific region. This includes preferences by different communities, rice industry stakeholders, and value chain actors. We also explored the biological aspects of rice grain quality in the region, as well as specific genetic improvements that have been made in these traits. Additionally, we evaluated the factors that can influence rice grain quality and discussed the future directions for ensuring food and nutritional security and meeting consumer demands for grain quality. We explored the diverse consumer bases and their varied preferences in Asian-Pacific countries including India, China, Nepal, Bhutan, Vietnam, Sri Lanka, Pakistan, Thailand, Cambodia, Philippines, Bangladesh, Indonesia, Korea, Myanmar and Japan. The quality preferences encompassed a range of factors, including rice head recovery, grain shape, uniform size before cooking, gelatinization, chalkiness, texture, amylose content, aroma, red-coloration of grain, soft and shine when cooked, unbroken when cooked, gelatinization, less water required for cooking, gelatinization temperature (less cooking time), aged rice, firm and dry when cooked (gel consistency), extreme white, soft when chewed, easy-to-cook rice (parboiled rice), vitamins, and minerals. These preferences were evaluated across high, low, and medium categories. A comprehensive analysis is provided on the enhancement of grain quality traits, including brown rice recovery, recovery rate of milled rice, head rice recovery, as well as morphological traits such as grain length, grain width, grain length-width ratio, and grain chalkiness. We also explored the characteristics of amylose, gel consistency, gelatinization temperature, viscosity, as well as the nutritional qualities of rice grains such as starch, protein, lipids, vitamins, minerals, phytochemicals, and bio-fortification potential. The various factors that impact the quality of rice grains, including pre-harvest, post-harvest, and genotype considerations were explored. Additionally, we discussed the future direction and genetic strategies to effectively tackle these challenges. These qualitative characteristics represent the fundamental focus of regional and national breeding strategies employed by different countries to meet consumer preference. Given the significance of rice as a staple food in Asia-Pacific countries, it is primarily consumed domestically, with only a small portion being exported internationally. All the important attributes must be clearly defined within specific parameters. It is crucial for geneticists and breeders to develop a rice variety that can meet the diverse demands of consumers worldwide by incorporating multiple desirable traits. Thus, the goal of addressing global food and nutritional security, and human healthy can be achieved.

Molecular mechanisms controlling grain size and weight and their biotechnological breeding applications in maize and other cereal crops

BACKGROUND

Cereal crops are a primary energy source for humans. Grain size and weight affect both evolutionary fitness and grain yield of cereals. Although studies on gene mining and molecular mechanisms controlling grain size and weight are constantly emerging in cereal crops, only a few systematic reviews on the underlying molecular mechanisms and their breeding applications are available so far.

AIM OF REVIEW

This review provides a general state-of-the-art overview of molecular mechanisms and targeted strategies for improving grain size and weight of cereals as well as insights for future yield-improving biotechnology-assisted breeding.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, the evolution of research on grain size and weight over the last 20 years is traced based on a bibliometric analysis of 1158 publications and the main signaling pathways and transcriptional factors involved are summarized. In addition, the roles of post-transcriptional regulation and photosynthetic product accumulation affecting grain size and weight in maize and rice are outlined. State-of-the-art strategies for discovering novel genes related to grain size and weight in maize and other cereal crops as well as advanced breeding biotechnology strategies being used for improving yield including marker-assisted selection, genomic selection, transgenic breeding, and genome editing are also discussed.

Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara

Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01483-0.

When Size Matters: New Insights on How Seed Size Can Contribute to the Early Stages of Plant Development

The seed habit is the most complex and successful method of sexual reproduction in vascular plants. It represents a remarkable moment in the evolution of plants that afterward spread on land. In particular, seed size had a pivotal role in evolutionary success and agronomic traits, especially in the field of crop domestication. Given that crop seeds constitute one of the primary products for consumption, it follows that seed size represents a fundamental determinant of crop yield. This adaptative feature is strictly controlled by genetic traits from both maternal and zygotic tissues, although seed development and growth are also affected by environmental cues. Despite being a highly exploited topic for both basic and applied research, there are still many issues to be elucidated for developmental biology as well as for agronomic science. This review addresses a number of open questions related to cues that influence seed growth and size and how they influence seed germination. Moreover, new insights on the genetic-molecular control of this adaptive trait are presented.

Rapid improvement of grain appearance in three-line hybrid rice via CRISPR/Cas9 editing of grain size genes

KEY MESSAGE

Genetic editing of grain size genes quickly improves three-line hybrid rice parents to increase the appearance quality and yield of hybrid rice. Grain size affects rice yield and quality. In this study, we used CRISPR/Cas9 to edit the grain size gene GW8 in the maintainer line WaitaiB (WTB) and restorer line Guanghui998 (GH998). The new slender sterile line WTEA (gw8) was obtained in the BC2F1 generation by transferring the grain mutation of the maintainer plant to the corresponding sterile line WantaiA (WTA, GW8) in the T1 generation. Two slender restorer lines, GH998E1 (gw8(II)) and GH998E2 (gw8(I)), were obtained in T1 generation. In the early stage, new sterile and restorer lines in grain mutations were created by targeted editing of GS3, TGW3, and GW8 genes. These parental lines were mated to detect the impact of grain-type mutations on hybrid rice yield and quality. Mutations in gs3, gw8, and tgw3 had a minimal impact on agronomic traits except the grain size and thousand-grain weight. The decrease in grain width in the combination mainly came from gw8/gw8, gs3/gs3 increased the grain length, gs3/gs3-gw8/gw8 had a more significant effect on the grain length, and gs3/gs3-gw8/gw8(I) contributed more to grain length than gs3/gs3-gw8/gw8(II). The heterozygous TGW3/tgw3 may not significantly increase grain length. Electron microscopy revealed that the low-chalky slender-grain variety had a cylindrical grain shape, a uniform distribution of endosperm cells, and tightly arranged starch grains. Quantitative fluorescence analysis of endospermdevelopment-related genes showed that the combination of slender grain hybrid rice caused by gs3 and gw8 mutations promoted endosperm development and improved appearance quality. An appropriate grain size mutation resulted in hybrid rice varieties with high yield and quality.

Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length-width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

The GW5-WRKY53-SGW5 module regulates grain size variation in rice

Grain size is a crucial agronomic trait that affects stable yield, appearance, milling quality, and domestication in rice. However, the molecular and genetic relationships among QTL genes (QTGs) underlying natural variation for grain size remain elusive. Here, we identified a novel QTG SGW5 (suppressor of gw5) by map-based cloning using an F2 segregation population by fixing same genotype of the master QTG GW5. SGW5 positively regulates grain width by influencing cell division and cell size in spikelet hulls. Two nearly isogenic lines exhibited a significant differential expression of SGW5 and a 12.2% increase in grain yield. Introducing the higher expression allele into the genetic background containing the lower expression allele resulted in increased grain width, while its knockout resulted in shorter grain hulls and dwarf plants. Moreover, a cis-element variation in the SGW5 promoter influenced its differential binding affinity for the WRKY53 transcription factor, causing the differential SGW5 expression, which ultimately leads to grain size variation. GW5 physically and genetically interacts with WRKY53 to suppress the expression of SGW5. These findings elucidated a new pathway for grain size regulation by the GW5-WRKY53-SGW5 module and provided a novel case for generally uncovering QTG interactions underlying the genetic diversity of an important trait in crops.

Transcription factor OsSHR2 regulates rice architecture and yield per plant in response to nitrogen

MAIN CONCLUSION

Mutation of OsSHR2 adversely impacted root and shoot growth and impaired plant response to N conditions, further reducing the yield per plant. Nitrogen (N) is a crucial factor that regulates the plant architecture. There is still a lack of research on it. In our study, it was observed that the knockout of the SHORTROOT 2 (OsSHR2) which was induced by N deficiency, can significantly affect the regulation of plant architecture response to N in rice. Under N deficiency, the mutation of OsSHR2 significantly reduced root growth, and impaired the sensitivity of the root meristem length to N deficiency. The mutants were found to have approximately a 15% reduction in plant height compared to wild type. But mutants showed a significant increase in tillering at post-heading stage, approximately 26% more than the wild type, particularly in high N conditions. In addition, due to reduced seed setting rate and 1000-grain weight, mutant yield was significantly decreased by approximately 33% under low N fertilizer supply. The mutation also changed the distribution of N between the vegetative and reproductive organs. Our findings suggest that the transcription factor OsSHR2 plays a regulatory role in the response of plant architecture and yield per plant to N in rice.

T-DNA insertion mutants of Arabidopsis DA1 orthologous genes displayed altered plant height and yield-related traits in rice (O. Sativa L.)

BACKGROUND

The Arabidopsis DA1 gene is a key player in the regulation of organ and seed development. To extend our understanding of its functional counterparts in rice, this study investigates the roles of orthologous genes, namely DA1, HDR3, HDR3.1, and the DA2 ortholog GW2, through the analysis of T-DNA insertion mutants.

OBJECTIVE

The aim of this research is to elucidate the impact of T-DNA insertions in DA1, HDR3, HDR3.1, and GW2 on agronomic traits in rice. By evaluating homozygous plants, we specifically focus on key parameters such as plant height, tiller number, days to heading, and grain size.

METHODS

T-DNA insertion locations were validated using PCR, and subsequent analyses were conducted on homozygous plants. Agronomic traits, including plant height, tiller number, days to heading, and grain size, were assessed. Additionally, leaf senescence assays were performed under dark incubation conditions to gauge the impact of T-DNA insertions on this physiological aspect.

RESULTS

The study revealed distinctive phenotypic outcomes associated with T-DNA insertions in HDR3, HDR3.1, GW2, and DA1. Specifically, HDR3 and HDR3.1 mutants exhibited significantly reduced plant height and smaller grain size, while GW2 and DA1 mutants displayed a notable increase in both plant height and grain size compared to the wild type variety Dongjin. Leaf senescence assays further indicated delayed leaf senescence in hdr3.1 mutants, contrasting with slightly earlier leaf senescence observed in hdr3 mutants under dark incubation.

CONCLUSIONS

The findings underscore the pivotal roles of DA1 orthologous genes in rice, shedding light on their significance in regulating plant growth and development. The observed phenotypic variations highlight the potential of these genes as targets for crop improvement strategies, offering insights that could contribute to the enhancement of agronomic traits in rice and potentially other crops.

Regulatory mechanism and molecular genetic dissection of rice (Oryza sativa L.) grain size

With the sharp increase of the global population, adequate food supply is a great challenge. Grain size is an essential determinant of rice yield and quality. It is a typical quantitative trait controlled by multiple genes. In this paper, we summarized the quantitative trait loci (QTL) that have been molecularly characterized and provided a comprehensive summary of the regulation mechanism and genetic pathways of rice grain size. These pathways include the ubiquitin-proteasome system, G-protein, mitogen-activated protein kinase, phytohormone, transcriptional factors, abiotic stress. In addition, we discuss the possible application of advanced molecular biology methods and reasonable breeding strategies, and prospective on the development of high-yielding and high-quality rice varieties using molecular biology techniques.

Dissecting the Genetic Basis of Yield Traits and Validation of a Novel Quantitative Trait Locus for Grain Width and Weight in Rice

Grain yield in rice is a complex trait and it is controlled by a number of quantitative trait loci (QTL). To dissect the genetic basis of rice yield, QTL analysis for nine yield traits was performed using an F2 population containing 190 plants, which was developed from a cross between Youyidao (YYD) and Sanfenhe (SFH), and each plant in the population evaluated with respect to nine yield traits. In this study, the correlations among the nine yield traits were analyzed. The grain yield per plant positively correlated with six yield traits, except for grain length and grain width, and showed the highest correlation coefficient of 0.98 with the number of filled grains per plant. A genetic map containing 133 DNA markers was constructed and it spanned 1831.7 cM throughout 12 chromosomes. A total of 36 QTLs for the yield traits were detected on nine chromosomes, except for the remaining chromosomes 5, 8, and 9. The phenotypic variation was explained by a single QTL that ranged from 6.19% to 36.01%. Furthermore, a major QTL for grain width and weight, qGW2-1, was confirmed to be newly identified and was narrowed down to a relatively smaller interval of about ~2.94-Mb. Collectively, we detected a total of 36 QTLs for yield traits and a major QTL, qGW2-1, was confirmed to control grain weight and width, which laid the foundation for further map-based cloning and molecular design breeding in rice.

Identification of qGL4.1 and qGL4.2, two closely linked QTL controlling grain length in rice

Grain size is an important appearance quality trait in rice, which also affects grain yield. In this study, a recombinant inbred line (RIL) population derived from a cross between indica variety 9311 and japonica variety Cypress was constructed. And 181 out of 600 RILs were sequenced, and a high-density genetic map containing 2842 bin markers was constructed, with a total map length of 1500.6 cM. A total of 10 quantitative trait loci (QTL) related to grain length (GL), grain width (GW), grain length-to-width ratio (LWR), and 1000-grain weight (TGW) were detected under two environments. The genetic effect of qGL4, a minor QTL for GL and TGW, was validated using three heterogeneous inbred family (HIF) segregation populations. It was further dissected into two closed linked QTL, qGL4.1 and qGL4.2. By progeny testing, qGL4.1 and qGL4.2 were successfully delimited to intervals of 1304-kb and 423-kb, respectively. Our results lay the foundation for the map-based cloning of qGL4.1 and qGL4.2 and provide new gene resources for the improvement of grain yield and quality in rice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01447-y.

miRNAs and genes as molecular regulators of rice grain morphology and yield

Rice is one of the most consumed crops worldwide and the genetic and molecular basis of its grain yield attributes are well understood. Various studies have identified different yield-related parameters in rice that are regulated by the microRNAs (miRNAs). MiRNAs are endogenous small non-coding RNAs that silence gene expression during or after transcription. They control a variety of biological or genetic activities in plants including growth, development and response to stress. In this review, we have summarized the available information on the genetic control of panicle architecture and grain yield (number and morphology) in rice. The miRNA nodes that are associated with their regulation are also described while focussing on the central role of miR156-SPL node to highlight the co-regulation of two master regulators that determine the fate of panicle development. Since abiotic stresses are known to negatively affect yield, the impact of abiotic stress induced alterations on the levels of these miRNAs are also discussed to highlight the potential of miRNAs for regulating crop yields.

Triacylglycerol lipase, OsSG34, plays an important role in grain shape and appearance quality in rice

Optimal grain-appearance quality is largely determined by grain size. To date, dozens of grain size-related genes have been identified. However, the regulatory mechanism of slender grain formation is not fully clear. We identified the OsSG34 gene by map-based cloning. A 9-bp deletion on 5'-untranslated region of OsSG34, which resulted in the expression difference between the wild-type and sg34 mutant, led to the slender grains and good transparency in sg34 mutant. OsSG34 as an α/β fold triacylglycerol lipase affected the triglyceride content directly, and the components of cell wall indirectly, especially the lignin between the inner and outer lemmas in rice grains, which could affect the change in grain size by altering cell proliferation and expansion, while the change in starch content and starch granule arrangement in endosperm could affect the grain-appearance quality. Moreover, the OsERF71 was identified to directly bind to cis-element on the mutant site, thereby regulating the OsSG34 expression. Knockout of three OsSG34 homologous genes resulted in slender grains as well. The study demonstrated OsSG34, involved in lipid metabolism, affected grain size and quality. Our findings suggest that the OsSG34 gene could be used in rice breeding for high yield and good grain-appearance quality via marker-assisted selection and gene-editing approaches.

2Gs and plant architecture: breaking grain yield ceiling through breeding approaches for next wave of revolution in rice (Oryza sativa L.)

Rice is a principal food crop for more than half of the global population. Grain number and grain weight (2Gs) are the two complex traits controlled by several quantitative trait loci (QTLs) and are considered the most critical components for yield enhancement in rice. Novel molecular biology and QTL mapping strategies can be utilized in dissecting the complex genetic architecture of these traits. Discovering the valuable genes/QTLs associated with 2Gs traits hidden in the rice genome and utilizing them in breeding programs may bring a revolution in rice production. Furthermore, the positional cloning and functional characterization of identified genes and QTLs may aid in understanding the molecular mechanisms underlying the 2Gs traits. In addition, knowledge of modern genomic tools aids the understanding of the nature of plant and panicle architecture, which enhances their photosynthetic activity. Rice researchers continue to combine important yield component traits (including 2Gs for the yield ceiling) by utilizing modern breeding tools, such as marker-assisted selection (MAS), haplotype-based breeding, and allele mining. Physical co-localization of GW7 (for grain weight) and DEP2 (for grain number) genes present on chromosome 7 revealed the possibility of simultaneous introgression of these two genes, if desirable allelic variants were found in the single donor parent. This review article will reveal the genetic nature of 2Gs traits and use this knowledge to break the yield ceiling by using different breeding and biotechnological tools, which will sustain the world's food requirements.

DGW1, encoding an hnRNP-like RNA binding protein, positively regulates grain size and weight by interacting with GW6 mRNA

Grain size and weight determine rice yield. Although numerous genes and pathways involved in regulating grain size have been identified, our knowledge of post-transcriptional control of grain size remains elusive. In this study, we characterize a rice mutant, decreased grain width and weight 1 (dgw1), which produces small grains. We show that DGW1 encodes a member of the heterogeneous nuclear ribonucleoprotein (hnRNP) family protein and preferentially expresses in developing panicles, positively regulating grain size by promoting cell expansion in spikelet hulls. Overexpression of DGW1 increases grain weight and grain numbers, leading to a significant rise in rice grain yield. We further demonstrate that DGW1 functions in grain size regulation by directly binding to the mRNA of Grain Width 6 (GW6), a critical grain size regulator in rice. Overexpression of GW6 restored the grain size phenotype of DGW1-knockout plants. DGW1 interacts with two oligouridylate binding proteins (OsUBP1a and OsUBP1b), which also bind the GW6 mRNA. In addition, the second RRM domain of DGW1 is indispensable for its mediated protein-RNA and protein-protein interactions. In summary, our findings identify a new regulatory module of DGW1-GW6 that regulates rice grain size and weight, providing important insights into the function of hnRNP-like proteins in the regulation of grain size.

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.)

The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.

Exploring the Effect of High-Energy Heavy Ion Beam on Rice Genome: Transposon Activation

High-energy heavy ion beams are a new type of physical mutagen that can produce a wide range of phenotypic variations. In order to understand the mechanism of high-energy heavy ion beams, we resequenced the whole genome of individual plants with obvious phenotypic variations in rice. The sequence alignment results revealed a large number of SNPs and InDels, as well as genetic variations related to grain type and heading date. The distribution of SNP and InDel on chromosomes is random, but they often occur in the up/downstream regions and the intergenic region. Mutagenesis can cause changes in transposons such as Dasheng, mPing, Osr13 and RIRE2, affecting the stability of the genome. This study obtained the major gene mutation types, discovered differentially active transposons, screened out gene variants related to phenotype, and explored the mechanism of high-energy heavy ion beam radiation on rice genes.

A rice variation map derived from 10 548 rice accessions reveals the importance of rare variants

Detailed knowledge of the genetic variations in diverse crop populations forms the basis for genetic crop improvement and gene functional studies. In the present study, we analyzed a large rice population with a total of 10 548 accessions to construct a rice super-population variation map (RSPVM), consisting of 54 378 986 single nucleotide polymorphisms, 11 119 947 insertion/deletion mutations and 184 736 presence/absence variations. Assessment of variation detection efficiency for different population sizes revealed a sharp increase of all types of variation as the population size increased and a gradual saturation of that after the population size reached 10 000. Variant frequency analysis indicated that ∼90% of the obtained variants were rare, and would therefore likely be difficult to detect in a relatively small population. Among the rare variants, only 2.7% were predicted to be deleterious. Population structure, genetic diversity and gene functional polymorphism of this large population were evaluated based on different subsets of RSPVM, demonstrating the great potential of RSPVM for use in downstream applications. Our study provides both a rich genetic basis for understanding natural rice variations and a powerful tool for exploiting great potential of rare variants in future rice research, including population genetics and functional genomics.

Negative regulators of grain yield and mineral contents in rice: potential targets for CRISPR-Cas9-mediated genome editing

Rice is a major global staple food crop, and improving its grain yield and nutritional quality has been a major thrust research area since last decades. Yield and nutritional quality are complex traits which are controlled by multiple signaling pathways. Sincere efforts during past decades of research have identified several key genetic and molecular regulators that governed these complex traits. The advent of clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-mediated gene knockout approaches has accelerated the development of improved varieties; however, finding out target gene with negative regulatory function in particular trait without giving any pleiotropic effect remains a challenge. Here, we have reviewed past and recent literature and identified important negative regulators of grain yield and mineral contents which could be potential targets for CRISPR-Cas9-mediated gene knockout. Additionally, we have also compiled a list of microRNAs (miRNAs), which target positive regulators of grain yield, plant stress tolerance, and grain mineral contents. Knocking out these miRNAs could help to increase expression of such positive regulators and thus improve the plant trait. The knowledge presented in this review would help to further accelerate the CRISPR-Cas9-mediated trait improvement in rice.

Structure and function of rice hybrid genomes reveal genetic basis and optimal performance of heterosis

Exploitation of crop heterosis is crucial for increasing global agriculture production. However, the quantitative genomic analysis of heterosis was lacking, and there is currently no effective prediction tool to optimize cross-combinations. Here 2,839 rice hybrid cultivars and 9,839 segregation individuals were resequenced and phenotyped. Our findings demonstrated that indica-indica hybrid-improving breeding was a process that broadened genetic resources, pyramided breeding-favorable alleles through combinatorial selection and collaboratively improved both parents by eliminating the inferior alleles at negative dominant loci. Furthermore, we revealed that widespread genetic complementarity contributed to indica-japonica intersubspecific heterosis in yield traits, with dominance effect loci making a greater contribution to phenotypic variance than overdominance effect loci. On the basis of the comprehensive dataset, a genomic model applicable to diverse rice varieties was developed and optimized to predict the performance of hybrid combinations. Our data offer a valuable resource for advancing the understanding and facilitating the utilization of heterosis in rice.

Fine mapping of qAHPS07 and functional studies of AhRUVBL2 controlling pod size in peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important oil and cash crop. Pod size is one of the major traits determining yield and commodity characteristic of peanut. Fine mapping of quantitative trait locus (QTL) and identification of candidate genes associated with pod size are essential for genetic improvement and molecular breeding of peanut varieties. In this study, a major QTL related to pod size, qAHPS07, was fine mapped to a 36.46 kb interval on chromosome A07 using F2 , recombinant inbred line (RIL) and secondary F2 populations. qAHPS07 explained 38.6%, 23.35%, 37.48%, 25.94% of the phenotypic variation for single pod weight (SPW), pod length (PL), pod width (PW) and pod shell thickness (PST), respectively. Whole genome resequencing and gene expression analysis revealed that a RuvB-like 2 protein coding gene AhRUVBL2 was the most likely candidate for qAHPS07. Overexpression of AhRUVBL2 in Arabidopsis led to larger seeds and plants than the wild type. AhRUVBL2-silenced peanut seedlings represented small leaves and shorter main stems. Three haplotypes were identified according to three SNPs in the promoter of AhRUVBL2 among 119 peanut accessions. Among them, SPW, PW and PST of accessions carrying Hap_ATT represent 17.6%, 11.2% and 26.3% higher than those carrying Hap_GAC，respectively. In addition, a functional marker of AhRUVBL2 was developed. Taken together, our study identified a key functional gene of peanut pod size, which provides new insights into peanut pod size regulation mechanism and offers practicable markers for the genetic improvement of pod size-related traits in peanut breeding.

Natural allelic variation in GRAIN SIZE AND WEIGHT 3 of wild rice regulates the grain size and weight

Grain size is important for yield in rice (Oryza sativa L.). Although many genes involved in grain size have been isolated, few can be used in breeding due to their interactions and phenotypic effects. Here, we describe natural variation in the granule-type quantitative trait locus GRAIN SIZE AND WEIGHT 3 (GSW3) located on chromosome 3 in wild rice (Oryza rufipogon Griff.) that encodes a GTPase-regulated protein and negatively regulates grain length, grain width, and 1,000-grain weight. The insertion of a 232-bp fragment of the genomic sequence in the wild rice, a natural allelic variant gene (GSW3), increased the expression levels and reduced the grain length and width and 1,000-grain weight. Knockout of GSW3 in the wild rice inbred line Huaye 3 increased the grain length and width and 1,000-grain weight. Introducing GSW3Huaye3 into cultivated rice line KJ01 and overexpressing GSW3Huaye3 in Huaye 3 resulted in reduced grain length and width and 1,000-grain weight, and grain size and 1,000-grain weight changes were closely related to GSW3 expression levels. GSW3 regulated the grain length and width simultaneously by promoting grain glume cell division and longitudinal and transverse cell growth. GSW3 was also involved in regulating the gibberellic acid signaling pathway and negatively regulated plant growth. Furthermore, a critical SNP in the GSW3 coding region was obviously correlated with grain size variation in a core collection of cultivated rice. This SNP resulted in an amino acid substitution from Gln to Arg at position 161 in GSW3, which reduced the grain size. Our study shows that GSW3 negatively regulates the grain shape, which could explain different grain shapes in modern cultivars and wild rice. GSW3 may also be used for breeding rice varieties with improved grain shapes and higher yield.

GS6.1 controls kernel size and plant architecture in rice

MAIN CONCLUSION

A novel QTL GS6.1 increases yield per plant by controlling kernel size, plant architecture, and kernel filling in rice. Kernel size and plant architecture are critical agronomic traits that greatly influence kernel yield in rice. Using the single-segment substitution lines (SSSLs) with an indica cultivar Huajingxian74 as a recipient parent and American Jasmine as a donor parent, we identified a novel quantitative trait locus (QTL), named GS6.1. Near isogenic line-GS6.1 (NIL-GS6.1) produces long and narrow kernels by regulating cell length and width in the spikelet hulls, thus increasing the 1000-kernel weight. Compared with the control, the plant height, panicles per plant, panicle length, kernels per plant, secondary branches per panicle, and yield per plant of NIL-GS6.1 are increased. In addition, GS6.1 regulates the kernel filling rate. GS6.1 controls kernel size by modulating the transcription levels of part of EXPANSINs, kernel filling-related genes, and kernel size-related genes. These results indicate that GS6.1 might be beneficial for improving kernel yield and plant architecture in rice breeding by molecular design.

Transfer of Stress Resilient QTLs and Panicle Traits into the Rice Variety, Reeta through Classical and Marker-Assisted Breeding Approaches

Reeta is a popular late-maturing high-yielding rice variety recommended for cultivation in the eastern Indian states. The cultivar is highly sensitive to submergence stress. Phosphorus deficiency is an additional constraint for realizing high yield. The quantitative trait loci (QTLs), Sub1, for submergence and Pup1 for low phosphorus stress tolerance along with narrow-grained trait, GW5 were introgressed into the variety from the donor parent, Swarna-Sub1 through marker-assisted breeding. In addition, phenotypic selections for higher panicle weight, grain number, and spikelet fertility were performed in each segregating generation. Foreground selection detected the 3 target QTLs in 9, 8 and 7 progenies in the BC₁F₁, BC₂F₁, and BC₃F₁ generation, respectively. Recurrent parent's genome recovery was analyzed using 168 SSR polymorphic markers. The foreground analysis in 452 BC₃F₂ progenies showed five pyramided lines in homozygous condition for the target QTLs. No donor fragment drag was noticed in the Sub1 and GW5 QTLs carrier while a segmentwas observed in the Pup1 carrier chromosome. The developed lines were higher yielding, had submergence, and had low phosphorus stress-tolerance alongwith similar to the recipient parent in the studied morpho-quality traits. A promising pyramided line is released in the name of Reeta-Panidhan (CR Dhan 413) for the flood-prone areas of Odisha state.

Genetic dissection of thousand-seed weight in linseed (Linum usitatissimum L.) using multi-locus genome-wide association study

Flaxseed/linseed is an important oilseed crop having applications in the food, nutraceutical, and paint industry. Seed weight is one of the most crucial determinants of seed yield in linseed. Here, quantitative trait nucleotides (QTNs) associated with thousand-seed weight (TSW) have been identified using multi-locus genome-wide association study (ML-GWAS). Field evaluation was carried out in five environments in multi-year-location trials. SNP genotyping information of the AM panel of 131 accessions comprising 68,925 SNPs was employed for ML-GWAS. From the six ML-GWAS methods employed, five methods helped identify a total of 84 unique significant QTNs for TSW. QTNs identified in ≥ 2 methods/environments were designated as stable QTNs. Accordingly, 30 stable QTNs have been identified for TSW accounting up to 38.65% trait variation. Alleles with positive effect on trait were analyzed for 12 strong QTNs with r ² ≥ 10.00%, which showed significant association of specific alleles with higher trait value in three or more environments. A total of 23 candidate genes have been identified for TSW, which included B3 domain-containing transcription factor, SUMO-activating enzyme, protein SCARECROW, shaggy-related protein kinase/BIN2, ANTIAUXIN-RESISTANT 3, RING-type E3 ubiquitin transferase E4, auxin response factors, WRKY transcription factor, and CBS domain-containing protein. In silico expression analysis of candidate genes was performed to validate their possible role in different stages of seed development process. The results from this study provide significant insight and elevate our understanding on genetic architecture of TSW trait in linseed.

TaTPP-7A positively feedback regulates grain filling and wheat grain yield through T6P-SnRK1 signalling pathway and sugar-ABA interaction

Grain size and filling are two key determinants of grain thousand-kernel weight (TKW) and crop yield, therefore they have undergone strong selection since cereal was domesticated. Genetic dissection of the two traits will improve yield potential in crops. A quantitative trait locus significantly associated with wheat grain TKW was detected on chromosome 7AS flanked by a simple sequence repeat marker of Wmc17 in Chinese wheat 262 mini-core collection by genome-wide association study. Combined with the bulked segregant RNA-sequencing (BSR-seq) analysis of an F₂ genetic segregation population with extremely different TKW traits, a candidate trehalose-6-phosphate phosphatase gene located at 135.0 Mb (CS V1.0), designated as TaTPP-7A, was identified. This gene was specifically expressed in developing grains and strongly influenced grain filling and size. Overexpression (OE) of TaTPP-7A in wheat enhanced grain TKW and wheat yield greatly. Detailed analysis revealed that OE of TaTPP-7A significantly increased the expression levels of starch synthesis- and senescence-related genes involved in abscisic acid (ABA) and ethylene pathways. Moreover, most of the sucrose metabolism and starch regulation-related genes were potentially regulated by SnRK1. In addition, TaTPP-7A is a crucial domestication- and breeding-targeted gene and it feedback regulates sucrose lysis, flux, and utilization in the grain endosperm mainly through the T6P-SnRK1 pathway and sugar-ABA interaction. Thus, we confirmed the T6P signalling pathway as the central regulatory system for sucrose allocation and source-sink interactions in wheat grains and propose that the trehalose pathway components have great potential to increase yields in cereal crops.

Armadillo repeat only protein GS10 negatively regulates brassinosteroid signaling to control rice grain size

Grain yield and grain quality are major determinants in modern breeding controlled by many quantitative traits loci (QTLs) in rice (Oryza sativa). However, the mechanisms underlying grain shape and quality are poorly understood. Here, we characterize a QTL for grain size and grain quality via map-based cloning from wild rice (W1943), GS10 (Grain Size on Chromosome 10), which encodes a protein with 6 tandem armadillo repeats. The null mutant gs10 shows slender and narrow grains with altered cell size, which has a pleiotropic effect on other agronomical traits. Functional analysis reveals that GS10 interacts with TUD1 (Taihu Dwarf1) and is epistatic to OsGSK2 (glycogen synthase kinase 2) through regulating grain shape and lamina joint inclination, indicating it is negatively involved in brassinosteroid (BR) signaling. Pyramiding gs10 and the grain size gene GW5 into cultivar GLA4 substantially improved grain shape and appearance quality. Natural variation analysis revealed that gs10 from the wild rice Oryza rufipogon W1943 is a rare allele across the rice population. Collectively, these findings advance our understanding of the underlying mechanism of grain shape and provide the beneficial allele of gs10 for future rice breeding and genetic improvement.

Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding

It is hypothesized that the genome-wide genic markers may increase the prediction accuracy of genomic selection for quantitative traits. To test this hypothesis, a set of candidate gene-based markers for yield and grain traits-related genes cloned across the rice genome were custom-designed. A multi-model, multi-locus genome-wide association study (GWAS) was performed using new genic markers developed to test their effectiveness for gene discovery. Two multi-locus models, FarmCPU and mrMLM, along with a single-locus mixed linear model (MLM), identified 28 significant marker-trait associations. These associations revealed novel causative alleles for grain weight and pleiotropic associations with other traits. For instance, the marker YD91 derived from the gene OsAAP3 on chromosome 1 was consistently associated with grain weight, while the gene has a significant effect on grain yield. Furthermore, nine genomic selection methods, including regression-based and machine learning-based models, were used to predict grain weight using a leave-one-out five-fold cross-validation approach to optimize the genomic selection model with genic markers. Among nine prediction models, Kernel Hilbert Space Regression (RKHS) is the best among regression-based models, and Random Forest Regression (RFR) is the best among machine learning-based models. Genomic prediction accuracies with and without GWAS significant markers were compared to assess the effectiveness of markers. The rapid decreases in prediction accuracy upon dropping GWAS significant markers indicate the effectiveness of new genic markers in genomic selection. Apart from that, the candidate gene-based markers were found to be more effective in genomic selection programs for better accuracy.

Grain quality characteristics analysis and application on breeding of Yuenongsimiao, a high-yielding and disease-resistant rice variety

Rice quality is one of the main targets of rice breeding and is a complex trait that involves grain appearance, milling, cooking, eating and nutritional quality. For many years, rice breeding has contended with imbalances in rice yield, quality, and disease and lodging resistance. Here, the milling and appearance quality, cooking quality, starch rapid viscosity analyzer (RVA) profile, and nutritional quality of grains of Yuenongsimiao (YNSM), an indica rice variety with high yield, high quality and disease resistance, were determined. YNSM had excellent appearance and quality, with low amylose contents and high gel consistency, and these characteristics exhibited significant correlations with the RVA profile such as hot paste viscosity, cool paste viscosity, setback viscosity, and consistency. Moreover, 5 genes related to length-to-width ratio (LWR) as well as the Wx gene were used to detect the main quality genotype of YNSM. The results showed that YNSM is a semilong-grain rice with a relatively high brown rice rate, milled rice rate and head rice yield and low chalkiness. The results indicated that the LWR and food quality of YNSM might be related to gs3, gw7 and Wx^b. This study also reports the quality characteristics of hybrid rice developed using YNSM as a restorer line. The quality characteristics and the genotype for grain quality determined through gene analysis in YNSM may facilitate the breeding of new rice varieties that achieve a balance of grain yield, resistance and quality.

Genetic Diversity and Association Mapping of Grain-Size Traits in Rice Landraces from the Honghe Hani Rice Terraces System in Yunnan Province

The Honghe Hani Rice Terraces System (HHRTS) of Yunnan Province is an important agricultural and cultural heritage landscape. Until now, a large number of local rice landraces have been planted. Mining excellent genes contained in these landraces provides a reference for variety improvement and new variety breeding. In this study, 96 rice landraces collected from the Hani terraces were planted in Honghe Mengzi, Yunnan Province, in 2013, 2014, 2015, and 2021, and five major grain traits were measured and analyzed. The genomic variation of 96 rice landraces was scanned by 201 simple sequence repeat (SSR) markers. The genetic diversity, population structure, and genetic relationships of the natural population were analyzed. The mixed linear model (MLM) method of the TASSEL software was used to analyze the associations between markers and traits. A total of 936 alleles were amplified by 201 pairs of SSR primers. The average number of observed alleles (Na), the effective number of alleles (Ne), Shannon's information index (I), heterozygosity (H), and the polymorphism information content (PIC) per marker were 4.66, 2.71, 1.08, 0.15, and 0.55, respectively. Ninety-six landraces were divided into two groups by population structure, clustering, and principal component analysis, and indica rice was the main group. The coefficients of variation of the five traits ranged from 6.80 to 15.24%, and their broad heritabilities were more than 70%. In addition, there were positive correlations among the same grain traits between different years. Through MLM analysis, 2, 36, 7, 7, and 4 SSR markers were significantly associated with grain length (GL), grain width (GW), grain thickness (GT), grain length-width ratio (LWR), and thousand-grain weight (TGW), respectively. The explanation rates of phenotypic variation were 16.31 (RM449, Chr. 1)-23.51% (RM316, Chr. 9), 10.84 (RM523, Chr. 3; RM161/RM305, Chr. 5)-43.01% (RM5496, Chr. 1), 11.98 (RM161/RM305, Chr. 5)-24.72% (RM275, Chr. 6), 12.68 (RM126, Chr. 8)-36.96% (RM5496, Chr. 1), and 17.65 (RM4499, Chr. 2)-26.32% (RM25, Chr. 8), respectively. The associated markers were distributed on 12 chromosomes of the genome.

Application of a Novel Quantitative Trait Locus Combination to Improve Grain Shape without Yield Loss in Rice (Oryza sativa L. spp. japonica)

Grain shape is one of the key factors deciding the yield product and the market value as appearance quality in rice (Oryza sativa L.). The grain shape of japonica cultivars in Korea is quite monotonous because the selection pressure of rice breeding programs works in consideration of consumer preference. In this study, we identified QTLs associated with grain shape to improve the variety of grain shapes in Korean cultivars. QTL analysis revealed that eight QTLs related to five tested traits were detected on chromosomes 2, 5, and 10. Among them, three QTLs-qGL2 (33.9% of PEV for grain length), qGW5 (64.42% for grain width), and qGT10 (49.2% for grain thickness)-were regarded as the main effect QTLs. Using the three QTLs, an ideal QTL combination (qGL2^P + qGW5^P + qGT10^B) could be constructed on the basis of the accumulated QTL effect without yield loss caused by the change in grain shape in the population. In addition, three promising lines with a slender grain type were selected as a breeding resource with a japonica genetic background based on the QTL combination. The application of QTLs detected in this study could improve the grain shape of japonica cultivars without any linkage drag or yield loss.

A chromosome-level genome assembly of an early matured aromatic Japonica rice variety Qigeng10 to accelerate rice breeding for high grain quality in Northeast China

Early-matured aromatic japonica rice from the Northeast is the most popular rice commodity in the Chinese market. The Qigeng10 (QG10) was one of the varieties with the largest planting area in this region in recent years. It was an early-matured japonica rice variety with a lot of superior traits such as semi-dwarf, lodging resistance, long grain, aromatic and good quality. Therefore, a high-quality assembly of Qigeng10 genome is critical and useful for japonica research and breeding. In this study, we produced a high-precision QG10 chromosome-level genome by using a combination of Nanopore and Hi-C platforms. Finally, we assembled the QG10 genome into 77 contigs with an N50 length of 11.80 Mb in 27 scaffolds with an N50 length of 30.55 Mb. The assembled genome size was 378.31Mb with 65 contigs and constituted approximately 99.59% of the 12 chromosomes. We identified a total of 1,080,819 SNPs and 682,392 InDels between QG10 and Nipponbare. We also annotated 57,599 genes by the Ab initio method, homology-based technique, and RNA-seq. Based on the assembled genome sequence, we detected the sequence variation in a total of 63 cloned genes involved in grain yield, grain size, disease tolerance, lodging resistance, fragrance, and many other important traits. Finally, we identified five elite alleles (qTGW2^Nipponbare , qTGW3^Nanyangzhan , GW5^IR24 , GW6^Suyunuo , and qGW8^Basmati385 ) controlling long grain size, four elite alleles (COLD1^Nipponbare , bZIP73^Nipponbare , CTB4a^{Kunmingxiaobaigu} , and CTB2^{Kunmingxiaobaigu} ) controlling cold tolerance, three non-functional alleles (DTH7^Kitaake , Ghd7^Hejiang19 , and Hd1^Longgeng31 ) for early heading, two resistant alleles (Pia^Akihikari and Pid4^Digu ) for rice blast, a resistant allele STV11^Kasalath for rice stripe virus, an NRT1.1B^IR24 allele for higher nitrate absorption activity, an elite allele SCM3^Chugoku117 for stronger culms, and the typical aromatic gene badh2-E2 for fragrance in QG10. These results not only help us to better elucidate the genetic mechanisms underlying excellent agronomic traits in QG10 but also have wide-ranging implications for genomics-assisted breeding in early-matured fragrant japonica rice.

Identification, Fine Mapping and Application of Quantitative Trait Loci for Grain Shape Using Single-Segment Substitution Lines in Rice (Oryza sativa L.)

Quantitative trait loci (QTLs) and HQTL (heterosis QTLs) for grain shape are two major genetic factors of grain yield and quality in rice (Oryza sativa L.). Although many QTLs for grain shape have been reported, only a few are applied in production. In this study, 54 QTLs for grain shape were detected on 10 chromosomes using 33 SSSLs (single-segment substitution lines) and methods of statistical genetics. Among these, 23 exhibited significant positive additive genetic effects, including some novel QTLs, among which qTGW4-(1,2), qTGW10-2, and qTGW10-3 were three QTLs newly found in this study and should be paid more attention. Moreover, 26 HQTLs for grain shape were probed. Eighteen of these exhibited significant positive dominant genetic effects. Thirty-three QTLs for grain shape were further mapped using linkage analysis. Most of the QTLs for grain shape produced pleiotropic effects, which simultaneously controlled multiple appearance traits of grain shape. Linkage mapping of the F₂ population derived from sub-single-segment substitution lines further narrowed the interval harbouring qTGW10-3 to 75.124 kb between PSM169 and RM25753. The candidate gene was identified and could be applied to breeding applications by molecular marker-assisted selection. These identified QTLs for grain shape will offer additional insights for improving grain yield and quality in rice breeding.

Integration of Auxin, Brassinosteroid and Cytokinin in the Regulation of Rice Yield

Crop varieties with a high yield are most desirable in the present context of the ever-growing human population. Mostly, the yield traits are governed by a complex of numerous molecular and genetic facets modulated by various quantitative trait loci (QTLs). With the identification and molecular characterizations of yield-associated QTLs over recent years, the central role of phytohormones in regulating plant yield is becoming more apparent. Most often, different groups of phytohormones work in close association to orchestrate yield attributes. Understanding this cross talk would thus provide new venues for phytohormone pyramiding by editing a single gene or QTL(s) for yield improvement. Here, we review a few important findings to integrate the knowledge on the roles of auxin, brassinosteroid and cytokinin and how a single gene or a QTL could govern cross talk among multiple phytohormones to determine the yield traits.

Integrating linkage mapping and comparative transcriptome analysis for discovering candidate genes associated with salt tolerance in rice

Salinity is one of the most widespread abiotic stresses affecting rice productivity worldwide. Understanding the genetic basis of salt tolerance is key for breeding salt-tolerant rice varieties. Numerous QTLs have been identified to help dissect rice salt-tolerance genetic mechanisms, yet only rare genes located in significant QTLs have been thoroughly studied or fine-mapped. Here, a combination of linkage mapping and transcriptome profiling analysis was used to identify salt tolerance-related functional candidate genes underlying stable QTLs. A recombinant inbred line (RIL) population derived from a cross between Jileng 1 (salt-sensitive) and Milyang 23 (salt-tolerant) was constructed. Subsequently, a high-density genetic map was constructed by using 2921 recombination bin markers developed from whole genome resequencing. A total of twelve QTLs controlling the standard evaluation score under salt stress were identified by linkage analysis and distributed on chromosomes 2, 3, 4, 6, 8 and 11. Notably, five QTL intervals were detected as environmentally stable QTLs in this study, and their functions were verified by comparative transcriptome analysis. By comparing the transcriptome profiles of the two parents and two bulks, we found 551 salt stress-specific differentially expressed genes. Among them, fifteen DEGs located in stable QTL intervals were considered promising candidate genes for salt tolerance. According to gene annotations, the gene OsRCI2-8(Os06g0184800) was the most promising, as it is known to be associated with salt stress, and its differential expression between the tolerant and sensitive RIL bulks highlights its important role in salt stress response pathways. Our findings provide five stable salt tolerance-related QTLs and one promising candidate gene, which will facilitate breeding for improved salt tolerance in rice varieties and promote the exploration of salt stress tolerance mechanisms in rice.

Genome-Wide Association Study of Rice Grain Shape and Chalkiness in a Worldwide Collection of Xian Accessions

Rice (Oryza sativa L.) appearance quality, which is mainly defined by grain shape and chalkiness, is an important target in rice breeding. In this study, we first re-sequenced 137 indica accessions and then conducted a genome-wide association study (GWAS) for six agronomic traits with the 2,998,034 derived single nucleotide polymorphisms (SNPs) by using the best linear unbiased prediction (BLUP) values for each trait. The results revealed that 195 SNPs had significant associations with the six agronomic traits. Based on the genome-wide linkage disequilibrium (LD) blocks, candidate genes for the target traits were detected within 100 kb upstream and downstream of the relevant SNP loci. Results indicate that six quantitative trait loci (QTLs) significantly associated with six traits (qTGW4.1, qTGW4.2, qGL4.1, qGL12.1, qGL12.2, qGW2.1, qGW4.1, qGW6.1, qGW8.1, qGW8.2, qGW9.1, qGW11.1, qGLWR2.1, qGLWR2.2, qGLWR4.2, qPGWC5.1 and qDEC6.1) were identified for haplotype analysis. Among these QTLs, two (qTGW4.2 and qGW6.1), were overlapped with FLO19 and OsbZIP47, respectively, and the remaining four were novel QTLs. These candidate genes were further validated by haplotype block construction.

Artificially Selected Grain Shape Gene Combinations in Guangdong Simiao Varieties of Rice (Oryza sativa L.)

BACKGROUND

Grain shape is a key trait in rice breeding. Although many QTLs and genes of grain shape have been identified, how different combinations of alleles of these genes affect grain shape is largely unknown. It is important to understand the effects of grain shape gene combinations for breeding by design. In the present study, we performed genetic dissection of the grain shapes in Guangdong Simiao varieties, a popular kind of rice in South China, to identify the effective alleles and their combination for breeding.

RESULTS

We selected two hundred nineteen indica accessions with diverse grain shapes and fifty-two Guangdong Simiao varieties with long and slender grain shapes for genome-wide selection analysis. The results showed that four (GS3, GS5, GW5 and GL7) of the twenty grain shape genes fall into the regions selected for in Guangdong Simiao varieties. Allele analysis and frequency distribution of these four genes showed that GS3allele3 and GW5allele2 accounted for 96.2%, and GL7allele2 and GS5allele2 accounted for 76.9% and 74.5% of the Simiao varieties, respectively. Further analysis of the allelic combinations showed that 30 allelic combinations were identified in the whole panel, with 28 allelic combinations found in the international indica accessions and 6 allelic combinations found in Guangdong Simiao varieties. There were mainly three combinations (combinations 17, 18 and 19) in the Guangdong Simiao varieties, with combination 19 (GS3allele3 + GW5allele2 + GL7allele2 + GS5allele2) having the highest percentage (51.9%). All three combinations carried GS3allele3 + GW5allele2, while combinations 17 (GL7allele1) and 19 (GL7allele2) showed significant differences in both grain length and length/width ratio due to differences in GL7 alleles. Pedigree analysis of Guang8B, the maintainer of the first released Simiao male sterile line Guang8A, showed that the parent lines and Guang8B carried GS3allele3 + GW5allele2 + GS5allele2, while the GL7 allele differed, resulting in significant differences in grain size.

CONCLUSION

The results suggest that specific alleles of GS3, GS5, GW5 and GL7 are the key grain shape genes used in the Guangdong Simiao varieties and selected for grain shape improvement. Combination 19 is the predominant allelic combination in the Guangdong Simiao varieties. Our current study is the first to dissect the genetics of grain shape in Guangdong Simiao varieties, and the results will facilitate molecular breeding of Guangdong Simiao varieties.

Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments

INTRODUCTION

The seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear.

METHODS

To understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining.

RESULTS

A total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis.

DISCUSSION

The results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits.

A Systemic Investigation of Genetic Architecture and Gene Resources Controlling Kernel Size-Related Traits in Maize

Grain yield is the most critical and complex quantitative trait in maize. Kernel length (KL), kernel width (KW), kernel thickness (KT) and hundred-kernel weight (HKW) associated with kernel size are essential components of yield-related traits in maize. With the extensive use of quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) analyses, thousands of QTLs and quantitative trait nucleotides (QTNs) have been discovered for controlling these traits. However, only some of them have been cloned and successfully utilized in breeding programs. In this study, we exhaustively collected reported genes, QTLs and QTNs associated with the four traits, performed cluster identification of QTLs and QTNs, then combined QTL and QTN clusters to detect consensus hotspot regions. In total, 31 hotspots were identified for kernel size-related traits. Their candidate genes were predicted to be related to well-known pathways regulating the kernel developmental process. The identified hotspots can be further explored for fine mapping and candidate gene validation. Finally, we provided a strategy for high yield and quality maize. This study will not only facilitate causal genes cloning, but also guide the breeding practice for maize.

Rice Pangenome Genotyping Array: an efficient genotyping solution for pangenome-based accelerated genetic improvement in rice

The advent of the pangenome era has unraveled previously unknown genetic variation existing within diverse crop plants, including rice. This untapped genetic variation is believed to account for a major portion of phenotypic variation existing in crop plants. However, the use of conventional single reference-guided genotyping often fails to capture a large portion of this genetic variation leading to a reference bias. This makes it difficult to identify and utilize novel population/cultivar-specific genes for crop improvement. Thus, we developed a Rice Pangenome Genotyping Array (RPGA) harboring probes assaying 80K single-nucleotide polymorphisms (SNPs) and presence-absence variants spanning the entire 3K rice pangenome. This array provides a simple, user-friendly and cost-effective (60-80 USD per sample) solution for rapid pangenome-based genotyping in rice. The genome-wide association study (GWAS) conducted using RPGA-SNP genotyping data of a rice diversity panel detected a total of 42 loci, including previously known as well as novel genomic loci regulating grain size/weight traits in rice. Eight of these identified trait-associated loci (dispensable loci) could not be detected with conventional single reference genome-based GWAS. A WD repeat-containing PROTEIN 12 gene underlying one of such dispensable locus on chromosome 7 (qLWR7) along with other non-dispensable loci were subsequently detected using high-resolution quantitative trait loci mapping confirming authenticity of RPGA-led GWAS. This demonstrates the potential of RPGA-based genotyping to overcome reference bias. The application of RPGA-based genotyping for population structure analysis, hybridity testing, ultra-high-density genetic map construction and chromosome-level genome assembly, and marker-assisted selection was also demonstrated. A web application (http://www.rpgaweb.com) was further developed to provide an easy to use platform for the imputation of RPGA-based genotyping data using 3K rice reference panel and subsequent GWAS.

Genome-wide association mapping and gene expression analysis reveal candidate genes for grain chalkiness in rice

Grain chalkiness is the main factor determining the market value of rice. Reducing chalkiness is an important breeding goal for genetic improvement of high quality rice. Identification of QTLs or genes controlling chalkiness is the prerequisite for molecular breeding in rice. Here, we conducted a genome-wide association study to identify QTLs associated with grain chalkiness including percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC) in 450 rice accessions consisting of 300 indica and 150 japonica rice in two environments. A total of 34 QTLs were identified, including 14 QTLs for PGWC and 20 QTLs for DEC. Among them, seven QTLs were commonly identified in two environments, and eight QTLs were simultaneously related to two traits. Based on the haplotype analysis, LD decay analysis, RNA-sequencing, qRT-PCR confirmation and haplotype comparisons, four genes (LOC_Os10g36170, LOC_Os10g36260, LOC_Os10g36340 and LOC_Os10g36610) were considered as the candidate genes for qDEC-10c^1w,2wj , which could be identified in both environments and had the most significant p-value among the newly identified QTLs. These results provided new insight into the genetic basis of grain chalkiness and gene resources for improving quality by molecular breeding in rice.

Detecting and pyramiding target QTL for plant- and grain-related traits via chromosomal segment substitution line of rice

INTRODUCTION

Plant height and grain length are important agronomic traits in rice, exhibiting a strong effect on plant architecture and grain quality of rice varieties.

METHODS

Methods: A novel rice chromosomal segment substitution line (CSSL), i.e., CSSL-Z1357, with significantly increased plant height (PH) and grain length (GL) was identified from CSSLs constructed by using Nipponbare as a receptor and a restorer line Xihui 18 as a donor. Seven agronomic traits of PH, PL, GL, GW, GPP, SPP, and TGW were phenotyped, and REML implemented in HPMIXED of SAS were used to detect the QTL for these traits. Secondary CSSLs were screened out via marker-assisted selection (MAS) to estimate the additive and epistatic effects of detected QTLs, evaluating the potential utilization of pyramiding the target QTLs for yield and quality improvement of rice varieties.

RESULTS AND DISCUSSION

Results and Discussion: CSSL-Z1357 carried nine segments from Xihui 18 with an average segment length of 4.13 Mb. The results show that the long grain of CSSL-Z1357 was caused by the increased number of surface cells and the length of the inner glume. Thirteen quantitative trait loci were identified via the F2 population of Nipponbare/CSSL-Z1357, including three each for GL (qGL-3, qGL-6, and qGL-7) and PH (qPH-1, qPH-7, and qPH-12I), among which qGL-3 increased GL by 0.23 mm with synergistic allele from CSSL-Z1357. Additionally, three single (S1 to S3), two double (D1, D2), and one triple segment (T1) substitution lines were developed in F3 via MAS. Results show that pyramiding the segments from Chr.3 (qGL-3 and qPH-3), Chr.6 (qGL-6 and qPH-6), and Chr.7 (Null and qPH-7) tended to result in better phenotype of increased GL and PH and decreased grain width, providing a potential basis for enhancing grain yield and quality in rice breeding.

Identification of quantitative trait loci for important agronomic traits using chromosome segment substitution lines from a japonica × indica cross in rice

Asian cultivated rice (Oryza sativa L.) has two subspecies, indica and japonica, which display clear differences in yield-related traits and environmental adaptation. Here, we developed a set of chromosome segment substitution lines (CSSLs) from an advanced backcross between japonica variety C418, as the recipient, and indica variety IR24, as the donor. Through evaluating the genotypes and phenotypes of 181 CSSLs, a total of 85 quantitative trait loci (QTLs) for 14 yield-related traits were detected, with individual QTLs explaining from 6.2 to 42.9% of the phenotypic variation. Moreover, twenty-six of these QTLs could be detected in the two trial sites (Beijing and Hainan). Among these loci, the QTLs for flag leaf width and effective tiller number, qFLW4.2 and qETN4.2, were delimited to an approximately 256-kb interval on chromosome 4. Through a comparison of nucleotide sequences and expression levels in "C418" and the CSSL CR31 containing qFLW4.2 and qETN4.2, we found that the NAL1 (LOC_Os04g52479) gene was the candidate gene for qFLW4.2 and qETN4.2. Our results show that CSSLs are powerful tools for identifying and fine-mapping QTLs, while the novel QTLs identified in this study will also provide new genetic resources for rice improvement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01343-3.

Control of Grain Weight and Size in Rice (Oryza sativa L.) by OsPUB3 Encoding a U-Box E3 Ubiquitin Ligase

Grain weight and size, mostly determined by grain length, width and thickness, are crucial traits affecting grain quality and yield in rice. A quantitative trait locus controlling grain length and width in rice, qGS1-35.2, was previously fine-mapped in a 57.7-kb region on the long arm of chromosome 1. In this study, OsPUB3, a gene encoding a U-box E3 ubiquitin ligase, was validated as the causal gene for qGS1-35.2. The effects were confirmed firstly by using CRISPR/Cas9-based mutagenesis and then through transgenic complementation of a Cas9-free knock-out (KO) mutant. Two homozygous KO lines were produced, each having a 1-bp insertion in OsPUB3 which caused frameshift mutation and premature termination. Compared with the recipient and a transgenic-negative control, both mutants showed significant decreases in grain weight and size. In transgenic complementation populations derived from four independent T₀ plants, grain weight of transgenic-positive plants was significantly higher than transgenic-negative plants, coming with increased grain length and a less significant decrease in grain width. Based on data documented in RiceVarMap V2.0, eight haplotypes were classified according to six single-nucleotide polymorphisms (SNPs) found in the OsPUB3 coding region of 4695 rice accessions. Significant differences on grain size traits were detected between the three major haplotypes, Hap1, Hap2 and Hap3 that jointly occupy 98.6% of the accessions. Hap3 having the largest grain weight and grain length but intermediate grain width exhibits a potential for simultaneously improving grain yield and quality. In another set of 257 indica rice cultivars tested in our study, Hap1 and Hap2 remained to be the two largest groups. Their differences on grain weight and size were significant in the background of non-functional gse5, but non-significant in the background of functional GSE5, indicating a genetic interaction between OsPUB3 and GSE5. Cloning of OsPUB3 provides a new gene resource for investigating the regulation of grain weight and size.

Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice

Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations.

Developing Genetic Engineering Techniques for Control of Seed Size and Yield

Many signaling pathways regulate seed size through the development of endosperm and maternal tissues, which ultimately results in a range of variations in seed size or weight. Seed size can be determined through the development of zygotic tissues (endosperm and embryo) and maternal ovules. In addition, in some species such as rice, seed size is largely determined by husk growth. Transcription regulator factors are responsible for enhancing cell growth in the maternal ovule, resulting in seed growth. Phytohormones induce significant effects on entire features of growth and development of plants and also regulate seed size. Moreover, the vegetative parts are the major source of nutrients, including the majority of carbon and nitrogen-containing molecules for the reproductive part to control seed size. There is a need to increase the size of seeds without affecting the number of seeds in plants through conventional breeding programs to improve grain yield. In the past decades, many important genetic factors affecting seed size and yield have been identified and studied. These important factors constitute dynamic regulatory networks governing the seed size in response to environmental stimuli. In this review, we summarized recent advances regarding the molecular factors regulating seed size in Arabidopsis and other crops, followed by discussions on strategies to comprehend crops' genetic and molecular aspects in balancing seed size and yield.