Importance of the Interaction between Heading Date Genes Hd1 and Ghd7 for Controlling Yield Traits in Rice

Allelic combinations of Hd1, Hd16, and Ghd7 exhibit pleiotropic effects on agronomic traits in rice

Heading date is a critical agronomic trait that significantly affects grain yield and quality in rice. As early heading is typically associated with reduced yield due to shorter growth duration, it is essential to harness optimum heading date genes and their allelic combinations to promote heading while minimizing yield penalties. In this study, we identified quantitative trait loci (QTLs) for heading date and other major agronomic traits in a recombinant inbred line (RIL) population derived from a cross between Koshihikari and Baegilmi. Analyses on 3 major QTLs for heading date and their underlying genes (Hd1, Hd16, and Ghd7) revealed their pleiotropic effects on culm length, panicle length, and head rice percentage. Additionally, Ghd7 exhibited pleiotropic effects on panicle number and grain size. Among 8 different types of allelic combinations of the 3 heading date genes, RILs carrying a single nonfunctional hd16 or ghd7 under the functional background of the other 2 genes (Hd1hd16Ghd7 and Hd1Hd16ghd7) showed potential for maintaining yield and quality-related traits while accelerating heading. These results provide valuable insights for fine-tuning heading dates in rice breeding programs.

QTL epistasis plays a role of homeostasis on heading date in rice

If there was no gene interaction, the gene aggregation effect would increase infinitely with the increase of gene number. Epistasis avoids the endless accumulation of gene effects, playing a role of homeostasis. To confirm the role, QTL epistases were analyzed by four single-segment substitution lines with heading date QTLs in this paper. We found that QTLs of three positive effects and one negative effect generated 62.5% negative dual QTL epistatic effects and 57.7% positive triple QTL epistatic effects, forming the relationship "positive QTLs-negative one order interactions-positive two order interactions". In this way, the aggregation effect of QTLs was partially neutralized by the opposite epistatic effect sum. There also were two exceptions, QTL OsMADS50 and gene Hd3a-2 were always with consistent effect directions with their epistases, implying they could be employed in pyramiding breeding with different objectives. This study elucidated the mechanism of epistatic interactions among four QTLs and provided valuable genetic resources for improving heading date in rice.

Phenotypic variation and genome-wide association studies of main culm panicle node number, maximum node production rate, and degree-days to heading in rice

Background

Grain yield is a complex trait that results from interaction between underlying phenotypic traits and climatic, edaphic, and biotic variables. In rice, main culm panicle node number (MCPNN; the node number on which the panicle is borne) and maximum node production rate (MNPR; the number of leaves that emerge per degree-day > 10°C) are primary phenotypic plant traits that have significant positive direct effects on yield-related traits. Degree-days to heading (DDTH), which has a significant positive effect on grain yield, is influenced by the interaction between MCPNN and MNPR. The objective of this research is to assess the phenotypic variation of MCPNN, MNPR, and DDTH in a panel of diverse rice accessions, determine regions in the rice genome associated with these traits using genome-wide association studies (GWAS), and identify putative candidate genes that control these traits.

Results

Considerable variation was observed for the three traits in a 220-genotype diverse rice population. MCPNN ranged from 8.1 to 20.9 nodes in 2018 and from 9.9 to 21.0 nodes in 2019. MNPR ranged from 0.0097 to 0.0214 nodes/degree day > 10°C in 2018 and from 0.0108 to 0.0193 nodes/degree-day > 10°C in 2019. DDTH ranged from 713 to 2,345 degree-days > 10°C in 2018 and from 778 to 2,404 degree-days > 10°C in 2019.

Thirteen significant (P < 2.91 x 10^-7) trait-single nucleotide polymorphism (SNP) associations were identified using the multilocus mixed linear model for GWAS. Significant associations between MCPNN and three SNPs in chromosome 2 (S02_12032235, S02_11971745, and S02_12030176) were detected with both the 2018 and best linear unbiased prediction (BLUP) datasets. Nine SNPs in chromosome 6 (S06_1970442, S06_2310856, S06_2550351, S06_1968653, S06_2296852, S06_1968680, S06_1968681, S06_1970597, and S06_1970602) were significantly associated with MNPR in the 2019 dataset. One SNP in chromosome 11 (S11_29358169) was significantly associated with the DDTH in the BLUP dataset.

Conclusions

This study identifies SNP markers that are putatively associated with MCPNN, MNPR, and DDTH. Some of these SNPs were located within or near gene models, which identify possible candidate genes involved in these traits. Validation of the putative candidate genes through expression and gene editing analyses are necessary to confirm their roles in regulating MCPNN, MNPR, and DDTH. Identifying the underlying genetic basis for primary phenotypic traits MCPNN and MNPR could lead to the development of fast and efficient approaches for their estimation, such as marker-assisted selection and gene editing, which is essential in increasing breeding efficiency and enhancing grain yield in rice. On the other hand, DDTH is a resultant variable that is highly affected by nitrogen and water management, plant density, and several other factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08629-y.

Rice functional genomics: decades' efforts and roads ahead

Rice (Oryza sativa L.) is one of the most important crops in the world. Since the completion of rice reference genome sequences, tremendous progress has been achieved in understanding the molecular mechanisms on various rice traits and dissecting the underlying regulatory networks. In this review, we summarize the research progress of rice biology over past decades, including omics, genome-wide association study, phytohormone action, nutrient use, biotic and abiotic responses, photoperiodic flowering, and reproductive development (fertility and sterility). For the roads ahead, cutting-edge technologies such as new genomics methods, high-throughput phenotyping platforms, precise genome-editing tools, environmental microbiome optimization, and synthetic methods will further extend our understanding of unsolved molecular biology questions in rice, and facilitate integrations of the knowledge for agricultural applications.

Hd1 Allele Types and Their Associations with Major Agronomic Traits in Korean Rice Cultivars

Optimizing flowering time in crop plants is critical for maximizing yield and quality under target environments. While there is a wide range of heading date variation in Korean rice cultivars, the underlying gene mechanisms are unclear. Here, we sequenced the protein coding regions of Hd1, the major rice heading date gene, from 293 Korean rice cultivars and investigated the associations between Hd1 allele types and major agronomic traits under four different environments. There were four functional Hd1 and five nonfunctional hd1 alleles distributed among the 293 Korean rice cultivars. The effects of the Hd1 allele types were highly significant for days to heading in all four environments, explaining 51.4-65.8% of the phenotypic variation. On average, cultivars carrying nonfunctional hd1 headed 13.7 days earlier than those carrying functional Hd1. While the Hd1 allele types exhibited highly significant effects on culm length and protein content under all four environments, the differences between cultivars carrying Hd1 and hd1 were minimal. The effects of the Hd1 allele types on amylose content were significant in only one of the four environments. Our results provide useful information for fine-tuning rice heading dates by utilizing different Hd1 alleles in rice breeding programs.

Development of an SSR marker-based genetic linkage map and identification of a QTL associated with flowering time in Eustoma

Lisianthus (Eustoma grandiflorum) is an important floricultural crop cultivated worldwide. Despite its commercial importance, few DNA markers are available for molecular genetic research. In this study, we constructed a genetic linkage map and to detect quantitative trait loci (QTLs) for important agronomic traits of lisianthus. To develop simple sequence repeat (SSR) markers, we used 454-pyrosequencing technology to obtain genomic shotgun sequences and subsequently identified 8263 putative SSRs. A total of 3990 primer pairs were designed in silico and 1189 unique primer pairs were extracted through a BLAST search. Amplification was successful for more than 1000 primer pairs, and ultimately 278 SSR markers exhibited polymorphism between the two lisianthus accessions evaluated. Based on these markers, a genetic linkage map was constructed using a breeding population derived from crosses between the two accessions, for which flowering time differed (>140 days when grown under 20°C). We detected one QTL associated with flowering time (phenotypic variance, 27%; LOD value, 3.7). The SSR marker located at this QTL may account for variation in flowering time among accessions (i.e., three accessions whose nodes of the first flower were over 30 had late-flowering alleles of this QTL).

Associations between TUBB-WWOX SNPs, their haplotypes, gene-gene, and gene-environment interactions and dyslipidemia

In this study, we investigated associations between single nucleotide polymorphisms (SNPs) in the tubulin beta class I (TUBB) and WW domain-containing oxidoreductase (WWOX) genes, gene-gene interactions, and gene-environment interactions and dyslipidemia in the Chinese Maonan ethnic group. Four SNPs (rs3132584, rs3130685, rs2222896, and rs2548861) were genotyped in unrelated subjects with normal lipid levels (864) or dyslipidemia (1129). While 5.0% of Maonan subjects carried the rs3132584TT genotype, none of the Chinese Han in Beijing subjects did. Allele and genotype frequencies differed between the normal and dyslipidemia groups for three SNPs (rs3132584, rs3130685, and rs2222896). rs2222896G allele carriers in the normal group had higher low-density lipoprotein cholesterol and lower high-density lipoprotein cholesterol levels. The rs3132584GG, rs3130685CC+TT, and rs2222896GG genotypes as well as the rs2222896G-rs2548861G and rs2222896G-rs2548861T haplotypes were associated with an elevated risk of dyslipidemia; the rs2222896A-rs2548861T and rs2222896A-rs2548861G haplotypes were associated with a reduced risk of dyslipidemia. Among the thirteen TUBB-WWOX interaction types identified, rs3132584T-rs3130685T-rs2222896G-rs2548861T increased the risk of dyslipidemia 1.371-fold. Fourteen two- to four-locus optimal interactive models for SNP-SNP, haplotype-haplotype, gene-gene, and gene-environment interactions exhibited synergistic or contrasting effects on dyslipidemia. Finally, the interaction between rs3132584 and rs2222896 increased the risk of dyslipidemia 2.548-fold and predicted hypertension.

Knockouts of a late flowering gene via CRISPR-Cas9 confer early maturity in rice at multiple field locations

OsGhd7 gene was discovered by screening our rice activation tagging population. CRISPR-Cas9 created knockouts of OsGhd7 conferred early flowering and early maturity in rice varieties across multiple geographical locations in China. Our research shows that OsGhd7 is a good target for breeding early maturity rice varieties, and an excellent example of the advantages of applying the CRISPR-Cas9 technology for trait improvement. Flowering time (heading date) is an important trait for crop cultivation and yield. In this study, we discovered a late flowering gene OsGhd7 by screening our rice activation tagging population, and demonstrated that overexpression of OsGhd7 delayed flowering time in rice, and the delay in flowering time depended on the transgene expression level. OsGhd7 is a functional allele of the Ghd7 gene family; knockouts of OsGhd7 generated by CRISPR-Cas9 significantly accelerated flowering time and the earliness of the flowering time depended on field location. The homozygous OsGhd7 knockout lines showed approximately 8, 10, and 20 days earlier flowering than controls at three different locations in China (Changsha City, Sanya City, and Beijing City, respectively) that varied from 18.25° N to 39.90° N. Furthermore, knockouts of OsGhd7 also showed an early flowering phenotype in different rice varieties, indicating OsGhd7 can be used as a common target gene for using the CRISPR technology to modulate rice flowering time. The importance of OsGhd7 and CRISPR technology for breeding early maturity rice varieties are discussed.

Environmental Signal-Dependent Regulation of Flowering Time in Rice

The transition from the vegetative to the reproductive stage of growth is a critical event in the lifecycle of a plant and is required for the plant’s reproductive success. Flowering time is tightly regulated by an internal time-keeping system and external light conditions, including photoperiod, light quality, and light quantity. Other environmental factors, such as drought and temperature, also participate in the regulation of flowering time. Thus, flexibility in flowering time in response to environmental factors is required for the successful adaptation of plants to the environment. In this review, we summarize our current understanding of the molecular mechanisms by which internal and environmental signals are integrated to regulate flowering time in Arabidopsis thaliana and rice (Oryza sativa).

Genome-Wide Identification of QTLs for Grain Protein Content Based on Genotyping-by-Resequencing and Verification of qGPC1-1 in Rice

To clarify the genetic mechanism underlying grain protein content (GPC) and to improve rice grain qualities, the mapping and cloning of quantitative trait loci (QTLs) controlling the natural variation of GPC are very important. Based on genotyping-by-resequencing, a total of 14 QTLs were detected with the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population in 2016 and 2017. Seven of the fourteen QTLs were repeatedly identified across two years. Using three residual heterozygote-derived populations, a stably inherited QTL named as qGPC1-1 was validated and delimited to a ~862 kb marker interval JD1006–JD1075 on the short arm of chromosome 1. Comparing the GPC values of the RIL population determined by near infrared reflectance spectroscopy (NIRS) and Kjeldahl nitrogen determination (KND) methods, high correlation coefficients (0.966 and 0.983) were observed in 2016 and 2017. Furthermore, 12 of the 14 QTLs were identically identified with the GPC measured by the two methods. These results indicated that instead of the traditional KND method, the rapid and easy-to-operate NIRS was suitable for analyzing a massive number of samples in mapping and cloning QTLs for GPC. Using the gel-based low-density map consisted of 208 simple sequence repeat (SSR) and insert/deletion (InDel) markers, the same number of QTLs (fourteen) were identified in the same HHZ/JZ1560 RIL population, and three QTLs were repeatedly detected across two years. More stably expressed QTLs were identified based on the genome resequencing, which might be attributed to the high-density map, increasing the detection power of minor QTLs. Our results are helpful in dissecting the genetic basis of GPC and improving rice grain qualities through molecular assisted selection.

Editorial for Special Issue "Plant Genetics and Molecular Breeding"

The development of new plant varieties is a long and tedious process involving the generation of large seedling populations to select the best individuals [...].

Automatic estimation of heading date of paddy rice using deep learning

BACKGROUND

Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location. The heading date also plays a vital role in determining grain yield for research experiments. Visual examination of the crop is laborious and time consuming. Therefore, quick and precise estimation of heading date of paddy rice is highly essential.

RESULTS

In this work, we propose a simple pipeline to detect regions containing flowering panicles from ground level RGB images of paddy rice. Given a fixed region size for an image, the number of regions containing flowering panicles is directly proportional to the number of flowering panicles present. Consequently, we use the flowering panicle region counts to estimate the heading date of the crop. The method is based on image classification using Convolutional Neural Networks. We evaluated the performance of our algorithm on five time series image sequences of three different varieties of rice crops. When compared to the previous work on this dataset, the accuracy and general versatility of the method has been improved and heading date has been estimated with a mean absolute error of less than 1 day.

CONCLUSION

An efficient heading date estimation method has been described for rice crops using time series RGB images of crop under natural field conditions. This study demonstrated that our method can reliably be used as a replacement of manual observation to detect the heading date of rice crops.