Mapping and verification of grain shape QTLs based on an advanced backcross population in rice

Genome-wide association study reveals the advantaged genes regulating japonica rice grain shape traits in northern China

Background

Rice, a staple food for over half of the global population, exhibits significant diversity in grain shape characteristics, which impact not only appearance and milling quality but also grain weight and yield. Identifying genes and loci underlying these traits is crucial for improving rice breeding programs. Previous studies have identified multiple quantitative trait loci (QTLs) and genes regulating grain length, width, and length-width ratio; however, further investigation is necessary to elucidate their regulatory pathways and their practical application in crop improvement.

Methods

This study employed a genome-wide association study (GWAS) on 280 japonica rice varieties from northern China to decipher the genetic basis of grain shape traits. Phenotyping included measurements of 11 grain-related traits, such as grain length, width, and area, along with their brown and white rice counterparts. High-density single nucleotide polymorphism (SNP) markers (33,579) were utilized for genotyping, and GWAS was performed using a mixed linear model (MLM) incorporating principal component analysis (PCA) and kinship (K) matrix to account for population structure and relatedness.

Results

Our analysis detected 15 QTLs associated with the 11 grain shape traits, of which five major QTL clusters emerged as crucial. Candidate genes, including LOC_Os01g50720 (qGL1), OsMKK4 (LOC_Os02g54600, influencing qBA2, qWL2, and qWA2), GW5 (LOC_Os05g09520, controlling qGW5, qBW5, qBR5, qWW5, and qWR5), GW6a (LOC_Os06g44100, associated with qGW6, qBW6, qBR6, qWW6, and qWR6), and FZP (LOC_Os07g47330, linked to qWL7), were identified based on functional annotations and haplotype analysis. These findings offer valuable insights into the genetic mechanisms underlying rice grain shape and suggest promising targets for marker-assisted selection to enhance rice quality and yield.

Genetic dissection of grain traits and their corresponding heterosis in an elite hybrid

Rice productivity has considerably improved due to the effective employment of heterosis, but the genetic basis of heterosis for grain shape and weight remains uncertain. For studying the genetic dissection of heterosis for grain shape/weight and their relationship with grain yield in rice, quantitative trait locus (QTL) mapping was performed on 1,061 recombinant inbred lines (RILs), which was developed by crossing xian/indica rice Quan9311B (Q9311B) and Wu-shan-si-miao (WSSM). Whereas, BC₁F₁ (a backcross F₁) was developed by crossing RILs with Quan9311A (Q9311A) combined with phenotyping in Hefei (HF) and Nanning (NN) environments. Overall, 114 (main-effect, mQTL) and 359 (epistatic QTL, eQTL) were identified in all populations (RIL, BC₁F₁, and mid-parent heterosis, H_MPs) for 1000-grain weight (TGW), grain yield per plant (GYP) and grain shape traits including grain length (GL), grain width (GW), and grain length to width ratio (GLWR). Differential QTL detection revealed that all additive loci in RILs population do not show heterotic effects, and few of them affect the performance of BC₁F₁. However, 25 mQTL not only contributed to BC₁F₁'s performance but also contributed to heterosis. A total of seven QTL regions was identified, which simultaneously affected multiple grain traits (grain yield, weight, shape) in the same environment, including five regions with opposite directions and two regions with same directions of favorable allele effects, indicating that partial genetic overlaps are existed between different grain traits. This study suggested different approaches for obtaining good grain quality with high yield by pyramiding or introgressing favorable alleles (FA) with the same direction of gene effect at the QTL regions affecting grain shape/weight and grain yield distributing on different chromosomes, or introgressing or pyramiding FA in the parents instead of fixing additive effects in hybrid as well as pyramiding the polymorphic overdominant/dominant loci between the parents and eliminating underdominant loci from the parents. These outcomes offer valuable information and strategy to develop hybrid rice with suitable grain type and weight.

Identification and verification of grain shape QTLs by SNP array in rice

Grain shape strongly influences the economic value and grain yield of rice. Thus, identifying quantitative trait loci (QTLs) for grain shape has been a longstanding goal in rice genetic research and breeding programs. Single nucleotide polymorphism (SNP) markers are ubiquitous in the rice genome and are more abundant and evenly distributed on the 12 rice chromosomes than traditional markers. An F₂ population was genotyped using the RICE6K SNP array to elucidate the mechanisms governing grain shape. Thirty-five QTLs for grain shape were detected on 11 of 12 chromosomes over 2 years. The major QTL cluster qGS7 was detected in both years and displayed strong genetic effects on grain length and width, showing consistency with GL7/GW7. Some minor QTLs were also detected, and the effects of four QTLs on seed size were then validated using BC₁F₆ populations with residual heterozygous lines in each QTL region. Our findings provide insights into the molecular basis of grain shape as well as additional resources and approaches for producing hybrid high-yield rice varieties.

Grain Size Selection Using Novel Functional Markers Targeting 14 Genes in Rice

BACKGROUND

Grain size is an extremely important aspect of rice breeding, affecting both grain yield and quality traits. It is controlled by multiple genes and tracking these genes in breeding schemes should expedite selection of lines with superior grain yield and quality, thus it is essential to develop robust, efficient markers.

RESULT

In this study, 14 genes related to grain size (GW2, GS2, qLGY3, GS3, GL3.1, TGW3, GS5, GW5, GS6, TGW6, GW6a, GLW7, GL7 and GW8) were selected for functional marker development. Twenty-one PCR-gel-based markers were developed to genotype the candidate functional nucleotide polymorphisms (FNPs) of these genes, and all markers can effectively recognize the corresponding allele types. To test the allele effects of different FNPs, a global collection of rice cultivars including 257 accessions from the Rice Diversity Panel 1 was used for allele mining, and four grain-size-related traits were investigated at two planting locations. Three FNPs for GW2, GS2 and GL3.1 were genotyped as rare alleles only found in cultivars with notably large grains, and the allele contributions of the remaining FNPs were clarified in both the indica and japonica subspecies. Significant trait contributions were found for most of the FNPs, especially GS3, GW5 and GL7. Of note, GW5 could function as a key regulator to coordinate the performance of other grain size genes. The allele effects of several FNPs were also tested by QTL analysis using an F2 population, and GW5 was further identified as the major locus with the largest contribution to grain width and length to width ratio.

CONCLUSIONS

The functional markers are robust for genotyping different cultivars and may facilitate the rational design of grain size to achieve a balance between grain yield and quality in future rice breeding efforts.

Detection of heading date QTLs in advanced-backcross populations of an elite indica rice cultivar, IR64

IR64 is one of the world's most popular rice cultivars. To collect genetic factors involved in controlling its heading date, we developed 70 reciprocal advanced-backcross populations with a total of 6284 individuals at the BC₄F₂ generation from crosses between Koshihikari and IR64. We detected 29 QTLs associated with heading date on chromosomes 3, 5-8, 10, and 12. Twenty QTLs were located in the same chromosome regions as previously isolated heading date genes (Hd1, Hd6, Hd16, Ghd7, DTH8, Hd17, and Hd18). The rest were located in other chromosome regions. We found more number of QTLs than previous studies using mapping populations of IR64. Fine mapping in additional advanced-backcross populations clearly revealed that QTLs on the long arm of chromosome 7 are overlapping and seem to be a novel genetic factor for heading date because of their different locations from OsPRR37. Our results suggest that the difference in heading date between IR64 and Koshihikari is genetically controlled by many factors, and that a non-functional allele of Hd1 contributes to early heading of IR64 in the genetic background of functional alleles of other heading date QTLs and genes such as Hd6 and Hd16.