Identification and verification of grain shape QTLs by SNP array in rice
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ABSTRACT:
SUBMITTER: Chen J
PROVIDER: S-EPMC8608341 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Rice is a major crop, providing calories and food for most of the world's population. Currently, the global population is rapidly increasing, and securing a yield of rice that can satisfy everyone is an ongoing challenge. The yield of rice can be increased by controlling 1000-grain weight as one of the important determining factors. Grain length, grain width, grain thickness, and 1000-grain weight, which determine grain size, are controlled by QTLs. To identify QTLs related to grain size, we screened and then mapped 88 RIL individuals derived from a cross between JJ625LG, which has a long grain size, long spindle-shaped grains, and low 1000-grain weight, and Namchan, which has short grains with round shape and heavy 1000-grain weight. In 2021 and 2022, 511 SNP markers were used to map QTLs related to grain size to a physical map. The QTLs found to be related to grain size are evenly distributed on chromosomes 2, 3, 5, 10, and 11. The mapping results also show that the QTLs qGl3-2, qRlw3, and qRlw3-2 of chromosome 3, and qGt5 and qRlw5 of chromosome 5 are, respectively, associated with GS3 and qSW5, which are the major genes previously cloned and found to be related to grain size. In addition, qGw10 and qGw10-1, which were additionally detected in this study, were found to be associated with Os10g0525200 (OsCPq10), a potential candidate gene involved in controlling grain size. This gene codes for a cytochrome P450 family protein and is reported to have a positive effect on grain size by interacting with proteins related to mechanisms determining grain size. In particular, OsCPq10 was screened in the same identified QTL region for 2 consecutive years, which is expected to have a positive effect on grain size. These results will be helpful for breeding elite rice cultivars with high yields through additional fine mapping related to grain size.
| S-EPMC10181466 | biostudies-literature
Project description: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.
| S-EPMC7014352 | biostudies-literature
Project description:Grain appearance is one of the most important attributes of rice. It is determined by grain size, shape, and weight, which in turn influences the rice yield and market value. In this study, QTLs for grain length, grain width, grain length/width ratio, and grain weight were mapped using the high-throughput indica/indica SNP platforms. The population of the mega indica variety IR64 and the high-quality aromatic variety Sadri from Iran was phenotyped. Based on this phenotypic data, plants of 94 F2:3 families including both parents were selected. A linkage map analysis of 210 SNP markers identified 14 QTLs controlling the grain length, grain width, length/width ratio, and 1,000 grain weight. Among these 14, one important region containing the QTLs for all the four studies' traits was mapped on chromosome 8. It was derived from Sadri for the decreased length/width ratio and increased grain weight. This study demonstrated the speed and efficiency in using multiplex SNP genotyping for QTL analysis. Moreover, this study identified four novel QTLs (qGL8, qTGW8, qLWR8, and qGW8) sharing the same position on chromosome 8 which were linked with grain quality characteristics between one indica and one aromatic variety. It will enable more precise marker-assisted selection for grain weight, shape, and size. Further in-depth studies are required to dissect this region of interest and identify the related gene(s).
| S-EPMC9437704 | biostudies-literature
Project description:BACKGROUND:Heat stress is one of the major abiotic threats to rice production, next to drought and salinity stress. Incidence of heat stress at reproductive phase of the crop results in abnormal pollination leading to floret sterility, low seed set and poor grain quality. Identification of QTLs and causal genes for heat stress tolerance at flowering will facilitate breeding for improved heat tolerance in rice. In the present study, we used 272 F8 recombinant inbred lines derived from a cross between Nagina22, a well-known heat tolerant Aus cultivar and IR64, a heat sensitive popular Indica rice variety to map the QTLs for heat tolerance. RESULTS:To enable precise phenotyping for heat stress tolerance, we used a controlled phenotyping facility available at ICAR-Indian Institute of Wheat and Barley Research, Karnal, India. Based on 'days to 50% flowering' data of the RILs, we followed staggered sowing to synchronize flowering to impose heat stress at uniform stage. Using the Illumina infinium 5K SNP array for genotyping the parents and the RILs, and stress susceptibility and stress tolerance indices (SSI and STI) of percent spikelet sterility and yield per plant (g), we identified five QTLs on chromosomes 3, 5, 9 and 12. The identified QTLs explained phenotypic variation in the range of 6.27 to 21. 29%. Of these five QTLs, two high effect QTLs, one novel (qSTIPSS9.1) and one known (qSTIY5.1/qSSIY5.2), were mapped in less than 400 Kbp genomic regions, comprising of 65 and 54 genes, respectively. CONCLUSIONS:The present study identified two major QTLs for heat tolerance in rice in narrow physical intervals, which can be employed for crop improvement by marker assisted selection (MAS) after development of suitable scorable markers for breeding of high yielding heat tolerant rice varieties. This is the first report of a major QTL for heat tolerance on chromosome 9 of rice. Further, a known QTL for heat tolerance on chromosome 5 was narrowed down from 23 Mb to 331 Kbp in this study.
| S-EPMC5459777 | biostudies-literature
Project description:Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.
| S-EPMC10775519 | biostudies-literature
Project description:To uncover the genetics of rice grain weight, we constructed an RIL population derived from a cross between a large grain accession M201 and a small size variety JY293. Specific Locus Amplified Fragment Sequencing (SLAF-Seq) technology was used to genotype two bulked DNA pools made from individual DNA of the heaviest 30 lines and the lightest 30 lines according to the 1000 grain weight (TGW). Bulked segregant analysis (BSA) was used to identify SLAFs strongly associated with TGW. Two marker-intensive regions at 24,600,000-24,850,000 bp and 25,000,000-25,350,000 bp on chromosome 3 were identified tightly related to the TGW. Then a linkage map of chromosome 3 was constructed with SSR markers and some SLAF derived single nucleotide polymorphisms (SNPs). Quantitative trait locus (QTL) mapping for TGW, grain length, grain width, and grain thickness revealed one major QTL in the second hot-region and two other minor QTLs for grain weight. These three QTLs displayed hierarchical effects on grain length and grain weight in order of qTGW3.2 (qGL3) qTGW3.1 (GS3) qTGW3.3. Multiple comparisons of means among the eight combinations of 3 QTLs revealed that the lines with two of three QTLs deriving from M201 displayed a large grain weight phenotype (TGW 40.2g, average data of three years) and lines with both qTGW3.1 and qTGW3.3 alleles from M201 (42.5g) had similar grain weight to the qTGW3.2 (40.8g) alone. Two strategies with similar effectiveness were proposed to improve grain weight by marker-assisted selection (MAS). One is to introduce the novel qTGW3.2 allele alone, and the other is to pyramid qTGW3.1 and qTGW3.3 alleles together. One new allele of GS3 (39 bp deletion in intron 1) and two SNPs in coding sequence of qGL3 identified in this study from M201 are useful in pyramiding elite alleles for molecular breeding for improvement of rice yield.
| S-EPMC4376791 | biostudies-literature
Project description: Not available
| S-BSST1640 | biostudies-other
Project description:The world population is growing rapidly, and food shortage remains a critical issue. Quantitative trait locus (QTL) mapping is a statistical analytical method that uses both phenotypic and genotypic data. The purpose of QTL mapping is to determine the exact gene location for various complex traits. Increasing grain weight is a way to increase yield in rice. Genes related to grain size were mapped using the Samgang/Nagdong double haploid (SNDH) populations. Grain sizes were diversely distributed in SNDH 113 populations, and OsBRKq1 was detected on chromosome 1 in an analysis of QTL mapping that used 1000 grain weight, grain length, and grain width. OsBRKq1 exhibited high sequence similarity with the brassinosteroid leucine-rich repeat-receptor kinases of Arabidopsis thaliana and Zea mays. It was also predicted to have a similar function because of its high homology. OsBRKq1 interacts with various grain-size control genes. Among the SNDH populations, the analysis of the relative expression level during the panicle formation stage of OsBRKq1 in panicles of SNDH117, which has the largest grain size, and SNDH6, which has the smallest grain size, the relative expression level was significantly increased in SNDH117 panicles. SNDH populations have been advancing generations for 10 years; various genetic traits have been fixed and are currently being used as bridging parents. Therefore, the stable expression level of OsBRKq1 was confirmed via QTL mapping. In the future, OsBRKq1 can be effectively used to increase the yield of rice and solve food problems by increasing the size of seeds.
| S-EPMC7956666 | biostudies-literature
Project description:A panel of 60 genotypes comprising New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes was phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found promising with an average grain yield varying from 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). This information may help in identification of potential parents for development of transgressive segregants with very high yield. The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1).Some of the SSRs were co-localized with more than two traits. The highest co-localization was identified with RM5709 linked to nine traits, followed by RM297 with five traits. Similarly, RM5575, RM204, RM168, RM112, RM26499 and RM22899 were also recorded to be co-localized with more than one trait and could be rated as important for marker-assisted backcross breeding programs, for pyramiding of these QTLs for important yield traits, to produce new-generation rice for prospective increment in yield potentiality and breaking yield ceiling.
| S-EPMC7365460 | biostudies-literature
Project description:High grain number is positively correlated with grain yield in rice, but it is compromised because of poor filling of basal spikelets in dense panicle bearing numerous spikelets. The phenomenon that turns the basal spikelets of compact panicle sterile in rice is largely unknown. In order to understand the factor(s) that possibly determines such spikelet sterility in compact panicle cultivars, QTLs and candidate genes were identified for spikelet fertility and associated traits like panicle compactness, and ethylene production that significantly influences the grain filling using recombinant inbred lines developed from a cross between indica rice cultivars, PDK Shriram (compact, high spikelet number) and Heera (lax, low spikelet number). Novel QTLs, qSFP1.1, qSFP3.1, and qSFP6.1 for spikelet fertility percentage; qIGS3.2 and qIGS4.1 for panicle compactness; and qETH1.2, qETH3.1, and qETH4.1 for ethylene production were consistently identified in both kharif seasons of 2017 and 2018. The comparative expression analysis of candidate genes like ERF3, AP2-like ethylene-responsive transcription factor, EREBP, GBSS1, E3 ubiquitin-protein ligase GW2, and LRR receptor-like serine/threonine-protein kinase ERL1 associated with identified QTLs revealed their role in poor grain filling of basal spikelets in a dense panicle. These candidate genes thus could be important for improving grain filling in compact-panicle rice cultivars through biotechnological interventions.
| S-EPMC8245594 | biostudies-literature