QTL mapping of grain quality traits in rice

Utilization of the Winkler scale of plants using big data temperature presented by the Korea Meteorological Administration

Introduction

Rice is an important food source that can provide a stable supply of calories for most people around the world. However, owing to the recent rapid temperature rise, we are facing social issues related to the increase in the Winkler scale. In this study, a strategy for screening potential candidate genes related to the yield according to the Winkler scale is presented, and the possibility of using a candidate gene identified through sequence haplotype and homology analysis as a breeding source is suggested.

Methods

QTL for the Winkler scale was identified using a population of 120 double haploids derived from a cross between Cheongchoneg, Indica, and Nagdong, Japonica.

Results and discussion

A total of 79 candidate genes were detected in the identified QTL region, and OsHAq8 was finally screened. Through haplotype analysis, OsHAq8 was derived from the Indica group and orthologous to Graminae's activator of Hsp90 ATPase, suggesting that it is a candidate gene involved in yield according to temperature during the growing period. The expression level of OsHAq8 increased as the Winkler scale increased. The findings of this study can serve as a crucial indicator for predicting harvest time and grain quality while achieving a stable yield through marker selection and adaptation to climate change. Climate change occurs more frequently. In these situations, it is very important to predict harvest time and apply relevant candidate genes to breeding. The candidate genes presented in this study can be effectively applied to rice breeding in preparation for climate change.

QTL detection for rice grain storage protein content and genetic effect verifications

Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating-cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions-albumins, globulins, prolamins, glutelin, and grain protein content-were evaluated by exploiting two BC3F2 mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01436-7.

Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids

Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F₂ population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits-the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness-of the F₂ population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%-61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.

The genetic basis of grain protein content in rice by genome-wide association analysis

The grain protein content (GPC) of rice is an important factor that determines its nutritional, cooking, and eating qualities. To date, although a number of genes affecting GPC have been identified in rice, most of them have been cloned using mutants, and only a few genes have been cloned in the natural population. In this study, 135 significant loci were detected in a genome-wide association study (GWAS), many of which could be repeatedly detected across different years and populations. Four minor quantitative trait loci affecting rice GPC at four significant association loci, qPC2.1, qPC7.1, qPC7.2, and qPC1.1, were further identified and validated in near-isogenic line F2 populations (NIL-F2), explaining 9.82, 43.4, 29.2, and 13.6% of the phenotypic variation, respectively. The role of the associated flo5 was evaluated with knockdown mutants, which exhibited both increased grain chalkiness rate and GPC. Three candidate genes in a significant association locus region were analyzed using haplotype and expression profiles. The findings of this study will help elucidate the genetic regulatory network of protein synthesis and accumulation in rice through cloning of GPC genes and provide new insights on dominant alleles for marker-assisted selection in the genetic improvement of rice grain quality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01347-z.

Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice

BACKGROUND

Protein, starch, amylose and total soluble sugars are basic metabolites of seed that influence the eating, cooking and nutritional qualities of rice. Chlorophyll is responsible for the absorption and utilization of the light energy influencing photosynthetic efficiency in rice plant. Mapping of these traits are very important for detection of more number of robust markers for improvement of these traits through molecular breeding approaches.

RESULTS

A representative panel population was developed by including 120 germplasm lines from the initial shortlisted 274 lines for mapping of the six biochemical traits using 136 microsatellite markers through association mapping. A wide genetic variation was detected for the traits, total protein, starch, amylose, total soluble sugars, chlorophyll a, and chlorophyll b content in the population. Specific allele frequency, gene diversity, informative markers and other diversity parameters obtained from the population indicated the effectiveness of utilization of the population and markers for mapping of these traits. The fixation indices values estimated from the population indicated the existence of linkage disequilibrium for the six traits. The population genetic structure at K = 3 showed correspondence with majority of the members in each group for the six traits. The reported QTL, qProt1, qPC6.2, and qPC8.2 for protein content; qTSS8.1 for total soluble sugar; qAC1.2 for amylose content; qCH2 and qSLCHH for chlorophyll a (Chl. a) while qChl5D for chlorophyll b (Chl. b) were validated in this population. The QTL controlling total protein content qPC1.2; qTSS7.1, qTSS8.2 and qTSS12.1 for total soluble sugars; qSC2.1, qSC2.2, qSC6.1 and qSC11.1 for starch content; qAC11.1, qAC11.2 and qAC11.3 for amylose content; qChla8.1 for Chl. a content and qChlb7.1 and qChlb8.1 for Chl. b identified by both Generalized Linear Model and Mixed Linear Model were detected as novel QTL. The chromosomal regions on chromosome 8 at 234 cM for grain protein content and total soluble sugars and at 363 cM for Chl. a and Chl. b along with the position at 48 cM on chromosome 11 for starch and amylose content are genetic hot spots for these traits.

CONCLUSION

The validated, co-localized and the novel QTL detected in this study will be useful for improvement of protein, starch, amylose, total soluble sugars and chlorophyll content in rice.

Genetic control of grain appearance quality in rice

Grain appearance, one of the key determinants of rice quality, reflects the ability to attract consumers, and is characterized by four major properties: grain shape, chalkiness, transparency, and color. Mining of valuable genes, genetic mechanisms, and breeding cultivars with improved grain appearance are essential research areas in rice biology. However, grain appearance is a complex and comprehensive trait, making it challenging to understand the molecular details, and therefore, achieve precise improvement. This review highlights the current findings of grain appearance control, including a detailed description of the key genes involved in the formation of grain appearance, and the major environmental factors affecting chalkiness. We also discuss the integration of current knowledge on valuable genes to enable accurate breeding strategies for generation of rice grains with superior appearance quality.

Mapping and Validation of QTLs for the Amino Acid and Total Protein Content in Brown Rice

Highly nutritious rice production will be benefited with the improvement of amino acid content (AAC) and protein content (PC). The identification of quantitative trait loci (QTLs) associated with the PC and AAC of rice grains could provide a basis for improving the nutritional value of rice grains. Here, we conducted QTL analyses using recombinant inbred lines from the cross between indica (Milyang 23 or M23) and japonica (Tong 88-7 or T887) rice varieties, afterward employing genotyping-by-sequencing to obtain a high-density genetic map. A total of 17 and 3 QTLs were detected for AAC and PC, respectively. Among them, two QTLs associated with more than 10 AACs, qAAC6.1 and qAAC7.1, were identified for the first time in this study. Each favorable allele that increased the AAC of the two QTLs was derived from M23 and T887, respectively. Allelic combination of qAAC6.1^M23 and qAAC7.1^T887 showed significantly higher content of associated amino acids (AAs) than other allelic combinations. Near-isogenic line (NIL) possessing qAAC7.1^T887 with M23 genetic background had significantly higher AACs than both parents. These results indicate that the pyramiding of QTLs would be useful in developing brown rice with a high AA and protein content.

Intervention of molecular breeding in water saving rice production system: aerobic rice

The aerobic rice system/methods developed to tackle shortage of water, is a sustainable method to enhance rice productivity. Approximately 50% of irrigation water could be saved using this system in contrast to lowland rice cultivation. The crop can be directly seeded or transplanted in dry soil in this system rather than irrigated system of rice production. Here in this review we had tried to present all the important development made in regards to aerobic rice. Many QTLs responsible for aerobic traits in rice that have been mapped already are enlisted here. Brief comparisons of aerobic rice and conventional rice, further improvements made in aerobic rice have also been discussed.

Genetic Mapping and Validation of Quantitative Trait Loci (QTL) for the Grain Appearance and Quality Traits in Rice (Oryza sativa L.) by Using Recombinant Inbred Line (RIL) Population

Rice grain shape and nutritional quality traits have high economic value for commercial production of rice and largely determine the market price, besides influencing the global food demand for high-quality rice. In order to understand the genetic components of grain appearance traits in paddy, brown, and head rice, 15 traits were evaluated by using 157 recombinant inbred lines (RILs) derived from a cross between two Iranian rice cultivars Ali-Kazemi (A) and Kadous (K). A significant variation was observed and showed transgressive segregation among the RILs. Correlations between the visual appearances of grain traits were studied. A linkage map with 65 polymorphic SSR markers was constructed, which covered 1517.32 cM of the rice genome. A total of seven QTLs were identified on four chromosomes, 1, 6, 9, and 12, associated with four traits, which are explained by the total phenotypic variation of 44.27% and LOD score of 32.77 in 2014 and 2015, respectively. Among these, four QTLs for two traits were consistently flanked by RM23904 and RM24432 on chromosome 9. Single QTL for head grain length (HGL) expressed in both the years on chromosomes 1 and 9. A major QTL for seed weight was detected on chromosome 9, which explained 10.18% of the phenotypic variation. The additive effect of all the QTLs was positively contributed by Ali-Kazemi allele, except one QTL on chromosome 6 (qBGL_6) that showed a negative additive effect being contributed by the Kadous allele. The study also validated the identified QTLs with the polymorphic SSR markers that were previously reported. Novel QTLs were identified on chromosomes 6 and 9, and many of the polymorphic markers were found to be associated with milling processing of grain quality, cooking, and nutraceutical properties of rice by extensive literature and database analysis. Therefore, these validated QTLs and marker information could be utilized in the marker-assisted selection to improve grain appearance and nutritional grain quality traits in rice.

Applications of the CRISPR/Cas9 System for Rice Grain Quality Improvement: Perspectives and Opportunities

Grain quality improvement is a key target for rice breeders, along with yield. It is a multigenic trait that is simultaneously influenced by many factors. Over the past few decades, breeding for semi-dwarf cultivars and hybrids has significantly contributed to the attainment of high yield demands but reduced grain quality, which thus needs the attention of researchers. The availability of rice genome sequences has facilitated gene discovery, targeted mutagenesis, and revealed functional aspects of rice grain quality attributes. Some success has been achieved through the application of molecular markers to understand the genetic mechanisms for better rice grain quality; however, researchers have opted for novel strategies. Genomic alteration employing genome editing technologies (GETs) like clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) for reverse genetics has opened new avenues of research in the life sciences, including for rice grain quality improvement. Currently, CRISPR/Cas9 technology is widely used by researchers for genome editing to achieve the desired biological objectives, because of its simple targeting. Over the past few years many genes that are related to various aspects of rice grain quality have been successfully edited via CRISPR/Cas9 technology. Interestingly, studies on functional genomics at larger scales have become possible because of the availability of GETs. In this review, we discuss the progress made in rice by employing the CRISPR/Cas9 editing system and its eminent applications. We also elaborate possible future avenues of research with this system, and our understanding regarding the biological mechanism of rice grain quality improvement.

Genetic Dissection of Grain Nutritional Traits and Leaf Blight Resistance in Rice

Colored rice is rich in nutrition and also a good source of valuable genes/quantitative trait loci (QTL) for nutrition, grain quality, and pest and disease resistance traits for use in rice breeding. Genome-wide association analysis using high-density single nucleotide polymorphism (SNP) is useful in precisely detecting QTLs and genes. We carried out genome-wide association analysis in 152 colored rice accessions, using 22,112 SNPs to map QTLs for nutritional, agronomic, and bacterial leaf blight (BLB) resistance traits. Wide variations and normal frequency distributions were observed for most of the traits except anthocyanin content and BLB resistance. The structural and principal component analysis revealed two subgroups. The linkage disequilibrium (LD) analysis showed 74.3% of the marker pairs in complete LD, with an average LD distance of 1000 kb and, interestingly, 36% of the LD pairs were less than 5 Kb, indicating high recombination in the panel. In total, 57 QTLs were identified for ten traits at p < 0.0001, and the phenotypic variance explained (PVE) by these QTLs varied from 9% to 18%. Interestingly, 30 (53%) QTLs were co-located with known or functionally-related genes. Some of the important candidate genes for grain Zinc (Zn) and BLB resistance were OsHMA9, OsMAPK6, OsNRAMP7, OsMADS13, and OsZFP252, and Xa1, Xa3, xa5, xa13 and xa26, respectively. Red rice genotype, Sayllebon, which is high in both Zn and anthocyanin content, could be a valuable material for a breeding program for nutritious rice. Overall, the QTLs identified in our study can be used for QTL pyramiding as well as genomic selection. Some of the novel QTLs can be further validated by fine mapping and functional characterization. The results show that pigmented rice is a valuable resource for mineral elements and antioxidant compounds; it can also provide novel alleles for disease resistance as well as for yield component traits. Therefore, large opportunities exist to further explore and exploit more colored rice accessions for use in breeding.

Phenotypic Performance of Rice (Oryza sativa L.) Populations Induced by the MNU Mutant on the Adaptive Characteristics

Mutation is an impressive method to induce potent characteristics in rice breeding. Evaluation on the phenotypic perfomance in mutant populations is important to examine the effectiveness of mutation. In this study, two rice populations of MNU ((N-methyl-N-Nitrosourea) -induced mutants were used to evaluate their phenotypes. The results showed that all of varieties and mutants expressed their ability to adapt with new environment condition via phenotypic expression. Grain yield of them ranged from 6.18 to 10.70 tons/ha. In general population S/TB performed their best characters. The distribution of related traits to grain yield and amylose content were also different from each population. It was observed that mutants expressed better characters than their parents. This study provided general information on phenotype of rice mutants and varieties in new environmental condition and revealed better adaptive characteristics of rice mutants. Findings of this study confirmed the the efficacy of MNU in rice breeding.

Genetic Basis of Variation in Rice Seed Storage Protein (Albumin, Globulin, Prolamin, and Glutelin) Content Revealed by Genome-Wide Association Analysis

Rice seed storage protein (SSP) is an important source of nutrition and energy. Understanding the genetic basis of SSP content and mining favorable alleles that control it will be helpful for breeding new improved cultivars. An association analysis for SSP content was performed to identify underlying genes using 527 diverse Oryza sativa accessions grown in two environments. We identified more than 107 associations for five different traits, including the contents of albumin (Alb), globulin (Glo), prolamin (Pro), glutelin (Glu), and total SSP (Total). A total of 28 associations were located at previously reported QTLs or intervals. A lead SNP sf0709447538, associated for Glu content in the indica subpopulation in 2015, was further validated in near isogenic lines NIL(Zhenshan97) and NIL(Delong208), and the Glu phenotype had significantly difference between two NILs. The association region could be target for map-based cloning of the candidate genes. There were 13 associations in regions close to grain-quality-related genes; five lead single nucleotide polymorphisms (SNPs) were located less than 20 kb upstream from grain-quality-related genes (PG5a, Wx, AGPS2a, RP6, and, RM1). Several starch-metabolism-related genes (AGPS2a, OsACS6, PUL, GBSSII, and ISA2) were also associated with SSP content. We identified favorable alleles of functional candidate genes, such as RP6, RM1, Wx, and other four candidate genes by haplotype analysis and expression pattern. Genotypes of RP6 and RM1 with higher Pro were not identified in japonica and exhibited much higher expression levels in indica group. The lead SNP sf0601764762, repeatedly detected for Alb content in 2 years in the whole association population, was located in the Wx locus that controls the synthesis of amylose. And Alb content was significantly and negatively correlated with amylose content and the level of 2.3 kb Wx pre-mRNA examined in this study. The associations or candidate genes identified would provide new insights into the genetic basis of SSP content that will help in developing rice cultivars with improved grain nutritional quality through marker-assisted breeding.

Rice grain nutritional traits and their enhancement using relevant genes and QTLs through advanced approaches

BACKGROUND

Rice breeding program needs to focus on development of nutrient dense rice for value addition and helping in reducing malnutrition. Mineral and vitamin deficiency related problems are common in the majority of the population and more specific to developing countries as their staple food is rice.

RESULTS

Genes and QTLs are recently known for the nutritional quality of rice. By comprehensive literature survey and public domain database, we provided a critical review on nutritional aspects like grain protein and amino acid content, vitamins and minerals, glycemic index value, phenolic and flavonoid compounds, phytic acid, zinc and iron content along with QTLs linked to these traits. In addition, achievements through transgenic and advanced genomic approaches have been discussed. The information available on genes and/or QTLs involved in enhancement of micronutrient element and amino acids are summarized with graphical representation.

CONCLUSION

Compatible QTLs/genes may be combined together to design a desirable genotype with superior in multiple grain quality traits. The comprehensive review will be helpful to develop nutrient dense rice cultivars by integrating molecular markers and transgenic assisted breeding approaches with classical breeding.

High-resolution QTL mapping for grain appearance traits and co-localization of chalkiness-associated differentially expressed candidate genes in rice

BACKGROUND

Grain appearance quality is a main determinant of market value in rice and one of the highly important traits requiring improvement in breeding programs. The genetic basis of grain shape and endosperm chalkiness have been given significant attention because of their importance in affecting grain quality. Meanwhile, the introduction of NGS (Next Generation Sequencing) has a significant part to play in the area of genomics, and offers the possibility for high-resolution genetic map construction, population genetics analysis and systematic expression profile study.

RESULTS

A RIL population derived from an inter-subspecific cross between indica rice PYZX and japonica rice P02428 was generated, based on the significant variations for the grain morphology and cytological structure between these two parents. Using the Genotyping-By-Sequencing (GBS) approach, 2711 recombination bin markers with an average physical length of 137.68 kb were obtained, and a high-density genetic map was constructed. Global genetic mapping of QTLs affecting grain shape and chalkiness traits was performed across four environments and the newly identified stable loci were obtained. Twelve important QTL clusters were detected, four of which were coincident with the genomic regions of cloned genes or fine mapped QTL reported. Eight novel QTL clusters (including six for grain shape, one for chalkiness, and one for both grain shape and chalkiness) were firstly obtained and highlighted the value and reliability of the QTL analysis. The important QTL cluster on chromosome 5 affects multiple traits including circularity (CS), grain width (GW), area size of grain (AS), percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC), indicating some potentially pleiotropic effects. The transcriptome analysis demonstrated an available gene expression profile responsible for the development of chalkiness, and several DEGs (differentially expressed genes) were co-located nearby the three chalkiness-related QTL regions on chromosomes 5, 7, and 8. Candidate genes were extrapolated, which were suitable for functional validation and breeding utilization.

CONCLUSION

QTLs affecting grain shape (grain width, grain length, length-width ratio, circularity, area size of grain, and perimeter length of grain) and chalkiness traits (percentage of grains with chalkiness and degree of endosperm chalkiness) were mapped with the high-density GBS-SNP based markers. The important differentially expressed genes (DEGs) were co-located in the QTL cluster regions on chromosomes 5, 7 and 8 affecting PGWC and DEC parameters. Our research provides a crucial insight into the genetic architecture of rice grain shape and chalkiness, and acquired potential candidate loci for molecular cloning and grain quality improvement.

OsAAP6 functions as an important regulator of grain protein content and nutritional quality in rice

Grains from cereals contribute an important source of protein to human food, and grain protein content (GPC) is an important determinant of nutritional quality in cereals. Here we show that the quantitative trait locus (QTL) qPC1 in rice controls GPC by regulating the synthesis and accumulation of glutelins, prolamins, globulins, albumins and starch. qPC1 encodes a putative amino acid transporter OsAAP6, which functions as a positive regulator of GPC in rice, such that higher expression of OsAAP6 is correlated with higher GPC. OsAAP6 greatly enhances root absorption of a range of amino acids and has effects on the distribution of various amino acids. Two common variations in the potential cis-regulatory elements of the OsAAP6 5'-untranslated region seem to be associated with GPC diversity mainly in indica cultivars. Our results represent the first step toward unravelling the mechanism of regulation underlying natural variation of GPC in rice.

[Mapping QTL for rice milling and appearance quality traits in indica rice]

Quantitative trait loci (QTL) controlling six milling and appearance quality traits were analyzed over 2 years using recombinant inbred lines derived from two indica rice Teqing and IRBB. A total of 30 QTL for these traits were detected, of which eight were for brown rice rate (BRR), two for milled rice recovery (MRR), two for head rice recovery (HRR), seven for grain length (GL), five for grain width (GW), and six for length/width ratio (LWR). The QTL were distributed on all chromosomes except for chromosomes 4 and 12. A QTL cluster with major effects on GL, LWR, BRR, and HRR was located in the RM15139-RM15303 interval on chromosome 3, which includes the GS3 gene for grain size. The phenotypic variances explained by the QTL were 59.51%, 36.68%, 19.51%, and 4.56%, respectively. QTL affecting GW, LWR, BRR, and MRR were clustered in the RM437-RM18038 region of chromosome 5,which covers the GW5 gene for grain width, and contributed 59.51%, 36.68%, 19.51%, and 4.56% to the total variance. QTL with minor effects on BRR and MRR were mapped to the RM190-RM587 interval covering the Wx gene for amylase content on chromosome 6. These results suggest that GS3 and GW5 may play a major roles in the genetic control of BRR and grain shape.

QTL analysis for grain quality traits in 2 BC2F2 populations derived from crosses between Oryza sativa cv Swarna and 2 accessions of O. nivara

The appearance and cooking quality of rice determine its acceptability and price to a large extent. Quantitative trait loci (QTLs) for 12 grain quality traits were mapped in 2 mapping populations derived from Oryza sativa cv Swarna × O. nivara. The BC(2)F(2) population of the cross Swarna × O. nivara IRGC81848 (population 1) was evaluated during 2005 and that from Swarna × O. nivara IRGC81832 (population 2) was evaluated during 2006. Linkage maps were constructed using 100 simple sequence repeat (SSR) markers in population 1 and 75 SSR markers in population 2. In all, 21 QTLs were identified in population 1 (43% from O. nivara) and 37 in population 2 (38% QTLs from O. nivara). The location of O. nivara-derived QTLs mp1.2 for milling percent, kw6.1 for kernel width, and klac12.1 for kernel length after cooking coincided in the 2 populations and appear to be useful for Marker Assisted Selection (MAS). Four QTLs for milling percent, 1 QTL each for amylose content, water uptake, elongation ratio, 2 QTLs for kernel width, and 3 QTLs for gel consistency, each explained more than 20% phenotypic variance. Three QTL clusters for grain quality traits were close to the genes/QTLs for shattering and seed dormancy. QTLs for 4 quality traits were associated with 5 of the 7 major yield QTLs reported in the same 2 mapping populations. Useful introgression lines have been developed for several agronomic traits. It emerges that 40% O. nivara alleles were trait enhancing in both populations, and QTLs for grain quality overlapped with yield meta-QTLs and QTLs for dormancy and seed shattering.

Deep sequencing reveals the complex and coordinated transcriptional regulation of genes related to grain quality in rice cultivars

Background

Milling yield and eating quality are two important grain quality traits in rice. To identify the genes involved in these two traits, we performed a deep transcriptional analysis of developing seeds using both massively parallel signature sequencing (MPSS) and sequencing-by-synthesis (SBS). Five MPSS and five SBS libraries were constructed from 6-day-old developing seeds of Cypress (high milling yield), LaGrue (low milling yield), Ilpumbyeo (high eating quality), YR15965 (low eating quality), and Nipponbare (control).

Results

The transcriptomes revealed by MPSS and SBS had a high correlation co-efficient (0.81 to 0.90), and about 70% of the transcripts were commonly identified in both types of the libraries. SBS, however, identified 30% more transcripts than MPSS. Among the highly expressed genes in Cypress and Ilpumbyeo, over 100 conserved cis regulatory elements were identified. Numerous specifically expressed transcription factor (TF) genes were identified in Cypress (282), LaGrue (312), Ilpumbyeo (363), YR15965 (260), and Nipponbare (357). Many key grain quality-related genes (i.e., genes involved in starch metabolism, aspartate amino acid metabolism, storage and allergenic protein synthesis, and seed maturation) that were expressed at high levels underwent alternative splicing and produced antisense transcripts either in Cypress or Ilpumbyeo. Further, a time course RT-PCR analysis confirmed a higher expression level of genes involved in starch metabolism such as those encoding ADP glucose pyrophosphorylase (AGPase) and granule bound starch synthase I (GBSS I) in Cypress than that in LaGrue during early seed development.

Conclusion

This study represents the most comprehensive analysis of the developing seed transcriptome of rice available to date. Using two high throughput sequencing methods, we identified many differentially expressed genes that may affect milling yield or eating quality in rice. Many of the identified genes are involved in the biosynthesis of starch, aspartate family amino acids, and storage proteins. Some of the differentially expressed genes could be useful for the development of molecular markers if they are located in a known QTL region for milling yield or eating quality in the rice genome. Therefore, our comprehensive and deep survey of the developing seed transcriptome in five rice cultivars has provided a rich genomic resource for further elucidating the molecular basis of grain quality in rice.

Mapping QTL main and interaction influences on milling quality in elite US rice germplasm

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 2005-2007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTL × environment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of genetic × environment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating year-location combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.