Comparison of quantitative trait loci controlling seedling characteristics at two seedling stages using rice recombinant inbred lines

Identification of a Seed Vigor-Related QTL Cluster Associated with Weed Competitive Ability in Direct-Seeded Rice (Oryza Sativa L.)

Direct seeding of rice (Oryza sativa L.) is a low-labor and sustainable cultivation method that is used worldwide. Seed vigor and early vigor are important traits associated with seedling stand density (SSD) and weed competitive ability (WCA), which are key factors in direct-seeded rice (DSR) cultivation systems. Here, we developed a set of chromosome segment substitution lines with Xiushui134 as receptor parent and Yangdao6 as donor parent and used these lines as a mapping population to identify quantitative trait loci (QTLs) for seed vigor, which we evaluated based on germinability-related indicators (germination percentage (GP), germination energy (GE), and germination index (GI)) and seedling vigor-related indicators (root number (RN), root length (RL), and shoot length (SL) at 14 days after imbibition) under controlled conditions in an incubator. Ten QTLs were detected across four chromosomes, of which a cluster of QTLs (qGP11, qGE11, qGI11, and qRL11) co-localized on Chr. 11 with high LOD values (12.03, 8.13, 7.14, and 8.75, respectively). Fine mapping narrowed down the QTL cluster to a 0.7-Mb interval between RM26797 and RM6680. Further analysis showed that the QTL cluster has a significant effect (p < 0.01) on early vigor under hydroponic culture (root length, total dry weight) and direct seeding conditions (tiller number, aboveground dry weight). Thus, our combined analysis revealed that the QTL cluster influenced both seed vigor and early vigor. Identifying favorable alleles at this QTL cluster could facilitate the improvement of SSD and WCA, thereby addressing both major factors in DSR cultivation systems.

Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed translational regulation in plants in response to various environmental stimuli. However, there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues, especially those of rice, a main staple crop that feeds nearly half of the world's population. Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice, Shanyou 63 (SY63), and its parental varieties Zhenshan 97 and Minghui 63. The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels. We identified 3392 upstream open reading frames (uORFs), and the uORF-containing genes were enriched in transcription factors. Only 668 of 13 492 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency. Overall, these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.

Unraveling the genomic regions controlling the seed vigour index, root growth parameters and germination per cent in rice

High seed vigour ensures good quality seed and higher productivity. Early seedling growth parameters indicate seed vigour in rice. Seed vigour via physiological growth parameters is a complex trait controlled by many quantitative trait loci. A panel was prepared representing a population of 274 rice landraces by including genotypes from all the phenotypic groups of sixseedling stage physiological parameters including germination % for association mapping. Wide variations for the six studiedtraits were observed in the population. The population was classified into 3 genetic groups. Fixation indices indicated the presence of linkage disequilibrium in the population. The population was classified into subpopulations and each subpopulation showed correspondence with the 6 physiological traits. A total of 5 reported QTLs viz., qGP8.1 for germination % (GP); qSVII2.1, qSVII6.1 and qSVII6.2 for seed vigour index II (SVII), and qRSR11.1 for root-shoot ratio (RSR) were validated in this mapping population. In addition, 13 QTLs regulating the physiological parameters such as qSVI 11.1 for seed vigour index I; qSVI11.1 and qSVI12.1 for seed vigour index II; qRRG10.1, qRRG8.1, qRRG8.2, qRRG6.1 and qRRG4.1 for rate of root growth (RRG); qRSR2.1, qRSR3.1 and qRSR5.1 for root-shoot ratio (RSR) while qGP6.2 and qGP6.3 for germination %were identified. Additionally, co-localization or co-inheritance of QTLs, qGP8.1 and qSVI8.1 for GP and SVI-1; qGP6.2 and qRRG6.1 for GP and RRG, and qSVI11.1 and qRSR11.1 for SVI and RSR were detected. The QTLs identified in this study will be useful for improvement of seed vigour trait in rice.

Proofing Direct-Seeded Rice with Better Root Plasticity and Architecture

The underground reserve (root) has been an uncharted research territory with its untapped genetic variation yet to be exploited. Identifying ideal traits and breeding new rice varieties with efficient root system architecture (RSA) has great potential to increase resource-use efficiency and grain yield, especially under direct-seeded rice, by adapting to aerobic soil conditions. In this review, we tried to mine the available research information on the direct-seeded rice (DSR) root system to highlight the requirements of different root traits such as root architecture, length, number, density, thickness, diameter, and angle that play a pivotal role in determining the uptake of nutrients and moisture at different stages of plant growth. RSA also faces several stresses, due to excess or deficiency of moisture and nutrients, low or high temperature, or saline conditions. To counteract these hindrances, adaptation in response to stress becomes essential. Candidate genes such as early root growth enhancer PSTOL1, surface rooting QTL qSOR1, deep rooting gene DRO1, and numerous transporters for their respective nutrients and stress-responsive factors have been identified and validated under different circumstances. Identifying the desired QTLs and transporters underlying these traits and then designing an ideal root architecture can help in developing a suitable DSR cultivar and aid in further advancement in this direction.

Genetic analysis of rice seedling traits related to machine transplanting under different seeding densities

BACKGROUND

Due to the diversity of rice varieties and cropping systems in China, the limitation of seeding density and seedling quality makes it hard to improve machine-transplanted efficiency. Previous studies have shown that indica and japonica varieties varied in machine transplanting efficiency and optimal seeding density. In this study, a RIL population derived from '9311' and 'Nipponbare' were performed to explore the seedling traits variations and the genetic mechanism under three seeding densities.

RESULTS

The parents and RIL population exhibited similar trends as the seeding density increased, including seedling height and first leaf sheath length increases, shoot dry weight and root dry weight decreases. Among the 37 QTLs for six traits detected under the three seeding densities, 12 QTLs were detected in both three seeding densities. Five QTL hotspots identified clustered within genomic regions on chromosomes 1, 2, 4, 6 and 11. Specific QTLs such as qRDW_1.1 and qFLSL_5.1 were detected under low and high seeding densities, respectively. Detailed analysis the QTL regions identified under specific seeding densities revealed several candidate genes involved in phytohormones signals and abiotic stress responses. Whole-genome additive effects showed that '9311' contributed more loci enhancing trait performances than 'Nipponbare', indicating '9311' was more sensitive to the seeding density than 'Nipponbare'. The prevalence of negative epistasis effects indicated that the complementary two-locus homozygotes may not have marginal advantages over the means of the two parental genotypes.

CONCLUSIONS

Our results revealed the differences between indica rice and japonica rice seedling traits in response to seeding density. Several QTL hotspots involved in different traits and specific QTLs (such as qRDW_1.1 and qFLSL_5.1) in diverse seeding densities had been detected. Genome-wide additive and two-locus epistasis suggested a dynamic of the genetic control underlying different seeding densities. It was concluded that novel QTLs, additive and epistasis effects under specific seeding density would provide adequate information for rice seedling improvement during machine transplanting.

Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice

Background

Improving yield and yield-related traits is the crucial goal in breeding programmes of cereals. Meta-QTL (MQTL) analysis discovers the most stable QTLs regardless of populations genetic background and field trial conditions and effectively narrows down the confidence interval (CI) for identification of candidate genes (CG) and markers development.

Results

A comprehensive MQTL analysis was implemented on 1052 QTLs reported for yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) in 122 rice populations evaluated under normal condition from 1996 to 2019. Consequently, these QTLs were confined into 114 MQTLs and the average CI was reduced up to 3.5 folds in compare to the mean CI of the original QTLs with an average of 4.85 cM CI in the resulted MQTLs. Among them, 27 MQTLs with at least five initial QTLs from independent studies were considered as the most stable QTLs over different field trials and genetic backgrounds. Furthermore, several known and novel CGs were detected in the high confident MQTLs intervals. The genomic distribution of MQTLs indicated the highest density at subtelomeric chromosomal regions. Using the advantage of synteny and comparative genomics analysis, 11 and 15 ortho-MQTLs were identified at co-linear regions between rice with barley and maize, respectively. In addition, comparing resulted MQTLs with GWAS studies led to identification of eighteen common significant chromosomal regions controlling the evaluated traits.

Conclusion

This comprehensive analysis defines a genome wide landscape on the most stable loci associated with reliable genetic markers and CGs for yield and yield-related traits in rice. Our findings showed that some of these information are transferable to other cereals that lead to improvement of their breeding programs.

QTLs identification for nitrogen and phosphorus uptake-related traits using ultra-high density SNP linkage

To understand the genetic basis of nitrogen and phosphorus uptake in the cultivated rice, quantitative trait loci (QTL) analysis for 7 nitrogen and phosphorus uptake-related traits including above-ground biomass (AGB), leaf colour value (SPAD) in heading stage, grain nitrogen concentration (GNC), grain nitrogen content of the plant, total nitrogen content (TNC), grain phosphorus concentration, total phosphorus content (TPC) were conducted using SNP markers in a F2 population derived from a cross between GH128 and W6827. A total of 21 QTLs for nitrogen and phosphorus uptake-related traits distributed in 16 regions along 6 chromosomes were detected using a high density genetic map consisting of 1582 bin markers, with QTLs maximum explaining 8.19% of the phenotypic variation. Nine QTLs (42.9% of total QTLs) were detected on chromosome 2. Among them, two QTL clusters including AGB, TNC, TPC and GNC were also detected in the region bin 140 and bin 146 on the chromosome 2. The distance between the two clusters was only 4.1 cM. The presence of QTL clusters has important significance and could be useful in molecular marker assisted breeding. These genomic regions might be deployed for the simultaneous improving the use efficiency of nitrogen and phosphorus in rice breeding.

Genome-wide association mapping of leaf mass traits in a Vietnamese rice landrace panel

Leaf traits are often strongly correlated with yield, which poses a major challenge in rice breeding. In the present study, using a panel of Vietnamese rice landraces genotyped with 21,623 single-nucleotide polymorphism markers, a genome-wide association study (GWAS) was conducted for several leaf traits during the vegetative stage. Vietnamese landraces are often poorly represented in panels used for GWAS, even though they are adapted to contrasting agrosystems and can contain original, valuable genetic determinants. A panel of 180 rice varieties was grown in pots for four weeks with three replicates under nethouse conditions. Different leaf traits were measured on the second fully expanded leaf of the main tiller, which often plays a major role in determining the photosynthetic capacity of the plant. The leaf fresh weight, turgid weight and dry weight were measured; then, from these measurements, the relative tissue weight and leaf dry matter percentage were computed. The leaf dry matter percentage can be considered a proxy for the photosynthetic efficiency per unit leaf area, which contributes to yield. By a GWAS, thirteen QTLs associated with these leaf traits were identified. Eleven QTLs were identified for fresh weight, eleven for turgid weight, one for dry weight, one for relative tissue weight and one for leaf dry matter percentage. Eleven QTLs presented associations with several traits, suggesting that these traits share common genetic determinants, while one QTL was specific to leaf dry matter percentage and one QTL was specific to relative tissue weight. Interestingly, some of these QTLs colocalize with leaf- or yield-related QTLs previously identified using other material. Several genes within these QTLs with a known function in leaf development or physiology are reviewed.

Genetic dissection of seedling vigour in a diverse panel from the 3,000 Rice (Oryza sativa L.) Genome Project

Seedling vigour (SV) is important for direct seeding rice (Oryza sativa L.), especially in a paddy-direct seeding system, but the genetic mechanisms behind the related traits remain largely unknown. Here, we used 744 germplasms, having at least two subsets, for the detection of quantitative trait loci (QTLs) affecting the SV-related traits tiller number, plant height, and aboveground dry weight at three sampling stages, 27, 34, and 41 d after sowing. A joint map based on GAPIT and mrMLM produced a satisfying balance between type I and II errors. In total, 42 QTL regions, containing 18 (42.9%) previously reported overlapping QTL regions and 24 new ones, responsible for SV were detected throughout the genome. Four QTL regions, qSV1a, qSV3e, qSV4c, and qSV7c, were delimited and harboured quantitative trait nucleotides that are responsible for SV-related traits. Favourable haplotype mining for the candidate genes within these four regions, as well as the early SV gene OsGA20ox1, was performed, and the favourable haplotypes were presented with donors from the 3,000 Rice Genome Project. This work provides new information and materials for the future molecular breeding of direct seeding rice, especially in paddy-direct seeding cultivation systems.

Genetic analysis of roots and shoots in rice seedling by association mapping

The vigorous shoots and roots help to improve drought resistance and post-transplanting recovery in rice seedlings (Oryza sativa L.). Hundreds of loci related to root system have been identified recently, but little research has been done on shoot traits, and the relationship between roots and shoots development is also still unclear. The objective of this study was to identify associated loci for roots and shoots in rice seedlings as well as to screen pleiotropic QTLs involved in coordinated development of roots and shoots. Using mini core collection of 273 cultivated rice accessions and 280 simple-sequence repeat markers, we investigated six traits [root length (RL), root thickness (RT), root weight (RW), shoot length (SL), shoot weight (SW) and ratio of root-to-shoot mass] in seedlings. Study was performed in hydroponic medium and genetic analysis was performed by association mapping using general linear model (GLM) with population structure (Q) and mixed linear model (MLM) involving Q and familial relatedness (K). Two subgroups indica and japonica showed significant differences in RT, RW and SW. Maximum correlation was observed between RW and SW. Using GLM 65 QTLs for root and 43 QTLs associated with shoot traits were detected. Among them, seven QTLs were present between RL and RW and five common QTLs were detected between SL and SW with high phenotypic variation effects (PVEs). Two key pleiotropic QTLs were also identified involved in collaborative development of roots and shoots in rice seedlings. Importantly, 17 and 10 QTLs were identified for root and shoot traits respectively in both studies of GLM and MLM. More common QTLs with high PVEs between root and shoot traits suggested that longitudinal growth (RL and SL) played an important role in accumulation of biomass (RW and SW). Considering the obvious phenotypic differences and fewer common QTLs between indica and japonica, we suggested that there could be different mechanisms of seedling development between both subpopulations. Key pleiotropic QTLs and QTLs identified for root and shoot traits in both studies of GLM and MLM could be preferentially used in marker-assisted breeding for strong rice seedling.

Genomic regions responsible for seminal and crown root lengths identified by 2D & 3D root system image analysis

Background

Genetic improvement of root system architecture is a promising approach for improved uptake of water and mineral nutrients distributed unevenly in the soil. To identify genomic regions associated with the length of different root types in rice, we quantified root system architecture in a set of 26 chromosome segment substitution lines derived from a cross between lowland indica rice, IR64, and upland tropical japonica rice, Kinandang Patong, (IK-CSSLs), using 2D & 3D root phenotyping platforms.

Results

Lengths of seminal and crown roots in the IK-CSSLs grown under hydroponic conditions were measured by 2D image analysis (RootReader2D). Twelve CSSLs showed significantly longer seminal root length than the recurrent parent IR64. Of these, 8 CSSLs also exhibited longer total length of the three longest crown roots compared to IR64. Three-dimensional image analysis (RootReader3D) for these CSSLs grown in gellan gum revealed that only one CSSL, SL1003, showed significantly longer total root length than IR64. To characterize the root morphology of SL1003 under soil conditions, SL1003 was grown in Turface, a soil-like growth media, and roots were quantified using RootReader3D. SL1003 had larger total root length and increased total crown root length than did IR64, although its seminal root length was similar to that of IR64. The larger TRL in SL1003 may be due to increased crown root length.

Conclusions

SL1003 carries an introgression from Kinandang Patong on the long arm of chromosome 1 in the genetic background of IR64. We conclude that this region harbors a QTL controlling crown root elongation.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4639-4) contains supplementary material, which is available to authorized users.

Detection of QTLs for seedling characteristics in barley (Hordeum vulgare L.) grown under hydroponic culture condition

BACKGROUND

Seedling characteristics play significant roles in the growth and development of barley (Hordeum vulgare L.), including stable stand establishment, water and nutrients uptake, biotic resistance and abiotic stresses, and can influence yield and quality. However, the genetic mechanisms underlying seedling characteristics in barley are largely unknown and little research has been done. In the present work, 21 seedling-related characteristics are assessed in a barley double haploid (DH) population, grown under hydroponic conditions. Of them, leaf age (LAG), shoot height (SH), maximum root length (MRL), main root number (MRN) and seedling fresh weight (SFW) were investigated at the 13th, 20th, 27th, and 34th day after germination. The objectives were to identify quantitative trait loci (QTLs) underlying these seedling characteristics using a high-density linkage map and to reveal the QTL expression pattern by comparing the QTLs among four different seedling growth stages.

RESULTS

A total of 70 QTLs were distributed over all chromosomes except 4H, and, individually, accounted for 5.01%-77.78% of phenotypic variation. Out of the 70 detected QTLs, 23 showed a major effect on 14 seedling-related characteristics. Ten co-localized chromosomal regions on 2H (five regions), 3H (two regions) and 7H (three regions) involved 39 QTLs (55.71%), each simultaneously influenced more than one trait. Meanwhile, 9 co-localized genomic regions involving 22 QTLs for five seedling characteristics (LAG, SH, MRL, MRN and SFW) at the 13th, 20th, 27th and 34th day-old seedling were common for two or more growth stages of seedling. QTL in the vicinity of Vrs1 locus on chromosome 2H with the favorable alleles from Huadamai 6 was found to have the largest main effects on multiple seedling-related traits.

CONCLUSIONS

Six QTL cluster regions associated with 16 seedling-related characteristics were observed on chromosome 2H, 3H and 7H. The majority of the 29 regions identified for five seedling characteristics were selectively expressed at different developmental stages. The genetic effects of 9 consecutive expression regions displayed different developmental influences at different developmental stages. These findings enhanced our understanding of a genetic basis underlying seedling characteristics in barley. Some QTLs detected here could be used for marker-assisted selection (MAS) in barley breeding.

QTL mapping using an ultra-high-density SNP map reveals a major locus for grain yield in an elite rice restorer R998

To dissect the genetic basis of yield formation in restorer line of hybrid rice, we conducted QTL analysis for 6 yield traits including panicles per plant (PPP), grains per panicle (GPP), grain yield per plant (GY), thousand-grain weight (TGW), above-ground biomass (AGB), and harvest index (HI) using SNP markers in a recombinant inbred lines (RILs) population derived from a cross between a tropical japonica inbred Francis and an elite indica restorer Guanghui 998 (R998). A total of 26 QTLs were detected using a high density genetic map consisting of 3016 bin markers. Nineteen out of the 26 QTL alleles from R998 had a beneficial effect on yield traits. Most of the QTLs were co-located with previously reported rice QTLs. qAGB6 and qHI9, controlling AGB and HI respectively, were detected as novel QTLs. Four QTLs for GY were repeatedly detected across two years, with all the beneficial alleles from R998. Notably, qGY8 explained over 20% of the yield variance in both years. Moreover, qGY8 together with qTGW8 and qHI8 formed a QTL cluster. Markers tightly linked with qGY8 were developed. Cloning of qGY8 will facilitate its further exploitation in high-yield breeding.

QTL Hotspots for Early Vigor and Related Traits under Dry Direct-Seeded System in Rice (Oryza sativa L.)

Strong seedling vigor is desirable trait in dry direct-seeded rice (DSR) for enhancing crop establishment and the ability to compete against weeds. A set of 253 BC3F4 lines derived from cross between Swarna and Moroberekan was phenotyped for early vigor (EV) and 8 related traits viz., early uniform emergence (EUE), shoot length (SHL), stem length (SL), shoot fresh weight (SFW), total fresh weight (TFW), shoot dry weight (SDW), total dry weight (TDW), and root dry weight (RDW). Composite interval mapping analysis using genotypic data from 194 SNP markers identified six genomic regions associated with traits on chromosomes 3, 4, 5, and 6 with phenotypic variance ranging from 2.5 to 18.6%. Among them 2 QTL regions; one on chr3 (id3001701-id300833) and the other on chr5 (wd5002636-id5001470) were identified as QTL hotspots A and B respectively and expressed consistently in field as well as glasshouse condition. The majority of QTLs identified for early vigor, and related traits were clustered in the QTL hotspots A (qEV3.1, qEUE3.1, qSHL3.1, qSL3.1, qSFW3.1, qTFW3.1, qRDW3.1 ) and QTL hotspot B (qEV5.1, qEUE5.1, qSHL5.1, qSL5.1, qSFW5.1, qSDW5.1, qTDW5.1 ). Ten putative candidate genes viz., 1-alpha-amylase precursor, 2-glutamate decarboxylase, 1-ethylene-insensitive 3, 3-expansin precursor, and 3-phenylalanine ammonia-lyase associated with the target traits were identified in the selected QTL regions. Mutations were identified in the coding region of alpha-amylase precursor and ethylene-insensitive 3 gene between the parents which can be utilized in marker assisted breeding. Trait relationships among the agro-physiological traits were examined to select the best genotypes for the given traits for use in future breeding programs.

Genetic Components of Heterosis for Seedling Traits in an Elite Rice Hybrid Analyzed Using an Immortalized F2 Population

Utilization of heterosis has greatly contributed to rice productivity in China and many Asian countries. Superior hybrids usually show heterosis at two stages: canopy development at vegetative stage and panicle development at reproductive stage resulting in heterosis in yield. Although the genetic basis of heterosis in rice has been extensively investigated, all the previous studies focused on yield traits at maturity stage. In this study, we analyzed the genetic basis of heterosis at seedling stage making use of an "immortalized F2" population composed of 105 hybrids produced by intercrossing recombinant inbred lines (RILs) from a cross between Zhenshan 97 and Minghui 63, the parents of Shanyou 63, which is an elite hybrid widely grown in China. Eight seedling traits, seedling height, tiller number, leaf number, root number, maximum root length, root dry weight, shoot dry weight and total dry weight, were investigated using hydroponic culture. We analyzed single-locus and digenic genetic effects at the whole genome level using an ultrahigh-density SNP bin map obtained by population re-sequencing. The analysis revealed large numbers of heterotic effects for seedling traits including dominance, overdominance and digenic dominance (epistasis) in both positive and negative directions. Overdominance effects were prevalent for all the traits, and digenic dominance effects also accounted for a large portion of the genetic effects. The results suggested that cumulative small advantages of the single-locus effects and two-locus interactions, most of which could not be detected statistically, could explain the genetic basis of seedling heterosis of the F1 hybrid.

Evidence for selection on gene expression in cultivated rice (Oryza sativa)

Artificial selection has been used throughout plant domestication and breeding to develop crops that are adapted to diverse environments. Here, we investigate whether gene regulatory changes have been widespread targets of lineage-specific selection in cultivated lines Minghui 63 and Zhenshan 97 of rice, Oryza sativa. A line experiencing positive selection for either an increase or a decrease in genes' transcript abundances is expected to have an overabundance of expression quantitative trait locus (eQTL) alleles that increase or decrease those genes' expression, respectively. Results indicate that several genes that share Gene Ontology terms or are members of the same coexpression module have eQTL alleles from one parent that consistently increase gene expression relative to the second parent. A second line of evidence for lineage-specific selection is an overabundance of cis-trans pairs of eQTL alleles that affect gene expression in the same direction (are reinforcing). Across all cis-trans pairs of eQTL, including pairs that both weakly and strongly affect gene expression, there is no evidence for selection. However, the frequency of genes with reinforcing eQTL increases with eQTL strength. Therefore, there is evidence that eQTL with strong effects were positively selected during rice cultivation. Among 41 cis-trans pairs with strong trans eQTL, 31 have reinforcing eQTL. Several of the candidate genes under positive selection accurately predict phenotypic differences between Minghui 63 and Zhenshan 97. Overall, our results suggest that positive selection for regulatory alleles may be a key factor in plant improvement.

Dro1, a major QTL involved in deep rooting of rice under upland field conditions

Developing a deep root system is an important strategy for avoiding drought stress in rice. Using the 'basket' method, the ratio of deep rooting (RDR; the proportion of total roots that elongated through the basket bottom) was calculated to evaluate deep rooting. A new major quantitative trait locus (QTL) controlling RDR was detected on chromosome 9 by using 117 recombinant inbred lines (RILs) derived from a cross between the lowland cultivar IR64, with shallow rooting, and the upland cultivar Kinandang Patong (KP), with deep rooting. This QTL explained 66.6% of the total phenotypic variance in RDR in the RILs. A BC(2)F(3) line homozygous for the KP allele of the QTL had an RDR of 40.4%, compared with 2.6% for the homozygous IR64 allele. Fine mapping of this QTL was undertaken using eight BC(2)F(3) recombinant lines. The RDR QTL Dro1 (Deeper rooting 1) was mapped between the markers RM24393 and RM7424, which delimit a 608.4 kb interval in the reference cultivar Nipponbare. To clarify the influence of Dro1 in an upland field, the root distribution in different soil layers was quantified by means of core sampling. A line homozygous for the KP allele of Dro1 (Dro1-KP) and IR64 did not differ in root dry weight in the shallow soil layers (0-25 cm), but root dry weight of Dro1-KP in deep soil layers (25-50 cm) was significantly greater than that of IR64, suggesting that Dro1 plays a crucial role in increased deep rooting under upland field conditions.

Genetic variation in biomass traits among 20 diverse rice varieties

Biofuels provide a promising route of producing energy while reducing reliance on petroleum. Developing sustainable liquid fuel production from cellulosic feedstock is a major challenge and will require significant breeding efforts to maximize plant biomass production. Our approach to elucidating genes and genetic pathways that can be targeted for improving biomass production is to exploit the combination of genomic tools and genetic diversity in rice (Oryza sativa). In this study, we analyzed a diverse set of 20 recently resequenced rice varieties for variation in biomass traits at several different developmental stages. The traits included plant size and architecture, aboveground biomass, and underlying physiological processes. We found significant genetic variation among the 20 lines in all morphological and physiological traits. Although heritability estimates were significant for all traits, heritabilities were higher in traits relating to plant size and architecture than for physiological traits. Trait variation was largely explained by variety and breeding history (advanced versus landrace) but not by varietal groupings (indica, japonica, and aus). In the context of cellulosic biofuels development, cell wall composition varied significantly among varieties. Surprisingly, photosynthetic rates among the varieties were inversely correlated with biomass accumulation. Examining these data in an evolutionary context reveals that rice varieties have achieved high biomass production via independent developmental and physiological pathways, suggesting that there are multiple targets for biomass improvement. Future efforts to identify loci and networks underlying this functional variation will facilitate the improvement of biomass traits in other grasses being developed as energy crops.

A global analysis of QTLs for expression variations in rice shoots at the early seedling stage

Analyses of quantitative trait loci (QTLs) for expression levels (eQTLs) of genes reveal a genetic relationship between expression variation and the regulator, thus unlocking information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used an Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. In total, 1632 single-feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hot spots in the rice genome, each of which controls transcript variations of many e-traits. Gene ontology analysis revealed an enrichment of certain functional categories of genes in some of the eQTL hot spots. In particular, eQTLs for e-traits involving the DNA metabolic process was significantly enriched in several eQTL hot spots on chromosomes 3, 5 and 10. Several e-traits co-localizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided clues for the identification and characterization of the regulatory network in the whole genome at the transcriptional level.

Fine-mapping of qRL6.1, a major QTL for root length of rice seedlings grown under a wide range of NH4(+) concentrations in hydroponic conditions

Root system development is an important target for improving yield in cereal crops. Active root systems that can take up nutrients more efficiently are essential for enhancing grain yield. In this study, we attempted to identify quantitative trait loci (QTL) involved in root system development by measuring root length of rice seedlings grown in hydroponic culture. Reliable growth conditions for estimating the root length were first established to renew nutrient solutions daily and supply NH4(+) as a single nitrogen source. Thirty-eight chromosome segment substitution lines derived from a cross between 'Koshihikari', a japonica variety, and 'Kasalath', an indica variety, were used to detect QTL for seminal root length of seedlings grown in 5 or 500 microM NH4(+). Eight chromosomal regions were found to be involved in root elongation. Among them, the most effective QTL was detected on a 'Kasalath' segment of SL-218, which was localized to the long-arm of chromosome 6. The 'Kasalath' allele at this QTL, qRL6.1, greatly promoted root elongation under all NH4(+) concentrations tested. The genetic effect of this QTL was confirmed by analysis of the near-isogenic line (NIL) qRL6.1. The seminal root length of the NIL was 13.5-21.1% longer than that of 'Koshihikari' under different NH4(+) concentrations. Toward our goal of applying qRL6.1 in a molecular breeding program to enhance rice yield, a candidate genomic region of qRL6.1 was delimited within a 337 kb region in the 'Nipponbare' genome by means of progeny testing of F2 plants/F3 lines derived from a cross between SL-218 and 'Koshihikari'.

Identification of related QTLs at late developmental stage in rice (Oryza sativa L.) under two nitrogen levels

QTL underlying related traits at the late developmental stage under two different nitrogen levels were investigated in rice using a population of chromosome segment substitution lines (CSSL) derived from a cross between Teqing and Lemont. A total of 31 QTLs referring 5 traits, that is, plant height (PH), panicle number per plant (PN), chlorophyll content (CC), shoot dry weight (SDW) and grain yield per plant (YD), were detected. Under normal N level, 3 QTLs were detected for each trait, while under low N level, 5, 4, 5 and 2 QTLs were detected for PH, PN, CC and SDW respectively. Most of the QTLs were located on chromosome 2, 3, 7, 11 and 12. QTLs controlling different traits or the same trait under different N levels were mapped on the same or adjacent intervals, forming several clusters in rice chromosomes. More than two traits were controlled by QTLs on one of four intervals (RM30-RM439, RM18-RM478, RM309-RM270, and RM235-RM17), suggesting that there were some pleiotropic effects. It was supposed that some QTLs only detected at low N level might be associated with the ability to tolerate the low N stress in rice.

Fine mapping of a major quantitative trait loci, qSSP7, controlling the number of spikelets per panicle as a single Mendelian factor in rice

In our previous studies, one putative QTL affecting number of spikelets per panicle (SPP) was identified in the pericentromeric region of rice chromosome 7 using a recombinant inbred population. In order to define the QTL (qSPP7), RI50, a recombinant inbred line with 70% of genetic background same as the female parent of Zhenshan 97, was selected to produce near-isogenic lines for the target region in the present study. In a BC(2)F(2) population consisting of 190 plants, the frequency distribution of SPP was shown to be discontinuous and followed the expected Mendelian ratios (1:2:1 by progeny test) for single locus segregation. qSPP7 was mapped to a 0.4 cM region between SSR marker RM3859 and RFLP marker C39 based on tests of the BC(2)F(2) population and its progeny. Its additive and dominant effects on SPP were 51.1 and 24.9 spikelets, respectively. Of great interest, the QTL region also had effects on grain yield per plant (YD), 1,000 grain weight (GW), tillers per plant (TPP) and seed setting ratio (SR). Significant correlations were observed between SPP and YD (r = 0.66) and between SPP and SR (r = -0.29) in the progeny test. 1082 extremely small panicle plants of a BC(3)F(2) population containing 8,400 individuals were further used to fine map the QTL. It turns out that qSPP7 co-segregated with two markers, RM5436 and RM5499 spanning a physical distance of 912.4 kb. Overall results suggested that recombination suppression occurred in the region and positional cloning strategy is infeasible for qSPP7 isolation. The higher grain yield of Minghui 63 homozygote as compared to the heterozygote suggested that Minghui 63 homozygote at qSPP7 in hybrid rice could further improve its yield.

Mapping QTLs for seedling characteristics under different water supply conditions in rice (Oryza sativa)

A greater understanding of the genetics of responses to water deficit/drought may be helpful in improving water-deficit resistance in the early stages of growth in rice. A recombinant inbred population derived from a cross between Zhenshan 97 and Minghui 63 was grown in hydroponic culture to characterize the responses of seedlings to water deficit imposed by PEG 6000 and to identify quantitative trait loci (QTLs) for seedling characteristics under both well-watered and water-deficit conditions. Generally, the two parents showed significant differences in plant height (PH), maximum root length (MRL), shoot fresh weight (SFW), root fresh weight (RFW), number of roots and root:shoot ratio based on fresh weight under both well-watered and water-deficit conditions. For two parents, PH and SFW were significantly inhibited under water deficit. However, the other four traits had larger values under water deficit. Among 26 and 34 QTLs detected for the six traits studied under the well-watered and water-deficit conditions, respectively, a total of 14 QTLs for SFW, PH, RFW and MRL (23% of total QTLs detected) were detected in similar or tight linkage regions in both conditions. Among 11 intervals on 7 chromosomes identified to harbor multiple QTLs, 8 intervals were found to affect related traits under the two water supply conditions and 3 intervals were observed to be water supply-specific regions and had effects only under well-watered conditions, suggesting that water supply-specific regions or QTLs may be closely associated with the responses of lines to water deficit in the study. Several regions for the traits studied were also found to affect the root-related traits in previous studies and might be used in marker-assisted selection for drought-resistant rice in breeding programs.

Mapping QTLs of root morphological traits at different growth stages in rice

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.

QTLs for shelf life in lettuce co-locate with those for leaf biophysical properties but not with those for leaf developmental traits

Developmental and biophysical leaf characteristics that influence post-harvest shelf life in lettuce, an important leafy crop, have been examined. The traits were studied using 60 informative F9 recombinant inbed lines (RILs) derived from a cross between cultivated lettuce (Lactuca sativa cv. Salinas) and wild lettuce (L. serriola acc. UC96US23). Quantitative trait loci (QTLs) for shelf life co-located most closely with those for leaf biophysical properties such as plasticity, elasticity, and breakstrength, suggesting that these are appropriate targets for molecular breeding for improved shelf life. Significant correlations were found between shelf life and leaf size, leaf weight, leaf chlorophyll content, leaf stomatal index, and epidermal cell number per leaf, indicating that these pre-harvest leaf development traits confer post-harvest properties. By studying the population in two contrasting environments in northern and southern Europe, the genotype by environment interaction effects of the QTLs relevant to leaf development and shelf life were assessed. In total, 107 QTLs, distributed on all nine linkage groups, were detected from the 29 traits. Only five QTLs were common in both environments. Several areas where many QTLs co-located (hotspots) on the genome were identified, with relatively little overlap between developmental hotspots and those relating to shelf life. However, QTLs for leaf biophysical properties (breakstrength, plasticity, and elasticity) and cell area correlated well with shelf life, confirming that the ideal ideotype lettuce should have small cells with strong cell walls. The identification of QTLs for leaf development, strength, and longevity will lead to a better understanding of processability at a genetic and cellular level, and allow the improvement of salad leaf quality through marker-assisted breeding.