Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population II: conventional QTL analysis

Quantitative Trait Loci Mapping Identified Candidate Genes Involved in Plant Height Regulation in Rice

Rice plant height is an agricultural trait closely related to biomass, lodging tolerance, and yield. Identifying quantitative trait loci (QTL) regions related to plant height regulation and developing strategies to screen potential candidate genes can improve agricultural traits in rice. In this study, a double haploid population (CNDH), derived by crossing 'Cheongcheong' and 'Nagdong' individuals, was used, and a genetic map was constructed with 222 single-sequence repeat markers. In the RM3482-RM212 region on chromosome 1, qPh1, qPh1-1, qPh1-3, qPh1-5, and qPh1-6 were identified for five consecutive years. The phenotypic variance explained ranged from 9.3% to 13.1%, and the LOD score ranged between 3.6 and 17.6. OsPHq1, a candidate gene related to plant height regulation, was screened in RM3482-RM212. OsPHq1 is an ortholog of gibberellin 20 oxidase 2, and its haplotype was distinguished by nine SNPs. Plants were divided into two groups based on their height, and tall and short plants were distinguished and clustered according to the expression level of OsPHq1. QTLs and candidate genes related to plant height regulation, and thus, biomass regulation, were screened and identified in this study, but the molecular mechanism of the regulation remains poorly known. The information obtained in this study will help develop molecular markers for marker-assisted selection and breeding through rice plant height control.

BSA-Seq and Fine Linkage Mapping for the Identification of a Novel Locus (qPH9) for Mature Plant Height in Rice (Oryza sativa)

BACKGROUND

Plant height is a key factor in the determination of rice yield since excessive height can easily cause lodging and reduce yield. Therefore, the identification and analysis of plant height-related genes to elucidate their physiological, biochemical, and molecular mechanisms have significant implications for rice breeding and production.

RESULTS

High-throughput quantitative trait locus (QTL) sequencing analysis of a 638-individual F2:3 mapping population resulted in the identification of a novel height-related QTL (qPH9), which was mapped to a 2.02-Mb region of Chromosome 9. Local QTL mapping, which was conducted using 13 single nucleotide polymorphism (SNP)-based Kompetitive allele-specific PCR (KASP) markers for the qPH9 region, and traditional linkage analysis, facilitated the localization of qPH9 to a 126-kb region that contained 15 genes. Subsequent haplotype and sequence analyses indicated that OsPH9 was the most probable candidate gene for plant height at this locus, and functional analysis of osph9 CRISPR/Cas9-generated OsPH9 knockout mutants supported this conclusion.

CONCLUSION

OsPH9 was identified as a novel regulatory gene associated with plant height in rice, along with a height-reducing allele in 'Dongfu-114' rice, thereby representing an important molecular target for rice improvement. The findings of the present study are expected to spur the investigation of genetic mechanisms underlying rice plant height and further the improvement of rice plant height through marker-assisted selection.

Shaping the root system architecture in plants for adaptation to drought stress

Root system architecture plays an important role in plant adaptation to drought stress. The root system architecture (RSA) consists of several structural features, which includes number and length of main and lateral roots along with the density and length of root hairs. These features exhibit plasticity under water-limited environments and could be critical to developing crops with efficient root systems for adaptation under drought. Recent advances in the omics approaches have significantly improved our understanding of the regulatory mechanisms of RSA remodeling under drought and the identification of genes and other regulatory elements. Plant response to drought stress at physiological, morphological, biochemical, and molecular levels in root cells is regulated by various phytohormones and their crosstalk. Stress-induced reactive oxygen species play a significant role in regulating root growth and development under drought stress. Several transcription factors responsible for the regulation of RSA under drought have proven to be beneficial for developing drought tolerant crops. Molecular breeding programs for developing drought-tolerant crops have been greatly benefitted by the availability of quantitative trait loci (QTLs) associated with the RSA regulation. In the present review, we have discussed the role of various QTLs, signaling components, transcription factors, microRNAs and crosstalk among various phytohormones in shaping RSA and present future research directions to better understand various factors involved in RSA remodeling for adaptation to drought stress. We believe that the information provided herein may be helpful in devising strategies to develop crops with better RSA for efficient uptake and utilization of water and nutrients under drought conditions.

Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship

The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.

Drought Resistance Loci in Recombinant Lines of Iranian Oryza sativa L. in Germination Stage

In order to locate control genes related to Oryza sativa L. traits at the germination stage under normal conditions and at drought stress levels (−4.5 and −9.0 bar), we evaluated 120 F8 generation offspring from the cross between two cultivars Neda × Ahlemitarum in a factorial experiment in a completely randomized block design with three replications in 2013 in the botanical laboratory of Gonbad Kavous University. A linkage map was prepared using 90 Simple Sequence Repeats (SSR) markers and 28 Inter Simple Sequence Repeats (ISSR), and 6 iPBS and 9 IRAP markers (265 polymorphic alleles). The results of the analysis of variance showed that all of the evaluated traits had a significant difference at the probability level of 1%. Hence, it can be noted that the desired genetic diversity can be found between genotypes. The results of the stepwise regression analysis for the germination percentage as a dependent variable and other traits as independent variables in the studied treatments showed that under normal conditions, there was variable coleoptile length, but under drought stress of −4.5 and −9.0 bar, the variable plumule dry weight entered the model. In this study, the markers included in RM1-RM490 and ISSR2-3-RM133 of chromosomes 1 and 6 of Oryza sativa were identified as the main regulators of traits associated with Oryza sativa drought resistance. In particular, they present the quantitative trait loci (QTL) that control the first stages of germination of Oryza sativa in water stress conditions.

Genome-Wide Association Study Reveals the Genetic Architecture of Seed Vigor in Oats

Seed vigor is crucial for crop early establishment in the field and is particularly important for forage crop production. Oat (Avena sativa L.) is a nutritious food crop and also a valuable forage crop. However, little is known about the genetics of seed vigor in oats. To investigate seed vigor-related traits and their genetic architecture in oats, we developed an easy-to-implement image-based phenotyping pipeline and applied it to 650 elite oat lines from the Collaborative Oat Research Enterprise (CORE). Root number, root surface area, and shoot length were measured in two replicates. Variables such as growth rate were derived. Using a genome-wide association (GWA) approach, we identified 34 and 16 unique loci associated with root traits and shoot traits, respectively, which corresponded to 41 and 16 unique SNPs at a false discovery rate < 0.1. Nine root-associated loci were organized into four sets of homeologous regions, while nine shoot-associated loci were organized into three sets of homeologous regions. The context sequences of five trait-associated markers matched to the sequences of rice, Brachypodium and maize (E-value < 10-10), including three markers matched to known gene models with potential involvement in seed vigor. These were a glucuronosyltransferase, a mitochondrial carrier protein domain containing protein, and an iron-sulfur cluster protein. This study presents the first GWA study on oat seed vigor and data of this study can provide guidelines and foundation for further investigations.

Root Response to Drought Stress in Rice (Oryza sativa L.)

The current unpredictable climate changes are causing frequent and severe droughts. Such circumstances emphasize the need to understand the response of plants to drought stress, especially in rice, one of the most important grain crops. Knowledge of the drought stress response components is especially important in plant roots, the major organ for the absorption of water and nutrients from the soil. Thus, this article reviews the root response to drought stress in rice. It is presented to provide readers with information of use for their own research and breeding program for tolerance to drought stress in rice.

Genetic dissection of developmental responses of agro-morphological traits under different doses of nutrient fertilizers using high-density SNP markers

The production and productivity of rice (Oryza sativa L.) are primarily influenced by the application of the critical nutrients nitrogen (N), phosphorus (P), and potassium (K). However, excessive application of these fertilizers is detrimental to the environment and increases the cost of production. Hence, there is a need to develop varieties that simultaneously increase yields under both optimal and suboptimal rates of fertilizer application by maximizing nutrient use efficiency (NuUE). To unravel the hidden genetic variation and understand the molecular and physiological mechanisms of NuUE, three different mapping populations (MPs; BC1F5) derived from three donors (Haoannong, Cheng-Hui 448, and Zhong 413) and recipient Weed Tolerant Rice 1 were developed. A total of three favorable agronomic traits (FATs) were considered as the measure of NuUE. Analysis of variance and descriptive statistics indicated the existence of genetic variation for NuUE and quantitative inheritance of FATs. The genotypic data from single-nucleotide polymorphism (SNP) markers from Tunable Genotyping-By-Sequencing (tGBS) and phenotypic values were used for locating the genomic regions conferring NuUE. A total of 19 quantitative trait loci (QTLs) were detected, out of which 11 QTLs were putative on eight chromosomes, which individually explained 17.02% to 34.85% of the phenotypic variation. Notably, qLC-II_1 and qLC-II_11 detected at zero fertilizer application showed higher performance for LC under zero percentage of NPK fertilizer. The remarkable findings of the present study are that the detected QTLs were associated in building tolerance to low/no nutrient application and six candidate genes on chromosomes 2 and 5 within these putative QTLs were found associated with low nutrient tolerance and related to several physiological and metabolic pathways involved in abiotic stress tolerance. The identified superior introgressed lines (ILs) and trait-associated genetic regions can be effectively used in marker-assisted selection (MAS) for NuUE breeding programs.

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.

Spatial Effects and GWA Mapping of Root Colonization Assessed in the Interaction Between the Rice Diversity Panel 1 and an Arbuscular Mycorrhizal Fungus

If water saving methods of rice management are to be adopted, the interaction between rice plants and arbuscular mycorrhizal (AM) fungi will grow in agronomic significance. As yet there are very few studies on the interaction between rice and AM fungi and none on host genetics. A subset 334 cultivars from the Rice Diversity Panel 1 were grown in 250 L boxes filled with phosphorus (P) deficient aerobic soil without addition, with added rock phosphate and with rock phosphate and the AM fungus Rhizophagus irregularis. Statistical analysis of position of plants revealed a positive effect of their neighbors on their dry weight which was stronger in the presence of rock phosphate and even stronger with rock phosphate and AM fungi. A weak but significant difference in the response of cultivars to AM fungus treatment in terms of shoot dry weight (SDW) was revealed. Neighbor hyphal colonization was positively related to a plant's hyphal colonization, providing insights into the way a network of AM fungi interact with multiple hosts. Hyphal colonization ranged from 21 to 89%, and 42% of the variation was explained by rice genotype. Colonization was slightly lower in aus cultivars than other rice subgroups and high in cultivars from the Philippines. Genome wide association (GWA) mapping for hyphal colonization revealed 23 putative quantitative trait loci (QTLs) indicating there is an opportunity to investigate the impact of allelic variation in rice on AM fungal colonization. Using published transcriptomics data for AM response in rice, some promising candidate genes are revealed under these QTLs being a calcium/calmodulin serine/threonine protein kinase at 4.9 Mbp on chromosome 1, two ammonium transporters genes at 24.6 Mbp on chromosome 2 and a cluster of subtilisin genes at 1.2 Mbp on chromosome 4. Future studies should concentrate on the biological significance of genetic variation in rice for AM colonization.

The Quantitative Genetic Control of Root Architecture in Maize

Roots remain an underexplored frontier in plant genetics despite their well-known influence on plant development, agricultural performance and competition in the wild. Visualizing and measuring root structures and their growth is vastly more difficult than characterizing aboveground parts of the plant and is often simply avoided. The majority of research on maize root systems has focused on their anatomy, physiology, development and soil interaction, but much less is known about the genetics that control quantitative traits. In maize, seven root development genes have been cloned using mutagenesis, but no genes underlying the many root-related quantitative trait loci (QTLs) have been identified. In this review, we discuss whether the maize mutants known to control root development may also influence quantitative aspects of root architecture, including the extent to which they overlap with the most recent maize root trait QTLs. We highlight specific challenges and anticipate the impacts that emerging technologies, especially computational approaches, may have toward the identification of genes controlling root quantitative traits.

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.

Multiple genomic regions influence root morphology and seedling growth in cultivated sunflower (Helianthus annuus L.) under well-watered and water-limited conditions

With climate change and an ever-increasing human population threatening food security, developing a better understanding of the genetic basis of crop performance under stressful conditions has become increasingly important. Here, we used genome-wide association studies to genetically dissect variation in seedling growth traits in cultivated sunflower (Helianthus annuus L.) under well-watered and water-limited (i.e., osmotic stress) conditions, with a particular focus on root morphology. Water limitation reduced seedling size and produced a shift toward deeper rooting. These effects varied across genotypes, and we identified 13 genomic regions that were associated with traits of interest across the two environments. These regions varied in size from a single marker to 186.2 Mbp and harbored numerous genes, some of which are known to be involved in the plant growth/development as well as the response to osmotic stress. In many cases, these associations corresponded to growth traits where the common allele outperformed the rare variant, suggesting that selection for increased vigor during the evolution of cultivated sunflower might be responsible for the relatively high frequency of these alleles. We also found evidence of pleiotropy across multiple traits, as well as numerous environmentally independent genetic effects. Overall, our results indicate the existence of genetic variation in root morphology and allocation and further suggest that the majority of alleles associated with these traits have consistent effects across environments.

Loci and natural alleles underlying robust roots and adaptive domestication of upland ecotype rice in aerobic conditions

A robust (long and thick) root system is characteristic of upland japonica rice adapted to drought conditions. Using deep sequencing and large scale phenotyping data of 795 rice accessions and an integrated strategy combining results from high resolution mapping by GWAS and linkage mapping, comprehensive analyses of genomic, transcriptomic and haplotype data, we identified large numbers of QTLs affecting rice root length and thickness (RL and RT) and shortlisted relatively few candidate genes for many of the identified small-effect QTLs. Forty four and 97 QTL candidate genes for RL and RT were identified, and five of the RL QTL candidates were validated by T-DNA insertional mutation; all have diverse functions and are involved in root development. This work demonstrated a powerful strategy for highly efficient cloning of moderate- and small-effect QTLs that is difficult using the classical map-based cloning approach. Population analyses of the 795 accessions, 202 additional upland landraces, and 446 wild rice accessions based on random SNPs and SNPs within robust loci suggested that there could be much less diversity in robust-root candidate genes among upland japonica accessions than in other ecotypes. Further analysis of nucleotide diversity and allele frequency in the robust loci among different ecotypes and wild rice accessions showed that almost all alleles could be detected in wild rice, and pyramiding of robust-root alleles could be an important genetic characteristic of upland japonica. Given that geographical distribution of upland landraces, we suggest that during domestication of upland japonica, the strongest pyramiding of robust-root alleles makes it a unique ecotype adapted to aerobic conditions.

Asian cultivated rice is well-known for its rich-within-species diversity with two major subspecies, indica and japonica and subpopulation differentiation. A robust (long and thick) root system that is characteristic of upland japonica rice represents a predominant ecotype grown under aerobic and rain-fed conditions. In this study, we identified candidate genes for root length and root thickness, and validated five root length candidates by T-DNA insertional mutations. Further analyses of an Asian cultivated and wild rice population were performed based on random SNPs and SNPs within robust loci. The findings hold promise for application in improving drought resistance and also reveal the adaptive domestication history of upland rice as a unique Asian cultivated rice ecotype.

Molecular Genetics and Breeding for Nutrient Use Efficiency in Rice

In the coming decades, rice production needs to be carried out sustainably to keep the balance between profitability margins and essential resource input costs. Many fertilizers, such as N, depend primarily on fossil fuels, whereas P comes from rock phosphates. How long these reserves will last and sustain agriculture remains to be seen. Therefore, current agricultural food production under such conditions remains an enormous and colossal challenge. Researchers have been trying to identify nutrient use-efficient varieties over the past few decades with limited success. The concept of nutrient use efficiency is being revisited to understand the molecular genetic basis, while much of it is not entirely understood yet. However, significant achievements have recently been observed at the molecular level in nitrogen and phosphorus use efficiency. Breeding teams are trying to incorporate these valuable QTLs and genes into their rice breeding programs. In this review, we seek to identify the achievements and the progress made so far in the fields of genetics, molecular breeding and biotechnology, especially for nutrient use efficiency in rice.

Genetic diversity of root system architecture in response to drought stress in grain legumes

Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.

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.

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

Genetic diversity and genomic strategies for improving drought and waterlogging tolerance in soybeans

Drought and its interaction with high temperature are the major abiotic stress factors affecting soybean yield and production stability. Ongoing climate changes are anticipated to intensify drought events, which will further impact crop production and food security. However, excessive water also limits soybean production. The success of soybean breeding programmes for crop improvement is dependent on the extent of genetic variation present in the germplasm base. Screening for natural genetic variation in drought- and flooding tolerance-related traits, including root system architecture, water and nitrogen-fixation efficiency, and yield performance indices, has helped to identify the best resources for genetic studies in soybean. Genomic resources, including whole-genome sequences of diverse germplasms, millions of single-nucleotide polymorphisms, and high-throughput marker genotyping platforms, have expedited gene and marker discovery for translational genomics in soybean. This review highlights the current knowledge of the genetic diversity and quantitative trait loci associated with root system architecture, canopy wilting, nitrogen-fixation ability, and flooding tolerance that contributes to the understanding of drought- and flooding-tolerance mechanisms in soybean. Next-generation mapping approaches and high-throughput phenotyping will facilitate a better understanding of phenotype-genotype associations and help to formulate genomic-assisted breeding strategies, including genomic selection, in soybean for tolerance to drought and flooding stress.

Drought-tolerant QTL qVDT11 leads to stable tiller formation under drought stress conditions in rice

Drought is an important limiting factor for rice production, but the genetic mechanisms of drought tolerance is poorly understood. Here, we screened 218 rice varieties to identify 32 drought-tolerant varieties. The variety Samgang exhibited strong drought tolerance and stable yield in rain-fed conditions and was selected for further study. To identify QTLs for drought tolerance, we examined visual drought tolerance (VDT) and relative water content (RWC) phenotypes in a doubled haploid (DH) population of 101 individuals derived from a cross between Samgang and Nagdong (a drought-sensitive variety). Three QTLs from Samgang were identified for VDT and explained 41.8% of the phenotypic variance. In particular, qVDT11 contributed 20.3% of the phenotypic variance for RWC. To determine QTL effects on drought tolerance in rain-fed paddy conditions, seven DH lines were selected according to the number of QTLs they contained. Of the drought-tolerance-associated QTLs, qVDT2 and qVDT6 did not affect tiller formation, but qVDT11 increased tiller number. Tiller formation was most stable when qVDT2 and qVDT11 were combined. DH lines with both of these drought-tolerance-associated QTLs exhibited the most stable tiller formation. Together, these results suggest that qVDT11 is important for drought tolerance and stable tiller formation in rain-fed paddy fields.

Identification of manganese efficiency candidate genes in winter barley (Hordeum vulgare) using genome wide association mapping

BACKGROUND

Manganese (Mn) has several essential functions in plants, including a role as cofactor in the oxygen evolving complex (OEC) of photosystem II (PSII). Manganese deficiency is a major plant nutritional disorder in winter cereals resulting in significant yield reductions and winter kill in more severe cases. Among the winter cereals, genotypes of winter barley are known to differ considerably in tolerance to Mn deficiency, but the genes controlling the Mn deficiency trait remains elusive.

RESULTS

Experiments were conducted using 248 barley varieties, cultivated in six distinct environments prone to induce Mn deficiency. High-throughput phenotyping for Mn deficiency was performed by chlorophyll a (Chl a) fluorescence analysis to quantify the quantum yield efficiency of PSII. High-throughput phenotyping in combination with ICP-OES based multi-element analyses allowed detection of marker-trait associations by genome wide association (GWA) mapping. Several key candidate genes were identified, including PSII subunit proteins, germin like proteins and Mn superoxide dismutase. The putative roles of the encoded proteins in Mn dependent metabolic processes are discussed.

CONCLUSIONS

Fifty-four candidate genes were identified by Chl a fluorescence phenotyping and association genetics. Tolerance of plants to Mn deficiency, which is referred to as Mn efficiency, appeared to be a complex trait involving many genes. Moreover, the trait appeared to be highly dependent on the environmental conditions in field. This study provides the basis for an improved understanding of the parameters influencing Mn efficiency and is valuable in future plant breeding aiming at producing new varieties with improved tolerance to cultivation in soil prone to induce Mn deficiency.

Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.)

Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.

QTLs underlying natural variation of root growth angle among rice cultivars with the same functional allele of DEEPER ROOTING 1

BACKGROUND

The functional allele of the rice gene DEEPER ROOTING 1 (DRO1) increases the root growth angle (RGA). However, wide natural variation in RGA is observed among rice cultivars with the functional DRO1 allele. To elucidate genetic factors related to such variation, we quantitatively measured RGA using the basket method and analyzed quantitative trait loci (QTLs) for RGA in three F2 mapping populations derived from crosses between the large RGA-type cultivar Kinandang Patong and each of three accessions with varying RGA: Momiroman has small RGA and was used to produce the MoK-F2 population; Yumeaoba has intermediate RGA (YuK-F2 population); Tachisugata has large RGA (TaK-F2 population). All four accessions belong to the same haplotype group of functional DRO1 allele.

RESULTS

We detected the following statistically significant QTLs: one QTL on chromosome 4 in MoK-F2, three QTLs on chromosomes 2, 4, and 6 in YuK-F2, and one QTL on chromosome 2 in TaK-F2. Among them, the two QTLs on chromosome 4 were located near DRO2, which has been previously reported as a major QTL for RGA, whereas the two major QTLs for RGA on chromosomes 2 (DRO4) and 6 (DRO5) were novel. With the LOD threshold reduced to 3.0, several minor QTLs for RGA were also detected in each population.

CONCLUSION

Natural variation in RGA in rice cultivars carrying functional DRO1 alleles may be controlled by a few major QTLs and by several additional minor QTLs.

Genes controlling root development in rice

In this review, we report on the recent developments made using both genetics and functional genomics approaches in the discovery of genes controlling root development in rice. QTL detection in classical biparental mapping populations initially enabled the identification of a very large number of large chromosomal segments carrying root genes. Two segments with large effects have been positionally cloned, allowing the identification of two major genes. One of these genes conferred a tolerance to low phosphate content in soil, while the other conferred a tolerance to drought by controlling root gravitropism, resulting in root system expansion deep in the soil. Findings based on the higher-resolution QTL detection offered by the development of association mapping are discussed. In parallel with genetics approaches, efforts have been made to screen mutant libraries for lines presenting alterations in root development, allowing for the identification of several genes that control different steps of root development, such as crown root and lateral root initiation and emergence, meristem patterning, and the control of root growth. Some of these genes are closely phylogenetically related to Arabidopsis genes involved in the control of lateral root initiation. This close relationship stresses the conservation among plant species of an auxin responsive core gene regulatory network involved in the control of post-embryonic root initiation. In addition, we report on several genetic regulatory pathways that have been described only in rice. The complementarities and the expected convergence of the direct and reverse genetic approaches used to decipher the genetic determinants of root development in rice are discussed in regards to the high diversity characterizing this species and to the adaptations of rice root system architecture to different edaphic environments.

Comparing simple root phenotyping methods on a core set of rice genotypes

Interest in belowground plant growth is increasing, especially in relation to arguments that shallow-rooted cultivars are efficient at exploiting soil phosphorus while deep-rooted ones will access water at depth. However, methods for assessing roots in large numbers of plants are diverse and direct comparisons of methods are rare. Three methods for measuring root growth traits were evaluated for utility in discriminating rice cultivars: soil-filled rhizotrons, hydroponics and soil-filled pots whose bottom was sealed with a non-woven fabric (a potential method for assessing root penetration ability). A set of 38 rice genotypes including the OryzaSNP set of 20 cultivars, additional parents of mapping populations and products of marker-assisted selection for root QTLs were assessed. A novel method of image analysis for assessing rooting angles from rhizotron photographs was employed. The non-woven fabric was the easiest yet least discriminatory method, while the rhizotron was highly discriminatory and allowed the most traits to be measured but required more than three times the labour of the other methods. The hydroponics was both easy and discriminatory, allowed temporal measurements, but is most likely to suffer from artefacts. Image analysis of rhizotrons compared favourably to manual methods for discriminating between cultivars. Previous observations that cultivars from the indica subpopulation have shallower rooting angles than aus or japonica cultivars were confirmed in the rhizotrons, and indica and temperate japonicas had lower maximum root lengths in rhizotrons and hydroponics. It is concluded that rhizotrons are the preferred method for root screening, particularly since root angles can be assessed.

Genotype-environment interactions affecting preflowering physiological and morphological traits of Brassica rapa grown in two watering regimes

Plant growth and productivity are greatly affected by drought, which is likely to become more threatening with the predicted global temperature increase. Understanding the genetic architecture of complex quantitative traits and their interaction with water availability may lead to improved crop adaptation to a wide range of environments. Here, the genetic basis of 20 physiological and morphological traits is explored by describing plant performance and growth in a Brassica rapa recombinant inbred line (RIL) population grown on a sandy substrate supplemented with nutrient solution, under control and drought conditions. Altogether, 54 quantitative trait loci (QTL) were identified, of which many colocated in 11 QTL clusters. Seventeen QTL showed significant QTL-environment interaction (Q×E), indicating genetic variation for phenotypic plasticity. Of the measured traits, only hypocotyl length did not show significant genotype-environment interaction (G×E) in both environments in all experiments. Correlation analysis showed that, in the control environment, stomatal conductance was positively correlated with total leaf dry weight (DW) and aboveground DW, whereas in the drought environment, stomatal conductance showed a significant negative correlation with total leaf DW and aboveground DW. This correlation was explained by antagonistic fitness effects in the drought environment, controlled by a QTL cluster on chromosome A7. These results demonstrate that Q×E is an important component of the genetic variance and can play a great role in improving drought tolerance in future breeding programmes.

Genetic engineering and breeding of drought-resistant crops

Drought is one of the most important environmental stresses affecting the productivity of most field crops. Elucidation of the complex mechanisms underlying drought resistance in crops will accelerate the development of new varieties with enhanced drought resistance. Here, we provide a brief review on the progress in genetic, genomic, and molecular studies of drought resistance in major crops. Drought resistance is regulated by numerous small-effect loci and hundreds of genes that control various morphological and physiological responses to drought. This review focuses on recent studies of genes that have been well characterized as affecting drought resistance and genes that have been successfully engineered in staple crops. We propose that one significant challenge will be to unravel the complex mechanisms of drought resistance in crops through more intensive and integrative studies in order to find key functional components or machineries that can be used as tools for engineering and breeding drought-resistant crops.

Root traits contributing to plant productivity under drought

Geneticists and breeders are positioned to breed plants with root traits that improve productivity under drought. However, a better understanding of root functional traits and how traits are related to whole plant strategies to increase crop productivity under different drought conditions is needed. Root traits associated with maintaining plant productivity under drought include small fine root diameters, long specific root length, and considerable root length density, especially at depths in soil with available water. In environments with late season water deficits, small xylem diameters in targeted seminal roots save soil water deep in the soil profile for use during crop maturation and result in improved yields. Capacity for deep root growth and large xylem diameters in deep roots may also improve root acquisition of water when ample water at depth is available. Xylem pit anatomy that makes xylem less "leaky" and prone to cavitation warrants further exploration holding promise that such traits may improve plant productivity in water-limited environments without negatively impacting yield under adequate water conditions. Rapid resumption of root growth following soil rewetting may improve plant productivity under episodic drought. Genetic control of many of these traits through breeding appears feasible. Several recent reviews have covered methods for screening root traits but an appreciation for the complexity of root systems (e.g., functional differences between fine and coarse roots) needs to be paired with these methods to successfully identify relevant traits for crop improvement. Screening of root traits at early stages in plant development can proxy traits at mature stages but verification is needed on a case by case basis that traits are linked to increased crop productivity under drought. Examples in lesquerella (Physaria) and rice (Oryza) show approaches to phenotyping of root traits and current understanding of root trait genetics for breeding.

Root traits contributing to plant productivity under drought

Geneticists and breeders are positioned to breed plants with root traits that improve productivity under drought. However, a better understanding of root functional traits and how traits are related to whole plant strategies to increase crop productivity under different drought conditions is needed. Root traits associated with maintaining plant productivity under drought include small fine root diameters, long specific root length, and considerable root length density, especially at depths in soil with available water. In environments with late season water deficits, small xylem diameters in targeted seminal roots save soil water deep in the soil profile for use during crop maturation and result in improved yields. Capacity for deep root growth and large xylem diameters in deep roots may also improve root acquisition of water when ample water at depth is available. Xylem pit anatomy that makes xylem less "leaky" and prone to cavitation warrants further exploration holding promise that such traits may improve plant productivity in water-limited environments without negatively impacting yield under adequate water conditions. Rapid resumption of root growth following soil rewetting may improve plant productivity under episodic drought. Genetic control of many of these traits through breeding appears feasible. Several recent reviews have covered methods for screening root traits but an appreciation for the complexity of root systems (e.g., functional differences between fine and coarse roots) needs to be paired with these methods to successfully identify relevant traits for crop improvement. Screening of root traits at early stages in plant development can proxy traits at mature stages but verification is needed on a case by case basis that traits are linked to increased crop productivity under drought. Examples in lesquerella (Physaria) and rice (Oryza) show approaches to phenotyping of root traits and current understanding of root trait genetics for breeding.

Genetic variation, linkage mapping of QTL and correlation studies for yield, root, and agronomic traits for aerobic adaptation

Background

Water scarcity and drought have seriously threatened traditional rice cultivation practices in several parts of the world, including India. Aerobic rice that uses significantly less water than traditional flooded systems has emerged as a promising water-saving technology. The identification of QTL conferring improved aerobic adaptation may facilitate the development of high-yielding aerobic rice varieties. In this study, experiments were conducted for mapping QTL for yield, root-related traits, and agronomic traits under aerobic conditions using HKR47 × MAS26 and MASARB25 × Pusa Basmati 1460 F_2:3 mapping populations.

Results

A total of 35 QTL associated with 14 traits were mapped on chromosomes 1, 2, 5, 6, 8, 9, and 11 in MASARB25 x Pusa Basmati 1460 and 14 QTL associated with 9 traits were mapped on chromosomes 1, 2, 8, 9, 10, 11, and 12 in HKR47 × MAS26. Two QTL (qGY_8.1 with an R² value of 34.0% and qGY_2.1 with an R² value of 22.8%) and one QTL (qGY_2.2 with an R² value of 43.2%) were identified for grain yield under aerobic conditions in the mapping populations MASARB25 × Pusa Basmati 1460 and HKR47 × MAS26, respectively.

A number of breeding lines with higher yield per plant, root length, dry biomass, length-breadth ratio, and with Pusa Basmati 1460-specific alleles in a homozygous or heterozygous condition at the BAD2 locus were identified that will serve as novel material for the selection of stable aerobic Basmati rice breeding lines.

Conclusions

Our results identified positive correlation between some of the root traits and yield under aerobic conditions, indicating the role of root traits for improving yield under aerobic situations possibly through improved water and nutrient uptake. Co-localization of QTL for yield, root traits, and yield-related agronomic traits indicates that the identified QTL may be immediately exploited in marker-assisted-breeding to develop novel high-yielding aerobic rice varieties.

Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper

A mixed model framework was defined for QTL analysis of multiple traits across multiple environments for a RIL population in pepper. Detection power for QTLs increased considerably and detailed study of QTL by environment interactions and pleiotropy was facilitated. For many agronomic crops, yield is measured simultaneously with other traits across multiple environments. The study of yield can benefit from joint analysis with other traits and relations between yield and other traits can be exploited to develop indirect selection strategies. We compare the performance of three multi-response QTL approaches based on mixed models: a multi-trait approach (MT), a multi-environment approach (ME), and a multi-trait multi-environment approach (MTME). The data come from a multi-environment experiment in pepper, for which 15 traits were measured in four environments. The approaches were compared in terms of number of QTLs detected for each trait, the explained variance, and the accuracy of prediction for the final QTL model. For the four environments together, the superior MTME approach delivered a total of 47 regions containing putative QTLs. Many of these QTLs were pleiotropic and showed quantitative QTL by environment interaction. MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. The large number of model parameters in the MTME approach was challenging and we propose several guidelines to help obtain a stable final QTL model. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.

3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture

Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala × Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r(2) = 24-37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops.

QTLs associated with root traits increase yield in upland rice when transferred through marker-assisted selection

Altering root morphology of rice (Oryza sativa L.) cultivars could improve yields in drought-prone upland ecosystems. Marker-assisted backcross breeding was used to introgress four QTLs for root traits into an upland rice cultivar. The QTLs had previously been identified under experimental conditions in a different genetic background. The introgressed lines and the recurrent parent were grown for 6 years by resource-poor farmers in upland sites in Eastern India and yields recorded. In combination the QTLs significantly increased yield by 1 t ha(-1) under relatively favourable field conditions. In less favourable trials, the QTL effects were not detected due to greater heterogeneity in soil-water availability in very low yielding environments and consequent yield variability. Root studies under controlled conditions showed that lines with the introgressions had longer roots throughout tillering than the recurrent parent (14 cm longer 2 weeks after sowing). Therefore, both improved roots and increased yield can be attributed to the introgression of QTLs. This is the first demonstration that marker-assisted backcross breeding (MABC) to introgress multiple root QTLs identified under controlled conditions is an effective strategy to improve farmers' yields of upland rice. The strategy was used to breed a novel upland rice cultivar that has been released in India as Birsa Vikas Dhan 111.

Approaches towards nitrogen- and phosphorus-efficient rice

BACKGROUND AND AIMS

Food production has to increase to meet the demand of a growing population. In light of the high energy costs and increasingly scarce resources, future agricultural systems have to be more productive and more efficient in terms of inputs such as fertilizer and water. The development of rice varieties with high yield under low-nutrient conditions has therefore become a breeding priority. The rapid progress made in sequencing and molecular-marker technology is now beginning to change the way breeding is done, providing new opportunities.

SCOPE

Nitrogen (N) and phosphorus (P) are applied to agricultural systems in large quantities and a deficiency of either nutrient leads to yield losses and triggers complex molecular and physiological responses. The underlying genes are now being identified and studied in detail, and an increasing number of quantitative trait loci (QTLs) related to N and P uptake and utilization are being reported. Here, we provide an overview of the different aspects related to N and P in rice production systems, and apply a breeder's perspective on the potential of relevant genes and pathways for breeding applications.

MAIN POINTS

For the development of nutrient-efficient rice, a holistic approach should be followed combining optimized fertilizer management with enhanced nutrient uptake via a vigorous root system, leading to increased grain filling and yield. Despite an increasing number of N- and P-related genes and QTLs being reported, very few are actively used in molecular breeding programmes. The complex regulation of N- and P-related pathways challenges breeders and the research community to identify large-effect genes/QTLs. For this it will be important to focus more on the analysis of tolerant genotypes rather than model plants, since tolerance pathways may employ a different set of genes.

Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities

Fine-mapping studies on four QTLs, qDTY(2.1), qDTY(2.2), qDTY(9.1) and qDTY(12.1), for grain yield (GY) under drought were conducted using four different backcross-derived populations screened in 16 experiments from 2006 to 2010. Composite and bayesian interval mapping analyses resolved the originally identified qDTY(2.1) region of 42.3 cM into a segment of 1.6 cM, the qDTY(2.2) region of 31.0 cM into a segment of 6.7 cM, the qDTY(9.1) region of 32.1 cM into two segments of 9.4 and 2.4 cM and the qDTY(12.1) region of 10.6 cM into two segments of 3.1 and 0.4 cM. Two of the four QTLs (qDTY(9.1) and qDTY(12.1)) having effects under varying degrees of stress severity showed the presence of more than one region within the original QTL. The study found the presence of a donor allele at RM262 within qDTY(2.1) and RM24334 within qDTY(9.1) showing a negative effect on GY under drought, indicating the necessity of precise fine mapping of QTL regions before using them in marker-assisted selection (MAS). However, the presence of sub-QTLs together in close vicinity to each other provides a unique opportunity to breeders to introgress such regions together as a unit into high-yielding drought-susceptible varieties through MAS.

Efficacy of microarray profiling data combined with QTL mapping for the identification of a QTL gene controlling the initial growth rate in rice

Seedling vigor, which is controlled by many quantitative trait loci (QTLs), is one of several important agronomic traits for direct-seedling rice systems. However, isolating these QTL genes is laborious and expensive. Here, we combined QTL mapping and microarray profiling to identify QTL genes for seedling vigor. By performing QTL mapping using 82 backcross inbred lines (BILs) of the Koshihikari (japonica) and Habataki (indica) cultivars for the rice initial growth, we identified two QTLs, early-stage plant development1/2 (qEPD1 and qEPD2), whose Koshihikari alleles promote plant height and/or leaf sheath length. Phenotypic analysis of the two substituted lines carrying the Habataki qEPD1 or qEPD2 allele revealed that qEPD2 functioned more dominantly for the initial growth of rice. From the microarray experiment, 55 and 45 candidate genes were found in the qEPD1 and qEPD2 genomic regions, which are expressed differentially between each substitution line (SL) and Koshihikari. Gibberellin 20 oxidase-2 (OsGA20ox2), which is identical to Semi Dwarf1 (SD1), was included among the 55 candidate genes of qEPD1, whereas its paralog, OsGA20ox1, was included among the 45 candidate genes of qEPD2. Consistently, introduction of the Koshihikari OsGA20ox1 allele into SL(qEPD2) increaseed its plant height and leaf sheath length significantly relative to the introduction of the Habataki OsGA20ox1 allele. Therefore, microarray profiling could be useful for rapidly screening QTL candidate genes. We concluded that OsGA20ox1 and OsGA20ox2 (SD1) function during the initial growth of rice, but OsGA20ox1 plays a dominant role in increasing plant height and leaf sheath length at the initial growth stage.

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.

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'.

Genetic control of root development in rice, the model cereal

Cereals possess a fibrous root system that is mainly composed of crown roots that emerge postembryonically from the nodes of the stem. Because the root system is not directly accessible and consequently difficult to study, it remains a target for breeders to improve the ability of plants to exploit the mineral and water resources of the soil. Breeding for root architecture necessitates identifying the genetic determinants of root development. This research is now underway in cereals, particularly in rice, the monocot model species. In this review, we examine recent data identifying genes that govern root development in cereals, such as ARL1/CRL1 in rice and RTCS in maize which encodes a conserved lateral organ boundary domain transcription factor involved in crown root initiation and development in response to auxin. Finally, we discuss the detection and validation of root development quantitative trait loci.

Imaging and analysis platform for automatic phenotyping and trait ranking of plant root systems

The ability to nondestructively image and automatically phenotype complex root systems, like those of rice (Oryza sativa), is fundamental to identifying genes underlying root system architecture (RSA). Although root systems are central to plant fitness, identifying genes responsible for RSA remains an underexplored opportunity for crop improvement. Here we describe a nondestructive imaging and analysis system for automated phenotyping and trait ranking of RSA. Using this system, we image rice roots from 12 genotypes. We automatically estimate RSA traits previously identified as important to plant function. In addition, we expand the suite of features examined for RSA to include traits that more comprehensively describe monocot RSA but that are difficult to measure with traditional methods. Using 16 automatically acquired phenotypic traits for 2,297 images from 118 individuals, we observe (1) wide variation in phenotypes among the genotypes surveyed; and (2) greater intergenotype variance of RSA features than variance within a genotype. RSA trait values are integrated into a computational pipeline that utilizes supervised learning methods to determine which traits best separate two genotypes, and then ranks the traits according to their contribution to each pairwise comparison. This trait-ranking step identifies candidate traits for subsequent quantitative trait loci analysis and demonstrates that depth and average radius are key contributors to differences in rice RSA within our set of genotypes. Our results suggest a strong genetic component underlying rice RSA. This work enables the automatic phenotyping of RSA of individuals within mapping populations, providing an integrative framework for quantitative trait loci analysis of RSA.

Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis

Background

Meta-analysis of QTLs combines the results of several QTL detection studies and provides narrow confidence intervals for meta-QTLs, permitting easier positional candidate gene identification. It is usually applied to multiple mapping populations, but can be applied to one. Here, a meta-analysis of drought related QTLs in the Bala × Azucena mapping population compiles data from 13 experiments and 25 independent screens providing 1,650 individual QTLs separated into 5 trait categories; drought avoidance, plant height, plant biomass, leaf morphology and root traits. A heat map of the overlapping 1 LOD confidence intervals provides an overview of the distribution of QTLs. The programme BioMercator is then used to conduct a formal meta-analysis at example QTL clusters to illustrate the value of meta-analysis of QTLs in this population.

Results

The heat map graphically illustrates the genetic complexity of drought related traits in rice. QTLs can be linked to their physical position on the rice genome using Additional file 1 provided. Formal meta-analysis on chromosome 1, where clusters of QTLs for all trait categories appear close, established that the sd1 semi-dwarfing gene coincided with a plant height meta-QTL, that the drought avoidance meta-QTL was not likely to be associated with this gene, and that this meta-QTL was not pleiotropic with close meta-QTLs for leaf morphology and root traits. On chromosome 5, evidence suggests that a drought avoidance meta-QTL was pleiotropic with leaf morphology and plant biomass meta-QTLs, but not with meta-QTLs for root traits and plant height 10 cM lower down. A region of dense root QTL activity graphically visible on chromosome 9 was dissected into three meta-QTLs within a space of 35 cM. The confidence intervals for meta-QTLs obtained ranged from 5.1 to 14.5 cM with an average of 9.4 cM, which is approximately 180 genes in rice.

Conclusion

The meta-analysis is valuable in providing improved ability to dissect the complex genetic structure of traits, and distinguish between pleiotropy and close linkage. It also provides relatively small target regions for the identification of positional candidate genes.

Root decisions

Root systems have recognizable developmental plans when grown in solution or agar; however, these plans often must be modified to cope with the prevailing conditions in the soil environment such as the avoidance of obstacles and the exploitation of nutrient-rich patches or water zones. The modular structure of roots enables them to respond to their environment, and roots are very adaptive at modifying growth throughout the root system to concentrate their efforts in the areas that are the most profitable. Roots also form associations with microorganisms as a strategy to enhance resource capture. However, while the responses of roots in nutrient patches are well-recognized, overall 'rules of response' and variation in strategy among plant species that can be applied in a number of different environments are still lacking. Finally, there is increasing evidence that root-root interactions are much more sophisticated than previously thought, and the evidence for roots to identify self from non-self roots will be briefly discussed.

Quantitative genetic analysis of biomass and wood chemistry of Populus under different nitrogen levels

The genetic control of carbon allocation and partitioning in woody perennial plants is poorly understood despite its importance for carbon sequestration, biofuels and other wood-based industries. It is also unclear how environmental cues, such as nitrogen availability, impact the genes that regulate growth, biomass allocation and wood composition in trees. We phenotyped 396 clonally replicated genotypes of an interspecific pseudo-backcross pedigree of Populus for wood composition and biomass traits in above- and below-ground organs. The loci that regulate growth, carbon allocation and partitioning under two nitrogen conditions were identified, defining the contribution of environmental cues to their genetic control. Sixty-three quantitative trait loci were identified for the 20 traits analyzed. The majority of quantitative trait loci are specific to one of the two nitrogen treatments, demonstrating significant nitrogen-dependent genetic control. A highly significant genetic correlation was observed between plant growth and lignin/cellulose composition, and quantitative trait loci co-localization identified the genomic position of potential pleiotropic regulators. Pleiotropic loci linking higher growth rates to wood with less lignin are excellent targets to engineer tree germplasm improved for pulp, paper and cellulosic ethanol production. The causative genes are being identified with a genetical genomics approach.

Comparison of QTLs for rice seedling morphology under different water supply conditions

The variation of seedling characteristics under different water supply conditions is strongly associated with drought resistance in rice (Oryza sativa L.) and a better elucidation of its genetics is helpful for improving rice drought resistance. Ninetysix doubled-haploid (DH) rice lines of an indica and japonica cross were grown in both flooding and upland conditions and QTLs for morphological traits at seedling stage were examined using 208 restriction fragment length polymorphism (RFLP) and 76 microsatellite (SSR) markers. A total of 32 putative QTLs were associated with the four seedling traits: average of three adventitious root lengths (ARL), shoot height (SH), shoot biomass (SW), and root to shoot dry weight ratio (RSR). Five QTLs detected were the same under control and upland conditions. The ratio between the mean value of the seedling trait under upland and flooding conditions was used for assessing drought tolerance. A total of six QTLs for drought tolerance were detected. Comparative analysis was performed for the QTLs detected in this case and those reported from two other populations with the same upland rice variety Azucena as parent. Several identical QTLs for seedling elongation across the three populations with the positive alleles from the upland rice Azucena were detected, which suggests that the alleles of Azucena might be involved in water stress-accelerated elongation of rice under different genetic backgrounds. Five cell wall-related candidate genes for OsEXP1, OsEXP2, OsEXP4, EXT, and EGase were mapped on the intervals carrying the QTLs for seedling traits.

Towards the understanding of complex traits in rice: substantially or superficially?

Completion of the genome analysis followed by extensive comprehensive studies on a variety of genes and gene families of rice (Oryza sativa) resulted in rapid accumulation of information concerning the presence of many complex traits that are governed by a number of genes of distinct functions in this most important crop cultivated worldwide. The genetic and molecular biological dissection of many important rice phenotypes has contributed to our understanding of the complex nature of the genetic control with respect to these phenotypes. However, in spite of the considerable advances made in the field, details of genetic control remain largely unsolved, thereby hampering our exploitation of this useful information in the breeding of new rice cultivars. To further strengthen the field application of the genome science data of rice obtained so far, we need to develop more powerful genomics-assisted methods for rice breeding based on information derived from various quantitative trait loci (QTL) and related analyses. In this review, we describe recent progresses and outcomes in rice QTL analyses, problems associated with the application of the technology to rice breeding and their implications for the genetic study of other crops along with future perspectives of the relevant fields.

Genome-wide analyses of rice root development QTLs and development of an online resource, Rootbrowse

Genetic control of root development in rice is complex and the underlying mechanisms (constitutive and adaptive) are poorly understood. Lowland and upland varieties of indica and japonica rice with contrasting root development characteristics have been crossed, mapping populations developed and a number of QTLs in different chromosomes were identified. As these studies have used different sets of markers and many of the QTLs identified are long, it is difficult to exploit the varietal difference for improved root traits by marker assisted selection and for identification of concerned alleles. Intensive data mining of literature resulted in the identification 861 root development QTLs and associated microsatellite markers located on different chromosomes. The QTL and marker data generated and the genome sequence of rice were used for construction of a relational database, Rootbrowse, using MySQL relational database management system and Bio::DB::GFF schema. The data is viewed using GBrowse visualization tool. It graphically displays a section of the genome and all features annotated on it including the QTLs. The QTLs can be displayed along with SSR markers, protein coding genes and/or known root development genes for prediction of probable candidate genes.

AVAILABILITY

Rootbrowse is freely available at http://www.ricebrowse.org.

Evidence from near-isogenic lines that root penetration increases with root diameter and bending stiffness in rice

Deep rooting can be inhibited by strong layers, although there is evidence for species and cultivar (cv.) differences in their penetration ability. Here, the availability of near-isogenic lines (NILs) in rice (Oryza sativa L.) was exploited to test the hypothesis that increased root diameter is associated with greater root bending stiffness, which leads to greater root penetration of strong layers. Wax/petrolatum discs (80% strong wax) were used as the strong layer, so that strength can be manipulated independently of water status. It was found that good root penetration was consistently associated with greater root diameter and bending stiffness, whether comparisons were made between cvs or between NILs. With NILs, this effect was seen with 'research' lines bred from recombinant inbred lines of a cross between cvs Bala and Azucena and also in improved lines developed from cv. Kalinga III by introgression of parts of the genome from Azucena. Much of the bending behaviour of roots could be explained by treating them as a simple cylinder of material. In both wax disc and sand culture systems, roots that had encountered a strong layer had lower bending stiffness than roots that had not encountered a strong layer which is a novel result and not previously reported.