Quantitative trait loci from identification to exploitation for crop improvement

Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara

Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.

Variety-dependent accumulation of glucomannan in the starchy endosperm and aleurone cell walls of rice grains and its possible genetic basis

Plant cell wall plays important roles in the regulation of plant growth/development and affects the quality of plant-derived food and industrial materials. On the other hand, genetic variability of cell wall structure within a plant species has not been well understood. Here we show that the endosperm cell walls, including both starchy endosperm and aleurone layer, of rice grains with various genetic backgrounds are clearly classified into two groups depending on the presence/absence of β-1,4-linked glucomannan. All-or-none distribution of the glucomannan accumulation among rice varieties is very different from the varietal differences of arabinoxylan content in wheat and barley, which showed continuous distributions. Immunoelectron microscopic observation suggested that the glucomannan was synthesized in the early stage of endosperm development, but the synthesis was down-regulated during the secondary thickening process associated with the differentiation of aleurone layer. Significant amount of glucomannan in the cell walls of the glucomannan-positive varieties, i.e., 10% or more of the starchy endosperm cell walls, and its close association with the cellulose microfibril suggested possible effects on the physicochemical/biochemical properties of these cell walls. Comparative genomic analysis indicated the presence of striking differences between OsCslA12 genes of glucomannan-positive and negative rice varieties, Kitaake and Nipponbare, which seems to explain the all-or-none glucomannan cell wall trait in the rice varieties. Identification of the gene responsible for the glucomannan accumulation could lead the way to clarify the effect of the accumulation of glucomannan on the agronomic traits of rice by using genetic approaches.

The Protective Effect of 11-Keto-β-Boswellic Acid against Diabetic Cardiomyopathy in Rats Entails Activation of AMPK

This study examined the protective effect of 11-keto-β-boswellic acid (AKBA) against streptozotocin (STZ)-induced diabetic cardiomyopathy (DC) in rats and examined the possible mechanisms of action. Male rats were divided into 5 groups (n = 8/each): (1) control, AKBA (10 mg/kg, orally), STZ (65 mg/kg, i.p.), STZ + AKBA (10 mg/kg, orally), and STZ + AKBA + compound C (CC/an AMPK inhibitor, 0.2 mg/kg, i.p.). AKBA improved the structure and the systolic and diastolic functions of the left ventricles (LVs) of STZ rats. It also attenuated the increase in plasma glucose, plasma insulin, and serum and hepatic levels of triglycerides (TGs), cholesterol (CHOL), and free fatty acids (FFAs) in these diabetic rats. AKBA stimulated the ventricular activities of phosphofructokinase (PFK), pyruvate dehydrogenase (PDH), and acetyl CoA carboxylase (ACC); increased levels of malonyl CoA; and reduced levels of carnitine palmitoyltransferase I (CPT1), indicating improvement in glucose and FA oxidation. It also reduced levels of malondialdehyde (MDA); increased mitochondria efficiency and ATP production; stimulated mRNA, total, and nuclear levels of Nrf2; increased levels of glutathione (GSH), heme oxygenase (HO-1), superoxide dismutase (SOD), and catalase (CAT); but reduced the expression and nuclear translocation of NF-κB and levels of tumor-necrosis factor-α (TNF-α) and interleukin-6 (IL-6). These effects were concomitant with increased activities of AMPK in the LVs of the control and STZ-diabetic rats. Treatment with CC abolished all these protective effects of AKBA. In conclusion, AKBA protects against DC in rats, mainly by activating the AMPK-dependent control of insulin release, cardiac metabolism, and antioxidant and anti-inflammatory effects.

Designing Novel Strategies for Improving Old Legumes: An Overview from Common Vetch

Common vetch (Vicia sativa L.) is a grain legume used in animal feeding, rich in protein content, fatty acid, and mineral composition that makes for a very adequate component to enrich feedstuff. In addition, relevant pharmacological properties have been reported in humans. The common vetch, similar to other legumes, can fix atmospheric nitrogen, a crucial feature for sustainable agricultural systems. These properties enhance the use of vetch as a cover crop and its sowing in intercropping systems. Moreover, several studies have recently pointed out the potential of vetch in the phytoremediation of contaminated soils. These characteristics make vetch a relevant crop, which different potential improvements target. Varieties with different yields, flowering times, shattering resistance, nutritional composition, rhizobacteria associations, drought tolerance, nitrogen fixation capacity, and other agronomic-relevant traits have been identified when different vetch accessions are compared. Recently, the analysis of genomic and transcriptomic data has allowed the development of different molecular markers to be used for assisted breeding purposes, promoting crop improvement. Here, we review the potential of using the variability of V. sativa genetic resources and new biotechnological and molecular tools for selecting varieties with improved traits to be used in sustainable agriculture systems.

Increasing Fruit Weight by Editing a Cis-Regulatory Element in Tomato KLUH Promoter Using CRISPR/Cas9

CRISPR/Cas-mediated genome editing is a powerful approach to accelerate yield enhancement to feed growing populations. Most applications focus on "negative regulators" by targeting coding regions and promoters to create nulls or weak loss-of-function alleles. However, many agriculturally important traits are conferred by gain-of-function alleles. Therefore, creating gain-of-function alleles for "positive regulators" by CRISPR will be of great value for crop improvement. CYP78A family members are the positive regulators of organ weight and size in crops. In this study, we engineered allelic variation by editing tomato KLUH promoter around a single-nucleotide polymorphism (SNP) that is highly associated with fruit weight. The SNP was located in a conserved putative cis-regulatory element (CRE) as detected by the homology-based prediction and the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). Twenty-one mutant alleles with various insertion and deletion sizes were generated in the LA1589 background. Five mutant alleles (m2+4bp , m3+1bp , m5-1bp , m13-8bp , and m14-9bp ) showed a consistent increase in fruit weight and a significant decrease in the proportion of small fruits in all experimental evaluations. Notably, m2+4bp and m3+1bp homozygote significantly increase fruit weight by 10.7-15.7 and 8.7-16.3%, respectively. Further analysis of fruit weight based on fruit position on the inflorescence indicated that the five beneficial alleles increase the weight of all fruits along inflorescence. We also found that allele types and transcriptional changes of SlKLUH were poor predictors of the changes in fruit weight. This study not only provides a way of identifying conserved CRE but also highlights enormous potential for CRISPR/Cas-mediated cis-engineering of CYP78A members in yield improvement.

Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel

Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich source of protein and other valuable minerals, vitamins, and antioxidants. The main objectives of this research were (1) to study the root traits related with the phenotypic and genetic diversity of 375 mung bean genotypes of the Iowa (IA) diversity panel and (2) to conduct genome-wide association studies of root-related traits using the Automated Root Image Analysis (ARIA) software. We collected over 9,000 digital images at three-time points (days 12, 15, and 18 after germination). A broad sense heritability for days 15 (0.22-0.73) and 18 (0.23-0.87) was higher than that for day 12 (0.24-0.51). We also reported root ideotype classification, i.e., PI425425 (India), PI425045 (Philippines), PI425551 (Korea), PI264686 (Philippines), and PI425085 (Sri Lanka) that emerged as the top five in the topsoil foraging category, while PI425594 (unknown origin), PI425599 (Thailand), PI425610 (Afghanistan), PI425485 (India), and AVMU0201 (Taiwan) were top five in the drought-tolerant and nutrient uptake "steep, cheap, and deep" ideotype. We identified promising genotypes that can help diversify the gene pool of mung bean breeding stocks and will be useful for further field testing. Using association studies, we identified markers showing significant associations with the lateral root angle (LRA) on chromosomes 2, 6, 7, and 11, length distribution (LED) on chromosome 8, and total root length-growth rate (TRL_GR), volume (VOL), and total dry weight (TDW) on chromosomes 3 and 5. We discussed genes that are potential candidates from these regions. We reported beta-galactosidase 3 associated with the LRA, which has previously been implicated in the adventitious root development via transcriptomic studies in mung bean. Results from this work on the phenotypic characterization, root-based ideotype categories, and significant molecular markers associated with important traits will be useful for the marker-assisted selection and mung bean improvement through breeding.

Perspectives and recent progress of genome-wide association studies (GWAS) in fruits

BACKGROUND

Earlier next-generation sequencing technologies are being vastly used to explore, administer, and investigate the gene space with accurate profiling of nucleotide variations in the germplasm. OVERVIEW AND PROGRESS: Recently, novel advancements in high-throughput sequencing technologies allow a genotyping-by-sequencing approach that has opened up new horizons for extensive genotyping exploiting single-nucleotide-polymorphisms (SNPs). This method acts as a bridge to support and minimize a genotype to phenotype gap allowing genetic selection at the genome-wide level, named genomic selection that could facilitate the selection of traits also in the pomology sector. In addition to this, genome-wide genotyping is a prerequisite for genome-wide association studies that have been used successfully to discover the genes, which control polygenic traits including the genetic loci, associated with the trait of interest in fruit crops.

AIMS AND PROSPECTS

This review article emphasizes the role of genome-wide approaches to unlock and explore the genetic potential along with the detection of SNPs affecting the phenotype of fruit crops and highlights the prospects of genome-wide association studies in fruits.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.

Will Plant Genome Editing Play a Decisive Role in "Quantum-Leap" Improvements in Crop Yield to Feed an Increasing Global Human Population?

Growing scientific evidence demonstrates unprecedented planetary-scale human impacts on the Earth's system with a predicted threat to the existence of the terrestrial biosphere due to population increase, resource depletion, and pollution. Food systems account for 21-34% of global carbon dioxide (CO2) emissions. Over the past half-century, water and land-use changes have significantly impacted ecosystems, biogeochemical cycles, biodiversity, and climate. At the same time, food production is falling behind consumption, and global grain reserves are shrinking. Some predictions suggest that crop yields must approximately double by 2050 to adequately feed an increasing global population without a large expansion of crop area. To achieve this, "quantum-leap" improvements in crop cultivar productivity are needed within very narrow planetary boundaries of permissible environmental perturbations. Strategies for such a "quantum-leap" include mutation breeding and genetic engineering of known crop genome sequences. Synthetic biology makes it possible to synthesize DNA fragments of any desired sequence, and modern bioinformatics tools may hopefully provide an efficient way to identify targets for directed modification of selected genes responsible for known important agronomic traits. CRISPR/Cas9 is a new technology for incorporating seamless directed modifications into genomes; it is being widely investigated for its potential to enhance the efficiency of crop production. We consider the optimism associated with the new genetic technologies in terms of the complexity of most agronomic traits, especially crop yield potential (Yp) limits. We also discuss the possible directions of overcoming these limits and alternative ways of providing humanity with food without transgressing planetary boundaries. In conclusion, we support the long-debated idea that new technologies are unlikely to provide a rapidly growing population with significantly increased crop yield. Instead, we suggest that delicately balanced humane measures to limit its growth and the amount of food consumed per capita are highly desirable for the foreseeable future.

Quantitative Trait Loci Controlling Agronomic and Biochemical Traits in Cannabis sativa

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp’s change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F₂ population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying co-localized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp.

Rhizobial-Host Interactions and Symbiotic Nitrogen Fixation in Legume Crops Toward Agriculture Sustainability

Symbiotic nitrogen fixation (SNF) process makes legume crops self-sufficient in nitrogen (N) in sharp contrast to cereal crops that require an external input by N-fertilizers. Since the latter process in cereal crops results in a huge quantity of greenhouse gas emission, the legume production systems are considered efficient and important for sustainable agriculture and climate preservation. Despite benefits of SNF, and the fact that chemical N-fertilizers cause N-pollution of the ecosystems, the focus on improving SNF efficiency in legumes did not become a breeder’s priority. The size and stability of heritable effects under different environment conditions weigh significantly on any trait useful in breeding strategies. Here we review the challenges and progress made toward decoding the heritable components of SNF, which is considerably more complex than other crop allelic traits since the process involves genetic elements of both the host and the symbiotic rhizobial species. SNF-efficient rhizobial species designed based on the genetics of the host and its symbiotic partner face the test of a unique microbiome for its success and productivity. The progress made thus far in commercial legume crops with relevance to the dynamics of host–rhizobia interaction, environmental impact on rhizobial performance challenges, and what collectively determines the SNF efficiency under field conditions are also reviewed here.

Root-omics for drought tolerance in cool-season grain legumes

Root traits can be exploited to increase the physiological efficiency of crop water use under drought. Root length, root hairs, root branching, root diameter, and root proliferation rate are genetically defined traits that can help to improve the water productivity potential of crops. Recently, high-throughput phenotyping techniques/platforms have been used to screen the germplasm of major cool-season grain legumes for root traits and their impact on different physiological processes, including nutrient uptake and yield potential. Advances in omics approaches have led to the dissection of genomic, proteomic, and metabolomic structures of these traits. This knowledge facilitates breeders to improve the water productivity and nutrient uptake of cultivars under limited soil moisture conditions in major cool-season grain legumes that usually face terminal drought. This review discusses the advances in root traits and their potential for developing drought-tolerant cultivars in cool-season grain legumes.

Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress

Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52-38.53%), phenotypic coefficient of variation (20.29-39.85%), heritability (92.50-93.90%), and genetic advance as a percentage of mean (38.68-76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-00977-5.

QTL Mapping for Seed Germination Response to Drought Stress in Brassica napus

Drought stress is one of the most environmental abiotic stresses affecting seed germination and crop growth. In the present study, the genetic characteristics of seed germination under drought stress in a Brassica napus double haploid population were analyzed. Five germination-related indexes, including germination percentage (GP), root length (RL), shoot length (SL), fresh weight (FW), and root-to-shoot length ratio (R/S) under control and drought stress, were calculated, and the drought stress index (DSI), including DSI-GP, DSI-RL, DSI-SL, DSI-FW, and DSI-R/S, was determined using the quantitative trait loci (QTLs) analysis based on high-density genetic linkage map. The phenotypic analysis indicated that the R/S is an effective morphological trait in the determination of drought tolerance in the seedling stage. Thirty-nine identified QTLs were observed for these traits and then integrated into 36 consensus QTLs, in which 18 QTLs were found to affect the DSI of four traits (GP, RL, SL, and R/S). Based on the co-linearity between genetic and physical maps of B. napus, 256 candidate genes were detected, and 128 genes have single-nucleotidepolymorphisms/insertion-deletion (SNP/InDel) variations between two parents, some of which were associated with the drought stress tolerance (for example, BnaC03g32780D, BnaC03g37030D, and BnaC09g27300D). The present results laid insights into drought tolerance and its genetic bases in B. napus.

How the pan-genome is changing crop genomics and improvement

Crop genomics has seen dramatic advances in recent years due to improvements in sequencing technology, assembly methods, and computational resources. These advances have led to the development of new tools to facilitate crop improvement. The study of structural variation within species and the characterization of the pan-genome has revealed extensive genome content variation among individuals within a species that is paradigm shifting to crop genomics and improvement. Here, we review advances in crop genomics and how utilization of these tools is shifting in light of pan-genomes that are becoming available for many crop species.

How the pan-genome is changing crop genomics and improvement

Crop genomics has seen dramatic advances in recent years due to improvements in sequencing technology, assembly methods, and computational resources. These advances have led to the development of new tools to facilitate crop improvement. The study of structural variation within species and the characterization of the pan-genome has revealed extensive genome content variation among individuals within a species that is paradigm shifting to crop genomics and improvement. Here, we review advances in crop genomics and how utilization of these tools is shifting in light of pan-genomes that are becoming available for many crop species.

Common Vetch, Valuable Germplasm for Resilient Agriculture: Genetic Characterization and Spanish Core Collection Development

Common vetch (Vicia sativa L.) is a legume used for animal feed because of its high protein content and great capacity for nitrogen fixation, making this crop relevant in sustainable agriculture. The Spanish vetch collection, conserved at the Spanish Plant Genetic Resources Center (CRF), is one of the largest collections of this species worldwide, including landraces, wild relatives mainly collected in Spain, and commercial cultivars, but also accessions of international origin. The analysis of the genetic diversity of this material, whose genome has not been sequenced yet, and the assembly of a representative collection could play a pivotal role in conserving and exploiting these genetic resources in breeding programs mainly in those focused on consequences and demands of climate change. In this work, a set of 14 simple sequence repeat (SSR) reference alleles for genetic diversity analysis of the CRF vetch collection has been developed, used for genotyping more than 545 common vetch accessions from all over the world and validated. All the tested markers were polymorphic for the analyzed accessions. Overall, at least 86 different loci were identified with 2-11 alleles per locus with an average of 6.1 alleles per locus. Also, the analyses of the generated SSR database support that most of these SSR markers are transferable across closely related species of Vicia genus. Analysis of molecular variance revealed that wild relatives have a higher genetic diversity than landraces. However, cultivars have similar diversity than landraces, indicating that genetic variability has been barely lost due to the breeding of this legume. Low differences of genetic variations between Spanish and non-Spanish accessions have been observed, suggesting a high degree of diversity within Spanish genotypes, which provide 95% of the total genetic variation, so we have focused our efforts on characterizing genotypes of Spanish origin that were further studied using storage protein profiles. Based on SSR, seed protein profiles, and agromorphological and passport data, a vetch core collection (VCC) containing 47 V. sativa accessions of Spanish origin has been established. In this collection, the characterization has been expanded using ISSR markers, and it has been reevaluated with new agromorphological data, including drought tolerance characters. This VCC presents a minimum loss of genetic diversity concerning the total collection and constitutes an invaluable material that can be used in future breeding programs for direct use in a resilient agricultural system.

Identification of QTLs Controlling α-Glucosidase Inhibitory Activity in Pepper (Capsicum annuum L.) Leaf and Fruit Using Genotyping-by-Sequencing Analysis

Diabetes mellitus, a group of metabolic disorders characterized by hyperglycemia, is one of the most serious and common diseases around the world and is associated with major complications such as diabetic neuropathy, retinopathy, and cardiovascular diseases. A widely used treatment for non-insulin-dependent diabetes is α-glucosidase inhibitors (AGIs) such as acarbose, which hinders hydrolytic cleavage of disaccharides and retard glucose absorption. The ability to inhibit α-glucosidase activity has been reported in leaf and fruit of pepper (Capsicum annuum L.). In this study, we aimed to identify quantitative trait loci (QTLs) controlling α-glucosidase inhibitory activity (AGI activity) in pepper leaf and fruit using enzyme assay and genotyping-by-sequencing (GBS) analysis. The AGI activity at three stages of leaf and one stage of fruit development was analyzed by 96 F2 individuals. GBS analysis identified 17,427 SNPs that were subjected to pepper genetic linkage map construction. The map, consisting of 763 SNPs, contained 12 linkage groups with a total genetic distance of 2379 cM. QTL analysis revealed seven QTLs (qAGI1.1, qAGI11.1, qAGI5.1, qAGI9.1, qAGI12.1, qAGI5.2, and qAGI12.2) controlling AGI activity in pepper leaf and fruit. The QTLs for AGI activity varied by plant age and organ. This QTL information is expected to provide a significant contribution to developing pepper varieties with high AGI activity.

GenoTypeMapper: graphical genotyping on genetic and sequence-based maps

BACKGROUND

The rising availability of assemblies of large genomes (e.g. bread and durum wheat, barley) and their annotations deliver the basis to graphically present genome organization of parents and progenies on a physical scale. Genetic maps are a very important tool for breeders but often represent distorted models of the actual chromosomes, e.g., in centromeric and telomeric regions. This biased picture might lead to imprecise assumptions and estimations about the size and complexity of genetic regions and the selection of suitable molecular markers for the incorporation of traits in breeding populations or near-isogenic lines (NILs). Some software packages allow the graphical illustration of genotypic data, but to the best of our knowledge, suitable software packages that allow the comparison of genotypic data on the physical and genetic scale are currently unavailable.

RESULTS

We developed a simple Java-based-software called GenoTypeMapper (GTM) for comparing genotypic data on genetic and physical maps and tested it for effectiveness on data of two NILs that carry QTL-regions for drought stress tolerance from wild emmer on chromosome 2BS and 7AS. Both NILs were more tolerant to drought stress than their recurrent parents but exhibited additional undesirable traits such as delayed heading time.

CONCLUSIONS

In this article, we illustrate that the software easily allows users to display and identify additional chromosomal introgressions in both NILs originating from the wild emmer parent. The ability to detect and diminish linkage drag can be of particular interest for pre-breeding purposes and the developed software is a well-suited tool in this respect. The software is based on a simple allele-matching algorithm between the offspring and parents of a crossing scheme. Despite this simple approach, GTM seems to be the only software that allows us to analyse, illustrate and compare genotypic data of offspring of different crossing schemes with up to four parents in two different maps. So far, up to 500 individuals with a maximum number of 50,000 markers can be examined with the software. The main limitation that hampers the performance of the software is the number of markers that are examined in parallel. Since each individual must be analysed separately, a maximum of ten individuals can currently be displayed in a single run. On a computer with an Intel five processor of the 8th generation, GTM can reliably either analyse a single individual with up to 12,000 markers or ten individuals with up to 3,600 markers in less than five seconds. Future work aims to improve the performance of the software so that more complex crossing schemes with more parents and more markers can be analysed.

Genetic mapping and identification of new major loci for tolerance to low phosphorus stress in rice

Phosphorus (P) is one of the essential macronutrients for rice. In this study, we used 120 rice backcross recombinant inbred lines (BRILs) derived from a cross indica cv. Changhui 891 and japonica cv. 02428. To elucidate the genetic control of P deficiency tolerance in rice, we have used high quality SNPs bin markers to identify some important loci underlying phosphorus deficiency. The bin map was generated which includes 3057 bins covering distance of 1266.5 cM with an average of 0.41 cM between markers. Based on this map, 50 loci, including four novel loci, qSL-3, qRL-11, qSDW-1, qRDW-1 with phenotypic variance 23.26%, 12.06%, 9.89% associated with P deficiency-related seedling traits were identified. No significant QTLs was found for root length under P+, shoot fresh weight P- and root length, shoot fresh weight for P+, P- and their ratio respectively. Root fresh weight, and root dry weight were strongly correlated to each other, and QTLs for these variables were located on the same chromosome 1 at the same region. Notably, 3 pleiotropic regions is the pioneer of our study, and these regions would facilitate map-based cloning to expedite the MAS selection for developing low phosphorous tolerant varieties. This study not only improves our knowledge about molecular processes associated with P deficiency, but also provides useful information to understand the genetic architecture of low phosphorous tolerance.

The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

The compelling need to increase global agricultural production requires new breeding approaches that facilitate exploiting the diversity available in the plant genetic resources. Multi-parent advanced generation inter-cross (MAGIC) populations are large sets of recombinant inbred lines (RILs) that are a genetic mosaic of multiple founder parents. MAGIC populations display emerging features over experimental bi-parental and germplasm populations in combining significant levels of genetic recombination, a lack of genetic structure, and high genetic and phenotypic diversity. The development of MAGIC populations can be performed using “funnel” or “diallel” cross-designs, which are of great relevance choosing appropriate parents and defining optimal population sizes. Significant advances in specific software development are facilitating the genetic analysis of the complex genetic constitutions of MAGIC populations. Despite the complexity and the resources required in their development, due to their potential and interest for breeding, the number of MAGIC populations available and under development is continuously growing, with 45 MAGIC populations in different crops being reported here. Though cereals are by far the crop group where more MAGIC populations have been developed, MAGIC populations have also started to become available in other crop groups. The results obtained so far demonstrate that MAGIC populations are a very powerful tool for the dissection of complex traits, as well as a resource for the selection of recombinant elite breeding material and cultivars. In addition, some new MAGIC approaches that can make significant contributions to breeding, such as the development of inter-specific MAGIC populations, the development of MAGIC-like populations in crops where pure lines are not available, and the establishment of strategies for the straightforward incorporation of MAGIC materials in breeding pipelines, have barely been explored. The evidence that is already available indicates that MAGIC populations will play a major role in the coming years in allowing for impressive gains in plant breeding for developing new generations of dramatically improved cultivars.

Genetic dissection of thousand-seed weight and fine mapping of cqSW.A03-2 via linkage and association analysis in rapeseed (Brassica napus L.)

KEY MESSAGE: cqSW.A03-2, one of the six identified quantitative trait loci associated with thousand-seed weight in rapeseed, is mapped to a 61.6-kb region on chromosome A03 and corresponds to the candidate gene BnaA03G37960D. Seed weight is an important factor that determines the seed yield of oilseed rape (Brassica napus L.). To elucidate the genetic mechanism of thousand-seed weight (TSW), quantitative trait locus (QTL) mapping was conducted using a double haploid population derived from the cross between an elite line ZY50 and a pol cytoplasmic male sterility restorer line 7-5. The genetic basis of TSW was dissected into six major QTLs. One major QTL denoted as cqSW.A03-2, which explained 8.46-13.70% of the phenotypic variation, was detected across multiple environments. To uncover the genetic basis of cqSW.A03-2, a set of near-isogenic lines were developed. Based on the test of self-pollinated progenies, cqSW.A03-2 was identified as a single Mendelian factor and the ZY50 allele at cqSW.A03-2 showed a positive effect on TSW. Fine mapping delimited the cqSW.A03-2 locus into a 61.6-kb region, and 18 genes within this region were predicted. Candidate gene association analysis and expression analysis indicated that a histidine kinase gene (BnaA03G37960D) is likely to be the candidate gene for the cqSW.A03-2 locus. Our results may contribute to a better understanding of the molecular mechanism of seed weight regulation and promote the breeding program for yield improvement in rapeseed.

Quantitative trait loci (QTL) underlying phenotypic variation in bioethanol-related processes in Neurospora crassa

Bioethanol production from lignocellulosic biomass has received increasing attention over the past decade. Many attempts have been made to reduce the cost of bioethanol production by combining the separate steps of the process into a single-step process known as consolidated bioprocessing. This requires identification of organisms that can efficiently decompose lignocellulose to simple sugars and ferment the pentose and hexose sugars liberated to ethanol. There have been many attempts in engineering laboratory strains by adding new genes or modifying genes to expand the capacity of an industrial microorganism. There has been less attention in improving bioethanol-related processes utilizing natural variation existing in the natural ecotypes. In this study, we sought to identify genomic loci contributing to variation in saccharification of cellulose and fermentation of glucose in the fermenting cellulolytic fungus Neurospora crassa through quantitative trait loci (QTL) analysis. We identified one major QTL contributing to fermentation of glucose and multiple putative QTL's underlying saccharification. Understanding the natural variation of the major QTL gene would provide new insights in developing industrial microbes for bioethanol production.

Association mapping for mungbean yellow mosaic India virus resistance in mungbean (Vigna radiata L. Wilczek)

The present study aimed to detect the marker-trait association of a selected diverse panel of 127 mungbean genotypes against mungbean yellow mosaic India virus (MYMIV). Virus-specific primers pairs viz., AC-abut/AV-abut and BC-abut/BV-abut confirmed the involvement of MYMIV in yellow mosaic disease development and the same was validated through restriction digestion analysis. 256 genome-wide microsatellite markers were screened on a test panel in which 93 polymorphic markers were used in association studies. Population structure analysis led to formation of six distinct subpopulations. 1097 alleles were detected among 127 test genotypes whereas number of alleles ranged 2-22 and PIC values ranged 0.27-0.92%, indicating ample amount of variation at genome level. 15 microsatellite markers were detected as associated with MYMIV resistance, among them three microsatellites explained 11-14% phenotypic variation. The specific regions close to CEDG293, DMB-SSR008 and DMB-SSR059 associated with MYMIV resistance were detected, located on linkage group 2, 4 and 9 and may prove useful in marker-assisted mungbean improvement programme for enhancing MYMIV resistance.

Integrated Genomic Strategies for Cereal Genetic Enhancement: Combining QTL and Association Mapping

Identification of genetic basis for important agronomic traits is essential for marker-assisted crop improvement. Linkage mapping is one of the most popular approaches utilized for identification of major quantitative trait loci (QTLs) governing important agronomic traits in cereals. However, the identified QTLs usually span large genomic intervals and very few of these are subsequently fine mapped to single major effect gene. This hinders application of these QTLs in marker-aided breeding and crop genetic enhancement. On the contrary, association mapping, another popular approach for identification of QTLs, provides very high resolution but suffers from high level of false positives. Joint linkage-association analysis provides a way to combine advantages and avoid the pitfalls associated with both these methods. In this context, we recently developed MetaQTL specific regional association analysis and demonstrated its utility to rapidly narrow down previously identified QTL intervals to few candidate genes. Here, we describe the detailed step-by-step guide for performing MetaQTL specific regional association analysis to identify important genomic regions and underlying potential major effect genes governing traits of agronomic importance in cereals.

Assessment of Cas12a-mediated gene editing efficiency in plants

The CRISPR/Cas12a editing system opens new possibilities for plant genome engineering. To obtain a comparative assessment of RNA-guided endonuclease (RGEN) types in plants, we adapted the CRISPR/Cas12a system to the GoldenBraid (GB) modular cloning platform and compared the efficiency of Acidaminococcus (As) and Lachnospiraceae (Lb) Cas12a variants with the previously described GB-assembled Streptococcus pyogenes Cas9 (SpCas9) constructs in eight Nicotiana benthamiana loci using transient expression. All three nucleases showed drastic target-dependent differences in efficiency, with LbCas12 producing higher mutagenesis rates in five of the eight loci assayed, as estimated with the T7E1 endonuclease assay. Attempts to engineer crRNA direct repeat (DR) had little effect improving on-target efficiency for AsCas12a and resulted deleterious in the case of LbCas12a. To complete the assessment of Cas12a activity, we carried out genome editing experiments in three different model plants, namely N. benthamiana, Solanum lycopersicum and Arabidopsis thaliana. For the latter, we also resequenced Cas12a-free segregating T2 lines to assess possible off-target effects. Our results showed that the mutagenesis footprint of Cas12a is enriched in deletions of -10 to -2 nucleotides and included in some instances complex rearrangements in the surroundings of the target sites. We found no evidence of off-target mutations neither in related sequences nor somewhere else in the genome. Collectively, this study shows that LbCas12a is a viable alternative to SpCas9 for plant genome engineering.

A major QTL and candidate genes for capsaicinoid biosynthesis in the pericarp of Capsicum chinense revealed using QTL-seq and RNA-seq

A major QTL and candidate genes controlling capsaicinoid content in the pericarp were identified by QTL-seq and RNA-seq in Capsicum chinense. Capsaicinoid biosynthesis was previously thought to be restricted to the placental tissue; however, the recent discovery of their biosynthesis in the pericarp provides new opportunities to increase the capsaicinoid content in pepper fruits. Currently, the genetic mechanisms regulating capsaicinoid biosynthesis in the pericarp remain unknown. Here, we performed quantitative trait loci (QTL) mapping and RNA sequencing (RNA-seq) to reveal the genes controlling capsaicinoid biosynthesis in the pericarp. A whole-genome sequencing-based QTL-seq strategy was employed, identifying a major QTL on chromosome 6. To validate the QTL on chromosome 6, we performed traditional QTL mapping using the same population in QTL-seq with an additional biparental population. A total of 15 QTLs for capsaicinoid content distributed on chromosomes 3, 6, and 11 were newly identified. Among these QTLs, the genetic loci on the lower arm of chromosome 6 were commonly detected in the two mapping populations, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. Our RNA-seq analysis identified candidate genes within the common QTL that were differentially expressed in the pungent and non-pungent pericarp tissues. Our results are expected to contribute to the elucidation of the regulation of capsaicinoid biosynthesis. We also demonstrated that a combination of QTL mapping and RNA-seq is helpful for refining the candidate genes of a complicated trait of interest.

Acid phosphatase gene GmHAD1 linked to low phosphorus tolerance in soybean, through fine mapping

KEY MESSAGE

Map-based cloning identified GmHAD1, a gene which encodes a HAD-like acid phosphatase, associated with soybean tolerance to low phosphorus stress. Phosphorus (P) deficiency in soils is a major limiting factor for crop growth worldwide. Plants may adapt to low phosphorus (LP) conditions via changes to root morphology, including the number, length, orientation, and branching of the principal root classes. To elucidate the genetic mechanisms for LP tolerance in soybean, quantitative trait loci (QTL) related to root morphology responses to LP were identified via hydroponic experiments. In total, we identified 14 major loci associated with these traits in a RIL population. The log-likelihood scores ranged from 2.81 to 7.43, explaining 4.23-13.98% of phenotypic variance. A major locus on chromosome 08, named qP8-2, was co-localized with an important P efficiency QTL (qPE8), containing phosphatase genes GmACP1 and GmACP2. Another major locus on chromosome 10 named qP10-2 explained 4.80-13.98% of the total phenotypic variance in root morphology. The qP10-2 contains GmHAD1, a gene which encodes an acid phosphatase. In the transgenic soybean hairy roots, GmHAD1 overexpression increased P efficiency by 8.4-16.5% relative to the control. Transgenic Arabidopsis plants had higher biomass than wild-type plants across both short- and long-term P reduction. These results suggest that GmHAD1, an acid phosphatase gene, improved the utilization of organic phosphate by soybean and Arabidopsis plants.

Prioritization of Candidate Genes in QTL Regions for Physiological and Biochemical Traits Underlying Drought Response in Barley (Hordeum vulgare L.)

Drought is one of the most adverse abiotic factors limiting growth and productivity of crops. Among them is barley, ranked fourth cereal worldwide in terms of harvested acreage and production. Plants have evolved various mechanisms to cope with water deficit at different biological levels, but there is an enormous challenge to decipher genes responsible for particular complex phenotypic traits, in order to develop drought tolerant crops. This work presents a comprehensive approach for elucidation of molecular mechanisms of drought tolerance in barley at the seedling stage of development. The study includes mapping of QTLs for physiological and biochemical traits associated with drought tolerance on a high-density function map, projection of QTL confidence intervals on barley physical map, and the retrievement of positional candidate genes (CGs), followed by their prioritization based on Gene Ontology (GO) enrichment analysis. A total of 64 QTLs for 25 physiological and biochemical traits that describe plant water status, photosynthetic efficiency, osmoprotectant and hormone content, as well as antioxidant activity, were positioned on a consensus map, constructed using RIL populations developed from the crosses between European and Syrian genotypes. The map contained a total of 875 SNP, SSR and CGs, spanning 941.86 cM with resolution of 1.1 cM. For the first time, QTLs for ethylene, glucose, sucrose, maltose, raffinose, α-tocopherol, γ-tocotrienol content, and catalase activity, have been mapped in barley. Based on overlapping confidence intervals of QTLs, 11 hotspots were identified that enclosed more than 60% of mapped QTLs. Genetic and physical map integration allowed the identification of 1,101 positional CGs within the confidence intervals of drought response-specific QTLs. Prioritization resulted in the designation of 143 CGs, among them were genes encoding antioxidants, carboxylic acid biosynthesis enzymes, heat shock proteins, small auxin up-regulated RNAs, nitric oxide synthase, ATP sulfurylases, and proteins involved in regulation of flowering time. This global approach may be proposed for identification of new CGs that underlies QTLs responsible for complex traits.

Genomic Regions Analysis of Seedling Root Traits and Their Regulation in Responses to Phosphorus Deficiency Tolerance in CSSL Population of Elite Super Hybrid Rice

Phosphorus (P) is the essential macro-element supporting rice productivity. Quantitative trait loci (QTL) underlying related traits at the seedling stage under two different phosphorus levels was investigated in rice using a population of 76 Chromosomal Sequence Substitution Lines (CSSLs) derived from a cross between the maintainer variety XieqingzaoB (P stress tolerant) and the restorer variety Zhonghui9308 (P stress sensitive); the parents of super hybrid rice Xieyou9308. A genetic linkage map with 120 DNA marker loci was constructed. At logarithmic odd (LOD) value of 2.0, a total of seven QTLs were detected for studied traits under two P levels and their relative ratio. The LOD values ranged from 2.00 to 3.32 and explaining 10.82% to 18.46% of phenotypic variation. Three QTLs were detected under low phosphorus (P⁻), one under normal (P⁺) and three under their relative ratio (P⁻/P⁺) on the rice chromosomes 3, 5, 6, 8 and 10. No significant QTLs were found for shoot dry weight (SDW) and total dry weight (TDW). The pleiotropic QTLs influencing root number (qRN5) and root dry weight (qRDW5) as novel QTLs under P⁻ level were detected near marker RM3638 on chromosome 5, which considered to directly contributing to phosphorus deficiency tolerance in rice. These QTLs need further analysis, including the fine mapping and cloning, which may use in molecular marker assisted breeding.

Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map

KEY MESSAGE

Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively. Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8-10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171-39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37-59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

Association of functional markers with flowering time in lentil

In the present study, a diverse panel of 96 accessions of lentil germplasm was used to study flowering time over environments and to identify simple sequence repeat markers associated with flowering time through association mapping. The study showed high broad sense heritability estimate (h ² bs=0.93) for flowering time in lentil. Screening of 534 SSR markers resulted in an identification of 75 SSR polymorphic markers (13.9%) across studied genotypes. These markers amplified 266 loci and generated 697 alleles ranging from two to 16 alleles per locus. Model-based cluster analysis used for the determination of population structure resulted in the identification of two distinct subpopulations. Distribution of flowering time was ranged from 40 to 70 days in subpopulation I and from 54 to 69 days in subpopulation II and did not skew either late or early flowering time within a subpopulation. No admixture was observed within the subpopulations. Use of the most accepted maximum likelihood model (P3D mixed linear model with optimum compression) of MTA analysis showed significant association of 26 SSR markers with flowering time at <0.05 probability. The percent of phenotypic explained by each associated marker with flowering time ranged from 2.1 to 21.8% and identified QTLs for flowering time explaining high phenotypic variation across the environments (10.7-21.8%) or in a particular environment (10.2-21.4%). In the present study, 13 EST-SSR showed significant association with flowering time and explained large phenotypic variation (2.3-21.8%) compared to genomic SSR markers (2.1-10.2%). Hence, these markers can be used as functional markers in the lentil breeding program to develop short duration cultivars.

A Multiple QTL-Seq Strategy Delineates Potential Genomic Loci Governing Flowering Time in Chickpea

Identification of functionally relevant potential genomic loci using an economical, simpler and user-friendly genomics-assisted breeding strategy is vital for rapid genetic dissection of complex flowering time quantitative trait in chickpea. A high-throughput multiple QTL-seq strategy was employed in two inter (Cicer arietinum desi accession ICC 4958 × C reticulatum wild accession ICC 17160)- and intra (ICC 4958 × C. arietinum kabuli accession ICC 8261)-specific RIL mapping populations to identify the major QTL genomic regions governing flowering time in chickpea. The whole genome resequencing discovered 1635117 and 592486 SNPs exhibiting differentiation between early- and late-flowering mapping parents and bulks, constituted by pooling the homozygous individuals of extreme flowering time phenotypic trait from each of two aforesaid RIL populations. The multiple QTL-seq analysis using these mined SNPs in two RIL mapping populations narrowed-down two longer (907.1 kb and 1.99 Mb) major flowering time QTL genomic regions into the high-resolution shorter (757.7 kb and 1.39 Mb) QTL intervals on chickpea chromosome 4. This essentially identified regulatory as well as coding (non-synonymous/synonymous) novel SNP allelic variants from two efl1 (early flowering 1) and GI (GIGANTEA) genes regulating flowering time in chickpea. Interestingly, strong natural allelic diversity reduction (88-91%) of two known flowering genes especially mapped at major QTL intervals as compared to that of background genomic regions (where no flowering time QTLs were mapped; 61.8%) in cultivated vis-à-vis wild Cicer gene pools was evident inferring the significant impact of evolutionary bottlenecks on these loci during chickpea domestication. Higher association potential of coding non-synonymous and regulatory SNP alleles mined from efl1 (36-49%) and GI (33-42%) flowering genes for early and late flowering time differentiation among chickpea accessions was evident. The robustness and validity of two functional allelic variants-containing genes localized at major flowering time QTLs was apparent by their identification from multiple intra-/inter-specific mapping populations of chickpea. The functionally relevant molecular tags delineated can be of immense use for deciphering the natural allelic diversity-based domestication pattern of flowering time and expediting genomics-aided crop improvement to develop early flowering cultivars of chickpea.

High Density Linkage Map Construction and QTL Detection for Three Silique-Related Traits in Orychophragmus violaceus Derived Brassica napus Population

Seeds per silique (SS), seed weight (SW), and silique length (SL) are important determinant traits of seed yield potential in rapeseed (Brassica napus L.), and are controlled by naturally occurring quantitative trait loci (QTLs). Mapping QTLs to narrow chromosomal regions provides an effective means of characterizing the genetic basis of these complex traits. Orychophragmus violaceus is a crucifer with long siliques, many SS, and heavy seeds. A novel B. napus introgression line with many SS was previously selected from multiple crosses (B. rapa ssp. chinesis × O. violaceus) × B. napus. In present study, a doubled haploid (DH) population with 167 lines was established from a cross between the introgression line and a line with far fewer SS, in order to detect QTLs for silique-related traits. By screening with a Brassica 60K single nucleotide polymorphism (SNP) array, a high-density linkage map consisting of 1,153 bins and spanning a cumulative length of 2,209.1 cM was constructed, using 12,602 high-quality polymorphic SNPs in the DH population. The average recombination bin densities of the A and C subgenomes were 1.7 and 2.4 cM, respectively. 45 QTLs were identified for the three traits in all, which explained 4.0-34.4% of the total phenotypic variation; 20 of them were integrated into three unique QTLs by meta-analysis. These unique QTLs revealed a significant positive correlation between SS and SL and a significant negative correlation between SW and SS, and were mapped onto the linkage groups A05, C08, and C09. A trait-by-trait meta-analysis revealed eight, four, and seven consensus QTLs for SS, SW, and SL, respectively, and five major QTLs (cqSS.A09b, cqSS.C09, cqSW.A05, cqSW.C09, and cqSL.C09) were identified. Five, three, and four QTLs for SS, SW, and SL, respectively, might be novel QTLs because of the existence of alien genetic loci for these traits in the alien introgression. Thirty-eight candidate genes underlying nine QTLs for silique-related traits were identified.

Characterization of Genetic Basis on Synergistic Interactions between Root Architecture and Biological Nitrogen Fixation in Soybean

Soybean [Glycine max (L.) Merr] is an important legume crop and its yield largely depends on root architecture (RA) and biological nitrogen fixation (BNF). However, the relationship between RA and BNF, and its genetics behind remain unclear. Here, two soybean genotypes contrasting in RA and their 175 F_9:11 recombinant inbred lines (RILs) were evaluated in field. The shallow-root parent, JD12, had better nodulation and higher yield than the deep-root parent, NF58. Strong correlations between shoot dry weight (SDW) and RA or BNF traits existed in the RILs, and the shallow-root group had more and heavier nodules, as well as higher SDW. After inoculating with rhizobia, roots became shallower and bigger, showing strong synergistic interactions between RA and BNF. In total, 70 QTLs were identified for the 21 tested traits. Among them, qBNF-RA-C2, qBNF-RA-O, and qBNF-RA-B1, were newly identified QTLs for BNF and/or RA traits in soybean, which co-located with the QTLs for SDW detected presently, and with the QTLs for yield identified previously. The results together suggest that there are synergistic interactions between RA and BNF, and the QTLs identified here could be used for breeding new soybean varieties with higher yields through optimization of RA traits and BNF capacity.