Genome-wide association mapping and agronomic impact of cowpea root architecture

Key message

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.

Abstract

Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

     

MyROOT: a method and software for the semiautomatic measurement of primary root length in Arabidopsis seedlings

Root analysis is essential for both academic and agricultural research. Despite the great advances in root phenotyping and imaging, calculating root length is still performed manually and involves considerable amounts of labor and time. To overcome these limitations, we developed MyROOT, a software for the semiautomatic quantification of root growth of seedlings growing directly on agar plates. Our method automatically determines the scale from the image of the plate, and subsequently measures the root length of the individual plants. To this aim, MyROOT combines a bottom‐up root tracking approach with a hypocotyl detection algorithm. At the same time as providing accurate root measurements, MyROOT also significantly minimizes the user intervention required during the process. Using Arabidopsis, we tested MyROOT with seedlings from different growth stages and experimental conditions. When comparing the data obtained from this software with that of manual root measurements, we found a high correlation between both methods (R² = 0.997). When compared with previous developed software with similar features (BRAT and EZ‐Rhizo), MyROOT offered an improved accuracy for root length measurements. Therefore, MyROOT will be of great use to the plant science community by permitting high‐throughput root length measurements while saving both labor and time.     

Analysis of Maize (Zea mays L.) Seedling Roots with the High-Throughput Image Analysis Tool ARIA (Automatic Root Image Analysis)

The maize root system is crucial for plant establishment as well as water and nutrient uptake. There is substantial genetic and phenotypic variation for root architecture, which gives opportunity for selection. Root traits, however, have not been used as selection criterion mainly due to the difficulty in measuring them, as well as their quantitative mode of inheritance. Seedling root traits offer an opportunity to study multiple individuals and to enable repeated measurements per year as compared to adult root phenotyping. We developed a new software framework to capture various traits from a single image of seedling roots. This framework is based on the mathematical notion of converting images of roots into an equivalent graph. This allows automated querying of multiple traits simply as graph operations. This framework is furthermore extendable to 3D tomography image data. In order to evaluate this tool, a subset of the 384 inbred lines from the Ames panel, for which extensive genotype by sequencing data are available, was investigated. A genome wide association study was applied to this panel for two traits, Total Root Length and Total Surface Area, captured from seedling root images from WinRhizo Pro 9.0 and the current framework (called ARIA) for comparison using 135,311 single nucleotide polymorphism markers. The trait Total Root Length was found to have significant SNPs in similar regions of the genome when analyzed by both programs. This high-throughput trait capture software system allows for large phenotyping experiments and can help to establish relationships between developmental stages between seedling and adult traits in the future.     

High‐throughput two‐dimensional root system phenotyping platform facilitates genetic analysis of root growth and development

High‐throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user‐guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large‐scale phenotyping studies. To demonstrate the unique capabilities and high‐throughput capacity of this phenotyping platform for studying root systems, genome‐wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.     

High-throughput root phenotyping screens identify genetic loci associated with root architectural traits in Brassica napus under contrasting phosphate availabilities

Background and Aims

Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus.

Methods

Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus [‘Tapidor’ × ‘Ningyou 7’ (TNDH)] using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP.

Key Results

In general, root and biomass traits were highly correlated under LP and HP conditions. ‘Ningyou 7’ had greater LRL, LRN and LRD than ‘Tapidor’, at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06.

Conclusions

High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.     

Assessing variability in root traits of wild Lupinus angustifolius germplasm: basis for modelling root system structure

Background and aims

Intra-specific variation in root system architecture and consequent efficiency of resource capture by major crops has received recent attention. The aim of this study was to assess variability in a number of root traits among wild genotypes of narrow-leafed lupin (Lupinus angustifolius L.), to provide a basis for modelling of root structure.

Methods

A subset of 111 genotypes of L. angustifolius was selected from a large germplasm pool based on similarity matrices calculated using Diversity Array Technology markers. Plants were grown for 6?weeks in the established semi-hydroponic phenotyping systems to measure the fine-scale features of the root systems.

Results

Root morphology of wild L. angustifolius was primarily dominated by the taproot and first-order branches, with the presence of densely or sparsely distributed second-order branches in the late growth stage. Large variation in most root traits was identified among the tested genotypes. Total root length, branch length and branch number in the entire root system and in the upper roots were the most varied traits (coefficient of variation CV >0.50). Over 94% of the root system architectural variation determined from the principal components analysis was captured by six components (eigenvalue >1). Five relatively homogeneous groups of genotypes with distinguished patterns of root architecture were separated by k-means clustering analysis.

Conclusions

Variability in the fine-scale features of root systems such as branching behaviour and taproot growth rates provides a basis for modelling root system structure, which is a promising path for selecting desirable root traits in breeding and domestication of wild and exotic resources of L. angustifolius for stressful or poor soil environments.     

Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations

Background

Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F₂ intercross population and a Chinese Sutai half-sib population.

Results

We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F₂ animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits.

Conclusions

We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0089-5) contains supplementary material, which is available to authorized users.     

Phenotype of Arabidopsis thaliana semi-dwarfs with deep roots and high growth rates under water-limiting conditions is independent of the GA5 loss-of-function alleles

Background and Aims The occurrence of Arabidopsis thaliana semi-dwarf accessions carrying inactive alleles at the gibberellin (GA) biosynthesis GA5 locus has raised the question whether there are pleiotropic effects on other traits at the root level, such as rooting depth. In addition, it is unknown whether semi-dwarfism in arabidopsis confers a growth advantage under water-limiting conditions compared with wild-type plants. The aim of this research was therefore to investigate whether semi-dwarfism has a pleiotropic effect in the root system and also whether semi-dwarfs might be more tolerant of water-limiting conditions.Methods The root systems of different arabidopsis semi-dwarfs and GA biosynthesis mutants were phenotyped in vitro using the GROWSCREEN-ROOT image-based software. Semi-dwarfs were phenotyped together with tall, near-related accessions. In addition, root phenotypes were investigated in soil-filled rhizotrons. Rosette growth trajectories were analysed with the GROWSCREEN-FLUORO setup based on non-invasive imaging.Key Results Mutations in the early steps of the GA biosynthesis pathway led to a reduction in shoot as well as root size. Depending on the genetic background, mutations at the GA5 locus yielded phenotypes characterized by decreased root length in comparison with related wild-type ones. The semi-dwarf accession Pak-3 showed the deepest root system both in vitro and in soil cultivation experiments; this comparatively deep root system, however, was independent of the ga5 loss-of-function allele, as shown by co-segregation analysis. When the accessions were grown under water-limiting conditions, semi-dwarf accessions with high growth rates were identified.Conclusions The observed diversity in root system growth and architecture occurs independently of semi-dwarf phenotypes, and is probably linked to a genetic background effect. The results show that there are no clear advantages of semi-dwarfism at low water availability in arabidopsis.     

RootAnalyzer: A Cross-Section Image Analysis Tool for Automated Characterization of Root Cells and Tissues

The morphology of plant root anatomical features is a key factor in effective water and nutrient uptake. Existing techniques for phenotyping root anatomical traits are often based on manual or semi-automatic segmentation and annotation of microscopic images of root cross sections. In this article, we propose a fully automated tool, hereinafter referred to as RootAnalyzer, for efficiently extracting and analyzing anatomical traits from root-cross section images. Using a range of image processing techniques such as local thresholding and nearest neighbor identification, RootAnalyzer segments the plant root from the image’s background, classifies and characterizes the cortex, stele, endodermis and epidermis, and subsequently produces statistics about the morphological properties of the root cells and tissues. We use RootAnalyzer to analyze 15 images of wheat plants and one maize plant image and evaluate its performance against manually-obtained ground truth data. The comparison shows that RootAnalyzer can fully characterize most root tissue regions with over 90% accuracy.     

Modelling root plasticity and response of narrow-leafed lupin to heterogeneous phosphorus supply

Background & Aims

Searching for root traits underpinning efficient nutrient acquisition has received increased attention in modern breeding programs aimed at improved crop productivity. Root models provide an opportunity to investigate root-soil interactions through representing the relationships between rooting traits and the non-uniform supply of soil resources. This study used simulation modelling to predict and identify phenotypic plasticity, root growth responses and phosphorus (P) use efficiency of contrasting Lupinus angustifolius genotypes to localised soil P in a glasshouse.

Methods

Two L. angustifolius genotypes with contrasting root systems were grown in cylindrical columns containing uniform soil with three P treatments (nil and 20 mg P kg^?1 either top-dressed or banded) in the glasshouse. Computer simulations were carried out with root architecture model ROOTMAP which was parameterized with root architectural data from an earlier published hydroponic phenotyping study.

Results

The experimental and simulated results showed that plants supplied with banded P had the largest root system and the greatest P-uptake efficiency. The P addition significantly stimulated root branching in the topsoil, whereas plants with nil P had relatively deeper roots. Genotype-dependent root growth plasticity in response to P supply was shown, with the greatest response to banded P.

Conclusions

Both experimental and simulation outcomes demonstrated that 1) root hairs and root proliferation increased plant P acquisition and were more beneficial in the localised P fertilisation scenario, 2) placing P deeper in the soil might be a more effective fertilisation method with greater P uptake than top dressing, and 3) the combination of P foraging strategies (including root architecture, root hairs and root growth plasticity) is important for efficient P acquisition from a localised source of fertiliser P.     

A multiple ion-uptake phenotyping platform reveals shared mechanisms affecting nutrient uptake by roots

Nutrient uptake is critical for crop growth and is determined by root foraging in soil. Growth and branching of roots lead to effective root placement to acquire nutrients, but relatively little is known about absorption of nutrients at the root surface from the soil solution. This knowledge gap could be alleviated by understanding sources of genetic variation for short-term nutrient uptake on a root length basis. A modular platform called RhizoFlux was developed for high-throughput phenotyping of multiple ion-uptake rates in maize (Zea mays L.). Using this system, uptake rates were characterized for the crop macronutrients nitrate, ammonium, potassium, phosphate, and sulfate among the Nested Association Mapping (NAM) population founder lines. The data revealed substantial genetic variation for multiple ion-uptake rates in maize. Interestingly, specific nutrient uptake rates (nutrient uptake rate per length of root) were found to be both heritable and distinct from total uptake and plant size. The specific uptake rates of each nutrient were positively correlated with one another and with specific root respiration (root respiration rate per length of root), indicating that uptake is governed by shared mechanisms. We selected maize lines with high and low specific uptake rates and performed an RNA-seq analysis, which identified key regulatory components involved in nutrient uptake. The high-throughput multiple ion-uptake kinetics pipeline will help further our understanding of nutrient uptake, parameterize holistic plant models, and identify breeding targets for crops with more efficient nutrient acquisition.

A platform for quantifying root uptake rates of multiple, simultaneous nutrients reveals these rates are correlated among nutrients, are heritable, and may have a common genetic basis.     

Exploring the natural variation for seedling traits and their link with seed dimensions in tomato

The success of germination, growth and final yield of every crop depends to a large extent on the quality of the seeds used to grow the crop. Seed quality is defined as the viability and vigor attribute of a seed that enables the emergence and establishment of normal seedlings under a wide range of environments. We attempt to dissect the mechanisms involved in the acquisition of seed quality, through a combined approach of physiology and genetics. To achieve this goal we explored the genetic variation found in a RIL population of Solanum lycopersicum (cv. Moneymaker) x Solanum pimpinellifolium through extensive phenotyping of seed and seedling traits under both normal and nutrient stress conditions and root system architecture (RSA) traits under optimal conditions. We have identified 62 major QTLs on 21 different positions for seed, seedling and RSA traits in this population. We identified QTLs that were common across both conditions, as well as specific to stress conditions. Most of the QTLs identified for seedling traits co-located with seed size and seed weight QTLs and the positive alleles were mostly contributed by the S. lycopersicum parent. Co-location of QTLs for different traits might suggest that the same locus has pleiotropic effects on multiple traits due to a common mechanistic basis. We show that seed weight has a strong effect on seedling vigor and these results are of great importance for the isolation of the corresponding genes and elucidation of the underlying mechanisms.     

Further genetic analysis of a major quantitative trait locus controlling root length and related traits in common wheat

Roots are essential for normal growth, development, and reproduction of higher plants. Consequently, improvement of root system architecture and functionality is of fundamental importance in crop improvement. However, the genetic mechanisms controlling root morphology and function are still not well understood, especially in common wheat, which possesses a complex and unsequenced hexaploid genome. Here we report a more detailed genetic analysis of qTaLRO-B1, a major quantitative trait locus (QTL) previously detected to affect root length and related traits in common wheat. A pair of QTL isolines with different qTaLRO-B1 alleles was developed. Line 178B, carrying the longer root allele, was significantly more efficient in taking up phosphate nutrient and biomass accumulation than line 178A, with the shorter root allele. We mapped qTaLRO-B1 to a 0.9-cM interval on common wheat chromosome 2BS with seven sequence-tagged-site (STS) markers developed from the genes conserved between wheat and Brachypodium distachyon. The seven STS markers were collinearly conserved in tetraploid wheat, but they covered a much larger genetic distance (22.8 cM) in the latter species. In conclusion, we have converted qTaLRO-B1 into a major gene that affects common wheat root length in a qualitative manner, and improved understanding of the genetic location of qTaLRO-B1 and the chromosomal segment carrying this important locus. The implications of our data for further study of qTaLRO-B1 are discussed.     

Functional ecology of growth in seedlings versus root sprouts of Fagus grandifolia Ehrh.

We assessed growth differences and the foliar traits underpinning production in paired samples of juvenile American beech (Fagus grandifolia Ehrh.) that originated from seed versus root sprouts. Root sprouts had significantly greater relative extension growth rate and slightly greater leaf mass per unit area compared to seed-derived individuals, but neither light-saturated net photosynthetic rate nor foliar chlorophyll and nitrogen concentrations differed significantly between paired seedlings and sprouts. The greater height growth rate of saplings originating as root sprouts does not result from differing foliar function, but rather depends on translocation of assimilates from the parent tree to sustain this unusual and ecologically important dual regeneration strategy in American beech.     

A Variant in the Neuropeptide Receptor npr-1 is a Major Determinant of Caenorhabditis elegans Growth and Physiology

The mechanistic basis for how genetic variants cause differences in phenotypic traits is often elusive. We identified a quantitative trait locus in Caenorhabditis elegans that affects three seemingly unrelated phenotypic traits: lifetime fecundity, adult body size, and susceptibility to the human pathogen Staphyloccus aureus. We found a QTL for all three traits arises from variation in the neuropeptide receptor gene npr-1. Moreover, we found that variation in npr-1 is also responsible for differences in 247 gene expression traits. Variation in npr-1 is known to determine whether animals disperse throughout a bacterial lawn or aggregate at the edges of the lawn. We found that the allele that leads to aggregation is associated with reduced growth and reproductive output. The altered gene expression pattern caused by this allele suggests that the aggregation behavior might cause a weak starvation state, which is known to reduce growth rate and fecundity. Importantly, we show that variation in npr-1 causes each of these phenotypic differences through behavioral avoidance of ambient oxygen concentrations. These results suggest that variation in npr-1 has broad pleiotropic effects mediated by altered exposure to bacterial food.     

A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects

? To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes. ? The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times. ? Using the system, a single researcher can phenotype up to 7000 plants d?1. Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excess mutant sex4-3 and the growth-enhanced mutant grf9. ? We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.     

Improvement of Rice Biomass Yield through QTL-Based Selection

Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F₂ plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F₆ lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield.