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Distribution of GWAS peaks. Pie charts showing the proportion of GWAS peaks identified using deviation versus non-deviation phenotype data (a), at location = KARE (UC Kearney) versus location = WREC (Westside Research and Extension) (b)., and for all combinations of DV vs NDV at the two locations (c). a All peaks were classified as DV and/or NDV, where DV peaks were those identified using the phenotype data calculated as the deviation between either the pre-flowering stress treatment or the post-flowering stress treatment and the control, and the NDV peaks were those identified using the raw phenotype data. The majority of peaks were identified regardless of whether DV or NDV data were used. c Each wedge shows the proportion of the peaks that were only identified for a particular combination of data, e.g., the largest proportion of peaks (~ 20%) were identified only using NDV data from KARE, DV data from WREC and NDV data from WREC
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Background:
Sorghum bicolor is the fifth most commonly grown cereal worldwide and is remarkable for its drought and abiotic stress tolerance. For these reasons and the large size of biomass varieties, it has been proposed as a bioenergy crop. However, little is known about the genes underlying sorghum's abiotic stress tolerance and biomass yield....
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With the recent development of genomic resources and high‐throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding, and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food dem...
Citations
... Key among these innovations are advanced imaging and light detection and ranging (lidar), which continue to grow in applications [3][4][5][6]. Such advancements facilitate cost-efficient, consistent measurements of plant architectural traits across various locations, growing seasons, and spatial scales [7]. Furthermore, lidar provides the basis for modeling the effects of genotype-by-environment interactions on various plant traits that can be exploited to advance crop development [2]. ...
Light detection and ranging (lidar) scanning tools are available that can make rapid digital estimations of biomass. Voxelization and convex hull are two algorithms used to calculate the volume of the scanned plant canopy, which is correlated with biomass, often the primary trait of interest. Voxelization splits the scans into regular-sized cubes, or voxels, whereas the convex hull algorithm creates a polygon mesh around the outermost points of the point cloud and calculates the volume within that mesh. In this study, digital estimates of biomass were correlated against hand-harvested biomass for field-grown corn, broom corn, and energy sorghum. Voxelization (r = 0.92) and convex hull (r = 0.95) both correlated well with plant dry biomass. Lidar data were also collected in a large breeding trial with nearly 900 genotypes of energy sorghum. In contrast to the manual harvest studies, digital biomass estimations correlated poorly with yield collected from a forage harvester for both voxel count (r = 0.32) and convex hull volume (r = 0.39). However, further analysis showed that the coefficient of variation (CV, a measure of variability) for harvester-based estimates of biomass was greater than the CV of the voxel and convex-hull-based biomass estimates, indicating that poor correlation was due to harvester imprecision, not digital estimations. Overall, results indicate that the lidar-based digital biomass estimates presented here are comparable or more precise than current approaches.
... For a brief overview of the key omics approaches used in plant breeding, refer to Box 1. By studying all these components together, omics techniques can provide a holistic understanding of how genes and proteins interact to produce complex phenotypes, such as crop yield (Naeem et al. 2022), nutritional quality (Paine et al. 2005), drought tolerance in Sorghum (Spindel et al. 2018), rice , and maize (Shikha et al. 2017), and disease resistance. (Strahl andAllis, 2000, Novik et al. 2002). ...
... Similarly, a genome-wide association study (GWAS) identified causal polymorphisms for traits like drought tolerance and biomass yield based on historical recombination events in sorghum by employing a drone (Spindel et al. 2018). The drone was a modified multirotor vehicle with Blue River's proprietary imaging payload (Spindel et al. 2018). ...
... Similarly, a genome-wide association study (GWAS) identified causal polymorphisms for traits like drought tolerance and biomass yield based on historical recombination events in sorghum by employing a drone (Spindel et al. 2018). The drone was a modified multirotor vehicle with Blue River's proprietary imaging payload (Spindel et al. 2018). The identified candidate genes are related to several proteins, like heat shock proteins, antifreeze proteins, and other domains recognized as important to plant stress responses. ...
Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.
... Among the field-based HTPS deployed for studying sorghum, unmanned aerial vehicles (UAVs) have been widely utilized to study the dynamics of traits such as plant height (Hu et al., 2018;Pugh et al., 2018;Varela et al., 2021;Watanabe et al., 2017), leaf area index (Spindel et al., 2018), and biomass (Spindel et al., 2018;Varela et al., 2021). Nevertheless, UAVs are not effective in characterizing lower canopy layers, especially in late growing stages (Gage et al., 2019;Sun et al., 2018). ...
... Among the field-based HTPS deployed for studying sorghum, unmanned aerial vehicles (UAVs) have been widely utilized to study the dynamics of traits such as plant height (Hu et al., 2018;Pugh et al., 2018;Varela et al., 2021;Watanabe et al., 2017), leaf area index (Spindel et al., 2018), and biomass (Spindel et al., 2018;Varela et al., 2021). Nevertheless, UAVs are not effective in characterizing lower canopy layers, especially in late growing stages (Gage et al., 2019;Sun et al., 2018). ...
... Hilley et al., 2016;J. L. Hilley et al., 2017) have been previously associated with biomass accumulation in sorghum Spindel et al., 2018), which were confirmed herein using HTP-derived descriptors to characterize the growth rate. Dw3 is an auxin transporter that controls not only plant height but also leaf angle (Mantilla-Perez & Salas Fernandez, 2017;Truong et al., 2015). ...
Canopy architecture traits are associated with productivity in sorghum [Sorghum bicolor (L.) Moench], and they are commonly measured at the time of flowering or harvest. Little is known about the dynamics of canopy architecture traits through the growing season. Utilizing the ground‐based high‐throughput phenotyping system Phenobot 1.0, we collected stereo images of a photoperiod‐sensitive and a photoperiod‐insensitive population over time to generate three‐dimensional (3D) representations of the canopy. Four descriptors were automatically extracted from the 3D point clouds: plot‐based plant height (PBPH), plot‐based plant width (PBPW), plant surface area (PSA), and convex hull volume (CHV). Additionally, genotypic growth rates were estimated for each canopy descriptor. Genome‐wide association analysis was performed on individual timepoints and the growth rates in both populations. We detected genotypic variation for each of the four canopy descriptors and their growth rates and discovered novel genomic regions associated with growth rates on chromosomes 1 (PBPH, CHV), 3 (PBPH), 4 (PBPH, PBPW), 5 (PBPH), 8 (PSA), and 9 (PBPW). These results provide new knowledge about the genetic control of canopy architecture, highlighting genomic regions that can be targeted in plant breeding programs.
... Recent studies have used genome-wide association studies (GWASs) to find potential SNPs for various traits, including improved stress tolerance indices, yield, and other traits in different species, including sorghum [202][203][204], rice [205], and sesame [206,207]. Although the AQP gene family improves drought resilience, multidrug and toxic compound extrusion (MATE) mediates the reaction to abiotic stresses [208]. ...
Flax, or linseed, is considered a “superfood”, which means that it is a food with diverse
health benefits and potentially useful bioactive ingredients. It is a multi-purpose crop that is prized
for its seed oil, fibre, nutraceutical, and probiotic qualities. It is suited to various habitats and
agro-ecological conditions. Numerous abiotic and biotic stressors that can either have a direct or
indirect impact on plant health are experienced by flax plants as a result of changing environmental
circumstances. Research on the impact of various stresses and their possible ameliorators is prompted
by such expectations. By inducing the loss of specific alleles and using a limited number of selected
varieties, modern breeding techniques have decreased the overall genetic variability required for
climate-smart agriculture. However, gene banks have well-managed collectionns of landraces, wild
linseed accessions, and auxiliary Linum species that serve as an important source of novel alleles. In
the past, flax-breeding techniques were prioritised, preserving high yield with other essential traits.
Applications of molecular markers in modern breeding have made it easy to identify quantitative
trait loci (QTLs) for various agronomic characteristics. The genetic diversity of linseed species and
the evaluation of their tolerance to abiotic stresses, including drought, salinity, heavy metal tolerance,
and temperature, as well as resistance to biotic stress factors, viz., rust, wilt, powdery mildew, and
alternaria blight, despite addressing various morphotypes and the value of linseed as a supplement,
are the primary topics of this review.
... Recent studies have used genome-wide association studies (GWASs) to find potential SNPs for various traits, including improved stress tolerance indices, yield, and other traits in different species, including sorghum [202][203][204], rice [205], and sesame [206,207]. Although the AQP gene family improves drought resilience, multidrug and toxic compound extrusion (MATE) mediates the reaction to abiotic stresses [208]. ...
Flax, or linseed, is considered a “superfood”, which means that it is a food with diverse health benefits and potentially useful bioactive ingredients. It is a multi-purpose crop that is prized for its seed oil, fibre, nutraceutical, and probiotic qualities. It is suited to various habitats and agro-ecological conditions. Numerous abiotic and biotic stressors that can either have a direct or
indirect impact on plant health are experienced by flax plants as a result of changing environmental circumstances. Research on the impact of various stresses and their possible ameliorators is prompted by such expectations. By inducing the loss of specific alleles and using a limited number of selected varieties, modern breeding techniques have decreased the overall genetic variability required for
climate-smart agriculture. However, gene banks have well-managed collections of landraces, wild linseed accessions, and auxiliary Linum species that serve as an important source of novel alleles. In the past, flax-breeding techniques were prioritised, preserving high yield with other essential traits. Applications of molecular markers in modern breeding have made it easy to identify quantitative trait loci (QTLs) for various agronomic characteristics. The genetic diversity of linseed species and the evaluation of their tolerance to abiotic stresses, including drought, salinity, heavy metal tolerance, and temperature, as well as resistance to biotic stress factors, viz., rust, wilt, powdery mildew, AND Alternaria blight, despite addressing various morphotypes and the value of linseed as a supplement, are the primary topics of this review.
... Recent release of draft genomes (Guo et al., 2017;Wu et al., 2022;Zou et al., 2019) and GBS based-SNP data (Johnson et al., 2019;Wallace et al., 2015) Recently, a well-designed non-destructive aerial drone (phenomics) platform has been developed in sorghum to dissect the biomass traits under drought conditions. A study by Spindel et al. (2018) using an aerial drone image analyser identified 213 highly reliable unique GWAS peaks, which were larger than any previously reported GWAS in sorghum. Interestingly, the newly identified GWAS peaks when validated multiple times in high-density phenotype trials showed 100% consistency across the environments. ...
... conducted by GWAS using high-throughput genotyping data have deciphered key genes controlling the agronomical and nutritional traits in various millets such as plant architecture(Luo et al., 2020;, yield-related traitsGirma et al., 2019), seed size(Tao et al., 2020;Zhang et al., 2015), stress resistance(Adeyanju et al., 2015;Ahn et al., 2019;Cuevas et al., 2018;Leiser et al., 2014;Prom et al., 2019), biomass(Spindel et al., 2018), grain polyphenol(Rhodes et al., 2014), flavonoid and starch/sugar(Bing-ru et al., 2019;Luo et al., 2020) in sorghum, yield-related traits(Varshney et al., 2017), flowering(Diack et al., 2020), protein content(Pujar et al., 2020) and micronutrients(Anuradha et al., 2017;Pujar et al., 2020) in pearl millet, morphoagronomical(Gupta et al., 2014;Jia et al., 2013) and nutritional traits in foxtail millet and grain yield(Sharma et al., 2018), ...
... Therefore, deep phenotyping methods are necessary to empower the GWAS strategy in detecting the candidate gene with higher confidence. The outline of GWAS workflow in crop plants is depicted inFigure 5.In the recent past, phenomics, a trans-disciplined field, has provided a link between the phenotype (traits) and genotype (gene/alleles variants) of the organism(Spindel et al., 2018). The high-throughput phenotyping (HTP) tools greatly advanced in large-scale phenotyping, data acquisition and processing in crop plants. ...
Millets are known for their resilience and nutritional benefits and hence believed to have a promising role in ensuring food and nutritional security under changing climatic conditions. Research on millets has intensified in recent years, especially in dissecting the genetic components of yield, stress tolerance and nutritional quality traits. Recent advances in next‐generation sequencing, bioinformatics and associated statistical procedures for genome‐wide association studies (GWAS) have provided wide opportunities to resolve the genetic complexity of polygenic traits by measuring historical and evolutionary recombination events in the natural population(s). During the past decade, GWAS has been successfully employed to identify key genes controlling growth, development, stress tolerance, nutrient use efficiency and nutritional quality traits in sorghum, pearl millet, foxtail millet and finger millet. However, progress in other minor millets is still in its infancy. Genetic dissection of these complex traits in millets may pave the way for genetic alteration of climate resilience, photosynthesis and nutrient accumulation in rice and wheat. In this review, progress in GWAS analysis in detecting QTLs underlying complex traits in sorghum and other millets is highlighted.
... These advances help in the selection of drought-tolerant and sensitive plants (Kim et al., 2020). With the help of this technology, researchers have been able to study drought response in a range of crops (Spindel et al., 2018). Through the use of metabolomics, studying the guard cell metabolome can provide insight into stomatal mobility and transpiration control in plants, in addition to phenotyping compounds that govern physiological processes in plants (Misra et al., 2015). ...
Drought is becoming a major threat to rice farming across the globe owing to the depletion of water tables in rice-growing belts. Drought affects rice plants at multiple stages, causing damage at morphological and physio-biochemical levels, leading to severe losses that exceed losses from all other stresses. The amalgamation of conventional breeding methods with modern molecular biology tools and biometrical methods could help accelerate the genetic gain for drought tolerance in rice. Many drought-tolerance traits with genetic determinants have been identified and exploited for tolerance rice variety breeding. The integration of genome-wide association study and genomic selection tools with speed breeding shortened the breeding cycle and aided in rapid improvement of genetic gain. In this review, we emphasized the progress made through classical breeding as well as the limitations and usefulness of current genomic methods in improving drought tolerance. We briefly addressed methods for identifying genetic determinants for drought tolerance and deploying them through genomics-assisted breeding programmes to develop high-yielding drought-tolerant rice cultivars.
... Similar findings have been shown in soybean using UAV-based phenotyping (Xavier et al., 2017), in cotton using ground-based vehicle phenotyping (Pauli et al., 2016), in wheat, rice, and triticale using tractor-based phenotyping (Würschum et al., 2014;Tanger et al., 2017;Lyra et al., 2020), as well as in maize and barley using automated-based phenotyping under greenhouse conditions (Muraya et al., 2017;Neumann et al., 2017;Zhang et al., 2017). Temporal NDVIs (normalized difference vegetation indexes) captured by UAVs have also been used in association studies in cotton (Pauli et al., 2016), sorghum (Spindel et al., 2018), and maize . However, the present study showed that NDVI discovered among the lowest number of SNPs in GWAS mapping (Fig. 8A). ...
High throughput phenotyping (HTP) has expanded the dimensionality of data in plant research, however HTP has resulted in few novel biological discoveries to date. Field based high-throughput phenotyping (FHTP), using small unoccupied aerial vehicles (UAV) equipped with imaging sensors can be deployed routinely to monitor segregating plant population interactions with the environment under biologically meaningful conditions. Here, flowering dates and plant height, important phenological fitness traits, were collected on 520 segregating recombinant maize inbred lines (RILs) in both irrigated and drought stress trials in 2018. Using UAV phenomic, SNP genomic, as well as combined data, flowering times were predicted using several scenarios. Untested genotypes were predicted with 0.58, 0.59 and 0.41 prediction ability for anthesis, silking and terminal plant height using genomic data; but prediction ability increased 0.77, 0.76 and 0.58 when phenomic and genomic data were used together. Using the phenomic data in a genome-wide association study, a heat related candidate gene (GRMZM2G083810; hsp18f) was discovered using temporal reflectance phenotypes belonging to flowering times (both irrigated and drought) trials where heat stress also peaked. Thus, a relation between plants and abiotic stresses belonging to a specific time of growth was revealed only through use of temporal phenomic data. Overall, this study showed that (i) it is possible to predict complex traits using high dimensional phenomic data between different environments, and (ii) temporal phenomic data can reveal time-dependent association between genotypes and abiotic stresses, which can help understand mechanisms to develop resilient plants.
... The broad genetic diversity of sorghum is captured by the sorghum association panel (SAP), which is composed of 400 temperate breeding lines as well as converted tropical lines that collectively represent the bulk of sorghum diversity (14). Association studies have identified genomic regions linked with drought response in sorghum (15) but unlike expression studies, it is challenging to link specific genes to underlying phenotypes. Here, we compared gene expression across the SAP during a natural drought event and leveraged these data to identify conserved and variable drought responses across sorghum lines. ...
Drought tolerance is a highly complex trait controlled by numerous interconnected pathways with substantial variation within and across plant species. This complexity makes it difficult to distill individual genetic loci underlying tolerance, and to identify core or conserved drought-responsive pathways. Here, we collected drought physiology and gene expression datasets across diverse genotypes of the C4 cereals sorghum and maize and searched for signatures defining water-deficit responses. Differential gene expression identified few overlapping drought-associated genes across sorghum genotypes, but using a predictive modeling approach, we found a shared core drought response across development, genotype, and stress severity. Our model had similar robustness when applied to datasets in maize, reflecting a conserved drought response between sorghum and maize. The top predictors are enriched in functions associated with various abiotic stress-responsive pathways as well as core cellular functions. These conserved drought response genes were less likely to contain deleterious mutations than other gene sets, suggesting that core drought-responsive genes are under evolutionary and functional constraints. Our findings support a broad evolutionary conservation of drought responses in C4 grasses regardless of innate stress tolerance, which could have important implications for developing climate resilient cereals.
... With the rapid development of molecular biology, molecular genetics and bioinformatics, genome-wide association studies (GWASs), based on the natural population and linkage disequilibrium, can detect genetic variation polymorphisms in the whole genome and conduct population-level statistical analysis of the genotype and phenotype, which can efficiently detect genes associated with traits, making it more convenient to mine genes that control the drought-tolerance traits of crops and identify excellent genetic variation materials. With the reduction in sequencing costs and the completion of most crop gene sequencing, GWASs have been widely applied in the drought-tolerance research of rice [4][5][6][7][8], wheat [9][10][11][12], maize [13][14][15], soybean [16,17], sorghum [18,19], cotton [20] and other crops, and many significant marker-trait association loci and candidate genes related to drought tolerance have been revealed, some of which are related to transcription factors (TFs) [7,8,10,16,18]. The quantitative trait locus identified by GWAS contains candidate genes with functions related to osmotic stress regulation, such as the basic leucine zipper (bZIP) protein gene OsbZIP80, which plays an important role in the tolerance of or adaptation to abiotic stress and is considered a rice-dehydration stress-inducible gene [8]. ...
... With the rapid development of molecular biology, molecular genetics and bioinformatics, genome-wide association studies (GWASs), based on the natural population and linkage disequilibrium, can detect genetic variation polymorphisms in the whole genome and conduct population-level statistical analysis of the genotype and phenotype, which can efficiently detect genes associated with traits, making it more convenient to mine genes that control the drought-tolerance traits of crops and identify excellent genetic variation materials. With the reduction in sequencing costs and the completion of most crop gene sequencing, GWASs have been widely applied in the drought-tolerance research of rice [4][5][6][7][8], wheat [9][10][11][12], maize [13][14][15], soybean [16,17], sorghum [18,19], cotton [20] and other crops, and many significant marker-trait association loci and candidate genes related to drought tolerance have been revealed, some of which are related to transcription factors (TFs) [7,8,10,16,18]. The quantitative trait locus identified by GWAS contains candidate genes with functions related to osmotic stress regulation, such as the basic leucine zipper (bZIP) protein gene OsbZIP80, which plays an important role in the tolerance of or adaptation to abiotic stress and is considered a rice-dehydration stress-inducible gene [8]. A dehydration response element-binding protein TF identified by a GWAS, related to drought tolerance in wheat, plays a transcriptional activation role in abscisic acid (ABA)independent drought stress responses by binding to the dehydration response element [10]. ...
... A GWAS, using high-density phenotypic genomics, was conducted to study the height, leaf area and biomass of 648 sorghum cultivars under drought and well-watered conditions. High-quality, repetitive and conserved gene associations have been revealed, which included many strong candidate genes encoding heat shock proteins and antifreeze proteins involved in stress response [18]. Hence, drought tolerance is a complex trait regulated by many genes and it involves a variety of drought-response signaling pathways and metabolic networks. ...
To understand the molecular mechanism of drought tolerance in sweet sorghum [Sorghum bicolor (L.) Moench], we found the genetic loci associated with single nucleotide polymorphism (SNP) markers and explored drought-tolerance candidate genes. A genome-wide association study (GWAS) of sweet sorghum was performed using the general linear model (GLM), mixed linear model (MLM) and the fixed and random model circulating probability unification (FarmCPU) method in R. Mean productivity (MP), relative drought index (RDI) and stress-tolerance index (STI), based on plant height under two water treatments, were obtained from 354 sweet sorghum accessions from home and abroad. These plant-height drought-tolerance indices showed continuous quantitative variation. Except for the RDI, the others were close to normal distribution. A total of 6186 SNPs were obtained from the resequencing data after quality control and filling. The marker densities on chromosomes 9, 10 and 5 were higher than those on other chromosomes, which were 40.4, 16.5 and 10.0 SNPs within 1 Mb, respectively. The GWAS results showed that 49, 5 and 25 significant SNP loci were detected by the GLM, the MLM and FarmCPU, respectively, many of which were detected by two or more models. Two candidate genes of drought tolerance were annotated: Sb08g019720.1, homologous to the gene encoding the early flowering MYB protein transcription factor in Arabidopsis thaliana; and Sb01g037050.1, homologous to the gene encoding the basic leucine zipper transcription factor in maize. The results of this study can facilitate the cultivar development of drought-tolerant sweet sorghum.
