Modeling soybean growth: A mixed model approach.

The evaluation of plant and animal growth, separately for genetic and environmental effects, is necessary for genetic understanding and genetic improvement of environmental responses of plants and animals. We propose to extend an existing approach that combines nonlinear mixed-effects model (NLMEM) and the stochastic approximation of the Expectation-Maximization algorithm (SAEM) to analyze genetic and environmental effects on plant growth. These tools are widely used in many fields but very rarely in plant biology. During model formulation, a nonlinear function describes the shape of growth, and random effects describe genetic and environmental effects and their variability. Genetic relationships among the varieties were also integrated into the model using a genetic relationship matrix. The SAEM algorithm was chosen as an efficient alternative to MCMC methods, which are more commonly used in the domain. It was implemented to infer the expected growth patterns in the analyzed population and the expected curves for each variety through a maximum-likelihood and a maximum-a-posteriori approaches, respectively. The obtained estimates can be used to predict the growth curves for each variety. We illustrate the strengths of the proposed approach using simulated data and soybean plant growth data obtained from a soybean cultivation experiment conducted at the Arid Land Research Center, Tottori University. In this experiment, plant height was measured daily using drones, and the growth was monitored for approximately 200 soybean cultivars for which whole-genome sequence data were available. The NLMEM approach improved our understanding of the determinants of soybean growth and can be successfully used for the genomic prediction of growth pattern characteristics.

Reaction norm for genomic prediction of plant growth: modeling drought stress response in soybean.

KEY MESSAGE: We proposed models to predict the effects of genomic and environmental factors on daily soybean growth and applied them to soybean growth data obtained with unmanned aerial vehicles. Advances in high-throughput phenotyping technology have made it possible to obtain time-series plant growth data in field trials, enabling genotype-by-environment interaction (G × E) modeling of plant growth. Although the reaction norm is an effective method for quantitatively evaluating G × E and has been implemented in genomic prediction models, no reaction norm models have been applied to plant growth data. Here, we propose a novel reaction norm model for plant growth using spline and random forest models, in which daily growth is explained by environmental factors one day prior. The proposed model was applied to soybean canopy area and height to evaluate the influence of drought stress levels. Changes in the canopy area and height of 198 cultivars were measured by remote sensing using unmanned aerial vehicles. Multiple drought stress levels were set as treatments, and their time-series soil moisture was measured. The models were evaluated using three cross-validation schemes. Although accuracy of the proposed models did not surpass that of single-trait genomic prediction, the results suggest that our model can capture G × E, especially the latter growth period for the random forest model. Also, significant variations in the G × E of the canopy height during the early growth period were visualized using the spline model. This result indicates the effectiveness of the proposed models on plant growth data and the possibility of revealing G × E in various growth stages in plant breeding by applying statistical or machine learning models to time-series phenotype data.

Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation.

The phenotypic variation of living organisms is shaped by genetics, environment, and their interaction. Understanding phenotypic plasticity under natural conditions is hindered by the apparently complex environment and the interacting genes and pathways. Herein, we report findings from the dissection of rice flowering-time plasticity in a genetic mapping population grown in natural long-day field environments. Genetic loci harboring four genes originally discovered for their photoperiodic effects (Hd1, Hd2, Hd5, and Hd6) were found to differentially respond to temperature at the early growth stage to jointly determine flowering time. The effects of these plasticity genes were revealed with multiple reaction norms along the temperature gradient. By coupling genomic selection and the environmental index, accurate performance predictions were obtained. Next, we examined the allelic variation in the four flowering-time genes across the diverse accessions from the 3000 Rice Genomes Project and constructed haplotypes at both individual-gene and multigene levels. The geographic distribution of haplotypes revealed their preferential adaptation to different temperature zones. Regions with lower temperatures were dominated by haplotypes sensitive to temperature changes, whereas the equatorial region had a majority of haplotypes that are less responsive to temperature. By integrating knowledge from genomics, gene cloning and functional characterization, and environment quantification, we propose a conceptual model with multiple levels of reaction norms to help bridge the gaps among individual gene discovery, field-level phenotypic plasticity, and genomic diversity and adaptation.

Prenatal metal concentrations and physical abnormalities in the Japan Environment and Children's Study.

BACKGROUND: The association between prenatal metal exposure and congenital anomalies is unclear. We aimed to examine the association between exposure to cadmium, lead, mercury, selenium, and manganese and physical abnormalities. METHODS: Data from 89,887 pregnant women with singleton pregnancies who participated in the Japan Environment and Children's Study (JECS) were used. The correlation between maternal blood metal concentrations and physical abnormalities during the second or third trimester was investigated using logistic regression models. Physical anomalies included those observed at birth or at 1 month, primarily from ICD-10 Chapter 17, particularly congenital anomalies associated with environmental factors (e.g., hypospadias, cryptorchidism, cleft lip and palate, digestive tract atresia, congenital heart disease, and chromosomal abnormalities) and minor abnormalities. RESULTS: After adjusting for covariates, the OR (95% CIs) of physical abnormalities for a one-unit rise in Mn concentrations in all individuals were 1.26 (1.08, 1.48). The OR (95% CIs) of physical abnormalities in the 4th quartile (≥18.7 ng/g) were 1.06 (1.01, 1.13) (p-value for the trend = 0.034) compared with those in the 1st quartile (≤12.5 ng/g). CONCLUSION: In Japan, maternal blood Mn concentrations above threshold during pregnancy may slightly increase the incidence of physical abnormalities. IMPACT: Physical abnormalities (including minor anomalies and congenital anomalies) are associated with prenatal manganese concentrations. They are not associated with cadmium, lead, mercury, and selenium concentrations.

Applicability of the histidine-tryptophan-ketoglutarate solution as a machine perfusion solution for marginal liver grafts.

BACKGROUND AND AIM: There are very few reports comparing the use of the University of Wisconsin solution and histidine-tryptophan-ketoglutarate solution as machine perfusion solutions for marginal liver grafts. We aimed to clarify whether the use of the histidine-tryptophan-ketoglutarate solution in hypothermic machine perfusion improves the split-liver graft function in a large animal model. METHODS: Porcine split-liver grafts were created by 75% liver resection. Hypothermic machine perfusion experimental groups were divided as follows: Group 1, perfusate, University of Wisconsin gluconate solution (UW group; n = 5), and Group 2, perfusate, histidine-tryptophan-ketoglutarate solution (HTK group; n = 4). After 4 h of preservation, the liver function was evaluated using an isolated liver reperfusion model for 2 h. RESULTS: In the HTK group, the portal vein and hepatic artery resistance during hypothermic machine perfusion and the portal vein resistance during isolated liver reperfusion were lower than those in the UW group. In addition, the total Suzuki score for hepatic ischemia-reperfusion injury in the HTK group was significantly better than that in the UW group. The number of anti-ETS-related genes staining-positive sinusoid epithelial cell nuclei in the HTK group was higher than that in the UW group (not significant). CONCLUSIONS: The histidine-tryptophan-ketoglutarate solution can be perfused with lower vascular resistance than the University of Wisconsin solution, reducing shear stress and preventing sinusoid epithelial cell injury in marginal grafts used as split-liver grafts.

DOMINANT AWN INHIBITOR Encodes the ALOG Protein Originating from Gene Duplication and Inhibits AWN Elongation by Suppressing Cell Proliferation and Elongation in Sorghum.

The awn, a needle-like structure extending from the tip of the lemma in grass species, plays a role in environmental adaptation and fitness. In some crops, awns appear to have been eliminated during domestication. Although numerous genes involved in awn development have been identified, several dominant genes that eliminate awns are also known to exist. For example, in sorghum (Sorghum bicolor), the dominant awn-inhibiting gene has been known since 1921; however, its molecular features remain uncharacterized. In this study, we conducted quantitative trait locus analysis and a genome-wide association study of awn-related traits in sorghum and identified DOMINANT AWN INHIBITOR (DAI), which encodes the ALOG family protein on chromosome 3. DAI appeared to be present in most awnless sorghum cultivars, likely because of its effectiveness. Detailed analysis of the ALOG protein family in cereals revealed that DAI originated from a duplication of its twin paralog (DAIori) on chromosome 10. Observations of immature awns in near-isogenic lines revealed that DAI inhibits awn elongation by suppressing both cell proliferation and elongation. We also found that only DAI gained a novel function to inhibit awn elongation through an awn-specific expression pattern distinct from that of DAIori. Interestingly, heterologous expression of DAI with its own promoter in rice inhibited awn elongation in the awned cultivar Kasalath. We found that DAI originated from gene duplication, providing an interesting example of gain-of-function that occurs only in sorghum but shares its functionality with rice and sorghum.

Sorghum Ionomics Reveals the Functional SbHMA3a Allele that Limits Excess Cadmium Accumulation in Grains.

Understanding uptake and redistribution of essential minerals or sequestering of toxic elements is important for optimized crop production. Although the mechanisms controlling mineral transport have been elucidated in rice and other species, little is understood in sorghum-an important C4 cereal crop. Here, we assessed the genetic factors that govern grain ionome profiles in sorghum using recombinant inbred lines (RILs) derived from a cross between BTx623 and NOG (Takakibi). Pairwise correlation and clustering analysis of 22 elements, measured in sorghum grains harvested under greenhouse conditions, indicated that the parental lines, as well as the RILs, show different ionomes. In particular, BTx623 accumulated significantly higher levels of cadmium (Cd) than NOG, because of differential root-to-shoot translocation factors between the two lines. Quantitative trait locus (QTL) analysis revealed a prominent QTL for grain Cd concentration on chromosome 2. Detailed analysis identified SbHMA3a, encoding a P1B-type ATPase heavy metal transporter, as responsible for low Cd accumulation in grains; the NOG allele encoded a functional HMA3 transporter (SbHMA3a-NOG) whose Cd-transporting activity was confirmed by heterologous expression in yeast. BTx623 possessed a truncated, loss-of-function SbHMA3a allele. The functionality of SbHMA3a in NOG was confirmed by Cd concentrations of F2 grains derived from the reciprocal cross, in which the NOG allele behaved in a dominant manner. We concluded that SbHMA3a-NOG is a Cd transporter that sequesters excess Cd in root tissues, as shown in other HMA3s. Our findings will facilitate the isolation of breeding cultivars with low Cd in grains or in exploiting high-Cd cultivars for phytoremediation.

Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs.

KEY MESSAGE: We propose a novel approach to the Bayesian optimization of multivariate genomic prediction models based on secondary traits to improve accuracy gains and phenotyping costs via efficient Pareto frontier estimation. Multivariate genomic prediction based on secondary traits, such as data from various omics technologies including high-throughput phenotyping (e.g., unmanned aerial vehicle-based remote sensing), has attracted much attention because it offers improved accuracy gains compared with genomic prediction based only on marker genotypes. Although there is a trade-off between accuracy gains and phenotyping costs of secondary traits, no attempt has been made to optimize these trade-offs. In this study, we propose a novel approach to optimize multivariate genomic prediction models for secondary traits measurable at early growth stages for improved accuracy gains and phenotyping costs. The proposed approach employs Bayesian optimization for efficient Pareto frontier estimation, representing the maximum accuracy at a given cost. The proposed approach successfully estimated the optimal secondary trait combinations across a range of costs while providing genomic predictions for only about [Formula: see text] of all possible combinations. The simulation results reflecting the characteristics of each scenario of the simulated target traits showed that the obtained optimal combinations were reasonable. Analysis of real-time target trait data showed that the proposed multivariate genomic prediction model had significantly superior accuracy compared to the univariate genomic prediction model.

Development of a high-throughput field phenotyping rover optimized for size-limited breeding fields as open-source hardware.

Phenotyping is a critical process in plant breeding, especially when there is an increasing demand for streamlining a selection process in a breeding program. Since manual phenotyping has limited efficiency, high-throughput phenotyping methods are recently popularized owing to progress in sensor and image processing technologies. However, in a size-limited breeding field, which is common in Japan and other Asian countries, it is challenging to introduce large machinery in the field or fly unmanned aerial vehicles over the field. In this study, we developed a ground-based high-throughput field phenotyping rover that could be easily introduced to a field regardless of the scale and location of the field even without special facilities. We also made the field rover open-source hardware, making its system available to public for easy modification, so that anyone can build one for their own use at a low cost. The trial run of the field rover revealed that it allowed the collection of detailed remote-sensing images of plants and quantitative analyses based on the images. The results suggest that the field rover developed in this study could allow efficient phenotyping of plants especially in a small breeding field.

From gene banks to farmer's fields: using genomic selection to identify donors for a breeding program in rice to close the yield gap on smallholder farms.

KEY MESSAGE: Despite phenotyping the training set under unfavorable conditions on smallholder farms in Madagascar, we were able to successfully apply genomic prediction to select donors among gene bank accessions. Poor soil fertility and low fertilizer application rates are main reasons for the large yield gap observed for rice produced in sub-Saharan Africa. Traditional varieties that are preserved in gene banks were shown to possess traits and alleles that would improve the performance of modern variety under such low-input conditions. How to accelerate the utilization of gene bank resources in crop improvement is an unresolved question and here our objective was to test whether genomic prediction could aid in the selection of promising donors. A subset of the 3,024 sequenced accessions from the IRRI rice gene bank was phenotyped for yield and agronomic traits for two years in unfertilized farmers' fields in Madagascar, and based on these data, a genomic prediction model was developed. This model was applied to predict the performance of the entire set of 3024 accessions, and the top predicted performers were sent to Madagascar for confirmatory trials. The prediction accuracies ranged from 0.10 to 0.30 for grain yield, from 0.25 to 0.63 for straw biomass, to 0.71 for heading date. Two accessions have subsequently been utilized as donors in rice breeding programs in Madagascar. Despite having conducted phenotypic evaluations under challenging conditions on smallholder farms, our results are encouraging as the prediction accuracy realized in on-farm experiments was in the range of accuracies achieved in on-station studies. Thus, we could provide clear empirical evidence on the value of genomic selection in identifying suitable genetic resources for crop improvement, if genotypic data are available.

RAINBOW: Haplotype-based genome-wide association study using a novel SNP-set method.

Difficulty in detecting rare variants is one of the problems in conventional genome-wide association studies (GWAS). The problem is closely related to the complex gene compositions comprising multiple alleles, such as haplotypes. Several single nucleotide polymorphism (SNP) set approaches have been proposed to solve this problem. These methods, however, have been rarely discussed in connection with haplotypes. In this study, we developed a novel SNP-set method named "RAINBOW" and applied the method to haplotype-based GWAS by regarding a haplotype block as a SNP-set. Combining haplotype block estimation and SNP-set GWAS, haplotype-based GWAS can be conducted without prior information of haplotypes. We prepared 100 datasets of simulated phenotypic data and real marker genotype data of Oryza sativa subsp. indica, and performed GWAS of the datasets. We compared the power of our method, the conventional single-SNP GWAS, the conventional haplotype-based GWAS, and the conventional SNP-set GWAS. Our proposed method was shown to be superior to these in three aspects: (1) controlling false positives; (2) in detecting causal variants without relying on the linkage disequilibrium if causal variants were genotyped in the dataset; and (3) it showed greater power than the other methods, i.e., it was able to detect causal variants that were not detected by the others, primarily when the causal variants were located very close to each other, and the directions of their effects were opposite. By using the SNP-set approach as in this study, we expect that detecting not only rare variants but also genes with complex mechanisms, such as genes with multiple causal variants, can be realized. RAINBOW was implemented as an R package named "RAINBOWR" and is available from CRAN (https://cran.r-project.org/web/packages/RAINBOWR/index.html) and GitHub (https://github.com/KosukeHamazaki/RAINBOWR).

Transcriptional switch for programmed cell death in pith parenchyma of sorghum stems.

Pith parenchyma cells store water in various plant organs. These cells are especially important for producing sugar and ethanol from the sugar juice of grass stems. In many plants, the death of pith parenchyma cells reduces their stem water content. Previous studies proposed that a hypothetical D gene might be responsible for the death of stem pith parenchyma cells in Sorghum bicolor, a promising energy grass, although its identity and molecular function are unknown. Here, we identify the D gene and note that it is located on chromosome 6 in agreement with previous predictions. Sorghum varieties with a functional D allele had stems enriched with dry, dead pith parenchyma cells, whereas those with each of six independent nonfunctional D alleles had stems enriched with juicy, living pith parenchyma cells. D expression was spatiotemporally coupled with the appearance of dead, air-filled pith parenchyma cells in sorghum stems. Among D homologs that are present in flowering plants, Arabidopsis ANAC074 also is required for the death of stem pith parenchyma cells. D and ANAC074 encode previously uncharacterized NAC transcription factors and are sufficient to ectopically induce programmed death of Arabidopsis culture cells via the activation of autolytic enzymes. Taken together, these results indicate that D and its Arabidopsis ortholog, ANAC074, are master transcriptional switches that induce programmed death of stem pith parenchyma cells. Thus, targeting the D gene will provide an approach to breeding crops for sugar and ethanol production.

A comparison of laparoscopic procedures performed by novice medical students using 8K ultra-high-definition/two-dimensional and 2K high-definition/three-dimensional monitors.

PURPOSE: 8K Ultra-high-definition (UHD) imaging has been developed in accordance with the progression of imaging technologies. We evaluated laparoscopic procedures performed by novice medical students using 2K/two-dimensional (2D), 2K/three-dimensional (3D) and 8K/2D monitors, with a particular focus on depth perception. METHODS: Nine medical students were enrolled. They performed two tasks using 2K/2D, 2K/3D and 8K/2D monitors. In Task 1, they were asked to grasp three metal rods with forceps using each hand. In Task 2, they were asked to grasp a metal rod with forceps held in the right hand, pass the metal rod through a metal ring and transfer it to their left hand. RESULTS: In Task 1, when performed with the dominant hand, the procedures performed using 2K/3D took a significantly shorter time than those performed using 8K/2D (P = 0.04). However, there was no significant difference among the three groups in the time required for procedures performed by the non-dominant hand. In Task 2, the procedure time with 2K/2D was significantly longer than that with 2K/3D or 8K/2D (P = 0.02). CONCLUSION: 2K/3D showed superior utility to 8K/2D for performing forceps procedures using the dominant hand. However, when the movement of both hands was coordinated ("bi-hand coordination"), the laparoscopic procedures were performed almost as deftly with 8K/2D and 2K/3D.

Spatial kernel models capturing field heterogeneity for accurate estimation of genetic potential.

According to Fisher's principles, an experimental field is typically divided into multiple blocks for local control. Although homogeneity is supposed within a block, this assumption may not be practical for large blocks, such as those including hundreds of plots. In line evaluation trials, which are essential in plant breeding, field heterogeneity must be carefully treated, because it can cause bias in the estimation of genetic potential. To more accurately estimate genotypic values in a large field trial, we developed spatial kernel models incorporating genome-wide markers, which consider continuous heterogeneity within a block and over the field. In the simulation study, the spatial kernel models were robust under various conditions. Although heritability, spatial autocorrelation range, replication number, and missing plots directly affected the estimation accuracy of genotypic values, the spatial kernel models always showed superior performance over the classical block model. We also employed these spatial kernel models for quantitative trait locus mapping. Finally, using field experimental data of bioenergy sorghum lines, we validated the performance of the spatial kernel models. The results suggested that a spatial kernel model is effective for evaluating the genetic potential of lines in a heterogeneous field.

RAD-seq-Based High-Density Linkage Map Construction and QTL Mapping of Biomass-Related Traits in Sorghum using the Japanese Landrace Takakibi NOG.

Sorghum [Sorghum bicolor (L.) Moench] grown locally by Japanese farmers is generically termed Takakibi, although its genetic diversity compared with geographically distant varieties or even within Takakibi lines remains unclear. To explore the genomic diversity and genetic traits controlling biomass and other physiological traits in Takakibi, we focused on a landrace, NOG, in this study. Admixture analysis of 460 sorghum accessions revealed that NOG belonged to the subgroup that represented Asian sorghums, and it was only distantly related to American/African accessions including BTx623. In an attempt to dissect major traits related to biomass, we generated a recombinant inbred line (RIL) from a cross between BTx623 and NOG, and we constructed a high-density linkage map based on 3,710 single-nucleotide polymorphisms obtained by restriction-site-associated DNA sequencing of 213 RIL individuals. Consequently, 13 fine quantitative trait loci (QTLs) were detected on chromosomes 2, 3, 6, 7, 8 and 9, which included five QTLs for days to heading, three for plant height (PH) and total shoot fresh weight and two for Brix. Furthermore, we identified two dominant loci for PH as being identical to the previously reported dw1 and dw3. Together, these results corroborate the diversified genome of Japanese Takakibi, while the RIL population and high-density linkage map generated in this study will be useful for dissecting other important traits in sorghum.

The need for home care physicians in Japan - 2020 to 2060.

BACKGROUND: Japan faces the most elderly society in the world, and the Japanese government has launched an unprecedented health plan to reinforce home care medicine and increase the number of home care physicians, which means that an understanding of future needs for geriatric home care is vital. However, little is known about the future need for home care physicians. We attempted to estimate the basic need for home care physicians from 2020 to 2060. METHODS: Our estimation is based on modification of major health work force analysis methods using previously reported official data. Two models were developed to estimate the necessary number of full-time equivalent (FTE) home care physicians: one based on home care patient mortality, the other using physician-to-patient ratio, working with estimated numbers of home and nursing home deaths from 2020 to 2060. Moreover, the final process considered and adjusted for future changes in the proportion of patients dying at home. Lastly, we converted estimated FTE physicians to an estimated head count. RESULTS: Results were concordant between our two models. In every instance, there was overlap of high- and low-estimations between the mortality method and the physician-to-patient method, and the estimates show highly similar patterns. Furthermore, our estimation is supported by the current number of physicians, which was calculated using a different method. Approximately 1.7 times (1.6 by head count) the current number of FTE home care physicians will be needed in Japan in the late 2030's, peaking at 33,500 FTE (71,500 head count). However, the need for home care physicians is anticipated to begin decreasing by 2040. CONCLUSION: The results indicate that the importance of home care physicians will rise with the growing elderly population, and that improvements in home care could partially suppress future need for physicians. After the late 2030's, the supply can be reduced gradually, accounting for the decreasing total number of deaths after 2040. In order to provide sufficient home care and terminal care at home, increasing the number of home care physicians is indispensable. However, the unregulated supply of home care physicians will require careful attention in the future.

Genomics-assisted breeding in minor and pseudo-cereals.

Minor and pseudo-cereals, which can grow with lower input and often produce specific nutrients compared to major cereal crops, are attracting worldwide attention. Since these crops generally have a large genetic diversity in a breeding population, rapid genetic improvement can be possible by the application of genomics-assisted breeding methods. In this review, we discuss studies related to biparental quantitative trait locus (QTL) mapping, genome-wide association study, and genomic selection for minor and pseudo-cereals. Especially, we focus on the current progress in a pseudo-cereal, buckwheat. Prospects for the practical utilization of genomics-assisted breeding in minor and pseudo-cereals are discussed including the issues to overcome especially for these crops.

Impacts of dominance effects on genomic prediction of sorghum hybrid performance.

Non-additive (dominance and epistasis) effects have remarkable influences on hybrid performance, e.g., via heterosis. Nevertheless, only additive effects are often considered in genomic predictions (GP). In this study, we demonstrated the importance of dominance effects in the prediction of hybrid performance in bioenergy sorghum [Sorghum bicolor (L.) Moench]. The dataset contained more than 400 hybrids between 200 inbred lines and two testers. The hybrids exhibited considerable heterosis in culm length and fresh weight, and the degree of heterosis was consistent with the genetic distance from the corresponding tester. The degree of heterosis was further different among subpopulations. Conversely, Brix exhibited limited heterosis. Regarding GP, we examined three statistical models and four training dataset types. In most of the dataset types, genomic best linear unbiased prediction (GBLUP) with additive effects had lower prediction accuracy than GBLUP with additive and dominance effects (GBLUP-AD) and Gaussian kernel regression (GK). The superiority of GBLUP-AD and GK depended on the level of dominance variance, which was high for culm length and fresh weight, and low for Brix. Considering subpopulations, the influence of dominance was more complex. Our findings highlight the importance of considering dominance effects in GP models for sorghum hybrid breeding.

Effect of salt tolerance on biomass production in a large population of sorghum accessions.

Salinity causes major reductions in cultivated land area, crop productivity, and crop quality, and salt-tolerant crops have been required to sustain agriculture in salinized areas. The annual C4 crop plant Sorghum bicolor (L.) Moench is salt tolerant, with large variation among accessions. Sorghum's salt tolerance is often evaluated during early growth, but such evaluations are weakly related to overall performance. Here, we evaluated salt tolerance of 415 sorghum accessions grown in saline soil (0, 50, 100, and 150 mM NaCl) for 3 months. Some accessions produced up to 400 g per plant of biomass and showed no growth inhibition at 50 mM NaCl. Our analysis indicated that the genetic factors that affected biomass production under 100 mM salt stress were more different from those without salt stress, comparing to the differences between those under 50 mM and 100 mM salt stress. A genome-wide association study for salt tolerance identified two single-nucleotide polymorphisms (SNPs) that were significantly associated with biomass production, only at 50 mM NaCl. Additionally, two SNPs were significantly associated with salt tolerance index as an indicator for growth response of each accession to salt stress. Our results offer candidate genetic resources and SNP markers for breeding salt-tolerant sorghum.