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Phenotypic plasticity is the property of a genotype to produce different phenotypes under different environmental conditions. Understanding genetic and environmental factors behind phenotypic plasticity helps answer some longstanding biology questions and improve phenotype prediction. In this study, we investigated the phenotypic plasticity of flowering time and plant height with a set of diverse sorghum lines evaluated across 14 natural field environments. An environmental index was identified to quantitatively connect the environments. Reaction norms were then obtained with the identified indices for genetic dissection of phenotypic plasticity and performance prediction. Genome-wide association studies (GWAS) detected different sets of loci for reaction-norm parameters (intercept and slope), including 10 new genomic regions in addition to known maturity (Ma1) and dwarfing genes (Dw1, Dw2, Dw3, Dw4 and qHT7.1). Cross-validations under multiple scenarios showed promising results in predicting diverse germplasm in dynamic environments. Additional experiments conducted at four new environments, including one from a site outside of the geographical region of the initial environments, further validated the predictions. Our findings indicate that identifying the environmental index enriches our understanding of gene-environmental interplay underlying phenotypic plasticity, and that genomic prediction with the environmental dimension facilitates prediction-guided breeding for future environments.
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BACKGROUND: The USDA Agriculture Research Service National Plant Germplasm System (NPGS) preserves the largest sorghum germplasm collection in the world, which includes 7,217 accessions from the center of diversity in Ethiopia. The characterization of this exotic germplasm at a genome-wide scale will improve conservation efforts and its utilization in research and breeding programs. Therefore, we phenotyped a representative core set of 374 Ethiopian accessions at two locations for agronomic traits and characterized the genomes. RESULTS: Using genotyping-by-sequencing, we identified 148,476 single-nucleotide polymorphism (SNP) markers distributed across the entire genome. Over half of the alleles were rare (frequency < 0.05). The genetic profile of each accession was unique (i.e., no duplicates), and the average genetic distance among accessions was 0.70. Based on population structure and cluster analyses, we separated the collection into 11 populations with pairwise F ST values ranging from 0.11 to 0.47. In total, 198 accessions (53%) were assigned to one of these populations with an ancestry membership coefficient of larger than 0.60; these covered 90% of the total genomic variation. We characterized these populations based on agronomic and seed compositional traits. We performed a cluster analysis with the sorghum association panel based on 26,026 SNPs and determined that nine of the Ethiopian populations expanded the genetic diversity in the panel. Genome-wide association analysis demonstrated that these low-coverage data and the observed population structure could be employed for the genomic dissection of important phenotypes in this core set of Ethiopian sorghum germplasm. CONCLUSIONS: The NPGS Ethiopian sorghum germplasm is a genetically and phenotypically diverse collection comprising 11 populations with high levels of admixture. Genetic associations with agronomic traits can be used to improve the screening of exotic germplasm for selection of specific populations. We detected many rare alleles, suggesting that this germplasm contains potentially useful undiscovered alleles, but their discovery and characterization will require extensive effort. The genotypic data available for these accessions provide a valuable resource for sorghum breeders and geneticists to effectively improve crops.
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Genoma de Planta , Genómica , Semillas/genética , Sorghum/genética , Alelos , Etiopía , Frecuencia de los Genes , Variación Genética , Genética de Población , Estudio de Asociación del Genoma Completo , Genómica/métodos , Fenotipo , Filogenia , Polimorfismo de Nucleótido Simple , Banco de Semillas , Selección Genética , Sorghum/clasificación , Estados Unidos , United States Department of AgricultureRESUMEN
BACKGROUND: Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are still unresolved. The goals of this study were to quantify natural variation of sorghum grain composition and to identify single-nucleotide polymorphisms (SNPs) associated with variation in grain composition concentrations. RESULTS: In this study, we quantified protein, fat, and starch in a global sorghum diversity panel using near-infrared spectroscopy (NIRS). Protein content ranged from 8.1 to 18.8%, fat content ranged from 1.0 to 4.3%, and starch content ranged from 61.7 to 71.1%. Durra and bicolor-durra sorghum from Ethiopia and India had the highest protein and fat and the lowest starch content, while kafir sorghum from USA, India, and South Africa had the lowest protein and the highest starch content. Genome-wide association studies (GWAS) identified quantitative trait loci (QTL) for sorghum protein, fat, and starch. Previously published RNAseq data was used to identify candidate genes within a GWAS QTL region. A putative alpha-amylase 3 gene, which has previously been shown to be associated with grain composition traits, was identified as a strong candidate for protein and fat variation. CONCLUSIONS: We identified promising sources of genetic material for manipulation of grain composition traits, and several loci and candidate genes that may control sorghum grain composition. This survey of grain composition in sorghum germplasm and identification of protein, fat, and starch QTL contributes to our understanding of the genetic basis of natural variation in sorghum grain nutritional traits.
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Estudios de Asociación Genética , Carácter Cuantitativo Heredable , Semillas/química , Semillas/genética , Sorghum/genética , Grano Comestible/química , Grano Comestible/genética , Estudio de Asociación del Genoma Completo , Genómica/métodos , Fenotipo , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Sorghum/química , Almidón/químicaRESUMEN
Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials.
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Because of its wide distribution, high yield potential, and short cycle, the potato has become essential for global food security. However, the complexity of tetrasomic inheritance, the high level of heterozygosity of the parents, the low multiplication rate of tubers, and the genotype-by-environment interactions impose severe challenges on tetraploid potato-breeding programs. The initial stages of selection take place in experiments with low selection accuracy for many of the quantitative traits of interest, for example, tuber yield. The goal of this study was to investigate the contribution of incorporating a family effect in the estimation of the total genotypic effect and selection of clones in the initial stage of a potato-breeding program. The evaluation included single trials (STs) and multi-environment trials (METs). A total of 1,280 clones from 67 full-sib families from the potato-breeding program at Universidade Federal de Lavras were evaluated for the traits total tuber yield and specific gravity. These clones were distributed in six evaluated trials that varied according to the heat stress level: without heat stress, moderate heat stress, and high heat stress. To verify the importance of the family effect, models with and without the family effect were compared for the analysis of ST and MET data for both traits. The models that included the family effect were better adjusted in the ST and MET data analyses for both traits, except when the family effect was not significant. Furthermore, the inclusion of the family effect increased the selective efficiency of clones in both ST and MET analyses via an increase in the accuracy of the total genotypic value. These same models also allowed the prediction of clone effects more realistically, as the variance components associated with family and clone effects within a family were not confounded. Thus, clonal selection based on the total genotypic value, combining the effects of family and clones within a family, proved to be a good alternative for potato-breeding programs that can accommodate the logistic and data tracking required in the breeding program.
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Both annual and perennial sorghum biomass serve as important forage for ruminant animals around the world. Unfortunately, sorghum can produce hydrogen cyanide (HCN), which, if occurring in high enough concentrations, can be toxic or lethal to animals that consume it. The objectives of this study were to develop a fast and inexpensive colorimetric assay to measure the hydrogen cyanide potential (HCN-P) as well as to compare this with existing visual assays while assessing the range of variation for HCN-P among perennial and annual sorghum biomass. The HCN-P of 100 sorghum lines derived from an interspecific hybridization program was determined over 2 years (establishment and regrowth) using both visual and colorimetric assays. Visual assessment underestimated the HCN-P and was less accurate than colorimetry. Repeatability for HCN-P across all sampling dates was functionally zero in the visual assessment and low for the colorimetric assay. This was mostly explained by the significant pedigree × year interaction effects and growth stage. Growth stage substantially influenced HCN-P, which should be considered when feeding animals on fresh forage.
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Traditional lignocellulosic feedstock research has focused on biomass characteristics essential for improving saccharification efficiency, yet the key biomass features underlying high-quality renewable lignin materials remain unknown. Nevertheless, modern biorefinery cannot achieve sustainability and cost-effectiveness unless the lignin stream can be valorized. We hereby addressed these scientific gaps by investigating biomass characteristics defining lignin-based carbon materials properties. Lignin from eight sorghum samples with diverse characteristics was fabricated into carbon fibers (CFs). Remarkably, only lignin uniformity was found to define CF mechanical performance, highlighting the new structure-property relationship. Contrarily, lignin content and composition did not impact on carbon material properties. Mechanistic study by XRD and Raman spectroscopy revealed that higher lignin uniformity enhanced CF microstructures, in particular, turbostratic carbon content. The study for the first time highlighted lignin uniformity as an important biomass structure determinant for renewable products, which opened up new avenues for feedstock design toward diverse products enabling sustainable and cost-effective bioeconomy.
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Identifying natural variation of health-promoting compounds in staple crops and characterizing its genetic basis can help improve human nutrition through crop biofortification. Some varieties of sorghum, a staple cereal crop grown worldwide, have high concentrations of proanthocyanidins and 3-deoxyanthocyanidins, polyphenols with antioxidant and anti-inflammatory properties. We quantified total phenols, proanthocyanidins, and 3-deoxyanthocyanidins in a global sorghum diversity panel (n = 381) using near-infrared spectroscopy (NIRS), and characterized the patterns of variation with respect to geographic origin and botanical race. A genome-wide association study (GWAS) with 404,628 SNP markers identified novel quantitative trait loci for sorghum polyphenols, some of which colocalized with homologues of flavonoid pathway genes from other plants, including an orthologue of maize (Zea mays) Pr1 and a homologue of Arabidopsis (Arabidopsis thaliana) TT16. This survey of grain polyphenol variation in sorghum germplasm and catalog of flavonoid pathway loci may be useful to guide future enhancement of cereal polyphenols.